ORCID Profile
0000-0002-5606-3970
Current Organisation
University of Queensland
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Crop and Pasture Production | Quantitative Genetics (incl. Disease and Trait Mapping Genetics) | Crop and Pasture Improvement (Selection and Breeding) | Crop and pasture production | Animal reproduction and breeding | Horticultural crop improvement (incl. selection and breeding) | Crop and pasture improvement (incl. selection and breeding) | Fisheries Sciences | Genetics | Plant Cell and Molecular Biology | Optimisation | Genomics | Fish Pests and Diseases | Fish Physiology and Genetics | Aquaculture | Animal Breeding
Wheat | Aquaculture Prawns | Barley | Beef Cattle | Aquaculture Fin Fish (excl. Tuna) | Oats | Fisheries - Aquaculture not elsewhere classified |
Publisher: Oxford University Press (OUP)
Date: 02-02-2021
Abstract: In the course of evolution, pecorans (i.e., higher ruminants) developed a remarkable ersity of osseous cranial appendages, collectively referred to as “headgear,” which likely share the same origin and genetic basis. However, the nature and function of the genetic determinants underlying their number and position remain elusive. Jacob and other rare populations of sheep and goats are characterized by polyceraty, the presence of more than two horns. Here, we characterize distinct POLYCERATE alleles in each species, both associated with defective HOXD1 function. We show that haploinsufficiency at this locus results in the splitting of horn bud primordia, likely following the abnormal extension of an initial morphogenetic field. These results highlight the key role played by this gene in headgear patterning and illustrate the evolutionary co-option of a gene involved in the early development of bilateria to properly fix the position and number of these distinctive organs of Bovidae.
Publisher: Wiley
Date: 26-02-2008
DOI: 10.1111/J.1365-2052.2007.01686.X
Abstract: A linkage map was constructed for bovine chromosome 6 (BTA6), using 399 single nucleotide polymorphisms (SNPs) detected primarily from PCR-resequencing. The efficiency of SNP detection was highly dependent on the source of sequence information chosen for primer design (BAC-end sequences, introns or promoters). The SNPs were used to build a linkage map comprising 104 cM on BTA6. The SNP order in the linkage map corresponded very well with radiation hybrid (RH) maps available for BTA6 as well as with expected positions in the human comparative map, but erged significantly from the current assembly of the bovine genome (Btau_3.1). When performing linkage analysis with the marker order suggested from the Btau_3.1 we observed an expansion of the genetic map from 104 cM to 137 cM, strongly suggesting a reordering of scaffolds in the current version of the bovine genome assembly. The extent of LD on BTA6 was evaluated by calculating the average r(2) for SNP pairs separated by given distances. The decline of LD was rapid with distance, such that r(2) was 0.1 at 100 kb. Our results indicate that linkage mapping will be a valuable source of information for correcting errors in the current bovine assembly. These errors were sufficiently frequent to be of concern for the accuracy of mapping QTL with panels of SNPs whose positions are based on the current assembly.
Publisher: American Dairy Science Association
Date: 10-2012
Abstract: With the aim of increasing the accuracy of genomic estimated breeding values for dry matter intake (DMI) in dairy cattle, data from Australia (AU), the United Kingdom (UK), and the Netherlands (NL) were combined using both single-trait and multi-trait models. In total, DMI records were available on 1,801 animals, including 843 AU growing heifers with records on DMI measured over 60 to 70 d at approximately 200 d of age, and 359 UK and 599 NL lactating heifers with records on DMI during the first 100 d in milk. The genotypes used in this study were obtained from the Illumina Bovine 50K chip (Illumina Inc., San Diego, CA). The AU, UK, and NL genomic data were matched using the single nucleotide polymorphism (SNP) name. Quality controls were applied by carefully comparing the genotypes of 40 bulls that were available in each data set. This resulted in 30,949 SNP being used in the analyses. Genomic predictions were estimated with genomic REML, using ASReml software. The accuracy of genomic prediction was evaluated in 11 validation sets that is, at least 3 validation sets per country were defined. The reference set (in which animals had both DMI phenotypes and genotypes) was either AU or Europe (UK and NL) or a multi-country reference set consisting of all data except the validation set. When DMI for each country was treated as the same trait, use of a multi-country reference set increased the accuracy of genomic prediction for DMI in UK, but not in AU and NL. Extending the model to a bivariate (AU-EU) or trivariate (AU-UK-NL) model increased the accuracy of genomic prediction for DMI in all countries. The highest accuracies were estimated for all countries when data were analyzed with a trivariate model, with increases of up to 5.5% compared with univariate models within countries.
Publisher: Springer Science and Business Media LLC
Date: 02-2016
Publisher: Springer Science and Business Media LLC
Date: 12-03-2016
Publisher: Wiley
Date: 2017
Publisher: Springer Science and Business Media LLC
Date: 05-11-2020
DOI: 10.1038/S41598-020-75438-2
Abstract: Heat stress in dairy cattle leads to reduction in feed intake and milk production as well as the induction of many physiological stress responses. The genes implicated in the response to heat stress in vivo are not well characterised. With the aim of identifying such genes, an experiment was conducted to perform differential gene expression in peripheral white blood cells and milk somatic cells in vivo in 6 Holstein Friesian cows in thermoneutral conditions and in 6 Holstein Friesian cows exposed to a short-term moderate heat challenge. RNA sequences from peripheral white blood cells and milk somatic cells were used to quantify full transcriptome gene expression. Genes commonly differentially expressed (DE) in both the peripheral white blood cells and in milk somatic cells were associated with the cellular stress response, apoptosis, oxidative stress and glucose metabolism. Genes DE in peripheral white blood cells of cows exposed to the heat challenge compared to the thermoneutral control were related to inflammation, lipid metabolism, carbohydrate metabolism and the cardiovascular system. Genes DE in milk somatic cells compared to the thermoneutral control were involved in the response to stress, thermoregulation and vasodilation. These findings provide new insights into the cellular adaptations induced during the response to short term moderate heat stress in dairy cattle and identify potential candidate genes ( BDKRB1 and SNORA19 ) for future research.
Publisher: Springer Science and Business Media LLC
Date: 12-11-2012
Publisher: Springer Science and Business Media LLC
Date: 29-12-2014
DOI: 10.1007/S00122-013-2258-7
Abstract: Best linear unbiased prediction (BLUP), which uses pedigree to estimate breeding values, can result in increased genetic gains for low heritability traits in autotetraploid potato. Conventional potato breeding strategies, based on outcrossing followed by phenotypic recurrent selection over a number of generations, can result in slow but steady improvements of traits with moderate to high heritability. However, faster gains, particularly for low heritability traits, could be made by selection on estimated breeding values (EBVs) calculated using more complete pedigree information in best linear unbiased prediction (BLUP) analysis. One complication in applying BLUP predictions of breeding value to potato breeding programs is the autotetraploid inheritance pattern of this species. Here we have used a large pedigree, dating back to 1908, to estimate heritability for nine key traits for potato breeding, modelling autotetraploid inheritance. We estimate the proportion of double reduction in potatoes from our data, and across traits, to be in the order of 10 %. Estimates of heritability ranged from 0.21 for breeder's visual preference, 0.58 for tuber yield, to 0.83 for plant maturity. Using the accuracies of the EBVs determined by cross generational validation, we model the genetic gain that could be achieved by selection of genotypes for breeding on BLUP EBVs and demonstrate that gains can be greater than in conventional schemes.
Publisher: American Dairy Science Association
Date: 04-2012
Abstract: Feed makes up a large proportion of variable costs in dairying. For this reason, selection for traits associated with feed conversion efficiency should lead to greater profitability of dairying. Residual feed intake (RFI) is the difference between actual and predicted feed intakes and is a useful selection criterion for greater feed efficiency. However, measuring in idual feed intakes on a large scale is prohibitively expensive. A panel of DNA markers explaining genetic variation in this trait would enable cost-effective genomic selection for this trait. With the aim of enabling genomic selection for RFI, we used data from almost 2,000 heifers measured for growth rate and feed intake in Australia (AU) and New Zealand (NZ) genotyped for 625,000 single nucleotide polymorphism (SNP) markers. Substantial variation in RFI and 250-d body weight (BW250) was demonstrated. Heritabilities of RFI and BW250 estimated using genomic relationships among the heifers were 0.22 and 0.28 in AU heifers and 0.38 and 0.44 in NZ heifers, respectively. Genomic breeding values for RFI and BW250 were derived using genomic BLUP and 2 bayesian methods (BayesA, BayesMulti). The accuracies of genomic breeding values for RFI were evaluated using cross-validation. When 624,930 SNP were used to derive the prediction equation, the accuracies averaged 0.37 and 0.31 for RFI in AU and NZ validation data sets, respectively, and 0.40 and 0.25 for BW250 in AU and NZ, respectively. The greatest advantage of using the full 624,930 SNP over a reduced panel of 36,673 SNP (the widely used BovineSNP50 array) was when the reference population included only animals from either the AU or the NZ experiment. Finally, the bayesian methods were also used for quantitative trait loci detection. On chromosome 14 at around 25 Mb, several SNP closest to PLAG1 (a gene believed to affect stature in humans and cattle) had an effect on BW250 in both AU and NZ populations. In addition, 8 SNP with large effects on RFI were located on chromosome 14 at around 35.7 Mb. These SNP may be associated with the gene NCOA2, which has a role in controlling energy metabolism.
Publisher: American Dairy Science Association
Date: 09-2017
Publisher: American Dairy Science Association
Date: 11-2010
Abstract: A deterministic model to calculate rates of genetic gain and inbreeding was used to compare a range of breeding scheme designs under genomic selection (GS) for a population of 140,000 cows. For most schemes it was assumed that the reliability of genomic breeding values (GEBV) was 0.6 across 4 pathways of selection. In addition, the effect of varying reliability on the ranking of schemes was also investigated. The schemes considered included intense selection in male pathways and genotyping of 1,000 young bulls (GS-Y). This scheme was extended to include selection in females and to include a "worldwide" scheme similar to GS-Y, but 6 times as large and assuming genotypes were freely exchanged between 6 countries. An additional worldwide scheme was modeled where GEBV were available through international genetic evaluations without exchange of genotypes. Finally, a closed nucleus herd that used juvenile in vitro embryo transfer in heifers was modeled so that the generation interval in female pathways was reduced to 1 or 2 yr. When the breeding schemes were compared using a GEBV reliability of 0.6, the rates of genetic gain were between 59 and 130% greater than the rate of genetic gain achieved in progeny testing. This was mainly through reducing the generation interval and increasing selection intensity. Genomic selection of females resulted in a 50% higher rate of genetic gain compared with restricting GS to young bulls only. The annual rates of inbreeding were, in general, 60% lower than with progeny testing, because more sires of bulls and sires of cows were selected, thus increasing the effective population size. The exception was in nucleus breeding schemes that had very short generation intervals, resulting in higher rates of both gain and inbreeding. It is likely that breeding companies will move rapidly to alter their breeding schemes to make use of genomic selection because benefits to the breeding companies and to the industry are considerable.
Publisher: Springer Science and Business Media LLC
Date: 29-10-2021
DOI: 10.1186/S12864-021-08116-W
Abstract: High-density SNP arrays are now available for a wide range of crop species. Despite the development of many tools for generating genetic maps, the genome position of many SNPs from these arrays is unknown. Here we propose a linkage disequilibrium (LD)-based algorithm to allocate unassigned SNPs to chromosome regions from sparse genetic maps. This algorithm was tested on sugarcane, wheat, and barley data sets. We calculated the algorithm’s efficiency by masking SNPs with known locations, then assigning their position to the map with the algorithm, and finally comparing the assigned and true positions. In the 20-fold cross-validation, the mean proportion of masked mapped SNPs that were placed by the algorithm to a chromosome was 89.53, 94.25, and 97.23% for sugarcane, wheat, and barley, respectively. Of the markers that were placed in the genome, 98.73, 96.45 and 98.53% of the SNPs were positioned on the correct chromosome. The mean correlations between known and new estimated SNP positions were 0.97, 0.98, and 0.97 for sugarcane, wheat, and barley. The LD-based algorithm was used to assign 5920 out of 21,251 unpositioned markers to the current Q208 sugarcane genetic map, representing the highest density genetic map for this species to date. Our LD-based approach can be used to accurately assign unpositioned SNPs to existing genetic maps, improving genome-wide association studies and genomic prediction in crop species with fragmented and incomplete genome assemblies. This approach will facilitate genomic-assisted breeding for many orphan crops that lack genetic and genomic resources.
Publisher: Annual Reviews
Date: 2013
DOI: 10.1146/ANNUREV-ANIMAL-031412-103705
Abstract: Three recent breakthroughs have resulted in the current widespread use of DNA information: the genomic selection (GS) methodology, which is a form of marker-assisted selection on a genome-wide scale, and the discovery of large numbers of single-nucleotide markers and cost effective methods to genotype them. GS estimates the effect of thousands of DNA markers simultaneously. Nonlinear estimation methods yield higher accuracy, especially for traits with major genes. The marker effects are estimated in a genotyped and phenotyped training population and are used for the estimation of breeding values of selection candidates by combining their genotypes with the estimated marker effects. The benefits of GS are greatest when selection is for traits that are not themselves recorded on the selection candidates before they can be selected. In the future, genome sequence data may replace SNP genotypes as markers. This could increase GS accuracy because the causative mutations should be included in the data.
Publisher: Hindawi Limited
Date: 02-2009
DOI: 10.1017/S0016672308009981
Abstract: Dense marker genotypes allow the construction of the realized relationship matrix between in iduals, with elements the realized proportion of the genome that is identical by descent (IBD) between pairs of in iduals. In this paper, we demonstrate that by replacing the average relationship matrix derived from pedigree with the realized relationship matrix in best linear unbiased prediction (BLUP) of breeding values, the accuracy of the breeding values can be substantially increased, especially for in iduals with no phenotype of their own. We further demonstrate that this method of predicting breeding values is exactly equivalent to the genomic selection methodology where the effects of quantitative trait loci (QTLs) contributing to variation in the trait are assumed to be normally distributed. The accuracy of breeding values predicted using the realized relationship matrix in the BLUP equations can be deterministically predicted for known family relationships, for ex le half sibs. The deterministic method uses the effective number of independently segregating loci controlling the phenotype that depends on the type of family relationship and the length of the genome. The accuracy of predicted breeding values depends on this number of effective loci, the family relationship and the number of phenotypic records. The deterministic prediction demonstrates that the accuracy of breeding values can approach unity if enough relatives are genotyped and phenotyped. For ex le, when 1000 full sibs per family were genotyped and phenotyped, and the heritability of the trait was 0·5, the reliability of predicted genomic breeding values (GEBVs) for in iduals in the same full sib family without phenotypes was 0·82. These results were verified by simulation. A deterministic prediction was also derived for random mating populations, where the effective population size is the key parameter determining the effective number of independently segregating loci. If the effective population size is large, a very large number of in iduals must be genotyped and phenotyped in order to accurately predict breeding values for unphenotyped in iduals from the same population. If the heritability of the trait is 0·3, and N e =1000, approximately 5750 in iduals with genotypes and phenotypes are required in order to predict GEBVs of un-phenotyped in iduals in the same population with an accuracy of 0·7.
Publisher: Oxford University Press (OUP)
Date: 06-2011
Abstract: A genome wide-association study for production traits in cattle was carried out using genotype data from the 10K Affymetrix (Santa Clara, CA) and the 50K Illumina (San Diego, CA) SNP chips. The results for residual feed intake (RFI), BW, and hip height in 3 beef breed types (Bos indicus, Bos taurus, and B. indicus × B. taurus), and for stature in dairy cattle, are presented. The aims were to discover SNP associated with all traits studied, but especially RFI, and further to test the consistency of SNP effects across different cattle populations and breed types. The data were analyzed within data sets and within breed types by using a mixed model and fitting 1 SNP at a time. In each case, the number of significant SNP was more than expected by chance alone. A total of 75 SNP from the reference population with 50K chip data were significant (P < 0.001) for RFI, with a false discovery rate of 68%. These 75 SNP were mapped on 24 different BTA. Of the 75 SNP, the 9 most significant SNP were detected on BTA 3, 5, 7, and 8, with P ≤ 6.0 × 10(-5). In a population of Angus cattle ergently selected for high and low RFI and 10K chip data, 111 SNP were significantly (P < 0.001) associated with RFI, with a false discovery rate of 7%. Approximately 103 of these SNP were therefore likely to represent true positives. Because of the small number of SNP common to both the 10K and 50K SNP chips, only 27 SNP were significantly (P < 0.05) associated with RFI in the 2 populations. However, other chromosome regions were found that contained SNP significantly associated with RFI in both data sets, although no SNP within the region showed a consistent effect on RFI. The SNP effects were consistent between data sets only when estimated within the same breed type.
Publisher: Springer Science and Business Media LLC
Date: 28-04-2021
DOI: 10.1186/S12711-021-00633-2
Abstract: Nellore cattle ( Bos indicus ) are well-known for their adaptation to warm and humid environments. Hair length and coat color may impact heat tolerance. The Nellore breed has been strongly selected for white coat, but bulls generally exhibit darker hair ranging from light grey to black on the head, neck, hump, and knees. Given the potential contribution of coat color variation to the adaptation of cattle populations to tropical and sub-tropical environments, our aim was to map positional and functional candidate genetic variants associated with darkness of hair coat (DHC) in Nellore bulls. We performed a genome-wide association study (GWAS) for DHC using data from 432 Nellore bulls that were genotyped for more than 777 k single nucleotide polymorphism (SNP) markers. A single major association signal was detected in the vicinity of the agouti signaling protein gene ( ASIP ). The analysis of whole-genome sequence (WGS) data from 21 bulls revealed functional variants that are associated with DHC, including a structural rearrangement involving ASIP ( ASIP -SV1). We further characterized this structural variant using Oxford Nanopore sequencing data from 13 Australian Brahman heifers, which share ancestry with Nellore cattle we found that this variant originates from a 1155-bp deletion followed by an insertion of a transposable element of more than 150 bp that may impact the recruitment of ASIP non-coding exons. Our results indicate that the variant ASIP sequence causes darker coat pigmentation on specific parts of the body, most likely through a decreased expression of ASIP and consequently an increased production of eumelanin.
Publisher: Oxford University Press (OUP)
Date: 07-2013
Abstract: The aim of this study was to assess the accuracy of genomic predictions for 19 traits including feed efficiency, growth, and carcass and meat quality traits in beef cattle. The 10,181 cattle in our study had real or imputed genotypes for 729,068 SNP although not all cattle were measured for all traits. Animals included Bos taurus, Brahman, composite, and crossbred animals. Genomic EBV (GEBV) were calculated using 2 methods of genomic prediction [BayesR and genomic BLUP (GBLUP)] either using a common training dataset for all breeds or using a training dataset comprising only animals of the same breed. Accuracies of GEBV were assessed using 5-fold cross-validation. The accuracy of genomic prediction varied by trait and by method. Traits with a large number of recorded and genotyped animals and with high heritability gave the greatest accuracy of GEBV. Using GBLUP, the average accuracy was 0.27 across traits and breeds, but the accuracies between breeds and between traits varied widely. When the training population was restricted to animals from the same breed as the validation population, GBLUP accuracies declined by an average of 0.04. The greatest decline in accuracy was found for the 4 composite breeds. The BayesR accuracies were greater by an average of 0.03 than GBLUP accuracies, particularly for traits with known genes of moderate to large effect mutations segregating. The accuracies of 0.43 to 0.48 for IGF-I traits were among the greatest in the study. Although accuracies are low compared with those observed in dairy cattle, genomic selection would still be beneficial for traits that are hard to improve by conventional selection, such as tenderness and residual feed intake. BayesR identified many of the same quantitative trait loci as a genomewide association study but appeared to map them more precisely. All traits appear to be highly polygenic with thousands of SNP independently associated with each trait.
Publisher: American Dairy Science Association
Date: 08-2012
Abstract: Selection of animals for breeding ranked on estimated breeding value maximizes genetic gain in the next generation but does not necessarily maximize long-term response. An alternative method, as practiced by plant breeders, is to build a desired genotype by selection on specific loci. Maximal long-term response in animal breeding requires selection on estimated breeding values with constraints on coancestry. In this paper, we compared long-term genetic response using either a genotype building or a genomic estimated breeding value (GEBV) strategy for the Australian Selection Index (ASI), a measure of profit. First, we used real marker effects from the Australian Dairy Herd Improvement Scheme to estimate breeding values for chromosome segments (approximately 25 cM long) for 2,650 Holstein bulls. Second, we selected 16 animals to be founders for a simulated breeding program where, between them, founders contain the best possible combination of 2 segments from 2 animals at each position in the genome. Third, we mated founder animals and their descendants over 30 generations with 2 breeding objectives: (1) to create a population with the "ideal genotype," where the best 2 segments from the founders segregate at each position, or (2) obtain the highest possible response in ASI with coancestry lower than that achieved under breeding objective 1. Results show that genotype building achieved the ideal genotype for breeding objective 1 and obtained a large gain in ASI over the current population (+A$864.99). However, selection on overall GEBV had greater short-term response and almost as much long-term gain (+A$820.42). When coancestry was lowered under breeding objective 2, selection on overall GEBV achieved a higher response in ASI than the genotype building strategy. Selection on overall GEBV seems more flexible in its selection decisions and was therefore better able to precisely control coancestry while maximizing ASI. We conclude that selection on overall GEBV while minimizing average coancestry is the more practical strategy for dairy cattle where selection is for highly polygenic traits, the reproductive rate is relatively low, and there is low tolerance of coancestry. The outcome may be different for traits controlled by few loci of relatively large effects or for different species. In contrast to other simulations, our results indicate that response to selection on overall GEBV may continue for several generations. This is because long-term genetic change in complex traits requires favorable changes to allele frequencies for many loci located throughout the genome.
Publisher: Public Library of Science (PLoS)
Date: 23-10-2015
Publisher: Wiley
Date: 27-05-2011
DOI: 10.1111/J.1365-2052.2011.02208.X
Abstract: Although genomic selection offers the prospect of improving the rate of genetic gain in meat, wool and dairy sheep breeding programs, the key constraint is likely to be the cost of genotyping. Potentially, this constraint can be overcome by genotyping selection candidates for a low density (low cost) panel of SNPs with sparse genotype coverage, imputing a much higher density of SNP genotypes using a densely genotyped reference population. These imputed genotypes would then be used with a prediction equation to produce genomic estimated breeding values. In the future, it may also be desirable to impute very dense marker genotypes or even whole genome re-sequence data from moderate density SNP panels. Such a strategy could lead to an accurate prediction of genomic estimated breeding values across breeds, for ex le. We used genotypes from 48 640 (50K) SNPs genotyped in four sheep breeds to investigate both the accuracy of imputation of the 50K SNPs from low density SNP panels, as well as prospects for imputing very dense or whole genome re-sequence data from the 50K SNPs (by leaving out a small number of the 50K SNPs at random). Accuracy of imputation was low if the sparse panel had less than 5000 (5K) markers. Across breeds, it was clear that the accuracy of imputing from sparse marker panels to 50K was higher if the genetic ersity within a breed was lower, such that relationships among animals in that breed were higher. The accuracy of imputation from sparse genotypes to 50K genotypes was higher when the imputation was performed within breed rather than when pooling all the data, despite the fact that the pooled reference set was much larger. For Border Leicesters, Poll Dorsets and White Suffolks, 5K sparse genotypes were sufficient to impute 50K with 80% accuracy. For Merinos, the accuracy of imputing 50K from 5K was lower at 71%, despite a large number of animals with full genotypes (2215) being used as a reference. For all breeds, the relationship of in iduals to the reference explained up to 64% of the variation in accuracy of imputation, demonstrating that accuracy of imputation can be increased if sires and other ancestors of the in iduals to be imputed are included in the reference population. The accuracy of imputation could also be increased if pedigree information was available and was used in tracking inheritance of large chromosome segments within families. In our study, we only considered methods of imputation based on population-wide linkage disequilibrium (largely because the pedigree for some of the populations was incomplete). Finally, in the scenarios designed to mimic imputation of high density or whole genome re-sequence data from the 50K panel, the accuracy of imputation was much higher (86-96%). This is promising, suggesting that in silico genome re-sequencing is possible in sheep if a suitable pool of key ancestors is sequenced for each breed.
Publisher: Springer Science and Business Media LLC
Date: 26-02-2008
Publisher: Springer Science and Business Media LLC
Date: 04-07-2018
Publisher: Springer Science and Business Media LLC
Date: 04-09-2014
DOI: 10.1007/S00122-014-2386-8
Abstract: Potatoes are highly heterozygous and the conventional breeding of superior germplasm is challenging, but use of a combination of MAS and EBVs can accelerate genetic gain. Cultivated potatoes are highly heterozygous due to their outbreeding nature, and suffer acute inbreeding depression. Modern potato cultivars also exhibit tetrasomic inheritance. Due to this genetic heterogeneity, the large number of target traits and the specific requirements of commercial cultivars, potato breeding is challenging. A conventional breeding strategy applies phenotypic recurrent selection over a number of generations, a process which can take over 10 years. Recently, major advances in genetics and molecular biology have provided breeders with molecular tools to accelerate gains for some traits. Marker-assisted selection (MAS) can be effectively used for the identification of major genes and quantitative trait loci that exhibit large effects. There are also a number of complex traits of interest, such as yield, that are influenced by a large number of genes of in idual small effect where MAS will be difficult to deploy. Progeny testing and the use of pedigree in the analysis can provide effective identification of the superior genetic factors that underpin these complex traits. Recently, it has been shown that estimated breeding values (EBVs) can be developed for complex potato traits. Using a combination of MAS and EBVs for simple and complex traits can lead to a significant reduction in the length of the breeding cycle for the identification of superior germplasm.
Publisher: Public Library of Science (PLoS)
Date: 14-09-2020
Publisher: Wiley
Date: 09-10-2017
DOI: 10.1111/JBG.12299
Abstract: We performed a genome-wide mapping for the age at first calving (AFC) with the goal of annotating candidate genes that regulate fertility in Nellore cattle. Phenotypic data from 762 cows and 777k SNP genotypes from 2,992 bulls and cows were used. Single nucleotide polymorphism (SNP) effects based on the single-step GBLUP methodology were blocked into adjacent windows of 1 Megabase (Mb) to explain the genetic variance. SNP windows explaining more than 0.40% of the AFC genetic variance were identified on chromosomes 2, 8, 9, 14, 16 and 17. From these windows, we identified 123 coding protein genes that were used to build gene networks. From the association study and derived gene networks, putative candidate genes (e.g., PAPPA, PREP, FER1L6, TPR, NMNAT1, ACAD10, PCMTD1, CRH, OPKR1, NPBWR1 and NCOA2) and transcription factors (TF) (STAT1, STAT3, RELA, E2F1 and EGR1) were strongly associated with female fertility (e.g., negative regulation of luteinizing hormone secretion, folliculogenesis and establishment of uterine receptivity). Evidence suggests that AFC inheritance is complex and controlled by multiple loci across the genome. As several windows explaining higher proportion of the genetic variance were identified on chromosome 14, further studies investigating the interaction across haplotypes to better understand the molecular architecture behind AFC in Nellore cattle should be undertaken.
Publisher: Elsevier BV
Date: 02-2014
DOI: 10.1016/J.MEATSCI.2013.07.008
Abstract: Previous association studies revealed several single nucleotide polymorphisms (SNPs) that explained the observed phenotypic variation for meat tenderness and long-chain omega-3 polyunsaturated fatty acid (PUFA) content of Australian lamb. To confirm the validity of these associated SNPs at predicting meat tenderness and omega-3 PUFA content, an independent validation study was designed. The OvineSNP50 genotypes of these animals were used to impute the 192 SNP Meat Quality Research (MQR) panel genotypes on nearly 6200 animals from the Cooperative Research Centre for Sheep Industry Innovation Information Nucleus Flock and Sheep Genomics Falkiner Memorial Field Station flock. Association analysis revealed numerous SNP from the 192 SNP MQR panel that were associated with carcass quality - fat depth at the C-site and eye muscle depth shear force at day 1 and day 5 after slaughter (SF1 and SF5) and omega-3 PUFA content at P<0.01. However, 1 SNP was independently validated for SF5 (i.e. CAST_101781475). The magnitude of the effect of each significant SNP and the relative allele frequencies across Merino-, Maternal- and Terminal-sired progeny was determined. The independently validated SNP for SF5 and the associated SNP with omega-3 PUFA content will accelerate efforts to improve these phenotypic traits in Australian lamb.
Publisher: Wiley
Date: 17-07-2014
DOI: 10.1111/AGE.12197
Abstract: The extent of linkage disequilibrium (LD) between genetic loci has implications for both association studies and the accuracy of genomic prediction. To characterise the persistence of LD in erse sheep breeds, two SNP genotyping platforms were used. First, existing SNP genotypes from 63 breeds obtained using the ovine SNP50 BeadChip (49,034 loci) were used to estimate LD decay in populations with contrasting levels of genetic ersity. Given the paucity of marker pairs separated by short physical distances on the SNP50 BeadChip, genotyping was subsequently performed for four breeds using the recently developed ovine HD BeadChip that assays approximately 600,000 SNPs with an average genomic spacing of 5 kb. This facilitated a highly accurate estimate of LD over short genomic distances (<30 kb) and revealed LD varies considerably between sheep breeds. Further, sheep appear to contain generally lower levels of LD than do other domestic species, likely a reflection of aspects of their past population history.
Publisher: Springer Science and Business Media LLC
Date: 06-01-2020
DOI: 10.1007/S00122-019-03526-7
Abstract: Multi-environment models using marker-based kinship information for both additive and dominance effects can accurately predict hybrid performance in different environments. Sorghum is an important hybrid crop that is grown extensively in many subtropical and tropical regions including Northern NSW and Queensland in Australia. The highly varying weather patterns in the Australian summer months mean that sorghum hybrids exhibit a great deal of variation in yield between locations. To ultimately enable prediction of the outcome of crossing parental lines, both additive effects on yield performance and dominance interaction effects need to be characterised. This paper demonstrates that fitting a linear mixed model that includes both types of effects calculated using genetic markers in relationship matrices improves predictions. Genotype by environment interactions was investigated by comparing FA1 (single-factor analytic) and FA2 (two-factor analytic) structures. The G×E causes a change in hybrid rankings between trials with a difference of up to 25% of the hybrids in the top 10% of each trial. The prediction accuracies increased with the addition of the dominance term (over and above that achieved with an additive effect alone) by an average of 15% and a maximum of 60%. The percentage of dominance of the total genetic variance varied between trials with the trials with higher broad-sense heritability having the greater percentage of dominance. The inclusion of dominance in the factor analytic models improves the accuracy of the additive effects. Breeders selecting high yielding parents for crossing need to be aware of effects due to environment and dominance.
Publisher: Research Square Platform LLC
Date: 09-09-2020
DOI: 10.21203/RS.3.RS-50937/V1
Abstract: To further the understanding of the evolution of transcriptional regulation, we profiled genome-wide transcriptional start sites ( TSSs ) in two sub-species, Bos taurus taurus and Bos taurus indicus , that erged approximately 500,000 years ago. Evolutionarily ergent TSSs were observed in more than half of the genes expressed across the sub-species, ranging from extreme cases in which a TSS was observed only in one sub-species to intermediate situations in which a corresponding TSS had been translocated by 50 nucleotides, to situations where the number of TSS differed between the sub-species. Fetal and adult stages not only had their own regulatory profile of active and inactive genes but also their own pattern of TSSs. Given indicus are more adapted to heat, we also specifically investigated TSSs for heat shock proteins. More variation was observed in number of TSSs for heat shock proteins in indicus than taurus . This study confirmed that most genes are regulated in a tissue-specific manner.
Publisher: American Dairy Science Association
Date: 08-2009
Abstract: Dairy farming is carried out under a wide range of production environments, including large variations in the level of feeding. Although reranking of dairy sires based on the level of feeding of their daughters has been reported, detecting the genetic mutations that cause this genotype by environment interaction has not been previously attempted. In our experiment to find genetic markers for such mutations, we selected 388 Holstein bulls from the Australian dairy bull population and genotyped them for 9,919 single nucleotide polymorphism (SNP) markers. Production data, consisting of first-lactation test-day records for milk yield, fat yield, protein yield, protein percentage, and fat percentage, from the daughters of the genotyped bulls were used to estimate the effect of each SNP, which was modeled as a regression on herd mean test-day yield, where herd mean test-day yield is a descriptor of the environment. Data were analyzed with 4 models in 2 models, daughter records were analyzed directly, with and without taking sire relationships into account. With the other 2 models, sire reaction norms for each trait were calculated and marker effects on the sire reaction norms were estimated with and without taking sire relationships into account. The results showed that using daughter records directly and accounting for sire relationships was necessary to obtain high power and to limit the number of false positives. With this approach, SNP with significant effects were found for all traits. Log transformation of the data did not affect the power of gene detection. The significant markers were categorized according to their joint effects on production and environmental sensitivity. Potential gene candidates and application of the markers is discussed. About one-third of the significant markers affect intercept and slope in opposite directions, and some of these facilitate marker-assisted selection for robustness.
Publisher: Wiley
Date: 03-2013
DOI: 10.1111/PBR.12037
Publisher: Wiley
Date: 31-01-2008
DOI: 10.1111/J.1439-0388.2007.00687.X
Abstract: The aim of this paper was to characterize the ersity among haplotypes based on 22 single nucleotide polymorphisms (SNPs) and one deletion within four casein genes in two geographically distant goat populations, the Sicilian Girgentana breed and the Norwegian goat breed. Forty Girgentana goats were genotyped for the aforementioned polymorphisms and the resulting data set was compared with 436 goats from the Norwegian population previously genotyped for these markers. Several casein gene polymorphisms were not in Hardy-Weinberg equilibrium either in Girgentana, or in the Norwegian breed. The SNP haplotype frequencies for the four casein genes were calculated and despite the large geographical distance and phenotypic ergence between these breeds, a proportion of casein loci haplotypes were found to be identical between both Norwegian and Girgentana goats. However, for the CSN2 gene there were no common haplotypes between the two populations. The level of linkage disequilibrium between the casein genes was less in the Girgentana population than in the Norwegian population.
Publisher: American Dairy Science Association
Date: 03-2014
Abstract: Residual feed intake (RFI), as a measure of feed conversion during growth, was estimated for around 2,000 growing Holstein-Friesian heifer calves aged 6 to 9 mo in New Zealand and Australia, and in iduals from the most and least efficient deciles (low and high RFI phenotypes) were retained. These animals (78 New Zealand cows, 105 Australian cows) were reevaluated during their first lactation to determine if ergence for RFI observed during growth was maintained during lactation. Mean daily body weight (BW) gain during assessment as calves had been 0.86 and 1.15 kg for the respective countries, and the ergence in RFI between most and least efficient deciles for growth was 21% (1.39 and 1.42 kg of dry matter, for New Zealand and Australia, respectively). At the commencement of evaluation during lactation, the cows were aged 26 to 29 mo. All were fed alfalfa and grass cubes it was the sole diet in New Zealand, whereas 6 kg of crushed wheat/d was also fed in Australia. Measurements of RFI during lactation occurred for 34 to 37 d with measurements of milk production (daily), milk composition (2 to 3 times per week), BW and BW change (1 to 3 times per week), as well as body condition score (BCS). Daily milk production averaged 13.8 kg for New Zealand cows and 20.0 kg in Australia. No statistically significant differences were observed between calf RFI decile groups for dry matter intake, milk production, BW change, or BCS however a significant difference was noted between groups for lactating RFI. Residual feed intake was about 3% lower for lactating cows identified as most efficient as growing calves, and no negative effects on production were observed. These results support the hypothesis that calves ergent for RFI during growth are also ergent for RFI when lactating. The causes for this reduced ergence need to be investigated to ensure that genetic selection programs based on low RFI (better efficiency) are robust.
Publisher: Public Library of Science (PLoS)
Date: 07-04-2015
Publisher: Springer Science and Business Media LLC
Date: 21-06-2007
Publisher: Oxford University Press (OUP)
Date: 09-11-2019
DOI: 10.1093/JAS/SKY428
Publisher: Springer Science and Business Media LLC
Date: 2014
Publisher: American Dairy Science Association
Date: 08-2010
Abstract: Multiple-trait genome-wide association study (GWAS) analyses were compared with single-trait GWAS for power to discover and subsequently validate genetic markers (single nucleotide polymorphisms SNP) associated with dairy traits. The SNP associations were discovered in 1 Holstein population and validated in both a Holstein population consisting of bulls younger than those in the discovery population and a Jersey population. The multivariate methods used were a principal component analysis and a series of bivariate analyses. The statistical power of detecting associations using multiple-trait GWAS was as good as or better than that of the best single-trait GWAS. Additional SNP associations were found with the multivariate methods that had not been discovered in the single-trait analyses this was achieved without an increase in the false discovery rate. From the multivariate analysis, 4 common pleiotropic patterns were identified among the putative quantitative trait loci (QTL) affecting the Australian selection index. These patterns could be interpreted as a primary effect of the putative QTL on 1 or more milk components and secondary effects on other components. The multivariate analysis did not appear to increase the precision with which putative QTL were mapped.
Publisher: Springer Science and Business Media LLC
Date: 12-03-2021
DOI: 10.1186/S12711-021-00622-5
Abstract: A cost-effective strategy to explore the complete DNA sequence in animals for genetic evaluation purposes is to sequence key ancestors of a population, followed by imputation mechanisms to infer marker genotypes that were not originally reported in a target population of animals genotyped with single nucleotide polymorphism (SNP) panels. The feasibility of this process relies on the accuracy of the genotype imputation in that population, particularly for potential causal mutations which may be at low frequency and either within genes or regulatory regions. The objective of the present study was to investigate the imputation accuracy to the sequence level in a Nellore beef cattle population, including that for variants in annotation classes which are more likely to be functional. Information of 151 key sequenced Nellore sires were used to assess the imputation accuracy from bovine HD BeadChip SNP (~ 777 k) to whole-genome sequence. The choice of the sires aimed at optimizing the imputation accuracy of a genotypic database, comprised of about 10,000 genotyped Nellore animals. Genotype imputation was performed using two computational approaches: FImpute3 and Minimac4 (after using Eagle for phasing). The accuracy of the imputation was evaluated using a fivefold cross-validation scheme and measured by the squared correlation between observed and imputed genotypes, calculated by in idual and by SNP. SNPs were classified into a range of annotations, and the accuracy of imputation within each annotation classification was also evaluated. High average imputation accuracies per animal were achieved using both FImpute3 (0.94) and Minimac4 (0.95). On average, common variants (minor allele frequency (MAF) 0.03) were more accurately imputed by Minimac4 and low-frequency variants (MAF ≤ 0.03) were more accurately imputed by FImpute3. The inherent Minimac4 Rsq imputation quality statistic appears to be a good indicator of the empirical Minimac4 imputation accuracy. Both software provided high average SNP-wise imputation accuracy for all classes of biological annotations. Our results indicate that imputation to whole-genome sequence is feasible in Nellore beef cattle since high imputation accuracies per in idual are expected. SNP-wise imputation accuracy is software-dependent, especially for rare variants. The accuracy of imputation appears to be relatively independent of annotation classification.
Publisher: Springer Science and Business Media LLC
Date: 2009
Publisher: Wiley
Date: 04-2022
DOI: 10.1111/EVA.13378
Abstract: The increasing global demand for food, due to the continuous growth of human population, requires improvements in the efficiency and sustainability of animal production systems. In addition, several challenges facing farming of aquatic and terrestrial organisms need to be overcome to ensure food security in the upcoming decades, e.g. adaptation to climate change, reduced availability of conventional animal feed ingredients, emerging infectious and parasitic diseases, among others. Genomic technologies such as massive parallel sequencing, high‐throughput genotyping, genome selection and gene editing, combined with highly efficient computational methods can accelerate the rate of genetic progress in animal breeding. Thus, such technologies can help us meet the needs for protein sources for human consumption in the upcoming years. This Special Issue aims at presenting current advancements in the field of genomic tools applied to aquatic and terrestrial farmed animal populations.
Publisher: Oxford University Press (OUP)
Date: 03-2011
DOI: 10.1534/GENETICS.110.123943
Abstract: Orthologous positions of 55 genes associated with height in four human populations were located on the bovine genome. Single nucleotide polymorphisms close to eight of these genes were significantly associated with stature in cattle (Bos taurus and Bos indicus). This suggests that these genes may contribute to controlling stature across mammalian species.
Publisher: Oxford University Press (OUP)
Date: 10-2012
Abstract: In genome-wide association studies, failure to remove variation due to population structure results in spurious associations. In contrast, for predictions of future phenotypes or estimated breeding values from dense SNP data, exploiting population structure arising from relatedness can actually increase the accuracy of prediction in some cases, for ex le, when the selection candidates are offspring of the reference population where the prediction equation was derived. In populations with large effective population size or with multiple breeds and strains, it has not been demonstrated whether and when accounting for or removing variation due to population structure will affect the accuracy of genomic prediction. Our aim in this study was to determine whether accounting for population structure would increase the accuracy of genomic predictions, both within and across breeds. First, we have attempted to decompose the accuracy of genomic prediction into contributions from population structure or linkage disequilibrium (LD) between markers and QTL using a erse multi-breed sheep (Ovis aries) data set, genotyped for 48,640 SNP. We demonstrate that SNP from a single chromosome can achieve up to 86% of the accuracy for genomic predictions using all SNP. This result suggests that most of the prediction accuracy is due to population structure, because a single chromosome is expected to capture relationships but is unlikely to contain all QTL. We then explored principal component analysis (PCA) as an approach to disentangle the respective contributions of population structure and LD between SNP and QTL to the accuracy of genomic predictions. Results showed that fitting an increasing number of principle components (PC as covariates) decreased within breed accuracy until a lower plateau was reached. We speculate that this plateau is a measure of the accuracy due to LD. In conclusion, a large proportion of the accuracy for genomic predictions in our data was due to variation associated with population structure. Surprisingly, accounting for this structure generally decreased the accuracy of across breed genomic predictions.
Publisher: Elsevier BV
Date: 11-2005
Publisher: Springer Science and Business Media LLC
Date: 20-05-2021
DOI: 10.1186/S12864-021-07694-Z
Abstract: Improving yield prediction and selection efficiency is critical for tree breeding. This is vital for macadamia trees with the time from crossing to production of new cultivars being almost a quarter of a century. Genomic selection (GS) is a useful tool in plant breeding, particularly with perennial trees, contributing to an increased rate of genetic gain and reducing the length of the breeding cycle. We investigated the potential of using GS methods to increase genetic gain and accelerate selection efficiency in the Australian macadamia breeding program with comparison to traditional breeding methods. This study evaluated the prediction accuracy of GS in a macadamia breeding population of 295 full-sib progeny from 32 families (29 parents, reciprocals combined), along with a subset of parents. Historical yield data for tree ages 5 to 8 years were used in the study, along with a set of 4113 SNP markers. The traits of focus were average nut yield from tree ages 5 to 8 years and yield stability, measured as the standard deviation of yield over these 4 years. GBLUP GS models were used to obtain genomic estimated breeding values for each genotype, with a five-fold cross-validation method and two techniques: prediction across related populations and prediction across unrelated populations. Narrow-sense heritability of yield and yield stability was low (h 2 = 0.30 and 0.04, respectively). Prediction accuracy for yield was 0.57 for predictions across related populations and 0.14 when predicted across unrelated populations. Accuracy of prediction of yield stability was high (r = 0.79) for predictions across related populations. Predicted genetic gain of yield using GS in related populations was 474 g/year, more than double that of traditional breeding methods (226 g/year), due to the halving of generation length from 8 to 4 years. The results of this study indicate that the incorporation of GS for yield into the Australian macadamia breeding program may accelerate genetic gain due to reduction in generation length, though the cost of genotyping appears to be a constraint at present.
Publisher: American Dairy Science Association
Date: 03-2016
Abstract: Routine genomic evaluations in animal breeding are usually based on either a BLUP with genomic relationship matrix (GBLUP) or single nucleotide polymorphism (SNP) BLUP model. For a multi-step genomic evaluation, these 2 alternative genomic models were proven to give equivalent predictions for genomic reference animals. The model equivalence was verified also for young genotyped animals without phenotypes. Due to incomplete linkage disequilibrium of SNP markers to genes or causal mutations responsible for genetic inheritance of quantitative traits, SNP markers cannot explain all the genetic variance. A residual polygenic effect is normally fitted in the genomic model to account for the incomplete linkage disequilibrium. In this study, we start by showing the proof that the multi-step GBLUP and SNP BLUP models are equivalent for the reference animals, when they have a residual polygenic effect included. Second, the equivalence of both multi-step genomic models with a residual polygenic effect was also verified for young genotyped animals without phenotypes. Additionally, we derived formulas to convert genomic estimated breeding values of the GBLUP model to its components, direct genomic values and residual polygenic effect. Third, we made a proof that the equivalence of these 2 genomic models with a residual polygenic effect holds also for single-step genomic evaluation. Both the single-step GBLUP and SNP BLUP models lead to equal prediction for genotyped animals with phenotypes (e.g., reference animals), as well as for (young) genotyped animals without phenotypes. Finally, these 2 single-step genomic models with a residual polygenic effect were proven to be equivalent for estimation of SNP effects, too.
Publisher: Wiley
Date: 03-2018
DOI: 10.2135/CROPSCI2017.08.0469
Abstract: Genomic selection can increase the rate of genetic gain in plant breeding programs by shortening the breeding cycle. Gain can also be increased through higher selection intensities, as the size of the population available for selection can be increased by predicting performance of non‐phenotyped, but genotyped, lines. This paper demonstrates the application of genomic prediction in a sorghum [ Sorghum bicolor (L.) Moench] breeding program and compares different genomic prediction models incorporating relationship information derived from molecular markers and pedigree information. In cross‐validation, the models using marker‐based relationships had higher selection accuracy than the selection accuracy for models that used pedigree‐based relationships. It was demonstrated that genotypes that have not been included in the trials could be predicted quite accurately using marker information alone. The accuracy of prediction declined as the genomic relationship of the predicted in idual to the training population declined. We also demonstrate that the accuracy of genomic breeding values from the prediction error variance derived from the mixed model equations is a useful indicator of the accuracy of prediction. This will be useful to plant breeders, as the accuracy of the genomic predictions can be assessed with confidence before phenotypes are available. Four distinct environments were studied and shown to perform very differently with respect to the accuracy of predictions and the composition of estimated breeding values. This paper shows that there is considerable potential for sorghum breeding programs to benefit from the implementation of genomic selection.
Publisher: Oxford University Press (OUP)
Date: 09-2011
DOI: 10.1534/GENETICS.111.128082
Abstract: Related in iduals share potentially long chromosome segments that trace to a common ancestor. We describe a phasing algorithm (ChromoPhase) that utilizes this characteristic of finite populations to phase large sections of a chromosome. In addition to phasing, our method imputes missing genotypes in in iduals genotyped at lower marker density when more densely genotyped relatives are available. ChromoPhase uses a pedigree to collect an in idual’s (the proband) surrogate parents and offspring and uses genotypic similarity to identify its genomic surrogates. The algorithm then cycles through the relatives and genomic surrogates one at a time to find shared chromosome segments. Once a segment has been identified, any missing information in the proband is filled in with information from the relative. We tested ChromoPhase in a simulated population consisting of 400 in iduals at a marker density of 1500/M, which is approximately equivalent to a 50K bovine single nucleotide polymorphism chip. In simulated data, 99.9% loci were correctly phased and, when imputing from 100 to 1500 markers, more than 87% of missing genotypes were correctly imputed. Performance increased when the number of generations available in the pedigree increased, but was reduced when the sparse genotype contained fewer loci. However, in simulated data, ChromoPhase correctly imputed at least 12% more genotypes than fastPHASE, depending on sparse marker density. We also tested the algorithm in a real Holstein cattle data set to impute 50K genotypes in animals with a sparse 3K genotype. In these data 92% of genotypes were correctly imputed in animals with a genotyped sire. We evaluated the accuracy of genomic predictions with the dense, sparse, and imputed simulated data sets and show that the reduction in genomic evaluation accuracy is modest even with imperfectly imputed genotype data. Our results demonstrate that imputation of missing genotypes, and potentially full genome sequence, using long-range phasing is feasible.
Publisher: Wiley
Date: 05-2012
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/AN15222
Abstract: This review examines research aimed at reducing enteric methane emissions from the Australian dairy industry. Calorimeter measurements of 220 forage-fed cows indicate an average methane yield of 21.1 g methane (CH4)/kg dry matter intake. Adoption of this empirical methane yield, rather than the equation currently used in the Australian greenhouse gas inventory, would reduce the methane emissions attributed to the Australian dairy industry by ~10%. Research also indicates that dietary lipid supplements and feeding high amounts of wheat substantially reduce methane emissions. It is estimated that, in 1980, the Australian dairy industry produced ~185 000 t of enteric methane and total enteric methane intensity was ~33.6 g CH4/kg milk. In 2010, the estimated production of enteric methane was 182 000 t, but total enteric methane intensity had declined ~40% to 19.9 g CH4/kg milk. This remarkable decline in methane intensity and the resultant improvement in the carbon footprint of Australian milk production was mainly achieved by increased per-cow milk yield, brought about by the on-farm adoption of research findings related to the feeding and breeding of dairy cows. Options currently available to further reduce the carbon footprint of Australian milk production include the feeding of lipid-rich supplements such as cottonseed, brewers grains, cold-pressed canola, hominy meal and grape marc, as well as feeding of higher rates of wheat. Future technologies for further reducing methane emissions include genetic selection of cows for improved feed conversion to milk or low methane intensity, vaccines to reduce ruminal methanogens and chemical inhibitors of methanogenesis.
Publisher: Springer Science and Business Media LLC
Date: 23-11-2015
Publisher: Oxford University Press (OUP)
Date: 2016
Publisher: Springer Science and Business Media LLC
Date: 13-07-2014
DOI: 10.1038/NG.3034
Abstract: The 1000 bull genomes project supports the goal of accelerating the rates of genetic gain in domestic cattle while at the same time considering animal health and welfare by providing the annotated sequence variants and genotypes of key ancestor bulls. In the first phase of the 1000 bull genomes project, we sequenced the whole genomes of 234 cattle to an average of 8.3-fold coverage. This sequencing includes data for 129 in iduals from the global Holstein-Friesian population, 43 in iduals from the Fleckvieh breed and 15 in iduals from the Jersey breed. We identified a total of 28.3 million variants, with an average of 1.44 heterozygous sites per kilobase for each in idual. We demonstrate the use of this database in identifying a recessive mutation underlying embryonic death and a dominant mutation underlying lethal chrondrodysplasia. We also performed genome-wide association studies for milk production and curly coat, using imputed sequence variants, and identified variants associated with these traits in cattle.
Publisher: Springer Science and Business Media LLC
Date: 2014
Publisher: Oxford University Press (OUP)
Date: 29-10-2019
DOI: 10.1093/JAS/SKY417
Publisher: Wiley
Date: 03-2016
DOI: 10.3835/PLANTGENOME2015.06.0046
Abstract: Genomic selection (GS) provides an attractive option for accelerating genetic gain in perennial ryegrass ( Lolium perenne L .) improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time). Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD) in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match ersity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot). Genomic estimated breeding values (GEBVs) for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively). Higher accuracy of GEBVs was obtained for flowering time (up to 0.7), partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4‐yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy.
Publisher: Wiley
Date: 14-01-2016
DOI: 10.1111/AGE.12411
Abstract: Polyceraty (presence of multiple horns) is rare in modern day ungulates. Although not found in wild sheep, polyceraty does occur in a small number of domestic sheep breeds covering a wide geographical region. Damara are fat-tailed hair sheep, from the south-western region of Africa, which display polyceraty, with horn number ranging from zero to four. We conducted a genome-wide association study for horn number with 43 Damara genotyped with 606 006 SNP markers. The analysis revealed a region with multiple significant SNPs on ovine chromosome 2, in a location different from the mutation for polled in sheep on chromosome 10. The causal mutation for polyceraty was not identified however, the region associated with polyceraty spans nine HOXD genes, which are critical in embryonic development of appendages. Mutations in HOXD genes are implicated in polydactly phenotypes in mice and humans. There was no evidence for epistatic interactions contributing to polyceraty. This is the first report on the genetic mechanisms underlying polyceraty in the under-studied Damara.
Publisher: Springer Science and Business Media LLC
Date: 26-06-2014
DOI: 10.1007/S00122-014-2341-8
Abstract: We have demonstrated that genomic selection in erse wheat landraces for resistance to leaf, stem and strip rust is possible, as genomic breeding values were moderately accurate. Markers with large effects in the Bayesian analysis confirmed many known genes, while also discovering many previously uncharacterised genome regions associated with rust scores. Genomic selection, where selection decisions are based on genomic estimated breeding values (GEBVs) derived from genome-wide DNA markers, could accelerate genetic progress in plant breeding. In this study, we assessed the accuracy of GEBVs for rust resistance in 206 hexaploid wheat (Triticum aestivum) landraces from the Watkins collection of phenotypically erse wheat genotypes from 32 countries. The landraces were genotyped for 5,568 SNPs using an Illumina iSelect 9 K bead chip assay and phenotyped for field-based leaf rust (Lr), stem rust (Sr) and stripe rust (Yr) responses across multiple years. Genomic Best Linear Unbiased Prediction (GBLUP) and a Bayesian Regression method (BayesR) were used to predict GEBVs. Based on fivefold cross-validation, the accuracy of genomic prediction averaged across years was 0.35, 0.27 and 0.44 for Lr, Sr and Yr using GBLUP and 0.33, 0.38 and 0.30 for Lr, Sr and Yr using BayesR, respectively. Inclusion of PCR-predicted genotypes for known rust resistance genes increased accuracy more substantially when the marker was diagnostic (Lr34/Sr57/Yr18) for the presence-absence of the gene rather than just linked (Sr2). Investigation of the impact of genetic relatedness between validation and reference lines on accuracy of genomic prediction showed that accuracy will be higher when each validation line had at least one close relationship to the reference lines. Overall, the prediction accuracies achieved in this study are encouraging, and confirm the feasibility of genomic selection in wheat. In several instances, estimated marker effects were confirmed by published literature and results of mapping experiments using Watkins accessions.
Publisher: Wiley
Date: 04-09-2009
DOI: 10.1111/J.1365-2052.2009.01908.X
Abstract: Quantitative trait loci affecting clinical mastitis were detected and fine mapped to a narrow region on bovine chromosome 6 in the Norwegian Red cattle population. The region includes the casein gene cluster and several candidate genes thought to influence clinical mastitis. The most significant results were found for SNPs within the Mucin 7 gene. This gene encodes an antimicrobial peptide and constitutes part of the first line of defence for the mucosal immune system. Detection of long haplotypes extending several Mb may indicate that artificial selection has influenced the haplotype structures in the region. A search for selection sweeps supports this observation and coincides with association results found both by single SNP and haplotype analyses. Our analyses identified haplotypes carrying quantitative trait loci alleles associated with high protein yield and simultaneously fewer incidences of clinical mastitis. The fact that such haplotypes are found in relative high frequencies in Norwegian Red may reflect the combined breeding goal that is characterized by selection for both milk production and disease resistance. The identification of these haplotypes raises the possibility of overcoming the unfavourable genetic correlation between these traits through haplotype-assisted selection.
Publisher: Elsevier BV
Date: 2015
Publisher: FapUNIFESP (SciELO)
Date: 29-11-2018
Publisher: Wiley
Date: 18-10-2012
DOI: 10.1111/J.1365-2052.2011.02271.X
Abstract: The aim of this study was to fine map the genomic location of the Horns locus in the Australian Merino sheep population and to identify markers that can be used to predict the horn phenotype. A linkage disequilibrium analysis of horn data from Australian Merino sheep mapped the Horns locus to a small region on chromosome 10. A single nucleotide polymorphism in the region was found to be highly predictive for the polled phenotype in an experimental population of Merino sheep. This was owing to a dominance effect of one of the alleles when inherited maternally. It was suggested that a genetic test would provide a good predictor of the polled phenotype. Finally, an evaluation of industry data showed that the SNP is at very different frequencies in Poll Merino sheep that have been bred for polledness (based on phenotype alone) compared with the Merino sheep breed.
Publisher: Springer Science and Business Media LLC
Date: 31-07-2023
Publisher: Wiley
Date: 04-2010
DOI: 10.1111/J.1439-0388.2009.00831.X
Abstract: There is increasing use of dense single nucleotide polymorphisms (SNPs) for whole-genome association studies (WGAS) in livestock to map and identify quantitative trait loci (QTL). These studies rely on linkage disequilibrium (LD) to detect an association between SNP genotypes and phenotypes. The power and precision of these WGAS are unknown, and will depend on the extent of LD in the experimental population. One complication for WGAS in livestock populations is that they typically consist of many paternal half-sib families, and in some cases full-sib families unless this subtle population stratification is accounted for, many spurious associations may be reported. Our aim was to investigate the power, precision and false discovery rates of WGAS for QTL discovery, with a commercial SNP array, given existing patterns of LD in cattle. We also tested the efficiency of selective genotyping animals. A total of 365 cattle were genotyped for 9232 SNPs. We simulated a QTL effect as well as polygenic and environmental effects for all animals. One QTL was simulated on a randomly chosen SNP and accounted for 5%, 10% or 18% of the total variance. The power to detect a moderate-sized additive QTL (5% of the phenotypic variance) with 365 animals genotyped was 37% (p < 0.001). Most importantly, if pedigree structure was not accounted for, the number of false positives significantly increased above those expected by chance alone. Selective genotyping also resulted in a significant increase in false positives, even when pedigree structure was accounted for.
Publisher: Springer Science and Business Media LLC
Date: 16-06-2011
Publisher: Elsevier BV
Date: 05-2007
Publisher: Public Library of Science (PLoS)
Date: 27-03-2014
Publisher: Cold Spring Harbor Laboratory
Date: 16-07-2021
DOI: 10.1101/2021.07.16.452615
Abstract: Most traits in livestock, crops and humans are polygenic, that is, a large number of loci contribute to genetic variation. Effects at these loci lie along a continuum ranging from common low-effect to rare high-effect variants that cumulatively contribute to the overall phenotype. Statistical methods to calculate the effect of these loci have been developed and can be used to predict phenotypes in new in iduals. In agriculture, these methods are used to select superior in iduals using genomic breeding values in humans these methods are used to quantitatively measure an in idual’s disease risk, termed polygenic risk scores. Both fields typically use SNP array genotypes for the analysis. Recently, genotyping-by-sequencing has become popular, due to lower cost and greater genome coverage (including structural variants). Oxford Nanopore Technologies’ (ONT) portable sequencers have the potential to combine the benefits genotyping-by-sequencing with portability and decreased turn-around time. This introduces the potential for in-house clinical genetic disease risk screening in humans or calculating genomic breeding values on-farm in agriculture. Here we demonstrate the potential of the later by calculating genomic breeding values for four traits in cattle using low-coverage ONT sequence data and comparing these breeding values to breeding values calculated from SNP arrays. At sequencing coverages between 2X and 4X the correlation between ONT breeding values and SNP array-based breeding values was 0.92 when imputation was used and 0.88 when no imputation was used. With an average sequencing coverage of 0.5x the correlation between the two methods was between 0.85 and 0.92 using imputation, depending on the trait. This demonstrates that ONT sequencing has great potential for in clinic or on-farm genomic prediction. Genomic prediction is a method that uses a large number of genetic markers to predict complex phenotypes in livestock, crops and humans. Currently the techniques we use to determine genotypes requires complex equipment which can only be used in laboratories. However, Oxford Nanopore Technologies’ have released a portable DNA sequencer, which can genotype a range of organisms in the field. As a result of the device’s higher error rate, it has largely only been considered for specific applications, such as characterising large mutations. Here we demonstrated that despite the devices error rate, accurate genomic prediction is also possible using this portable device. The ability to accurately predict complex phenotypes such as the predisposition to schizophrenia in humans or lifetime fertility in livestock in-situ would decrease the turnaround time and ultimately increase the utility of this method in the human clinical and on-farm settings.
Publisher: Cold Spring Harbor Laboratory
Date: 07-04-2019
DOI: 10.1101/601658
Abstract: Many genome variants shaping mammalian phenotype are hypothesized to regulate gene transcription and/or to be under selection. However, most of the evidence to support this hypothesis comes from human studies. Systematic evidence for regulatory and evolutionary signals contributing to complex traits in a different mammalian model is needed. Sequence variants associated with gene expression (eQTLs) and concentration of metabolites (mQTLs), and under histone modification marks in several tissues were discovered from multi-omics data of over 400 cattle. Variants under selection and evolutionary constraint were identified using genome databases of multiple species. These analyses defined 30 sets of variants and for each set we estimated the genetic variance the set explained across 34 complex traits in 11,923 bulls and 32,347 cows with 17,669,372 imputed variants. The per-variant trait heritability of these sets across traits was highly consistent ( r .94) between bulls and cows. Based on the per-variant heritability, conserved sites across 100 vertebrate species and mQTLs ranked the highest, followed by eQTLs, young variants, those under histone modification marks and selection signatures. From these results, we defined a F unctional- A nd- E volutionary T rait H eritability (FAETH) score indicating the functionality and predicted heritability of each variant. In 7,551 Danish cattle, the high FAETH-ranking variants had significantly increased genetic variances and genomic prediction accuracies in 3 production traits compared to the low FAETH-ranking variants. The FAETH framework combines the information of gene regulation, evolution and trait heritability to rank variants and the publicly available FAETH data provides a set of biological priors for cattle genomic selection worldwide.
Publisher: Hindawi Limited
Date: 18-08-2010
Publisher: American Dairy Science Association
Date: 10-2014
Publisher: Cold Spring Harbor Laboratory
Date: 05-11-2021
DOI: 10.1101/2021.11.05.467409
Abstract: Reproductive traits are often genetically correlated. Yet, we don’t fully understand the complexities, synergism, or trade-offs between male and female fertility. Here, we introduce correlation scan, a novel framework for identifying the drivers or antagonizers of the genetic correlation between male and female fertility traits across the bovine genome. The identification of these regions facilitates the understanding of the complexity of these traits. Although the methodology was applied to cattle phenotypes, using high-density SNP genotypes, the general framework developed can be applied to any species or traits, and it can easily accommodate genome sequence data.
Publisher: Cold Spring Harbor Laboratory
Date: 04-01-2018
DOI: 10.1101/242792
Abstract: Topological association domains (TADs) are chromosomal domains characterised by frequent internal DNA-DNA interactions. The transcription factor CTCF binds to conserved DNA sequence patterns called CTCF binding motifs to either prohibit or facilitate chromosomal interactions. TADs and CTCF binding motifs control gene expression, but they are not yet well defined in the bovine genome. In this paper, we sought to improve the annotation of bovine TADs and CTCF binding motifs, and assess whether the new annotation can reduce the search space for cis -regulatory variants. We used genomic synteny to map TADs and CTCF binding motifs from humans, mice, dogs and macaques to the bovine genome. We found that our mapped TADs exhibited the same hallmark properties of those sourced from experimental data, such as housekeeping gene, tRNA genes, CTCF binding motifs, SINEs, H3K4me3 and H3K27ac. Then we showed that runs of genes with the same pattern of allele-specific expression (ASE) (either favouring paternal or maternal allele) were often located in the same TAD or between the same conserved CTCF binding motifs. Analyses of variance showed that when averaged across all bovine tissues tested, TADs explained 14% of ASE variation (standard deviation, SD: 0.056), while CTCF explained 27% (SD: 0.078). Furthermore, we showed that the quantitative trait loci (QTLs) associated with gene expression variation (eQTLs) or ASE variation (aseQTLs), which were identified from mRNA transcripts from 141 lactating cows’ white blood and milk cells, were highly enriched at putative bovine CTCF binding motifs. The most significant aseQTL and eQTL for each genic target were located within the same TAD as the gene more often than expected (Chi-Squared test P-value ≤ 0.001). Our results suggest that genomic synteny can be used to functionally annotate conserved transcriptional components, and provides a tool to reduce the search space for causative regulatory variants in the bovine genome.
Publisher: Cold Spring Harbor Laboratory
Date: 20-12-2022
DOI: 10.1101/2022.12.19.521119
Abstract: Mate-allocation in breeding programs can improve progeny performance by exploiting non-additive effects. Breeding decisions in the mate-allocation approach are based on predicted progeny merit rather than parental breeding value. This is particularly attractive when non-additive effects are significant, and the best-predicted progeny can be clonally propagated, for ex le sugarcane. We compared mate-allocation strategies that leverage non-additive and heterozygosity effects to maximise sugarcane clonal performance to schemes that use only additive effects to maximise breeding value. We used phenotypes and genotypes from a population of 2,909 clones phenotyped in Australia’s sugarcane breeding program’s final assessment trials for three traits: tonnes of cane per hectare (TCH), commercial cane sugar (CCS), and fibre. The clones from the last generation of this data set were used as parents to simulate families from all possible crosses (1,225), each with 50 progenies. The breeding and clonal values of progeny were predicted using GBLUP (considering only additive effects) and the e-GBLUP model (incorporating additive, non-additive and heterozygosity effects). Integer linear programming was used to identify the optimal mate-allocation among the selected parents. Compared to the breeding value, the predicted progeny value of allocated crossing pairs based on clonal performance (e-GBLUP) increased by 57%, 12%, and 16% for TCH, CCS, and fibre, respectively. In our study, the mate-allocation strategy exploiting non-additive and heterozygosity effects resulted in better clonal performance. However, there was a noticeable decline in additive gain, particularly for TCH, which might have been caused by the presence of large epistatic effects. When crosses were chosen based on clonal performance for TCH, progenies’ inbreeding coefficients were found significantly lower than for random mating, indicating that utilising non-additive and heterozygosity effects has advantages for controlling inbreeding depression. Therefore, mate-allocation is recommended in clonal crops to improve clonal performance and reduce inbreeding.
Publisher: Springer Science and Business Media LLC
Date: 29-10-2013
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/AN14311
Abstract: It is suggested that one-third of the inter-animal differences in efficiency is explained by differences in digestion, heat production, body composition and activity while the remaining variation is the result of energy expenditure due to biological processes such as ion pumps and mitochondrial function. Inefficient animals may be wasting energy on inefficient processes resulting in increased heat production that may be reflected by differences in skin and core temperature. While the association between heat production and residual feed intake (RFI) has been touched on, it is yet to be fully elucidated. It is hypothesised that more efficient animals will expend less energy as heat, which will be reflected by differences in core and skin temperature measures. Fifty-four primiparous, Holstein-Friesian cows previously assessed for RFI (26 inefficient/high RFI, 28 efficient/low RFI) were selected and drafted into outdoor holding yards for measurements on two occasions (once during lactation and once during the non-lactating ‘dry’ period). Measures of body temperature were obtained using an infrared (IR) camera to obtain skin (surface) temperatures at multiple locations [muzzle, eye, jaw, ear, leg (front and back), rump, shoulder, teat, udder, side and tail] and rectal temperatures were measured using a digital thermometer. Respiration rates (RR) were obtained by counting the number of flank movements in 1 min. A subset of 16 cows (8 efficient and 8 inefficient) were utilised for further IR imagery in an undercover environment (to eliminate the influences of external environments). Skin temperature measurement obtained using an IR camera during the outdoor period demonstrated that inefficient cows had higher (0.65°C) teat temperatures (P = 0.05). Rectal temperature and RR were not influenced by efficiency group. When IR images were obtained undercover inefficient cows tended to have higher shoulder (0.85°C) and neck (0.98°C) temperatures than efficient cows (P 0.087) while udder temperature was significantly greater (1.61°C) for inefficient than efficient cows (P = 0.018). These data indicate that some of the differences in efficiency may be attributed to differences in thermoregulation, as reflected by differences in skin (but not core) temperature and that IR imagery is a suitable method for determining these differences in a non-invasive manner. Further research is required to further establish these relationships, and the measurement of skin temperatures should be undertaken indoors to eliminate external environmental influences.
Publisher: Springer Science and Business Media LLC
Date: 27-05-2020
DOI: 10.1186/S12711-020-00546-6
Abstract: Distinct domestication events, adaptation to different climatic zones, and ergent selection in productive traits have shaped the genomic differences between taurine and indicine cattle. In this study, we assessed the impact of artificial selection and environmental adaptation by comparing whole-genome sequences from European taurine and Asian indicine breeds and from African cattle. Next, we studied the impact of ergent selection by exploiting predicted and experimental functional annotation of the bovine genome. We identified selective sweeps in beef cattle taurine and indicine populations, including a 430-kb selective sweep on indicine cattle chromosome 5 that is located between 47,670,001 and 48,100,000 bp and spans five genes, i.e. HELB , IRAK3 , ENSBTAG00000026993 , GRIP1 and part of HMGA2 . Regions under selection in indicine cattle display significant enrichment for promoters and coding genes. At the nucleotide level, sites that show a strong ergence in allele frequency between European taurine and Asian indicine are enriched for the same functional categories. We identified nine single nucleotide polymorphisms (SNPs) in coding regions that are fixed for different alleles between subspecies, eight of which were located within the DNA helicase B ( HELB ) gene. By mining information from the 1000 Bull Genomes Project, we found that HELB carries mutations that are specific to indicine cattle but also found in taurine cattle, which are known to have been subject to indicine introgression from breeds, such as N’Dama, Anatolian Red, Marchigiana, Chianina, and Piedmontese. Based on in-house genome sequences, we proved that mutations in HELB segregate independently of the copy number variation HMGA2 -CNV, which is located in the same region. Major genomic sequence differences between Bos taurus and Bos indicus are enriched for promoter and coding regions. We identified a 430-kb selective sweep in Asian indicine cattle located on chromosome 5, which carries SNPs that are fixed in indicine populations and located in the coding sequences of the HELB gene. HELB is involved in the response to DNA damage including exposure to ultra-violet light and is associated with reproductive traits and yearling weight in tropical cattle. Thus, HELB likely contributed to the adaptation of tropical cattle to their harsh environment.
Publisher: American Society for Horticultural Science
Date: 04-2019
Abstract: Current macadamia breeding programs involve a lengthy and laborious two-stage selection process: evaluation of a large number of unreplicated seedling progeny, followed by replicated trials of clonally propagated elite seedlings. Yield component traits, such as nut-in-shell weight (NW), kernel weight (KW), and kernel recovery (KR) are commercially important, are more easily measured than yield, and have a higher heritability. A genome-wide association study (GWAS) combined with marker-assisted selection offers an opportunity to reduce the time of candidate evaluation. In this study, a total of 281 progeny from 32 families, and 18 of their 29 parents have been genotyped for 7126 single nucleotide polymorphism (SNP) markers. A GWAS was performed using ASReml with 4352 SNPs. We found five SNPs significantly associated with NW, nine with KW, and one with KR. Further, three of the top 10 markers for NW and KW were shared between the two traits. Future macadamia breeding could involve prescreening of in iduals for desired traits using these significantly associated markers, with only predicted elite in iduals continuing to the second stage of selection, thus potentially reducing the selection process by 7 years.
Publisher: Research Square Platform LLC
Date: 12-08-2022
DOI: 10.21203/RS.3.RS-1778864/V1
Abstract: Background Genomic prediction describes the use of SNP genotypes to predict complex phenotypes and has been widely applied in humans and agriculture species. Genotyping-by-sequencing, a method which uses low-coverage sequence data paired with genotype imputation, is becoming increasingly popular for SNP genotyping. The development of Oxford Nanopore Technologies’ (ONT) MinION sequencer has now made genotyping-by-sequencing portable and rapid. Here we evaluate the speed and accuracy of genomic predictions using low-coverage ONT sequence data in a population of cattle using four imputation approaches. We also investigate the effect of SNP reference panel size on their performance. Results SNP array genotypes and ONT sequence data for 64 beef heifers were used to calculate genomic estimated breeding values (GEBVs) from 641k SNP for four traits. Accuracy of the GEBVs was much higher when flanking SNP from sequence data was used to help impute the 641k panel used for genomic predictions. Using the imputation package QUILT, correlations between ONT and low-density SNP array genomic breeding values were greater than 0.91 and up to 0.97 for sequencing coverages as low as 0.1x using a panel of 48 million SNP that flanked the 641k in the prediction equation. Imputation time was significantly reduced by decreasing the number of flanking sequence SNP used in imputation for all methods. Genomic breeding values calculated using QUILT also had higher correlations to high density SNP arrays than genomic breeding values from imputed-low density arrays for coverages as low as 0.5x. Conclusions Here we demonstrated accurate genomic prediction is possible with ONT sequence data from sequencing coverages as low as 0.1x, and imputation time can be as short as 10 minutes per s le.
Publisher: Oxford University Press (OUP)
Date: 05-2011
DOI: 10.1534/GENETICS.107.084301
Abstract: When a genetic marker and a quantitative trait locus (QTL) are in linkage disequilibrium (LD) in one population, they may not be in LD in another population or their LD phase may be reversed. The objectives of this study were to compare the extent of LD and the persistence of LD phase across multiple cattle populations. LD measures r and r2 were calculated for syntenic marker pairs using genomewide single-nucleotide polymorphisms (SNP) that were genotyped in Dutch and Australian Holstein–Friesian (HF) bulls, Australian Angus cattle, and New Zealand Friesian and Jersey cows. Average r2 was ∼0.35, 0.25, 0.22, 0.14, and 0.06 at marker distances 10, 20, 40, 100, and 1000 kb, respectively, which indicates that genomic selection within cattle breeds with r2 ≥ 0.20 between adjacent markers would require ∼50,000 SNPs. The correlation of r values between populations for the same marker pairs was close to 1 for pairs of very close markers (& kb) and decreased with increasing marker distance and the extent of ergence between the populations. To find markers that are in LD with QTL across erged breeds, such as HF, Jersey, and Angus, would require ∼300,000 markers.
Publisher: Wiley
Date: 11-11-2008
DOI: 10.1111/J.1365-2052.2008.01773.X
Abstract: The objective of this study was to identify QTL for growth rate in the blacklip abalone Haliotis rubra using selective DNA pooling. Three full-sibling families of H. rubra derived from crosses of wild broodstock were used. DNA was extracted from the largest and smallest 10% of progeny and combined into two pools for each phenotypic tail. The DNA pools were typed with 139 microsatellites, and markers showing significant differences between the peak height ratios of alleles inherited from the parents were in idually genotyped and analysed by interval mapping. A strong correlation (r = 0.94, P < 0.001) was found between the t-values from the analysis of pools and the t-values from the analysis of in idual genotypes. Based on the interval mapping analysis, QTL were detected on nine linkage groups at a chromosome-wide P < 0.01 and one linkage group at a chromosome-wide P < 0.05. The study demonstrated that selective DNA pooling is efficient and effective as a first-pass screen for the discovery of QTL in an aquaculture species.
Publisher: CSIRO Publishing
Date: 2013
DOI: 10.1071/AN12369
Abstract: The rumen of the dairy cow contains a rich and erse collection of microbes that during feed digestion produce significant quantities of methane gas and ammonia, both of which contribute to greenhouse gas emissions. Strategies to redirect rumen carbon and nitrogen metabolism away from these products provide opportunities for significant productivity improvements in livestock systems not only by improving nutrient retention, but also by reducing greenhouse gas emissions. In order to develop these strategies, a greater knowledge of the ersity of the microbes within their rumen and their genomic capability is required. Many have used several techniques to study the rumen microbes, and the technology continues to improve. Among them include researchers at the Department of Primary Industries Victoria (DPI Vic) and the Dairy Futures Cooperative Research Centre (CRC) who are addressing the issue of regulation of methane emissions in dairy cattle, while scientists in Queensland and New South Wales, as part of the most recent Beef CRC program, focus on beef cattle. In this brief review, we examine how the techniques used in rumen microbial ecology have changed, and how technology improvements continue to allow us to examine the rumen microbiota of cattle and other ruminants, so as to better understand and possibly select animals with superior traits, leading to improvements in feed efficiency, methane emissions and nitrogen retention.
Publisher: Springer Science and Business Media LLC
Date: 18-11-2014
Publisher: Springer Science and Business Media LLC
Date: 17-06-2019
DOI: 10.1038/S41587-019-0152-9
Abstract: Crop improvements can help us to meet the challenge of feeding a population of 10 billion, but can we breed better varieties fast enough? Technologies such as genotyping, marker-assisted selection, high-throughput phenotyping, genome editing, genomic selection and de novo domestication could be galvanized by using speed breeding to enable plant breeders to keep pace with a changing environment and ever-increasing human population.
Publisher: Springer Science and Business Media LLC
Date: 2008
Publisher: Springer Science and Business Media LLC
Date: 10-11-2021
DOI: 10.1038/S41586-021-04066-1
Abstract: Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources 1 . So far, few chickpea ( Cicer arietinum ) germplasm accessions have been characterized at the genome sequence level 2 . Here we present a detailed map of variation in 3,171 cultivated and 195 wild accessions to provide publicly available resources for chickpea genomics research and breeding. We constructed a chickpea pan-genome to describe genomic ersity across cultivated chickpea and its wild progenitor accessions. A ergence tree using genes present in around 80% of in iduals in one species allowed us to estimate the ergence of Cicer over the last 21 million years. Our analysis found chromosomal segments and genes that show signatures of selection during domestication, migration and improvement. The chromosomal locations of deleterious mutations responsible for limited genetic ersity and decreased fitness were identified in elite germplasm. We identified superior haplotypes for improvement-related traits in landraces that can be introgressed into elite breeding lines through haplotype-based breeding, and found targets for purging deleterious alleles through genomics-assisted breeding and/or gene editing. Finally, we propose three crop breeding strategies based on genomic prediction to enhance crop productivity for 16 traits while avoiding the erosion of genetic ersity through optimal contribution selection (OCS)-based pre-breeding. The predicted performance for 100-seed weight, an important yield-related trait, increased by up to 23% and 12% with OCS- and haplotype-based genomic approaches, respectively.
Publisher: Springer Science and Business Media LLC
Date: 25-03-2022
Publisher: American Dairy Science Association
Date: 07-2010
Abstract: Genome-wide association studies (GWAS) were used to discover genomic regions explaining variation in dairy production and fertility traits. Associations were detected with either single nucleotide polymorphism (SNP) markers or haplotypes of SNP alleles. An across-breed validation strategy was used to narrow the genomic interval containing causative mutations. There were 39,048 SNP tested in a discovery population of 780 Holstein sires and validated in 386 Holsteins and 364 Jersey sires. Previously identified mutations affecting milk production traits were confirmed. In addition, several novel regions were identified, including a putative quantitative trait loci for fertility on chromosome 18 that was detected only using haplotypes greater than 3 SNP long. It was found that the precision of quantitative trait loci mapping increased with haplotype length as did the number of validated haplotypes discovered, especially across breed. Promising candidate genes have been identified in several of the validated regions.
Publisher: Oxford University Press (OUP)
Date: 02-09-2021
DOI: 10.1093/BIOINFORMATICS/BTAB630
Abstract: Trimming and filtering tools are useful in DNA sequencing analysis because they increase the accuracy of sequence alignments and thus the reliability of results. Oxford nanopore technologies (ONT) trimming and filtering tools are currently rudimentary, generally only filtering reads based on whole read average quality. This results in discarding reads that contain regions of high-quality sequence. Here, we propose Prowler, a trimmer that uses a window-based approach inspired by algorithms used to trim short read data. Importantly, we retain the phase and read length information by optionally replacing trimmed sections with Ns. Prowler was applied to mammalian and bacterial datasets, to assess its effect on alignment and assembly, respectively. Compared to data filtered with Nanofilt, alignments of data trimmed with Prowler had lower error rates and more mapped reads. Assemblies of Prowler trimmed data had a lower error rate than those filtered with Nanofilt however, this came at some cost to assembly contiguity. Prowler is implemented in Python and is available at github.com/ProwlerForNanopore/ProwlerTrimmer. Supplementary data are available at Bioinformatics online.
Publisher: CSIRO Publishing
Date: 03-08-2021
DOI: 10.1071/AN21097
Abstract: Context Studies have shown that favourable genetic correlations exist between female and male fertility traits. However, investigations regarding these correlations in Australian tropical beef cattle are limited to either pedigree or single-breed analysis. Aim The study aims to use genomic information to estimate genetic parameters of six female and seven male fertility traits measured during the first 2 years of life, in two tropical breeds. Methods Single-, bivariate and multi-trait models were used to analyse fertility data from Brahman (BB 996 cows and 1022 bulls) and Tropical Composite (TC 1091 cows and 998 bulls) cattle genotyped with high-density single-nucleotide polymorphism chip assay. Key results Heritability estimates in BB cows ranged from low (0.07 ± 0.04) for days to calving at the first calving opportunity (DC1, days) to high (0.57 ± 0.08) for age at first corpus luteum (AGECL, days). In BB bulls, estimates varied from low (0.09 ± 0.05) for sperm motility (score 1–5) to high (0.64 ± 0.06) for scrotal circumference (SC) measured at 24 months (SC24, cm). Similarly, heritability estimates in TC cows were low (0.04 ± 0.03) for DC1 and high (0.69 ± 0.02) for AGECL. In TC bulls, the heritability was low (0.09 ± 0.05) for sperm motility and high (0.69 ± 0.07) for SC24. Within-sex for both breeds, blood concentrations of insulin growth-factor 1 (IGF1) measured in cows at 18 months (IGF1c) were negatively correlated with female fertility phenotypes. In BB, across-sex, bulls’ blood concentration of IGF1 measured at 6 months (IGF1b) was a good indicator trait for the following four female traits: AGECL, the first postpartum anoestrus interval, age at first calving and DC1. In TC, IGF1b and percentage normal sperm were good predictors of female fertility phenotypes. Conclusions The heritability estimates and genomic correlations from the present study generally support and confirmed the earlier estimates from pedigree analyses. The findings suggest that selection for female fertility traits will benefit male fertility, and vice versa. Implications Heritability estimates and genomic correlations suggest that we can select for fertility traits measured early in life, with benefits within and across sex. Using traits available through veterinary assessment of bull fertility as selection indicators will enhance bull and cow fertility, which can lead to better breeding rates in tropical herds.
Publisher: Elsevier BV
Date: 04-2013
DOI: 10.1016/J.TIG.2012.11.009
Abstract: As the global population and global wealth both continue to increase, so will the demand for livestock products, especially those that are highly nutritious. However, competition with other uses for land and water resources will also intensify, necessitating more efficient livestock production. In addition, as climate change escalates, reduced methane emissions from cattle and sheep will be a critical goal. Application of new technologies, including genomic selection and advanced reproductive technologies, will play an important role in meeting these challenges. Genomic selection, which enables prediction of the genetic merit of animals from genome-wide SNP markers, has already been adopted by dairy industries worldwide and is expected to double genetic gains for milk production and other traits. Here, we review these gains. We also discuss how the use of whole-genome sequence data should both accelerate the rate of gain and enable rapid discovery and elimination of genetic defects from livestock populations.
Publisher: Springer Science and Business Media LLC
Date: 15-02-2021
Publisher: Wiley
Date: 11-10-2011
Publisher: Wiley
Date: 24-09-2021
DOI: 10.1111/JBG.12651
Abstract: Vietnamese smallholder dairy cows (VDC) are the result of crossbreeding between different zebu (ZEB) and taurine dairy breeds through many undefined generations. Thus, the predominant breed composition of VDC is currently unknown. This study aimed to evaluate the level of genetic ersity and breed composition of VDC. The SNP data of 344 animals from 32 farms located across four dairy regions of Vietnam were collected and merged with genomic reference data, which included three ZEB breeds: Red Sindhi, Sahiwal and Brahman, three taurine breeds: Holstein (HOL), Jersey (JER) and Brown Swiss (BSW), and a composite breed: Chinese Yellow cattle. Diversity and admixture analyses were applied to the merged data set. The VDC were not excessively inbred, as indicated by very low inbreeding coefficients (Wright's F IS ranged from −0.017 to 0.003). The genetic fractions in the test herds suggested that the VDC are primarily composed of HOL (85.0%) however, JER (6.0%), BSW 5.3%) and ZEB (4.5%) had also contributed. Furthermore, major genotype groupings in the test herds were pure HOL (48%), B3:15/16HOL_1/16ZEB (22%) and B2:7/8HOL_1/8ZEB (12%). The genetic makeup of the VDC is mainly components of various dairy breeds but also has a small percentage of ZEB thus, the VDC could be a good genetic base for selecting high milk‐producing cows with some degree of adaptation to tropical conditions.
Publisher: Elsevier BV
Date: 05-2006
Publisher: Springer Science and Business Media LLC
Date: 26-04-2021
DOI: 10.1007/S00122-021-03822-1
Abstract: Non-additive genetic effects seem to play a substantial role in the expression of complex traits in sugarcane. Including non-additive effects in genomic prediction models significantly improves the prediction accuracy of clonal performance. In the recent decade, genetic progress has been slow in sugarcane. One reason might be that non-additive genetic effects contribute substantially to complex traits. Dense marker information provides the opportunity to exploit non-additive effects in genomic prediction. In this study, a series of genomic best linear unbiased prediction (GBLUP) models that account for additive and non-additive effects were assessed to improve the accuracy of clonal prediction. The reproducible kernel Hilbert space model, which captures non-additive genetic effects, was also tested. The models were compared using 3,006 genotyped elite clones measured for cane per hectare (TCH), commercial cane sugar (CCS), and Fibre content. Three forward prediction scenarios were considered to investigate the robustness of genomic prediction. By using a pseudo-diploid parameterization, we found significant non-additive effects that accounted for almost two-thirds of the total genetic variance for TCH. Average heterozygosity also had a major impact on TCH, indicating that directional dominance may be an important source of phenotypic variation for this trait. The extended-GBLUP model improved the prediction accuracies by at least 17% for TCH, but no improvement was observed for CCS and Fibre. Our results imply that non-additive genetic variance is important for complex traits in sugarcane, although further work is required to better understand the variance component partitioning in a highly polyploid context. Genomics-based breeding will likely benefit from exploiting non-additive genetic effects, especially in designing crossing schemes. These findings can help to improve clonal prediction, enabling a more accurate identification of variety candidates for the sugarcane industry.
Publisher: Springer Science and Business Media LLC
Date: 24-08-2017
DOI: 10.1007/S00122-017-2972-7
Abstract: Using NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection to accelerate improvement in grain end-use quality traits of wheat. Grain end-use quality traits are among the most important in wheat breeding. These traits are difficult to breed for, as their assays require flour quantities only obtainable late in the breeding cycle, and are expensive. These traits are therefore an ideal target for genomic selection. However, large reference populations are required for accurate genomic predictions, which are challenging to assemble for these traits for the same reasons they are challenging to breed for. Here, we use predictions of end-use quality derived from near infrared (NIR) or nuclear magnetic resonance (NMR), that require very small amounts of flour, as well as end-use quality measured by industry standard assay in a subset of accessions, in a multi-trait approach for genomic prediction. The NIR and NMR predictions were derived for 19 end-use quality traits in 398 accessions, and were then assayed in 2420 erse wheat accessions. The accessions were grown out in multiple locations and multiple years, and were genotyped for 51208 SNP. Incorporating NIR and NMR phenotypes in the multi-trait approach increased the accuracy of genomic prediction for most quality traits. The accuracy ranged from 0 to 0.47 before the addition of the NIR/NMR data, while after these data were added, it ranged from 0 to 0.69. Genomic predictions were reasonably robust across locations and years for most traits. Using NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection for grain end-use quality traits in wheat breeding.
Publisher: American Dairy Science Association
Date: 07-2018
Abstract: Residual feed intake (RFI) is defined as the difference between the actual and expected feed intake required to support animal maintenance and growth. Thus, a cow with a low RFI can obtain nutrients for maintenance and growth from a reduced amount of feed compared with a cow with a high RFI. Variation in RFI is underpinned by a combination of factors, including genetics, metabolism, thermoregulation and body composition hypothalamic-pituitary-adrenal (HPA) axis responsiveness is also a possible contributor. Responses to 3 metabolic challenges were measured in lactating and nonlactating dairy cattle. Sixteen Holstein Friesian cows with phenotypic RFI measurements that were obtained during the growth period (188-220 d old) were grouped as either low-calfhood RFI (n = 8) or high-calfhood RFI (n = 8). An ACTH (2 µg/kg of body weight), insulin (0.12 U/kg), and epinephrine (a low dose of 0.1 µg/kg and a high dose of 1.6 µg/kg of epinephrine) challenge were each conducted during both midlactation (122 ± 23.4 d in milk) and the nonlactating period (dry period approximately 38 d after cessation of milking). Cows were housed in metabolism stalls for the challenges and were fed a diet of alfalfa cubes ad libitum for at least 10 d before the experiment (lactating cows also were offered a total of 6 kg of dry matter/d of crushed wheat grain plus minerals fed as 3 kg of dry matter at each milking) and were fasted for 12 h before the challenges. The efficiency of conversion of feed into milk (the ratio of feed consumed to milk produced over the 7 d before the experiment) during midlactation was better (lower) in low-calfhood RFI cows, although dry matter intake did not differ between RFI groups. Low-calfhood RFI cows exhibited a lower plasma cortisol response to the ACTH challenge than high-calfhood RFI cows, particularly in midlactation (-15%). The low-calfhood RFI cows had a greater plasma insulin-like growth factor-1 response to the insulin challenge and plasma fatty acid response to epinephrine compared with the high-calfhood RFI cows. These data suggest that high-calfhood RFI cows exhibit a more responsive HPA axis. As ergence in RFI measured during growth is retained (although reduced) during lactation, it is possible that energy is used to respond to HPA axis activation at the expense of production in high-calfhood RFI dairy cattle during lactation and contributes to a decrease in overall feed use efficiency.
Publisher: CSIRO Publishing
Date: 2012
DOI: 10.1071/AN11172
Abstract: New genomic technologies can help farmers to (1) achieve higher annual rates of genetic gain through using genomically tested bulls in their herds, (2) select for ‘difficult’ to measure traits, such as feed conversion efficiency, methane emissions and energy balance, (3) select the best heifers to become herd replacements, (4) sell pedigree heifers at a premium, (5) use mating plans to optimise rates of genetic gain while controlling inbreeding, (6) achieve certainty in parentage of in idual cows and (7) avoid genetic defects that could arise from mating cows to bulls that are known carriers of genetic diseases that are the result of a single lethal mutation. The first use does not require genotyping females and could approximately double the net income per cow that arises due to genetic improvement, mainly through a reduction in generation interval. On the basis of current rates of genetic gain, the net profit from using genotyped bulls could be worth AU$20/cow per year and is permanent and cumulative. One of the most powerful uses of genomic selection is to select for economically important, yet difficult- or expensive-to-measure traits, such as residual feed intake or energy balance. Provided the accuracy of genomic breeding values is high enough (i.e. correlation between the true and estimated breeding values), these traits lend themselves well to genomic selection. For selecting replacement heifers, if genotyping costs are AU$50/cow, the net profit of genotyping 40 heifers to select the top 20 as replacements (per 100 cows) would be worth approximately AU$41 per cow. However, using parent average estimated breeding-value information is free and can already be used to select replacement heifers. So, genotyping costs would need to be very low to be more profitable than selecting on parent average estimated breeding value. However, extra value from genotyping can also be captured by using other strategies. For ex le, mating plans that use genomic relationships rather than pedigree relationships to capture inbreeding are superior in terms of reducing progeny inbreeding at a desired level of genetic gain, although pedigree does an adequate job. So, again, the benefits of genotyping are small ( AU$10). Ascertainment of pedigree is an additional use of genotyping and is potentially worth ~AU$30 per cow. Avoidance of genetic diseases and selling of pedigree heifers have a value that should be estimated case-by-case. Because genotyping costs continue to fall, it may become increasingly popular to capture the extra value from genotyping females.
Publisher: Springer Science and Business Media LLC
Date: 26-08-2020
DOI: 10.1186/S12711-020-00569-Z
Abstract: Temperament traits are of high importance across species. In humans, temperament or personality traits correlate with psychological traits and psychiatric disorders. In cattle, they impact animal welfare, product quality and human safety, and are therefore of direct commercial importance. We hypothesized that genetic factors that contribute to variation in temperament among in iduals within a species will be shared between humans and cattle. Using imputed whole-genome sequence data from 9223 beef cattle from three cohorts, a series of genome-wide association studies was undertaken on cattle flight time, a temperament phenotype measured as the time taken for an animal to cover a short-fixed distance after release from an enclosure. We also investigated the association of cattle temperament with polymorphisms in bovine orthologs of risk genes for neuroticism, schizophrenia, autism spectrum disorders (ASD), and developmental delay disorders in humans. Variants with the strongest associations were located in the bovine orthologous region that is involved in several behavioural and cognitive disorders in humans. These variants were also partially validated in independent cattle cohorts. Genes in these regions ( BARHL2 , NDN , SNRPN , MAGEL2 , A BCA12 , KIFAP3 , TOPAZ1 , FZD3 , UBE3A , and GABRA5 ) were enriched for the GO term neuron migration and were differentially expressed in brain and pituitary tissues in humans. Moreover, variants within 100 kb of ASD susceptibility genes were associated with cattle temperament and explained 6.5% of the total additive genetic variance in the largest cattle cohort. The ASD genes with the most significant associations were GABRB3 and CUL3 . Using the same 100 kb window, a weak association was found with polymorphisms in schizophrenia risk genes and no association with polymorphisms in neuroticism and developmental delay disorders risk genes. Our analysis showed that genes identified in a meta-analysis of cattle temperament contribute to neuron development functions and are differentially expressed in human brain tissues. Furthermore, some ASD susceptibility genes are associated with cattle temperament. These findings provide evidence that genetic control of temperament might be shared between humans and cattle and highlight the potential for future analyses to leverage results between species.
Publisher: Oxford University Press (OUP)
Date: 2019
Publisher: CSIRO Publishing
Date: 2019
DOI: 10.1071/AN18487
Abstract: About 80% of the world’s cattle are affected by ticks and tick-borne diseases, both of which cause significant production losses. Cattle host resistance to ticks is the most important factor affecting the economics of tick control, but it is largely neglected in tick-control programs due to technical difficulties and costs associated with identifying in idual-animal variation in resistance. The present paper reviews the scientific literature to identify factors affecting resistance of cattle to ticks and the biological mechanisms of host tick resistance, to develop alternative phenotype(s) for tick resistance. If new cost-effective phenotype(s) can be developed and validated, then tick resistance of cattle could be genetically improved using genomic selection, and incorporated into breeding objectives to simultaneously improve cattle productive attributes and tick resistance. The phenotype(s) could also be used to improve tick control by using cattle management. On the basis of the present review, it is recommended that three possible phenotypes (haemolytic analysis measures of skin hypersensitivity reactions simplified artificial tick infestations) be further developed to determine their practical feasibility for consistently, cost-effectively and reliably measuring cattle tick resistance in thousands of in idual animals in commercial and smallholder farmer herds in tropical and subtropical areas globally. During evaluation of these potential new phenotypes, additional measurements should be included to determine the possibility of developing a volatile-based resistance phenotype, to simultaneously improve cattle resistance to both ticks and biting flies. Because the current measurements of volatile chemistry do not satisfy the requirements of a simple, cost-effective phenotype for use in commercial cattle herds, consideration should also be given to inclusion of potentially simpler measures to enable indirect genetic selection for volatile-based resistance to ticks.
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/AN14200
Abstract: The objective of this experiment was to compare the whole-tract digestibility of dry matter (DM) and nitrogen (N) in Holstein-Friesian dairy cows selected for ergent feed conversion efficiency. The experiment used 16 primiparous Holstein–Friesian dairy cows selected based on their residual feed intake (RFI) measured as growing calves. The cows were housed in in idual metabolism stalls and fed lucerne cubes ad libitum plus 6 kg DM per day of crushed wheat grain. Feed intake, milk yield, faecal and urine output were measured for 5 days. Rumen fluid was collected per os from each cow on one occasion. Milk production parameters and intakes of DM, organic matter, neutral detergent fibre, acid detergent fibre and N did not differ between RFI groups. Apparent whole-tract DM digestibility and N digestibility did not differ between RFI treatment groups. Rumen metabolites were also unaffected by RFI. In conclusion, ergence in RFI as calves was not associated with differences in whole-tract DM or N digestibility in lactating cows. Therefore, emphasis on selection for phenotypic ergence in RFI may not contribute to improved utilisation of consumed nutrients in Australian Holstein-Friesian dairy cows.
Publisher: American Dairy Science Association
Date: 07-2012
Abstract: Achieving accurate genomic estimated breeding values for dairy cattle requires a very large reference population of genotyped and phenotyped in iduals. Assembling such reference populations has been achieved for breeds such as Holstein, but is challenging for breeds with fewer in iduals. An alternative is to use a multi-breed reference population, such that smaller breeds gain some advantage in accuracy of genomic estimated breeding values (GEBV) from information from larger breeds. However, this requires that marker-quantitative trait loci associations persist across breeds. Here, we assessed the gain in accuracy of GEBV in Jersey cattle as a result of using a combined Holstein and Jersey reference population, with either 39,745 or 624,213 single nucleotide polymorphism (SNP) markers. The surrogate used for accuracy was the correlation of GEBV with daughter trait deviations in a validation population. Two methods were used to predict breeding values, either a genomic BLUP (GBLUP_mod), or a new method, BayesR, which used a mixture of normal distributions as the prior for SNP effects, including one distribution that set SNP effects to zero. The GBLUP_mod method scaled both the genomic relationship matrix and the additive relationship matrix to a base at the time the breeds erged, and regressed the genomic relationship matrix to account for s ling errors in estimating relationship coefficients due to a finite number of markers, before combining the 2 matrices. Although these modifications did result in less biased breeding values for Jerseys compared with an unmodified genomic relationship matrix, BayesR gave the highest accuracies of GEBV for the 3 traits investigated (milk yield, fat yield, and protein yield), with an average increase in accuracy compared with GBLUP_mod across the 3 traits of 0.05 for both Jerseys and Holsteins. The advantage was limited for either Jerseys or Holsteins in using 624,213 SNP rather than 39,745 SNP (0.01 for Holsteins and 0.03 for Jerseys, averaged across traits). Even this limited and nonsignificant advantage was only observed when BayesR was used. An alternative panel, which extracted the SNP in the transcribed part of the bovine genome from the 624,213 SNP panel (to give 58,532 SNP), performed better, with an increase in accuracy of 0.03 for Jerseys across traits. This panel captures much of the increased genomic content of the 624,213 SNP panel, with the advantage of a greatly reduced number of SNP effects to estimate. Taken together, using this panel, a combined breed reference and using BayesR rather than GBLUP_mod increased the accuracy of GEBV in Jerseys from 0.43 to 0.52, averaged across the 3 traits.
Publisher: Springer Science and Business Media LLC
Date: 31-03-2017
DOI: 10.1007/S00122-017-2863-Y
Abstract: Heuristic genomic inbreeding controls reduce inbreeding in genomic breeding schemes without reducing genetic gain. Genomic selection is increasingly being implemented in plant breeding programs to accelerate genetic gain of economically important traits. However, it may cause significant loss of genetic ersity when compared with traditional schemes using phenotypic selection. We propose heuristic strategies to control the rate of inbreeding in outbred plants, which can be categorised into three types: controls during mate allocation, during selection, and simultaneous selection and mate allocation. The proposed mate allocation measure GminF allocates two or more parents for mating in mating groups that minimise coancestry using a genomic relationship matrix. Two types of relationship-adjusted genomic breeding values for parent selection candidates ([Formula: see text]) and potential offspring ([Formula: see text]) are devised to control inbreeding during selection and even enabling simultaneous selection and mate allocation. These strategies were tested in a case study using a simulated perennial ryegrass breeding scheme. As compared to the genomic selection scheme without controls, all proposed strategies could significantly decrease inbreeding while achieving comparable genetic gain. In particular, the scenario using [Formula: see text] in simultaneous selection and mate allocation reduced inbreeding to one-third of the original genomic selection scheme. The proposed strategies are readily applicable in any outbred plant breeding program.
Publisher: Wiley
Date: 14-08-2019
DOI: 10.1111/JBG.12429
Abstract: The aim of this study was to identify candidate regions associated with sexual precocity in Bos indicus. Nellore and Brahman were set as validation and discovery populations, respectively. SNP selected in Brahman to validate in Nellore were from gene regions affecting reproductive traits (G1) and significant SNP (p ≤ 10
Publisher: Oxford University Press (OUP)
Date: 2016
DOI: 10.2527/AF.2016-0002
Publisher: Wiley
Date: 17-02-2017
DOI: 10.1111/AGE.12541
Abstract: Economically important reproduction traits in sheep, such as number of lambs weaned and litter size, are expressed only in females and later in life after most selection decisions are made, which makes them ideal candidates for genomic selection. Accurate genomic predictions would lead to greater genetic gain for these traits by enabling accurate selection of young rams with high genetic merit. The aim of this study was to design and evaluate the accuracy of a genomic prediction method for female reproduction in sheep using daughter trait deviations (DTD) for sires and ewe phenotypes (when in idual ewes were genotyped) for three reproduction traits: number of lambs born (NLB), litter size (LSIZE) and number of lambs weaned. Genomic best linear unbiased prediction (GBLUP), BayesR and pedigree BLUP analyses of the three reproduction traits measured on 5340 sheep (4503 ewes and 837 sires) with real and imputed genotypes for 510 174 SNPs were performed. The prediction of breeding values using both sire and ewe trait records was validated in Merino sheep. Prediction accuracy was evaluated by across sire family and random cross-validations. Accuracies of genomic estimated breeding values (GEBVs) were assessed as the mean Pearson correlation adjusted by the accuracy of the input phenotypes. The addition of sire DTD into the prediction analysis resulted in higher accuracies compared with using only ewe records in genomic predictions or pedigree BLUP. Using GBLUP, the average accuracy based on the combined records (ewes and sire DTD) was 0.43 across traits, but the accuracies varied by trait and type of cross-validations. The accuracies of GEBVs from random cross-validations (range 0.17-0.61) were higher than were those from sire family cross-validations (range 0.00-0.51). The GEBV accuracies of 0.41-0.54 for NLB and LSIZE based on the combined records were amongst the highest in the study. Although BayesR was not significantly different from GBLUP in prediction accuracy, it identified several candidate genes which are known to be associated with NLB and LSIZE. The approach provides a way to make use of all data available in genomic prediction for traits that have limited recording.
Publisher: American Dairy Science Association
Date: 05-2010
Abstract: Good performance in extended lactations of dairy cattle may have a beneficial effect on food costs, health, and fertility. Because data for extended lactation performance is scarce, lactation persistency has been suggested as a suitable selection criterion. Persistency phenotypes were calculated in several ways: P1 was yield relative to an approximate peak, P2 was the slope after peak production, and P3 was a measure derived to be phenotypically uncorrelated to yield and calculated as a function of linear regressions on test-day deviations of days in milk. Phenotypes P1, P2, and P3 were calculated for sires as solutions estimated from a random regression model fitted to milk yield. Because total milk yield, calculated as the sum of daily sire solutions, was correlated to P1 and P2 (r=0.30 and 0.35 for P1 and P2, respectively), P1 and P2 were also adjusted for milk yield (P1adj and P2adj, respectively). To find genomic regions associated with the persistency phenotypes, we used a discovery population of 743 Holstein bulls proven before 2005 and 2 validation data sets of 357 Holstein bulls proven after 2005 and 294 Jersey sires. Two strategies were used to search for genomic regions associated with persistency: 1) persistency solutions were regressed on each single nucleotide polymorphism (SNP) in turn and 2) a genomic selection method (BayesA) was used where all SNP were fitted simultaneously. False discovery rates in the validation data were high (>66% in Holsteins and >77% in Jerseys). However, there were 2 genomic regions on chromosome 6 that validated in both breeds, including a cluster of 6 SNP at around 13.5 to 23.7 Mbp and another cluster of 5 SNP (70.4 to 75.6 Mbp). A third cluster validated in both breeds on chromosome 26 (0.33 to 1.46 Mbp). Validating SNP effects across 2 breeds is unlikely to happen by chance even when false discovery rates within each breed are high. However, marker-assisted selection on these selected SNP may not be the best way to improve this trait because the average variation explained by validated SNP was only 1 to 2%. Genomic selection could be a better alternative. Correlations between genomic breeding values predicted using all SNP simultaneously and estimated breeding values based on progeny test were twice as high as the equivalent correlations between estimated breeding values and parent average. Persistency is a good candidate for genomic selection because the trait is expressed late in lactation.
Publisher: Wiley
Date: 11-09-2015
DOI: 10.1111/AGE.12340
Abstract: Genotyping sheep for genome-wide SNPs at lower density and imputing to a higher density would enable cost-effective implementation of genomic selection, provided imputation was accurate enough. Here, we describe the design of a low-density (12k) SNP chip and evaluate the accuracy of imputation from the 12k SNP genotypes to 50k SNP genotypes in the major Australian sheep breeds. In addition, the impact of imperfect imputation on genomic predictions was evaluated by comparing the accuracy of genomic predictions for 15 novel meat traits including carcass and meat quality and omega fatty acid traits in sheep, from 12k SNP genotypes, imputed 50k SNP genotypes and real 50k SNP genotypes. The 12k chip design included 12 223 SNPs with a high minor allele frequency that were selected with intermarker spacing of 50-475 kb. SNPs for parentage and horned or polled tests also were represented. Chromosome ends were enriched with SNPs to reduce edge effects on imputation. The imputation performance of the 12k SNP chip was evaluated using 50k SNP genotypes of 4642 animals from six breeds in three different scenarios: (1) within breed, (2) single breed from multibreed reference and (3) multibreed from a single-breed reference. The highest imputation accuracies were found with scenario 2, whereas scenario 3 was the worst, as expected. Using scenario 2, the average imputation accuracy in Border Leicester, Polled Dorset, Merino, White Suffolk and crosses was 0.95, 0.95, 0.92, 0.91 and 0.93 respectively. Imputation scenario 2 was used to impute 50k genotypes for 10 396 animals with novel meat trait phenotypes to compare genomic prediction accuracy using genomic best linear unbiased prediction (GBLUP) with real and imputed 50k genotypes. The weighted mean imputation accuracy achieved was 0.92. The average accuracy of genomic estimated breeding values (GEBVs) based on only 12k data was 0.08 across traits and breeds, but accuracies varied widely. The mean GBLUP accuracies with imputed 50k data more than doubled to 0.21. Accuracies of genomic prediction were very similar for imputed and real 50k genotypes. There was no apparent impact on accuracy of GEBVs as a result of using imputed rather than real 50k genotypes, provided imputation accuracy was >90%.
Publisher: Wiley
Date: 22-08-2017
DOI: 10.1111/JCPP.12791
Abstract: While the prevalence of language and communication difficulties among young people in custody is well established, holistic understanding of the complexity and co-occurrence of additional vulnerabilities among this population are rare. Ninety-three young people in a young offenders institution in England were assessed using the Comprehensive Health Assessment Tool, the Test of Word Knowledge, and a range of additional assessments of communication, cognition, and neurodevelopmental difficulties. Forty-seven percent of the young people demonstrated an aspect of language skills significantly below the population average, with more than one in four identified as having impairment. Only one in four of those with an impairment had previously accessed speech and language services. Language needs were associated with difficulties with social communication and nonverbal cognition, as well as higher risk of self-harm and substance misuse. Earlier identification of language difficulties requires routine assessment of young people at risk of engagement in offending behavior. Where language difficulties are identified, holistic assessments of needs should be undertaken. There is a need for speech and language therapy provision within youth justice services, as well as in other services accessed by young people at risk of engagement in offending.
Publisher: MDPI AG
Date: 19-02-2021
DOI: 10.3390/ANI11020541
Abstract: Structural variations (SVs) are large DNA segments of deletions, duplications, copy number variations, inversions and translocations in a re-sequenced genome compared to a reference genome. They have been found to be associated with several complex traits in dairy cattle and could potentially help to improve genomic prediction accuracy of dairy traits. Imputation of SVs was performed in in iduals genotyped with single-nucleotide polymorphism (SNP) panels without the expense of sequencing them. In this study, we generated 24,908 high-quality SVs in a total of 478 whole-genome sequenced Holstein and Jersey cattle. We imputed 4489 SVs with R2 0.5 into 35,568 Holstein and Jersey dairy cattle with 578,999 SNPs with two pipelines, FImpute and Eagle2.3-Minimac3. Genome-wide association studies for production, fertility and overall type with these 4489 SVs revealed four significant SVs, of which two were highly linked to significant SNP. We also estimated the variance components for SNP and SV models for these traits using genomic best linear unbiased prediction (GBLUP). Furthermore, we assessed the effect on genomic prediction accuracy of adding SVs to GBLUP models. The estimated percentage of genetic variance captured by SVs for production traits was up to 4.57% for milk yield in bulls and 3.53% for protein yield in cows. Finally, no consistent increase in genomic prediction accuracy was observed when including SVs in GBLUP.
Publisher: Springer Science and Business Media LLC
Date: 06-07-2017
Publisher: Frontiers Media SA
Date: 18-11-2021
DOI: 10.3389/FGENE.2021.760450
Abstract: Extensively grazed cattle are often mustered only once a year. Therefore, birthdates are typically unknown or inaccurate. Birthdates would be useful for deriving important traits (growth rate calving interval), breed registrations, and making management decisions. Epigenetic clocks use methylation of DNA to predict an in idual’s age. An epigenetic clock for cattle could provide a solution to the challenges of industry birthdate recording. Here we derived the first epigenetic clock for tropically adapted cattle using portable sequencing devices from tail hair, a tissue which is widely used in industry for genotyping. Cattle ( n = 66) with ages ranging from 0.35 to 15.7 years were sequenced using Oxford Nanopore Technologies MinION and methylation was called at CpG sites across the genome. Sites were then filtered and used to calculate a covariance relationship matrix based on methylation state. Best linear unbiased prediction was used with 10-fold cross validation to predict age. A second methylation relationship matrix was also calculated that contained sites associated with genes used in the dog and human epigenetic clocks. The correlation between predicted age and actual age was 0.71 for all sites and 0.60 for dog and human gene epigenetic clock sites. The mean absolute deviation was 1.4 years for animals aged less than 3 years of age, and 1.5 years for animals aged 3–10 years. This is the first reported epigenetic clock using industry relevant s les in cattle.
Publisher: CSIRO Publishing
Date: 2010
DOI: 10.1071/AN10096
Abstract: Estimated breeding values for the selection of more profitable sheep for the sheep meat and wool industries are currently based on pedigree and phenotypic records. With the advent of a medium-density DNA marker array, which genotypes ~50 000 ovine single nucleotide polymorphisms, a third source of information has become available. The aim of this paper was to determine whether this genomic information can be used to predict estimated breeding values for wool and meat traits. The effects of all single nucleotide polymorphism markers in a multi-breed sheep reference population of 7180 in iduals with phenotypic records were estimated to derive prediction equations for genomic estimated breeding values (GEBV) for greasy fleece weight, fibre diameter, staple strength, breech wrinkle score, weight at ultrasound scanning, scanned eye muscle depth and scanned fat depth. Five hundred and forty industry sires with very accurate Australian sheep breeding values were used as a validation population and the accuracies of GEBV were assessed according to correlations between GEBV and Australian sheep breeding values . The accuracies of GEBV ranged from 0.15 to 0.79 for wool traits in Merino sheep and from –0.07 to 0.57 for meat traits in all breeds studied. Merino industry sires tended to have more accurate GEBV than terminal and maternal breeds because the reference population consisted mainly of Merino haplotypes. The lower accuracy for terminal and maternal breeds suggests that the density of genetic markers used was not high enough for accurate across-breed prediction of marker effects. Our results indicate that an increase in the size of the reference population will increase the accuracy of GEBV.
Publisher: Springer Science and Business Media LLC
Date: 16-07-2013
Publisher: Wiley
Date: 20-09-2023
DOI: 10.1002/TPG2.20390
Publisher: Elsevier BV
Date: 2014
Publisher: Springer Science and Business Media LLC
Date: 27-05-2020
DOI: 10.1186/S12711-020-00547-5
Abstract: In tropically-adapted beef heifers, application of genomic prediction for age at puberty has been limited due to low prediction accuracies. Our aim was to investigate novel methods of pre-selecting whole-genome sequence (WGS) variants and alternative analysis methodologies including genomic best linear unbiased prediction (GBLUP) with multiple genomic relationship matrices (MGRM) and Bayesian (BayesR) analyses, to determine if prediction accuracy for age at puberty can be improved. Genotypes and phenotypes were obtained from two research herds. In total, 868 Brahman and 960 Tropical Composite heifers were recorded in the first population and 3695 Brahman, Santa Gertrudis and Droughtmaster heifers were recorded in the second population. Genotypes were imputed to 23 million whole-genome sequence variants. Eight strategies were used to pre-select variants from genome-wide association study (GWAS) results using conditional or joint (COJO) analyses. Pre-selected variants were included in three models, GBLUP with a single genomic relationship matrix (SGRM), GBLUP MGRM and BayesR. Five-way cross-validation was used to test the effect of marker panel density (6 K, 50 K and 800 K), analysis model, and inclusion of pre-selected WGS variants on prediction accuracy. In all tested scenarios, prediction accuracies for age at puberty were highest in BayesR analyses. The addition of pre-selected WGS variants had little effect on the accuracy of prediction when BayesR was used. The inclusion of WGS variants that were pre-selected using a meta-analysis with COJO analyses by chromosome, fitted in a MGRM model, had the highest prediction accuracies in the GBLUP analyses, regardless of marker density. When the low-density (6 K) panel was used, the prediction accuracy of GBLUP was equal (0.42) to that with the high-density panel when only six additional sequence variants (identified using meta-analysis COJO by chromosome) were included. While BayesR consistently outperforms other methods in terms of prediction accuracies, reasonable improvements in accuracy can be achieved when using GBLUP and low-density panels with the inclusion of a relatively small number of highly relevant WGS variants.
Publisher: Springer Science and Business Media LLC
Date: 08-05-2015
Publisher: Springer Science and Business Media LLC
Date: 22-07-2015
Publisher: Springer Science and Business Media LLC
Date: 19-02-2018
DOI: 10.1038/S41588-018-0056-5
Abstract: Stature is affected by many polymorphisms of small effect in humans
Publisher: Springer Science and Business Media LLC
Date: 10-05-2006
Abstract: Whereas detection and positioning of genes that affect quantitative traits (quantitative trait loci (QTL)) using linkage mapping uses only information from recombinants in the genotyped generations, linkage disequilibrium (LD) mapping uses historical recombinants. Thus, whereas linkage mapping requires large family sizes to detect and accurately position QTL, LD mapping is more dependent on the number of families s led from the population. In commercial Atlantic salmon breeding programmes, only a small number of in iduals per family are routinely phenotyped for traits such as disease resistance and meat colour. In this paper, we assess the power and accuracy of combined linkage disequilibrium linkage analysis (LDLA) to detect QTL in the commercial population using simulation. When 15 half-sib sire families (each sire mated to 30 dams, each dam with 10 progeny) were s led from the population for genotyping, we were able to detect a QTL explaining 10% of the phenotypic variance in 85% of replicates and position this QTL within 3 cM of the true position in 70% of replicates. When recombination was absent in males, a feature of the salmon genome, power to detect QTL increased however, the accuracy of positioning the QTL was decreased. By increasing the number of sire families s led from the population to be genotyped to 30, we were able to increase both the proportion of QTL detected and correctly positioned (even with no recombination in males). QTL with much smaller effect could also be detected. The results suggest that even with the existing recording structure in commercial salmon breeding programmes, there is considerable power to detect and accurately position QTL using LDLA.
Publisher: Oxford University Press (OUP)
Date: 18-09-2014
DOI: 10.1534/GENETICS.114.168344
Abstract: The use of dense SNPs to predict the genetic value of an in idual for a complex trait is often referred to as “genomic selection” in livestock and crops, but is also relevant to human genetics to predict, for ex le, complex genetic disease risk. The accuracy of prediction depends on the strength of linkage disequilibrium (LD) between SNPs and causal mutations. If sequence data were used instead of dense SNPs, accuracy should increase because causal mutations are present, but demographic history and long-term negative selection also influence accuracy. We therefore evaluated genomic prediction, using simulated sequence in two contrasting populations: one reducing from an ancestrally large effective population size (Ne) to a small one, with high LD common in domestic livestock, while the second had a large constant-sized Ne with low LD similar to that in some human or outbred plant populations. There were two scenarios in each population causal variants were either neutral or under long-term negative selection. For large Ne, sequence data led to a 22% increase in accuracy relative to ∼600K SNP chip data with a Bayesian analysis and a more modest advantage with a BLUP analysis. This advantage increased when causal variants were influenced by negative selection, and accuracy persisted when 10 generations separated reference and validation populations. However, in the reducing Ne population, there was little advantage for sequence even with negative selection. This study demonstrates the joint influence of demography and selection on accuracy of prediction and improves our understanding of how best to exploit sequence for genomic prediction.
Publisher: Proceedings of the National Academy of Sciences
Date: 09-09-2019
Abstract: Many genome variants shaping mammalian phenotype are hypothesized to regulate gene transcription and/or to be under selection. However, most of the evidence to support this hypothesis comes from human studies. Systematic evidence for regulatory and evolutionary signals contributing to complex traits in a different mammalian model is needed. Sequence variants associated with gene expression (expression quantitative trait loci [eQTLs]) and concentration of metabolites (metabolic quantitative trait loci [mQTLs]) and under histone-modification marks in several tissues were discovered from multiomics data of over 400 cattle. Variants under selection and evolutionary constraint were identified using genome databases of multiple species. These analyses defined 30 sets of variants, and for each set, we estimated the genetic variance the set explained across 34 complex traits in 11,923 bulls and 32,347 cows with 17,669,372 imputed variants. The per-variant trait heritability of these sets across traits was highly consistent ( r 0.94) between bulls and cows. Based on the per-variant heritability, conserved sites across 100 vertebrate species and mQTLs ranked the highest, followed by eQTLs, young variants, those under histone-modification marks, and selection signatures. From these results, we defined a Functional-And-Evolutionary Trait Heritability (FAETH) score indicating the functionality and predicted heritability of each variant. In additional 7,551 cattle, the high FAETH-ranking variants had significantly increased genetic variances and genomic prediction accuracies in 3 production traits compared to the low FAETH-ranking variants. The FAETH framework combines the information of gene regulation, evolution, and trait heritability to rank variants, and the publicly available FAETH data provide a set of biological priors for cattle genomic selection worldwide.
Publisher: Wiley
Date: 06-05-2010
DOI: 10.1111/J.1365-2052.2009.01998.X
Abstract: Dystocia and stillbirth are significant causes of female and neonatal death in many species and there is evidence for a genetic component to both traits. Identifying causal mutations affecting these traits through genome wide association studies could reveal the genetic pathways involved and will be a step towards targeted interventions. Norwegian Red cattle are an ideal model breed for such studies as very large numbers of records are available. We conducted a genome wide association study for direct and maternal effects of dystocia and stillbirth using almost 1 million records of these traits. Genotyping costs were minimized by genotyping the sires of the recorded cows, and using daughter averages as phenotypes. A dense marker map containing 17,343 single nucleotide polymorphisms covering all autosomal chromosomes was utilized. The genotyped sires were assigned to one of two groups in an attempt to ensure independence between the groups. Associations were only considered validated if they occurred in both groups. Strong associations were found and validated on chromosomes 4, 5, 6, 9, 12, 20, 22 and 28. The QTL region on chromosome 6 was refined using LDLA analysis. The results showed that this chromosome most probably contains two QTL for direct effect on dystocia and one for direct effect on stillbirth. Several candidate genes may be identified close to these QTL. Of these, a cluster of genes expected to affect bone and cartilage formation (i.e. SPP1, IBSP and MEPE) are of particular interest and we suggest that these genes are screened in candidate gene studies for dystocia and stillbirth in cattle as well as other species.
Publisher: MDPI AG
Date: 03-03-2021
DOI: 10.3390/ANI11030674
Abstract: Smallholder dairy farms (SDFs) are distributed widely across lowland and highland regions in Vietnam, but data on the productivity and welfare status of these cows remains limited. This cross-sectional study was conducted to describe and compare the productivity and welfare status of SDF cows across contrasting regions. It was conducted in autumn 2017 on 32 SDFs randomly selected from four typical but contrasting dairy regions (eight SDFs per region) a south lowland, a south highland, a north lowland, and a north highland region. Each farm was visited over a 24-h period (an afternoon followed by a morning milking and adjacent husbandry activities) to collect data of in idual lactating cows (n = 345) and dry cows (n = 123), which included: milk yield and concentrations, body weight (BW), body condition score (BCS, 5-point scale, 5 = very fat), inseminations per conception, and level of heat stress experienced (panting score, 4.5-point scale, 0 = no stress). The high level of heat stress (96% of lactating cows were moderate to highly heat-stressed in the afternoon), low energy corrected milk yield (15.7 kg/cow/d), low percentage of lactating cows (37.3% herd), low BW (498 and 521 kg in lactating and dry cows, respectively), and low BCS of lactating cows (2.8) were the most important productivity and welfare concerns determined and these were most serious in the south lowland. By contrast, cows in the north lowland, a relatively hot but new dairying region, performed similarly to those in the south highland a region historically considered to be one of the most suitable for dairy cows in Vietnam due to its cool environment. This indicates the potential to mitigate heat stress through new husbandry strategies. Cows in the north highland had the highest BW (535 and 569 kg in lactating and dry cows, respectively) and the highest energy corrected milk yield (19.2 kg/cow/d). Cows in all regions were heat-stressed during the daytime, although less so in the highlands compared to the lowlands. Opportunities for research into improving the productivity and welfare of Vietnamese SDF cows are discussed.
Publisher: Hindawi Limited
Date: 12-2010
DOI: 10.1017/S0016672310000613
Abstract: Most traits of economic importance in livestock are either quantitative or complex. Despite considerable efforts, there has been only limited success in identifying the polymorphisms that cause variation in these traits. Nevertheless, selection based on estimated breeding values (BVs), calculated from data on phenotypic performance and pedigree has been very successful. Genomic tools, such as single nucleotide polymorphism (SNP) chips, have led to a new method of selection called ‘genomic selection’ in which dense SNP genotypes covering the genome are used to predict the BV. In this review we consider the statistical methodology for estimating BVs from SNP data, factors affecting the accuracy, the long-term response to genomic selection and the design of breeding programmes including the management of inbreeding.
Publisher: American Dairy Science Association
Date: 02-2017
Publisher: Wiley
Date: 14-10-2013
DOI: 10.1111/EVA.12113
Publisher: Oxford University Press (OUP)
Date: 12-2009
DOI: 10.1534/GENETICS.109.104935
Abstract: Genomic prediction of future phenotypes or genetic merit using dense SNP genotypes can be used for prediction of disease risk, forensics, and genomic selection of livestock and domesticated plant species. The reliability of genomic predictions is their squared correlation with the true genetic merit and indicates the proportion of the genetic variance that is explained. As reliability relies heavily on the number of phenotypes, combining data sets from multiple populations may be attractive as a way to increase reliabilities, particularly when phenotypes are scarce. However, this strategy may also decrease reliabilities if the marker effects are very different between the populations. The effect of combining multiple populations on the reliability of genomic predictions was assessed for two simulated cattle populations, A and B, that had erged for T = 6, 30, or 300 generations. The training set comprised phenotypes of 1000 in iduals from population A and 0, 300, 600, or 1000 in iduals from population B, while marker density and trait heritability were varied. Adding in iduals from population B to the training set increased the reliability in population A by up to 0.12 when the marker density was high and T = 6, whereas it decreased the reliability in population A by up to 0.07 when the marker density was low and T = 300. Without in iduals from population B in the training set, the reliability in population B was up to 0.77 lower than in population A, especially for large T. Adding in iduals from population B to the training set increased the reliability in population B to close to the same level as in population A when the marker density was sufficiently high for the marker–QTL linkage disequilibrium to persist across populations. Our results suggest that the most accurate genomic predictions are achieved when phenotypes from all populations are combined in one training set, while for more erged populations a higher marker density is required.
Publisher: Oxford University Press (OUP)
Date: 02-2020
Abstract: Many breeds of modern cattle are naturally horned, and for sound husbandry management reasons the calves frequently undergo procedures to physically remove the horns by disbudding or dehorning. These procedures are however a welfare concern. Selective breeding for polledness – absence of horns – has been effective in some cattle breeds but not in others (Bos indicus genotypes) due in part to the complex genetics of horn phenotype. To address this problem different approaches to genetic testing which provide accurate early-in-life prediction of horn phenotype have been evaluated, initially using microsatellites (MSAT) and more recently single nucleotide polymorphism (SNP). A direct gene test is not effective given the genetic heterogeneity and large-sized sequence variants associated with polledness in different breeds. The current study investigated 39,943 animals of multiple breeds to assess the accuracy of available poll testing assays. While the standard SNP-based test was an improvement on the earlier MSAT haplotyping method, 1999 (9.69%) out of 20,636 animals tested with this SNP-based assay did not predict a genotype, most commonly associated with the Indicus-influenced breeds. The current study has developed an optimized poll gene test that resolved the vast majority of these 1999 unresolved animals, while the predicted genotypes of those previously resolved remained unchanged. Hence the optimized poll test successfully predicted a genotype in 99.96% of s les assessed. We demonstrated that a robust set of 5 SNPs can effectively determine PC and PF alleles and eliminate the ambiguous and undetermined results of poll gene testing previously identified as an issue in cattle.
Publisher: Elsevier BV
Date: 11-2021
DOI: 10.1016/J.CELREP.2021.110058
Abstract: Mouse hematopoietic tissues contain abundant tissue-resident macrophages that support immunity, hematopoiesis, and bone homeostasis. A systematic strategy to characterize macrophage subsets in mouse bone marrow (BM), spleen, and lymph node unexpectedly reveals that macrophage surface marker staining emanates from membrane-bound subcellular remnants associated with unrelated cells. Intact macrophages are not present within these cell preparations. The macrophage remnant binding profile reflects interactions between macrophages and other cell types in vivo. Depletion of CD169
Publisher: Public Library of Science (PLoS)
Date: 18-08-2009
Publisher: Frontiers Media SA
Date: 15-11-2019
Publisher: American Dairy Science Association
Date: 04-2016
Abstract: Temperature and humidity levels above a certain threshold decrease milk production in dairy cattle, and genetic variation is associated with the amount of lost production. To enable selection for improved heat tolerance, the aim of this study was to develop genomic estimated breeding values (GEBV) for heat tolerance in dairy cattle. Heat tolerance was defined as the rate of decline in production under heat stress. We combined herd test-day recording data from 366,835 Holstein and 76,852 Jersey cows with daily temperature and humidity measurements from weather stations closest to the tested herds for test days between 2003 and 2013. We used daily mean values of temperature-humidity index averaged for the day of test and the 4 previous days as the measure of heat stress. Tolerance to heat stress was estimated for each cow using a random regression model with a common threshold of temperature-humidity index=60 for all cows. The slope solutions for cows from this model were used to define the daughter trait deviations of their sires. Genomic best linear unbiased prediction was used to calculate GEBV for heat tolerance for milk, fat, and protein yield. Two reference populations were used, the first consisted of genotyped sires only (2,300 Holstein and 575 Jersey sires), and the other included genotyped sires and cows (2,189 Holstein and 1,188 Jersey cows). The remainder of the genotyped sires were used as a validation set. All animals had genotypes for 632,003 single nucleotide polymorphisms. When using only genotyped sires in the reference set and only the first parity data, the accuracy of GEBV for heat tolerance in relation to changes in milk, fat, and protein yield were 0.48, 0.50, and 0.49 in the Holstein validation sires and 0.44, 0.61, and 0.53 in the Jersey validation sires, respectively. Some slight improvement in the accuracy of prediction was achieved when cows were included in the reference population for Holsteins. No clear improvements in the accuracy of genomic prediction were observed when data from the second and third parities were included. Correlations of GEBV for heat tolerance with Australian Breeding Values for other traits suggested heat tolerance had a favorable genetic correlation with fertility (0.29-0.39 in Holsteins and 0.15-0.27 in Jerseys), but unfavorable correlations for some production traits. Options to improve heat tolerance with genomic selection in Australian dairy cattle are discussed.
Publisher: Springer Science and Business Media LLC
Date: 13-06-2019
DOI: 10.1038/S41588-019-0463-2
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publisher: Wiley
Date: 16-05-2018
Abstract: We have developed the first comprehensive simulator for polyploid genomes (PolySim) and demonstrated its value by performing large-scale simulations to examine the effect of different population parameters on the evolution of polyploids. PolySim is unlimited in terms of ploidy, population size or number of simulated loci. Our process considered the evolution of polyploids from diploid ancestors, polysomic inheritance, inbreeding, recombination rate change in polyploids and gene flow from lower to higher ploidies. We compared the number of segregating single nucleotide polymorphisms, minor allele frequency, heterozygosity, R
Publisher: Wiley
Date: 12-2007
DOI: 10.1111/J.1439-0388.2007.00702.X
Abstract: Genomic selection is a form of marker-assisted selection in which genetic markers covering the whole genome are used so that all quantitative trait loci (QTL) are in linkage disequilibrium with at least one marker. This approach has become feasible thanks to the large number of single nucleotide polymorphisms (SNP) discovered by genome sequencing and new methods to efficiently genotype large number of SNP. Simulation results and limited experimental results suggest that breeding values can be predicted with high accuracy using genetic markers alone but more validation is required especially in s les of the population different from that in which the effect of the markers was estimated. The ideal method to estimate the breeding value from genomic data is to calculate the conditional mean of the breeding value given the genotype of the animal at each QTL. This conditional mean can only be calculated by using a prior distribution of QTL effects so this should be part of the research carried out to implement genomic selection. In practice, this method of estimating breeding values is approximated by using the marker genotypes instead of the QTL genotypes but the ideal method is likely to be approached more closely as more sequence and SNP data is obtained. Implementation of genomic selection is likely to have major implications for genetic evaluation systems and for genetic improvement programmes generally and these are discussed.
Publisher: Public Library of Science (PLoS)
Date: 15-08-2014
Publisher: Springer Science and Business Media LLC
Date: 12-2017
Publisher: MDPI AG
Date: 29-12-2020
DOI: 10.3390/ANI11010051
Abstract: This study tested the hypothesis that Bacillus amyloliquefaciens strain H57 (H57) improves preference by reducing the development of microbial volatile organic compounds (mVOCs) in feed pellets. Sixteen bull calves were, for 4 weeks, provided equal access to a panel of 8 automated feed bunks in a single paddock with some hay. Each bunk contained pellets with (H57) or without (Control) the H57, each aged for 4 months at either ambient or chiller temperature. Each treatment was changed to a new bunk pair position weekly. Relative preference was determined according to weight of pellets remaining per hour per treatment bunk pair per 24 h. Pellets were analysed for volatile organic compounds (VOCs) and the concentrations tested for correlation with relative preference. Calves showed the lowest preference (p 0.0001) for the Control/Ambient treatment whereas preference for all other treatments (H57/Ambient H57/Chiller Control/Chiller) was similar. The Control/Ambient treatment odour profile grouped differently to the other 3 treatments which grouped similarly to each other. Up to 16 mVOCs were determined to have potential as pre-ingestive signals for the extent of microbial spoilage. Further studies are required to find which combination of these mVOCs, when added to pellets, results in feed aversion.
Publisher: Cold Spring Harbor Laboratory
Date: 12-03-2003
DOI: 10.1101/GR.387103
Abstract: Linkage disequilibrium (LD) between densely spaced, polymorphic genetic markers in humans and other species contains information about historical population size. Inferring past population size is of interest both from an evolutionary perspective (e.g., testing the “out of Africa” hypothesis of human evolution) and to improve models for mapping of disease and quantitative trait genes. We propose a novel multilocus measure of LD, the chromosome segment homozygosity (CSH). CSH is defined for a specific chromosome segment, up to the full length of the chromosome. In computer simulations CSH was generally less variable than the r 2 measure of LD, and variability of CSH decreased as the number of markers in the chromosome segment was increased. The essence and utility of our novel measure is that CSH over long distances reflects recent effective population size ( N ), whereas CSH over small distances reflects the effective size in the more distant past. We illustrate the utility of CSH by calculating CSH from human and dairy cattle SNP and microsatellite marker data, and predicting N at various times in the past for each species. Results indicated an exponentially increasing N in humans and a declining N in dairy cattle. CSH is a valuable statistic for inferring population histories from haplotype data, and has implications for mapping of disease loci.
Publisher: Wiley
Date: 14-01-2013
DOI: 10.1111/J.1439-0388.2013.01001.X
Abstract: The reliability of genomic evaluations depends on the proportion of genetic variation explained by the DNA markers. In this study, we have estimated the proportion of variance in daughter trait deviations (DTDs) of dairy bulls explained by 45 993 genome wide single-nucleotide polymorphism (SNP) markers for 29 traits in Australian Holstein-Friesian dairy cattle. We compare these proportions to the proportion of variance in DTDs explained by the additive relationship matrix derived from the pedigree, as well as the sum of variance explained by both pedigree and marker information when these were fitted simultaneously. The proportion of genetic variance in DTDs relative to the total genetic variance (the total genetic variance explained by the genomic relationships and pedigree relationships when both were fitted simultaneously) varied from 32% for fertility to approximately 80% for milk yield traits. When fitting genomic and pedigree relationships simultaneously, the variance unexplained (i.e. the residual variance) in DTDs of the total variance for most traits was reduced compared to fitting either in idually, suggesting that there is not complete overlap between the effects. The proportion of genetic variance accounted by the genomic relationships can be used to modify the blending equations used to calculate genomic estimated breeding value (GEBV) from direct genomic breeding value (DGV) and parent average. Our results, from a validation population of young dairy bulls with DTD, suggest that this modification can improve the reliability of GEBV by up to 5%.
Publisher: Public Library of Science (PLoS)
Date: 24-10-2008
Publisher: Oxford University Press (OUP)
Date: 16-03-2022
DOI: 10.1093/JAS/SKAC084
Abstract: Variation in the genome region coding for PLAG1 has well-documented associations with skeletal growth and age at puberty in cattle. However, the influence of PLAG1 on other economically important traits such as cow stayability has not yet been explored. Here we investigate the effect of PLAG1 variation on early and later in life female fertility, as well as size and growth, in a well-phenotyped Australian Brahman herd. Yearly pregnancy and productivity records were collected from 2,839 genotyped Brahman cows and used to generate fertility, growth, and weight phenotypes. A variant on chromosome 14 in PLAG1 (NC_037341.1:g.23338890G& T, rs109815800) was previously determined to be a putative causative mutation associated with variation in cattle stature. The imputed PLAG1 genotype at this variant was isolated for each animal and the effect of PLAG1 genotype on each trait was estimated using linear modeling. Regardless of how heifer fertility was measured, there was a significant (P & 0.05) and desirable relationship between the additive effects of PLAG1 genotype and successful heifer fertility. Heifers with two copies of the alternate allele (TT) conceived earlier and had higher pregnancy and calving rates. However, the effects of PLAG1 genotype on fertility began to diminish as cows aged and did not significantly influence stayability at later ages. While there was no effect of genotype on growth, PLAG1 had a negative effect on mature cow weight (P & 0.01), where females with two copies of the alternate allele (TT) were significantly smaller than those with either one or none. Selection emphasis on improved Brahman heifer fertility will likely increase the frequency of the T allele of rs109815800, which may also increase herd profitability and long-term sustainability through improved reproductive efficiency and reduced mature cow size.
Publisher: Hindawi Limited
Date: 04-2009
Publisher: Springer Science and Business Media LLC
Date: 14-02-2019
DOI: 10.1038/S41598-019-38488-9
Abstract: Human milk contains abundant oligosaccharides (OS) which are believed to have strong health benefits for neonates. OS are a minor component of bovine milk and little is known about how the production of OS is regulated in the bovine mammary gland. We have measured the abundance of 12 major OS in milk of 360 cows, which had high density SNP marker genotypes. Most of the OS were found to be highly heritable (h 2 between 50 and 84%). A genome-wide association study allowed us to fine-map several QTL and identify candidate genes with major effects on five OS. Among them, a putative causal mutation close to the ABO gene on Chromosome 11 accounted for approximately 80% of genetic variance for two OS, N -acetylgalactosaminyllactose and lacto- N -neotetraose. This mutation lies very close to a variant associated with the expression levels of ABO. A third QTL mapped close to ST3GAL6 on Chromosome 1 explaining 33% of genetic variation of an abundant OS, 3′-sialyllactose. The presence of major gene effects suggests that targeted marker-assisted selection would lead to a significant increase in the level of these OS in milk. This is the first attempt to map candidate genes and causal mutations for bovine milk OS.
Publisher: Canadian Science Publishing
Date: 11-2010
DOI: 10.1139/G10-076
Abstract: Results from genome-wide association studies in livestock, and humans, has lead to the conclusion that the effect of in idual quantitative trait loci (QTL) on complex traits, such as yield, are likely to be small therefore, a large number of QTL are necessary to explain genetic variation in these traits. Given this genetic architecture, gains from marker-assisted selection (MAS) programs using only a small number of DNA markers to trace a limited number of QTL is likely to be small. This has lead to the development of alternative technology for using the available dense single nucleotide polymorphism (SNP) information, called genomic selection. Genomic selection uses a genome-wide panel of dense markers so that all QTL are likely to be in linkage disequilibrium with at least one SNP. The genomic breeding values are predicted to be the sum of the effect of these SNPs across the entire genome. In dairy cattle breeding, the accuracy of genomic estimated breeding values (GEBV) that can be achieved and the fact that these are available early in life have lead to rapid adoption of the technology. Here, we discuss the design of experiments necessary to achieve accurate prediction of GEBV in future generations in terms of the number of markers necessary and the size of the reference population where marker effects are estimated. We also present a simple method for implementing genomic selection using a genomic relationship matrix. Future challenges discussed include using whole genome sequence data to improve the accuracy of genomic selection and management of inbreeding through genomic relationships.
Publisher: Springer Science and Business Media LLC
Date: 07-2021
DOI: 10.1038/S42003-021-02340-6
Abstract: To further the understanding of the evolution of transcriptional regulation, we profiled genome-wide transcriptional start sites ( TSSs ) in two sub-species, Bos taurus taurus and Bos taurus indicus , that erged approximately 500,000 years ago. Evolutionary and developmental-stage differences in TSSs were detected across the sub-species, including translocation of dominant TSS and changes in TSS distribution. The 16% of all SNPs located in significant differentially used TSS clusters across sub-species had significant shifts in allele frequency (472 SNPs), indicating they may have been subject to selection. In spleen and muscle, a higher relative TSS expression was observed in Bos indicus than Bos taurus for all heat shock protein genes, which may be responsible for the tropical adaptation of Bos indicus .
Publisher: American Chemical Society (ACS)
Date: 21-02-2013
DOI: 10.1021/PR301056Q
Abstract: A detailed understanding of the relationships between the distinct metabolic compartments of blood and milk would be of potential benefit to our understanding of the physiology of lactation, and potentially for development of biomarkers for health and commercially relevant traits in dairy cattle. NMR methods were used to measure metabolic profiles from blood and milk s les from Holstein cows. Data were analyzed using PLS regression to identify quantitative relationships between metabolic profiles and important traits. Statistical Heterospectroscopy (SHY), a powerful approach to recovering latent biological information in NMR spectroscopic data sets from multiple complementary s les, was employed to explore the metabolic relationships between blood and milk from these animals. The study confirms milk is a distinct metabolic compartment with a metabolite composition largely not influenced by plasma composition under normal circumstances. However, several significant relationships were identified, including a high correlation for trimethylamine (TMA) and dimethylsulfone (DMSO(2)) across plasma and milk compartments, and evidence plasma valine levels are linked to differences in amino acid catabolism in the mammary gland. The findings provide insights into the physiological mechanisms underlying lactation and identification of links between key metabolites and milk traits such as the protein and fat content of milk. The approach has the potential to enable measurement of health, metabolic status and other important phenotypes with milk s ling.
Publisher: Cold Spring Harbor Laboratory
Date: 04-11-2020
DOI: 10.1101/2020.11.04.363069
Abstract: In the course of evolution, pecorans (i.e. higher ruminants) developed a remarkable ersity of osseous cranial appendages, collectively referred to as ‘headgear’, which likely share the same origin and genetic basis. However, the nature and function of the genetic determinants underlying their number and position remain elusive. Jacob and other rare populations of sheep and goats, are characterized by polyceraty, the presence of more than two horns. Here, we characterize distinct POLYCERATE alleles in each species, both associated with defective HOXD1 function. We show that haploinsufficiency at this locus results in the splitting of horn bud primordia, likely following the abnormal extension of an initial morphogenetic field. These results highlight the key role played by this gene in headgear patterning and illustrate the evolutionary co-option of a gene involved in the early development of bilateria to properly fix the position and number of these distinctive organs of Bovidae.
Publisher: Springer Science and Business Media LLC
Date: 12-08-2020
DOI: 10.1186/S12711-020-00563-5
Abstract: Twenty-five phenotypes were measured as indicators of bull fertility (1099 Brahman and 1719 Tropical Composite bulls). Measurements included sperm morphology, scrotal circumference, and sperm chromatin phenotypes such as DNA fragmentation and protamine deficiency. We estimated the heritability of these phenotypes and carried out genome-wide association studies (GWAS) within breed, using the bovine high-density chip, to detect quantitative trait loci (QTL). Our analyses suggested that both sperm DNA fragmentation and sperm protamine deficiency are heritable (h 2 from 0.10 to 0.22). To confirm these first estimates of heritability, further studies on sperm chromatin traits, with larger datasets are necessary. Our GWAS identified 12 QTL for bull fertility traits, based on at least five polymorphisms (P 10 −8 ) for each QTL. Five QTL were identified in Brahman and another seven in Tropical Composite bulls. Most of the significant polymorphisms detected in both breeds and nine of the 12 QTL were on chromosome X. The QTL were breed-specific, but for some traits, a closer inspection of the GWAS results revealed suggestive single nucleotide polymorphism (SNP) associations (P 10 −7 ) in both breeds. For ex le, the QTL for inhibin level in Braham could be relevant to Tropical Composites too (many polymorphisms reached P 10 −7 in the same region). The QTL for sperm midpiece morphological abnormalities on chromosome X (QTL peak at 4.92 Mb, P 10 −17 ) is an ex le of a breed-specific QTL, supported by 143 significant SNPs (P 10 −8 ) in Brahman, but absent in Tropical Composites. Our GWAS results add evidence to the mammalian specialization of the X chromosome, which during evolution has accumulated genes linked to spermatogenesis. Some of the polymorphisms on chromosome X were associated to more than one genetically correlated trait (correlations ranged from 0.33 to 0.51). Correlations and shared polymorphism associations support the hypothesis that these phenotypes share the same underlying cause, i.e. defective spermatogenesis. Genetic improvement for bull fertility is possible through genomic selection, which is likely more accurate if the QTL on chromosome X are considered in the predictions. Polymorphisms associated with male fertility accumulate on this chromosome in cattle, as in humans and mice, suggesting its specialization.
Publisher: Wiley
Date: 11-2016
DOI: 10.3835/PLANTGENOME2016.02.0021
Abstract: Potato ( Solanum tuberosum L.) breeders consider a large number of traits during cultivar development and progress in conventional breeding can be slow. There is accumulating evidence that some of these traits, such as yield, are affected by a large number of genes with small in idual effects. Recently, significant efforts have been applied to the development of genomic resources to improve potato breeding, culminating in a draft genome sequence and the identification of a large number of single nucleotide polymorphisms (SNPs). The availability of these genome‐wide SNPs is a prerequisite for implementing genomic selection for improvement of polygenic traits such as yield. In this review, we investigate opportunities for the application of genomic selection to potato, including novel breeding program designs. We have considered a number of factors that will influence this process, including the autotetraploid and heterozygous genetic nature of potato, the rate of decay of linkage disequilibrium, the number of required markers, the design of a reference population, and trait heritability. Based on estimates of the effective population size derived from a potato breeding program, we have calculated the expected accuracy of genomic selection for four key traits of varying heritability and propose that it will be reasonably accurate. We compared the expected genetic gain from genomic selection with the expected gain from phenotypic and pedigree selection, and found that genetic gain can be substantially improved by using genomic selection.
Publisher: Oxford University Press (OUP)
Date: 09-2006
DOI: 10.1534/GENETICS.106.058966
Abstract: In goat milk the most abundant proteins are the casein genes, CSN1S1, CSN2, CSN1S2, and CSN3. Mutations have been identified within these genes affecting the level of gene expression, and effects on milk production traits have been reported. The aim of this study was to detect polymorphisms (SNPs) in the casein genes of Norwegian goats, resolve haplotype structures within the loci, and assess the effect of these haplotypes on milk production traits. Four hundred thirty-six Norwegian bucks were genotyped for 39 polymorphic sites across the four loci. The numbers of unique haplotypes present in each locus were 10, 6, 4, and 8 for CSN1S1, CSN2, CSN1S2, and CSN3, respectively. The effects of the CSN1S1 haplotypes on protein percentage and fat kilograms were significant, as were the effects of CSN3 haplotypes on fat percentage and protein percentage. A deletion in exon 12 of CSN1S1, unique to the Norwegian goat population, explained the effects of CSN1S1 haplotypes on fat kilograms, but not protein percentage. Investigation of linkage disequilibrium between all possible pairs of SNPs revealed higher levels of linkage disequilbrium for SNP pairs within casein loci than for SNP pairs between casein loci, likely reflecting low levels of intragenic recombination. Further, there was evidence for a site of preferential recombination between CSN2 and CSN1S2. The value of the haplotypes for haplotype-assisted selection (HAS) is discussed.
Publisher: Elsevier BV
Date: 2014
Publisher: American Dairy Science Association
Date: 04-2011
Abstract: Large numbers of dairy cattle are now routinely genotyped for dense single nucleotide polymorphism (SNP) arrays for the purpose of predicting genomic estimated breeding values. Such SNP arrays contain very good information for parentage assignment and pedigree reconstruction. The main challenge in using this information for parentage assignment and pedigree reconstruction is development of computationally efficient strategies that enable a candidate animal to be assigned its sire and dam with the large volume of data. Here we describe an efficient algorithm for parentage assignment with SNP data and demonstrate very accurate assignment with 50,000-SNP and 3,000-SNP panels. The computer code implementing the algorithm is given in the Appendix.
Publisher: American Dairy Science Association
Date: 06-2014
Abstract: The economic benefit of expanding the Australian Profit Ranking (APR) index to include residual feed intake (RFI) was evaluated using a multitrait selection index. This required the estimation of genetic parameters for RFI and genetic correlations using single nucleotide polymorphism data (genomic) correlations with other traits. Heritabilities of RFI, dry matter intake (DMI), and all the traits in the APR (milk, fat, and protein yields somatic cell count fertility survival milking speed and temperament), and genomic correlations between these traits were estimated using a Bayesian framework, using data from 843 growing Holstein heifers with phenotypes for DMI and RFI, and bulls with records for the other traits. Heritability estimates of DMI and RFI were 0.44 and 0.33, respectively, and the genomic correlation between them was 0.03 and nonsignificant. The genomic correlations between the feed-efficiency traits and milk yield traits were also close to zero, ranging between -0.11 and 0.10. Positive genomic correlations were found for DMI with stature (0.16) and with overall type (0.14), suggesting that taller cows eat more as heifers. One issue was that the genomic correlation estimates for RFI with calving interval (ClvI) and with body condition score were both unfavorable (-0.13 and 0.71 respectively), suggesting an antagonism between feed efficiency and fertility. However, because of the relatively small numbers of animals in this study, a large 95% probability interval existed for the genomic correlation between RFI and ClvI (-0.66, 0.36). Given these parameters, and a genetic correlation between heifer and lactating cow RFI of 0.67, inclusion of RFI in the APR index would reduce RFI by 1.76 kg/cow per year. Including RFI in the APR would result in the national Australian Holstein herd consuming 1.73 × 10(6) kg less feed, which is worth 0.55 million Australian dollars (A$) per year and is 3% greater than is currently possible to achieve. Other traits contributing to profitability, such as milk production and fertility, will also improve through selection on this index for ex le, ClvI would be reduced by 0.53 d/cow per year, which is 96% of the gain for this trait that is achieved without RFI in the APR.
Publisher: Springer Science and Business Media LLC
Date: 30-10-2017
Publisher: Springer Science and Business Media LLC
Date: 06-2009
DOI: 10.1038/NRG2575
Abstract: Genome-wide panels of SNPs have recently been used in domestic animal species to map and identify genes for many traits and to select genetically desirable livestock. This has led to the discovery of the causal genes and mutations for several single-gene traits but not for complex traits. However, the genetic merit of animals can still be estimated by genomic selection, which uses genome-wide SNP panels as markers and statistical methods that capture the effects of large numbers of SNPs simultaneously. This approach is expected to double the rate of genetic improvement per year in many livestock systems.
Publisher: Wiley
Date: 13-03-2011
DOI: 10.1111/J.1365-2052.2011.02179.X
Abstract: Reproductive performance is a critical trait in dairy cattle. Poor reproductive performance leads to prolonged calving intervals, higher culling rates and extra expenses related to multiple inseminations, veterinary treatments and replacements. Genetic gain for improved reproduction through traditional selection is often slow because of low heritability and negative correlations with production traits. Detection of DNA markers associated with improved reproductive performance through genome-wide association studies could lead to genetic gain that is more balanced between fertility and production. Norwegian Red cattle are well suited for such studies, as very large numbers of detailed reproduction records are available. We conducted a genome-wide association study for non-return rate, fertility treatments and retained placenta using almost 1 million records on these traits and 17 343 genome-wide single-nucleotide polymorphisms. Genotyping costs were minimized by genotyping the sires of the cows recorded and by using daughter averages as phenotypes. The genotyped sires were assigned to either a discovery or a validation population. Associations were only considered to be validated if they were significant in both groups. Strong associations were found and validated on chromosomes 1, 5, 8, 9, 11 and 12. Several of these were highly supported by findings in other studies. The most important result was an association for non-return rate in heifers in a region of BTA12 where several associations for milk production traits have previously been found. Subsequent fine-mapping verified the presence of a quantitative trait loci (QTL) having opposing effects on non-return rate and milk production at 18 Mb. The other reproduction QTL did not have pleiotropic effects on milk production, and these are therefore of considerable interest for use in marker-assisted selection.
Publisher: Oxford University Press (OUP)
Date: 02-09-2022
DOI: 10.1093/G3JOURNAL/JKAC216
Abstract: Simulation tools are key to designing and optimizing breeding programs that are multiyear, high-effort endeavors. Tools that operate on real genotypes and integrate easily with other analysis software can guide users toward crossing decisions that best balance genetic gains and genetic ersity required to maintain gains in the future. Here, we present genomicSimulation, a fast and flexible tool for the stochastic simulation of crossing and selection based on real genotypes. It is fully written in C for high execution speeds, has minimal dependencies, and is available as an R package for the integration with R’s broad range of analysis and visualization tools. Comparisons of a simulated recreation of a breeding program to a real data set demonstrate the simulated offspring from the tool correctly show key population features, such as genomic relationships and approximate linkage disequilibrium patterns. Both versions of genomicSimulation are freely available on GitHub: The R package version at llrs/genomicSimulation/ and the C library version at llrs/genomicSimulationC/.
Publisher: Springer Science and Business Media LLC
Date: 03-2019
Publisher: Hindawi Limited
Date: 08-2010
Publisher: American Dairy Science Association
Date: 07-2018
Publisher: International Society for Horticultural Science (ISHS)
Date: 11-2016
Publisher: Oxford University Press (OUP)
Date: 12-12-2011
DOI: 10.1093/BIOINFORMATICS/BTQ673
Abstract: Motivation: Due to a genome duplication event in the recent history of salmonids, modern Atlantic salmon (Salmo salar) have a mosaic genome with roughly one-third being tetraploid. This is a complicating factor in genotyping and genetic mapping since polymorphisms within duplicated regions (multisite variants MSVs) are challenging to call and to assign to the correct paralogue. Standard genotyping software offered by Illumina has not been written to interpret MSVs and will either fail or miscall these polymorphisms. For the purpose of mapping, linkage or association studies in non-diploid species, there is a pressing need for software that includes analysis of MSVs in addition to regular single nucleotide polymorphism (SNP) markers. Results: A software package is presented for the analysis of partially tetraploid genomes genotyped using Illumina Infinium BeadArrays (Illumina Inc.) that includes pre-processing, clustering, plotting and validation routines. More than 3000 salmon from an aquacultural strain in Norway, distributed among 266 full-sib families, were genotyped on a 15K BeadArray including both SNP- and MSV-markers. A total of 4268 SNPs and 1471 MSVs were identified, with average call accuracies of 0.97 and 0.86, respectively. A total of 150 MSVs polymorphic in both paralogs were dissected and mapped to their respective chromosomes, yielding insights about the salmon genome reversion to diploidy and improving marker genome coverage. Several retained homologies were found and are reported. Availability and implementation: R-package beadarrayMSV freely available on the web at cran.r-project.org/ Contact: lg@camo.no Supplementary information: Supplementary data are available at Bioinformatics online.
Publisher: CSIRO Publishing
Date: 07-07-2021
DOI: 10.1071/AN21057
Abstract: Context Beef cattle breeds in Australia can broadly be broken up into two subspecies, namely, Bos indicus and Bos taurus. Due to the time since ergence between the subspecies, it is likely that mutations affecting quantitative traits have developed independently in each. Aims We hypothesise that this will affect the prediction accuracy of genomic selection of admixed and composite populations that include both ancestral subspecies. Our study investigates methods to quantify population stratification in a multibreed population of tropically adapted heifers, with the aim of improving prediction accuracy of genomic selection for reproductive maturity score. Methods We used genotypes and reproductive maturity phenotypes from 3695 tropically adapted heifers from three purebred populations, namely, Brahman, Santa Gertrudis and Droughtmaster. Two of these breeds, Santa Gertrudis and Droughtmaster, are stabilised composites of varying B. indicus × B. taurus ancestry, and the third breed, Brahman, has predominately B. indicus ancestry. Genotypes were imputed to three marker-panel densities and population stratification was accounted for in genomic relationship matrices by using breed-specific allele frequencies when calculating the genomic relationships among animals. Prediction accuracy and bias were determined using a five-fold cross validation of randomly selected multibreed cohorts. Key Results Our results showed that the use of breed-adjusted genomic relationship matrices did not improve either prediction accuracy or bias for a lowly heritable trait such as reproductive maturity score. However, using breed-adjusted genomic relationship matrices allowed the capture of a higher proportion of additive genetic effects when estimating variance components. Conclusions These findings suggest that, despite seeing no improvement in prediction accuracy, it may still be beneficial to use breed-adjusted genomic relationship matrices in multibreed populations to improve the estimation of variance components. Implications As such, genomic evaluations using breed-adjusted genomic relationship matrices may be beneficial in multibreed populations.
Publisher: Elsevier BV
Date: 02-2010
Publisher: Springer Science and Business Media LLC
Date: 2012
Publisher: Hindawi Limited
Date: 12-2009
DOI: 10.1017/S0016672309990334
Abstract: We used a least absolute shrinkage and selection operator (LASSO) approach to estimate marker effects for genomic selection. The least angle regression (LARS) algorithm and cross-validation were used to define the best subset of markers to include in the model. The LASSO–LARS approach was tested on two data sets: a simulated data set with 5865 in iduals and 6000 Single Nucleotide Polymorphisms (SNPs) and a mouse data set with 1885 in iduals genotyped for 10 656 SNPs and phenotyped for a number of quantitative traits. In the simulated data, three approaches were used to split the reference population into training and validation subsets for cross-validation: random splitting across the whole population random s ling of validation set from the last generation only, either within or across families. The highest accuracy was obtained by random splitting across the whole population. The accuracy of genomic estimated breeding values (GEBVs) in the candidate population obtained by LASSO–LARS was 0·89 with 156 explanatory SNPs. This value was higher than those obtained by Best Linear Unbiased Prediction (BLUP) and a Bayesian method (BayesA), which were 0·75 and 0·84, respectively. In the mouse data, 1600 in iduals were randomly allocated to the reference population. The GEBVs for the remaining 285 in iduals estimated by LASSO–LARS were more accurate than those obtained by BLUP and BayesA for weight at six weeks and slightly lower for growth rate and body length. It was concluded that LASSO–LARS approach is a good alternative method to estimate marker effects for genomic selection, particularly when the cost of genotyping can be reduced by using a limited subset of markers.
Publisher: Public Library of Science (PLoS)
Date: 07-02-2012
Publisher: Springer Science and Business Media LLC
Date: 2014
Publisher: Springer Science and Business Media LLC
Date: 04-04-2017
DOI: 10.1007/S00122-017-2895-3
Abstract: Imputing genotypes from the 90K SNP chip to exome sequence in wheat was moderately accurate. We investigated the factors that affect imputation and propose several strategies to improve accuracy. Imputing genetic marker genotypes from low to high density has been proposed as a cost-effective strategy to increase the power of downstream analyses (e.g. genome-wide association studies and genomic prediction) for a given budget. However, imputation is often imperfect and its accuracy depends on several factors. Here, we investigate the effects of reference population selection algorithms, marker density and imputation algorithms (Beagle4 and FImpute) on the accuracy of imputation from low SNP density (9K array) to the Infinium 90K single-nucleotide polymorphism (SNP) array for a collection of 837 hexaploid wheat Watkins landrace accessions. Based on these results, we then used the best performing reference selection and imputation algorithms to investigate imputation from 90K to exome sequence for a collection of 246 globally erse wheat accessions. Accession-to-nearest-entry and genomic relationship-based methods were the best performing selection algorithms, and FImpute resulted in higher accuracy and was more efficient than Beagle4. The accuracy of imputing exome capture SNPs was comparable to imputing from 9 to 90K at approximately 0.71. This relatively low imputation accuracy is in part due to inconsistency between 90K and exome sequence formats. We also found the accuracy of imputation could be substantially improved to 0.82 when choosing an equivalent number of exome SNP, instead of 90K SNPs on the existing array, as the lower density set. We present a number of recommendations to increase the accuracy of exome imputation.
Publisher: Springer Science and Business Media LLC
Date: 13-09-2017
DOI: 10.1038/S41598-017-11523-3
Abstract: In humans, the clinical and molecular characterization of sporadic syndromes is often hindered by the small number of patients and the difficulty in developing animal models for severe dominant conditions. Here we show that the availability of large data sets of whole-genome sequences, high-density SNP chip genotypes and extensive recording of phenotype offers an unprecedented opportunity to quickly dissect the genetic architecture of severe dominant conditions in livestock. We report on the identification of seven dominant de novo mutations in CHD7 , COL1A1 , COL2A1 , COPA , and MITF and exploit the structure of cattle populations to describe their clinical consequences and map modifier loci. Moreover, we demonstrate that the emergence of recessive genetic defects can be monitored by detecting de novo deleterious mutations in the genome of bulls used for artificial insemination. These results demonstrate the attractiveness of cattle as a model species in the post genomic era, particularly to confirm the genetic aetiology of isolated clinical case reports in humans.
Publisher: Wiley
Date: 15-02-2011
DOI: 10.1111/J.1365-2052.2010.02165.X
Abstract: Mastitis is the most frequent and costly disease in dairy production and solutions leading to a reduction in the incidence of mastitis are highly demanded. Here a genome-wide association study was performed to identify polymorphisms affecting susceptibility to mastitis. Genotypes for 17 349 SNPs distributed across the 29 bovine autosomal chromosomes from a total of 2589 sires with 1 389 776 daughters with records on clinical mastitis were included in the analysis. Records of occurrence of clinical mastitis were ided into seven time periods in the first three lactations in order to identify quantitative trait loci affecting mastitis susceptibility in particular phases of lactation. The most convincing results from the association mapping were followed up and validated by a combined linkage disequilibrium and linkage analysis. The study revealed quantitative trait loci affecting occurrence of clinical mastitis in the periparturient period on chromosomes 2, 6 and 20 and a quantitative trait locus affecting occurrence of clinical mastitis in late lactation on chromosome 14. None of the quantitative trait loci for clinical mastitis detected in the study seemed to affect lactation average of somatic cell score. The SNPs highly associated with clinical mastitis lie near both the gene encoding interleukin 8 on chromosome 6 and the genes encoding the two interleukin 8 receptors on chromosome 2.
Publisher: Cold Spring Harbor Laboratory
Date: 16-04-2020
DOI: 10.1101/2020.04.16.044685
Abstract: Genome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where s le sizes are limiting, it may help to integrate the results of GWAS for equivalent traits in humans as prior information. In this study, we sought to investigate the usefulness of results from a GWAS on human height as prior information for identifying the genes and gene-associated variants that affect stature in cattle, using GWAS summary data on s les sizes of 700,000 and 58,265 for humans and cattle, respectively. Using Fisher's exact test, we observed a significant proportion of cattle stature-associated genes (30/77) that are also associated with human height (odds ratio = 5.1, p = 3.1e-10). Result of randomized s ling tests showed that cattle orthologs of human height-associated genes, hereafter referred to as candidate genes (C-genes), were more enriched for cattle stature GWAS signals than random s les of genes in the cattle genome (p=0.01). Randomly s led SNPs within the C-genes also tend to explain more genetic variance for cattle stature (up to 13.2%) than randomly s led SNPs within random cattle genes (p=0.09). The most significant SNPs from a cattle GWAS for stature within the C-genes did not explain more genetic variance for cattle stature than the most significant SNPs within random cattle genes (p=0.87). Altogether, our findings support previous studies that suggest a similarity in the genetic regulation of height across mammalian species. However, with the availability of a powerful GWAS for stature that combined data from 8 cattle breeds, prior information from human-height GWAS does not seem to provide any additional benefit with respect to the identification of genes and gene-associated variants that affect stature in cattle.
Publisher: The Royal Society
Date: 27-07-2016
Abstract: Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until recently, few of the polymorphisms that cause variation in these traits were known. Genome-wide association studies (GWAS), based on the ability to assay thousands of single nucleotide polymorphisms (SNPs), have revolutionized our understanding of the genetics of complex traits. We advocate the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution. We illustrate how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits. The genetic architecture of complex traits is even more complex than previously thought: in almost every trait studied there are thousands of polymorphisms that explain genetic variation. Methods of predicting future phenotypes, collectively known as genomic selection or genomic prediction, have been widely adopted in livestock and crop breeding, leading to increased rates of genetic improvement.
Publisher: American Dairy Science Association
Date: 02-2012
Abstract: Single nucleotide polymorphism (SNP) associations with milk production traits found to be significant in different screening experiments, including SNP in genes hypothesized to be in gene pathways affecting milk production, were tested in a validation population to confirm their association. In total, 423 SNP were genotyped across 411 Holstein bulls, and their association with 6 milk production traits--Australian Selection Index (indicating the profitability of an animal's milk production), protein, fat, and milk yields, and protein and fat composition--were tested using single SNP regressions. Seventy-two SNP were significantly associated with one or more of the traits their effects were in the same direction as in the screening experiment and therefore their association was considered validated. An over-representation of SNP (43 of the 423) on chromosome 20 was observed, including a SNP in the growth hormone receptor gene previously published as having an association with protein composition and protein and milk yields. The association with protein composition was confirmed in this experiment, but not the association with protein and milk yields. A multiple SNP regression analysis for all SNP on chromosome 20 was performed for all 6 traits, which revealed that this mutation was not significantly associated with any of the milk production traits and that at least 2 other quantitative trait loci were present on chromosome 20.
Publisher: Springer Science and Business Media LLC
Date: 02-01-2018
Publisher: Springer Science and Business Media LLC
Date: 17-06-2019
DOI: 10.1038/S41477-019-0445-5
Abstract: The world cropping area for wheat exceeds that of any other crop, and high grain yields in intensive wheat cropping systems are essential for global food security. Breeding has raised yields dramatically in high-input production systems however, selection under optimal growth conditions is widely believed to diminish the adaptive capacity of cultivars to less optimal cropping environments. Here, we demonstrate, in a large-scale study spanning five decades of wheat breeding progress in western Europe, where grain yields are among the highest worldwide, that breeding for high performance in fact enhances cultivar performance not only under optimal production conditions but also in production systems with reduced agrochemical inputs. New cultivars incrementally accumulated genetic variants conferring favourable effects on key yield parameters, disease resistance, nutrient use efficiency, photosynthetic efficiency and grain quality. Combining beneficial, genome-wide haplotypes could help breeders to more efficiently exploit available genetic variation, optimizing future yield potential in more sustainable production systems.
Publisher: American Dairy Science Association
Date: 02-2009
Abstract: A new technology called genomic selection is revolutionizing dairy cattle breeding. Genomic selection refers to selection decisions based on genomic breeding values (GEBV). The GEBV are calculated as the sum of the effects of dense genetic markers, or haplotypes of these markers, across the entire genome, thereby potentially capturing all the quantitative trait loci (QTL) that contribute to variation in a trait. The QTL effects, inferred from either haplotypes or in idual single nucleotide polymorphism markers, are first estimated in a large reference population with phenotypic information. In subsequent generations, only marker information is required to calculate GEBV. The reliability of GEBV predicted in this way has already been evaluated in experiments in the United States, New Zealand, Australia, and the Netherlands. These experiments used reference populations of between 650 and 4,500 progeny-tested Holstein-Friesian bulls, genotyped for approximately 50,000 genome-wide markers. Reliabilities of GEBV for young bulls without progeny test results in the reference population were between 20 and 67%. The reliability achieved depended on the heritability of the trait evaluated, the number of bulls in the reference population, the statistical method used to estimate the single nucleotide polymorphism effects in the reference population, and the method used to calculate the reliability. A common finding in 3 countries (United States, New Zealand, and Australia) was that a straightforward BLUP method for estimating the marker effects gave reliabilities of GEBV almost as high as more complex methods. The BLUP method is attractive because the only prior information required is the additive genetic variance of the trait. All countries included a polygenic effect (parent average breeding value) in their GEBV calculation. This inclusion is recommended to capture any genetic variance not associated with the markers, and to put some selection pressure on low-frequency QTL that may not be captured by the markers. The reliabilities of GEBV achieved were significantly greater than the reliability of parental average breeding values, the current criteria for selection of bull calves to enter progeny test teams. The increase in reliability is sufficiently high that at least 2 dairy breeding companies are already marketing bull teams for commercial use based on their GEBV only, at 2 yr of age. This strategy should at least double the rate of genetic gain in the dairy industry. Many challenges with genomic selection and its implementation remain, including increasing the accuracy of GEBV, integrating genomic information into national and international genetic evaluations, and managing long-term genetic gain.
Publisher: Springer Science and Business Media LLC
Date: 12-2015
Publisher: Springer Science and Business Media LLC
Date: 12-2011
Publisher: Public Library of Science (PLoS)
Date: 28-03-2012
Publisher: Springer Science and Business Media LLC
Date: 03-03-2017
Publisher: Cold Spring Harbor Laboratory
Date: 09-03-2007
DOI: 10.1101/GR.6023607
Abstract: Effective population size ( N e ) determines the amount of genetic variation, genetic drift, and linkage disequilibrium (LD) in populations. Here, we present the first genome-wide estimates of human effective population size from LD data. Chromosome-specific effective population size was estimated for all autosomes and the X chromosome from estimated LD between SNP pairs kb apart. We account for variation in recombination rate by using coalescent-based estimates of fine-scale recombination rate from one s le and correlating these with LD in an independent s le. Phase I of the HapMap project produced between 18 and 22 million SNP pairs in s les from four populations: Yoruba from Ibadan (YRI), Nigeria Japanese from Tokyo (JPT) Han Chinese from Beijing (HCB) and residents from Utah with ancestry from northern and western Europe (CEU). For CEU, JPT, and HCB, the estimate of effective population size, adjusted for SNP ascertainment bias, was ∼3100, whereas the estimate for the YRI was ∼7500, consistent with the out-of-Africa theory of ancestral human population expansion and concurrent bottlenecks. We show that the decay in LD over distance between SNPs is consistent with recent population growth. The estimates of N e are lower than previously published estimates based on heterozygosity, possibly because they represent one or more bottlenecks in human population size that occurred ∼10,000 to 200,000 years ago.
Publisher: Springer Science and Business Media LLC
Date: 02-04-2015
Publisher: Oxford University Press (OUP)
Date: 10-2016
Publisher: Springer Science and Business Media LLC
Date: 05-04-2018
Publisher: Public Library of Science (PLoS)
Date: 26-01-2023
DOI: 10.1371/JOURNAL.PONE.0279398
Abstract: Worldwide, most beef breeding herds are naturally mated. As such, the ability to identify and select fertile bulls is critically important for both productivity and genetic improvement. Here, we collected ten fertility-related phenotypes for 6,063 bulls from six tropically adapted breeds. Phenotypes were comprised of four bull conformation traits and six traits directly related to the quality of the bull’s semen. We also generated high-density DNA genotypes for all the animals. In total, 680,758 single nucleotide polymorphism (SNP) genotypes were analyzed. The genomic correlation of the same trait observed in different breeds was positive for scrotal circumference and sheath score on most breed comparisons, but close to zero for the percentage of normal sperm, suggesting a ergent genetic background for this trait. We confirmed the importance of a breed being present in the reference population to the generation of accurate genomic estimated breeding values (GEBV) in an across-breed validation scenario. Average GEBV accuracies varied from 0.19 to 0.44 when the breed was not included in the reference population. The range improved to 0.28 to 0.59 when the breed was in the reference population. Variants associated with the gene HDAC4, six genes from the spermatogenesis-associated (SPATA) family of proteins, and 29 transcription factors were identified as candidate genes. Collectively these results enable very early in-life selection for bull fertility traits, supporting genetic improvement strategies currently taking place within tropical beef production systems. This study also improves our understanding of the molecular basis of male fertility in mammals.
Publisher: Elsevier BV
Date: 09-2004
Publisher: Elsevier BV
Date: 12-2006
DOI: 10.1016/J.GENE.2006.06.027
Abstract: Toll-like receptors (TLRs) are a family of recognition receptors playing a crucial role in the innate immune system. Different combinations of TLRs are thought to be crucial for effective immune response, thus insight into the organization and expression of TLRs is important for understanding disease resistance. Mastitis is the most frequent and costly disease in dairy production, and the innate immune system is considered to be important in the first line defence against this disease. In the present paper we have characterized the genomic organization of TLR6-TLR1-TLR10 in a approximately 50 kb region of bovine chromosome 6, including 5'-untranslated exons not previously described. A method for gene expression analysis was developed and used for transcription profiling of the three paralogous genes in different bovine tissues. The expression analysis showed similar expression profiles for TLR1 and TLR6, which indicate a co-regulation of these two genes in cattle. TLR10 had a different expression profile, pointing toward a stronger functional ersification compared to TLR1 and TLR6. The differences in expression are in accordance with the evolutionary history of this gene cluster, where TLR10 erged from the common ancestral gene before the duplication event that created TLR1 and TLR6.
Publisher: Wiley
Date: 24-07-2016
DOI: 10.1111/AGE.12466
Publisher: Cold Spring Harbor Laboratory
Date: 07-05-2023
DOI: 10.1101/2023.05.05.539510
Abstract: Loss of genetic ersity in elite crop breeding pools can severely limit long-term genetic gains, and limits gain for new traits that are becoming important as the climate changes, such as heat tolerance. Introgression of specific traits and pre-breeding germplasm is an alternative to introduce new ersity, however, introgression is typically slow and challenging. Here we use a genetic algorithm (GA) to select sets of parents which between them contain chromosome segments with very high segment breeding values for the target trait, as an alternative to truncation selection on genomic estimated breeding values (GEBVs). Repeated recurrent selection and intercrossing for a yield trait, beginning with a founder population of wheat genotypes and guided by the GA, was compared to repeated recurrent selection and to optimal contribution selection (OCS) on yield GEBV. After 100 generations of selection and intercrossing, truncation selection had exhausted the genetic ersity, while considerable ersity remained in the GA population. In some situations, particularly where the number of parents crossed each generation was relatively small and the number of progeny per cross was large, gain from the GA exceeded that from truncation selection. Compared to OCS, selection under the GA maintained more useful ersity, i.e. erse segments with high yield GEBV, which allowed it to maintain higher rates of gain for longer. These results indicate that GA-based parent selection could be a promising method to maintain erse alleles with higher genetic merit in breeding populations with little additional effort to a regular genomic selection program. A segment-stacking algorithm can outperform optimal contribution selection and truncation selection in long-term crop breeding programs, particularly with small populations, while also maintaining more useful ersity.
Publisher: Wiley
Date: 31-01-2008
DOI: 10.1111/J.1365-2052.2007.01683.X
Abstract: The extent and pattern of linkage disequilibrium (LD) between closely spaced markers contain information about population history, including past population size and selection history. Selection signatures can be identified by comparing the LD surrounding a putative selected allele at a locus to the putative non-selected allele. In livestock populations, locations of selection signatures identified in this way should be correlated with QTL affecting production traits, as the populations have been under strong artificial selection for these traits. We used a dense SNP map of bovine chromosome 6 to characterize the pattern of LD on this chromosome in Norwegian Red cattle, a breed which has been strongly selected for milk production. The pattern of LD was generally consistent with strong selection in regions containing QTL affecting milk production traits, including a strong selection signature in a region containing a mutation known to affect milk production. The results demonstrate that in livestock populations, the origin of selection signatures will often be QTL for livestock production traits, and illustrate the value of selection signatures in uncovering new mutations with potential effects on quantitative traits.
Publisher: Oxford University Press (OUP)
Date: 22-04-2020
DOI: 10.1093/JAS/SKAA127
Abstract: Brahman cattle (Bos indicus) are well adapted to thrive in tropical environments. Since their introduction to Australia in 1933, Brahman’s ability to grow and reproduce on marginal lands has proven their value in the tropical beef industry. The poll phenotype, which describes the absence of horns, has become desirable in the cattle industry for animal welfare and handler safety concerns. The poll locus has been mapped to chromosome one. Four alleles, each a copy number variant, have been reported across this locus in B. indicus and Bos taurus. However, the causative mutation in Brahman cattle has not been fully characterized. Oxford Nanopore Technologies’ minION sequencer was used to sequence four homozygous poll (PcPc), four homozygous horned (pp), and three heterozygous (Pcp) Brahmans to characterize the poll allele in Brahman cattle. A total of 98 Gb were sequenced and an average coverage of 3.33X was achieved. Read N50 scores ranged from 9.9 to 19 kb. Examination of the mapped reads across the poll locus revealed insertions approximately 200 bp in length in the poll animals that were absent in the horned animals. These results are consistent with the Celtic poll allele, a 212-bp duplication that replaces 10 bp. This provides direct evidence that the Celtic poll allele is segregating in the Australian Brahman population.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 24-04-2009
Abstract: A survey of genetic ersity of cattle suggests two domestication events in Asia and selection by husbandry.
Publisher: Springer Science and Business Media LLC
Date: 19-01-2017
DOI: 10.1038/SREP39896
Abstract: Scientific Reports 6: Article number: 34114 published online: 29 September 2016 updated: 19 January 2017. The original version of this Article omitted an affiliation for J. B. Garner. The correct affiliations are listed below: Agriculture Victoria, Department of Economic Development, Jobs, Transport and Resources, 1301 Hazeldean Road, Ellinbank, Victoria 3821, Australia.
Publisher: Research Square Platform LLC
Date: 27-05-2019
Abstract: Background MicroRNAs regulate many eukaryotic biological processes in a temporal- and spatial-specific manner. Yet in cattle it is not fully known which microRNAs are expressed in each tissue, which genes they regulate, or which sites a given microRNA bind to within messenger RNAs (mRNAs). An improved annotation of tissue-specific microRNA network may in the future assist with the identification of causal variants affecting complex traits. Results We report findings from analysing short RNA sequence from 17 tissues from a single lactating dairy cow. Using miRDeep2, we identified 699 expressed mature microRNAs. Using TargetScan, known (60%) and novel (40%) microRNAs were predicted to interact with 780,481 sites in bovine mRNAs homologous with human. Putative interactions between microRNA families and targets were significantly enriched for interactions from previous experimental and computational identification. Characterizing features of microRNAs and targets, we showed that (1) mature microRNAs derived from different arms of the same precursor targeted different genes in different tissues (2) miRNA target sites preferentially occurred within gene regions undergoing active histone modification (3) variants within microRNAs and targets had lower allele frequencies than variants across the genome, as identified from 65 million whole genome sequence variants (4) no significant correlation was found between the abundance of microRNAs and mRNAs differentially expressed in the same tissue (5) microRNAs and target sites weren’t significantly associated with allelic imbalance of gene targets. Conclusion This study contributes to the goals of Functional Annotation of Animal Genomes consortium to improve the annotation of genomes of domestic animals.
Publisher: Springer Science and Business Media LLC
Date: 10-12-2018
DOI: 10.1038/S41598-018-35698-5
Abstract: Brahman cattle have a Bos indicus and Bos taurus mosaic genome, as a result of the process used to create the breed (repeat backcrossing of Bos taurus females to Bos indicus bulls). With the aim of identifying Bos taurus segments in the Brahman genome at sequence level resolution, we sequenced the genomes of 46 influential Brahman bulls. Using 36 million variants identified in the sequences, we searched for regions close to fixation for Bos indicus or Bos taurus segments that were longer than expected by chance (from simulation of the breed formation history of Brahman cattle). Regions close to fixation for Bos indicus content were enriched for protein synthesis genes, while regions of higher Bos taurus content included genes of the G-protein coupled receptor family (including genes implicated in puberty, such as THRS ). The region with the most extreme Bos taurus enrichment was on chromosome 14 surrounding PLAG1 . The introgressed Bos taurus allele at PLAG1 increases stature and the high frequency of the allele likely reflects strong selection for the trait. Finally, we provide evidence that the polled mutation in Brahmans, a desirable trait under very strong recent selection, is of Celtic origin and is introgressed from Bos taurus .
Publisher: Hindawi Limited
Date: 08-2007
DOI: 10.1017/S0016672307008865
Abstract: A key question for the implementation of marker-assisted selection (MAS) using markers in linkage disequilibrium with quantitative trait loci (QTLs) is how many markers surrounding each QTL should be used to ensure the marker or marker haplotypes are in sufficient linkage disequilibrium (LD) with the QTL. In this paper we compare the accuracy of MAS using either single markers or marker haplotypes in an Angus cattle data set consisting of 9323 genome-wide single nucleotide polymorphisms (SNPs) genotyped in 379 Angus cattle. The extent of LD in the data set was such that the average marker–marker r 2 was 0·2 at 200 kb. The accuracy of MAS increased as the number of markers in the haplotype surrounding the QTL increased, although only when the number of markers in the haplotype was 4 or greater did the accuracy exceed that achieved when the SNP in the highest LD with the QTL was used. A large number of phenotypic records ( ) were required to accurately estimate the effects of the haplotypes.
Publisher: Wiley
Date: 09-2016
Publisher: American Dairy Science Association
Date: 09-2013
Abstract: Variation in the composition of microorganisms in the rumen (the rumen microbiome) of dairy cattle (Bos taurus) is of great interest because of possible links to methane emission levels. Feed additives are one method being investigated to reduce enteric methane production by dairy cattle. Here we report the effect of 2 methane-mitigating feed additives (grapemarc and a combination of lipids and tannin) on rumen microbiome profiles of Holstein dairy cattle. We used untargeted (shotgun) massively parallel sequencing of microbes present in rumen fluid to generate quantitative rumen microbiome profiles. We observed large effects of the feed additives on the rumen microbiome profiles using multiple approaches, including linear mixed modeling, hierarchical clustering, and metagenomic predictions. The effect on the fecal microbiome profiles was not detectable using hierarchical clustering, but was significant in the linear mixed model and when metagenomic predictions were used, suggesting a more subtle effect of the diets on the lower gastrointestinal microbiome. A differential representation analysis (analogous to differential expression in RNA sequencing) showed significant overlap in the contigs (which are genome fragments representing different microorganism species) that were differentially represented between experiments. These similarities suggest that, despite the different additives used, the 2 diets assessed in this investigation altered the microbiomes of the s les in similar ways. Contigs that were differentially represented in both experiments were tested for associations with methane production in an independent set of animals. These animals were not treated with a methane-mitigating diet, but did show substantial natural variation in methane emission levels. The contigs that were significantly differentially represented in response to both dietary additives showed a significant enrichment for associations with methane production. This suggests that these methane-mitigating diets have altered the rumen microbiome toward naturally low methane-emitting microbial profiles. The contig sequences are predominantly new and include Faecalibacterium spp. The contigs we have identified here are potential biomarkers for low-methane-emitting cattle.
Publisher: Springer Science and Business Media LLC
Date: 25-07-2007
Abstract: Genetic variation explains a considerable part of observed phenotypic variation in gene expression networks. This variation has been shown to be located both locally ( cis ) and distally ( trans ) to the genes being measured. Here we explore to which degree the phenotypic manifestation of local and distant polymorphisms is a dynamic feature of regulatory design. By combining mathematical models of gene expression networks with genetic maps and linkage analysis we find that very different network structures and regulatory motifs give similar cis / trans linkage patterns. However, when the shape of the cis- regulatory input functions is more nonlinear or threshold-like, we observe for all networks a dramatic increase in the phenotypic expression of distant compared to local polymorphisms under otherwise equal conditions. Our findings indicate that genetic variation affecting the form of cis -regulatory input functions may reshape the genotype-phenotype map by changing the relative importance of cis and trans variation. Our approach combining nonlinear dynamic models with statistical genetics opens up for a systematic investigation of how functional genetic variation is translated into phenotypic variation under various systemic conditions.
Publisher: Springer Science and Business Media LLC
Date: 17-04-2015
Publisher: Cold Spring Harbor Laboratory
Date: 13-12-2021
DOI: 10.1101/2021.12.12.472291
Abstract: Simulation tools are key to designing and optimising breeding programs that are multi-year, high-effort endeavours. Tools that operate on real genotypes and integrate easily with other analysis software are needed to guide users to crossing decisions that best balance genetic gains and ersity to maintain gains in the future. This paper presents genomicSimulation, a fast and flexible tool for the stochastic simulation of crossing and selection on real genotypes. It is fully written in C for high execution speeds, has minimal dependencies, and is available as an R package for integration with R’s broad range of analysis and visualisation tools. Comparisons of a simulated recreation of a breeding program to the real data shows that the tool’s simulated offspring correctly show key population features, such as linkage disequilibrium patterns and genomic relationships. Both versions of genomicSimulation are freely available on GitHub: The R package version at llrs/genomicSimulation/ and the C library version at llrs/genomicSimulationC/
Publisher: MDPI AG
Date: 18-03-2021
DOI: 10.3390/ANI11030870
Abstract: Breeding for polled animals is deemed the most practical solution to eradicate horns naturally and circumvent management costs and risks on health and welfare. However, there has been a historical reluctance by some farmers to select polled animals due to perceived lower productivity of their calves. This study has compared estimated breeding values (EBVs) between horned and polled animals (N = 2,466,785) for 12 production and carcass traits to assess historical (before 2000) and recent (2000–2018) genetic implications of poll breeding. Older generations of the polled animals in most breeds had significantly lower (Bonferroni-corrected p = 0.05) genetic merits for live (birth to maturity) and carcass weights, milk, meat quality, and fat content traits. Substantial gains of genetic potential were achieved during 2000 to 2018 in each breed, such that polled animals have significantly improved for the majority of traits studied. Generally, polled cohorts showed advantageous EBVs for live and carcass weights irrespective of the lower birth weights in some breeds. While Polled Brahman showed inferior production parameters, the poll genetics’ effect size (d) and correlation (r) were very small on recent birth weight (d = −0.30, r = −0.08), 200 days (−0.19, −0.05), 400 days (−0.06, −0.02), 600 days (−0.05, −0.01), mature cow live weight (−0.08, −0.02), and carcass weight (−0.19, −0.05). In conclusion, although there is some evidence that historical selection for polled breeding animals may have reduced productivity, there is strong evidence that more recent selection for polled genotypes in the breeds studied has not resulted in any adverse effects on genetic merit.
Publisher: Springer Science and Business Media LLC
Date: 15-02-2021
Publisher: American Dairy Science Association
Date: 2012
Abstract: In this study, 3 strategies for controlling progeny inbreeding in mating plans were compared. The strategies used information from pedigree inbreeding coefficients, genomic relationships, or shared runs of homozygosity. The strategies were compared for the reduction in genetic gain and progeny inbreeding that would be expected from selected matings, and for the decrease of homozygosity of deleterious recessive alleles. Using real pedigree, genotype [43,115 single nucleotide polymorphism (SNP) markers], and estimated breeding value data from Holstein cattle, mating plans were derived for herds of 300 cows with 20 sires available for mating, replicated 50 times. Each of the 300 in iduals allocated as dams were matched to 1 of 20 sires to maximize genetic merit minus the penalty for estimated progeny inbreeding, and given the restriction that the sire could not be mated to more than 10% of the cows. The strategy that used a genomic relationship matrix (GRM) was the most effective in reducing average progeny inbreeding this strategy also resulted in fewer homozygous SNP out of 1,000 low-frequency SNP compared with the strategy using pedigree information. In the future, large numbers of cattle may be genotyped for low-density SNP panels. A GRM constructed using 3,123 SNP produced results similar to a GRM constructed using the full 43,115 SNP. These results demonstrate that using GRM information, a 1% reduction in progeny inbreeding (valued at around $5 per cow) can be made with very little compromise in the overall breeding objective. These results and the availability of low-cost, low-density genotyping make it attractive to apply mating plans that use genomic information in commercial dairy herds.
Publisher: Public Library of Science (PLoS)
Date: 07-12-2015
Publisher: MDPI AG
Date: 20-11-2021
DOI: 10.3390/AGRICULTURE11111172
Abstract: Genomic selection has transformed animal and plant breeding in advanced economies globally, resulting in economic, social and environmental benefits worth billions of dollars annually. Although genomic selection offers great potential in low- to middle-income countries because detailed pedigrees are not required to estimate breeding values with useful accuracy, the difficulty of effective phenotype recording, complex funding arrangements for a limited number of essential reference populations in only a handful of countries, questions around the sustainability of those livestock-resource populations, lack of on-farm, laboratory and computing infrastructure and lack of human capacity remain barriers to implementation. This paper examines those challenges and explores opportunities to mitigate or reduce the problems, with the aim of enabling smallholder livestock-keepers and their associated value chains in low- to middle-income countries to also benefit directly from genomic selection.
Publisher: Springer Science and Business Media LLC
Date: 05-2019
DOI: 10.1038/S41588-019-0382-2
Abstract: Introgression is a potential source of beneficial genetic ersity. The contribution of introgression to adaptive evolution and improvement of wheat as it was disseminated worldwide remains unknown. We used targeted re-sequencing of 890 erse accessions of hexaploid and tetraploid wheat to identify wild-relative introgression. Introgression, and selection for improvement and environmental adaptation, each reduced deleterious allele burden. Introgression increased ersity genome wide and in regions harboring major agronomic genes, and contributed alleles explaining a substantial proportion of phenotypic variation. These results suggest that historic gene flow from wild relatives made a substantial contribution to the adaptive ersity of modern bread wheat.
Publisher: Cold Spring Harbor Laboratory
Date: 10-02-2022
DOI: 10.1101/2022.02.09.479458
Abstract: Recent advances in sequencing technology have revolutionised access to large scale genomic data that can be assembled into a platinum quality genome. Here we present a high quality genome assembly with less than 300 gaps of a Brahman cow ( B. taurus indicus ). The assembly was generated using 195GB of PacBio and 169GB of Oxford Nanopore Technologies sequence data. The high quality genome assembly allows us to identify substantial GC content variation that is positively associated with gene rich islands, and negatively associated with genetic variation in the form of structural variants. In addition, 92371 structural variants that are segregating in the brahman population were identified. Gene ontology analysis revealed that genes with varying copy numbers were enriched for gene ontology terms related to immune function. This analysis has revealed the complex structure of the mammalian genome of an outbred species, and identifies the ability of long read data from diploid species can be used to not only assemble a high quality genome, but also discover novel genetic variation within that genome.
Publisher: Annual Reviews
Date: 15-02-2019
DOI: 10.1146/ANNUREV-ANIMAL-020518-115024
Abstract: The 1000 Bull Genomes Project is a collection of whole-genome sequences from 2,703 in iduals capturing a significant proportion of the world's cattle ersity. So far, 84 million single-nucleotide polymorphisms (SNPs) and 2.5 million small insertion deletions have been identified in the collection, a very high level of genetic ersity. The project has greatly accelerated the identification of deleterious mutations for a range of genetic diseases, as well as for embryonic lethals. The rate of identification of causal mutations for complex traits has been slower, reflecting the typically small effect size of these mutations and the fact that many are likely in as-yet-unannotated regulatory regions. Both the deleterious mutations that have been identified and the mutations associated with complex trait variation have been included in low-cost SNP array designs, and these arrays are being genotyped in tens of thousands of dairy and beef cattle, enabling management of deleterious mutations in these populations as well as genomic selection.
Publisher: Hindawi Limited
Date: 12-2009
DOI: 10.1017/S0016672309990310
Abstract: A number of farmed species are characterized by breeding populations of large full-sib families, including aquaculture species and outcrossing plant species. Whole genome association studies in such species must account for stratification arising from the full-sib family structure to avoid high rates of false discovery. Here, we demonstrate the value of selective genotyping strategies which balance the contribution of families across high and low phenotypes to greatly reduce rates of false discovery with a minimal effect on power.
Publisher: Cold Spring Harbor Laboratory
Date: 12-03-2019
DOI: 10.1101/574954
Abstract: MicroRNAs regulate many eukaryotic biological processes in a temporal- and spatial-specific manner. Yet in cattle it is not fully known which microRNAs are expressed in each tissue, which genes they regulate, or which sites a given microRNA bind to within messenger RNAs. An improved annotation of tissue-specific microRNA network may in the future assist with the identification of causal variants affecting complex traits. Here, we report findings from analysing short RNA sequence from 17 tissues from a single lactating dairy cow. Using miRDeep2, we identified 699 expressed mature microRNA sequences. Using TargetScan, known (60%) and novel (40%) microRNAs were predicted to interact with 780,481 sites in bovine messenger RNAs homologous with human. Putative interactions between microRNA families and targets were significantly enriched for interactions from previous experimental and computational identification. Characterizing features of microRNAs and targets, we showed that (1) mature microRNAs derived from different arms of the same precursor targeted different genes in different tissues (2) miRNA target sites preferentially occurred within gene regions marked with active histone modification (3) variants within microRNAs and targets had lower allele frequencies than variants across the genome, as identified from 65 million whole genome sequence variants (4) no significant correlation was found between the abundance of microRNAs and messenger RNAs differentially expressed in the same tissue (5) microRNAs and target sites weren’t significantly associated with allelic imbalance of gene targets. This study contributes to the goals of Functional Annotation of Animal Genomes consortium to improve the annotation of genomes of domestic animals.
Publisher: Springer Science and Business Media LLC
Date: 2014
Publisher: Springer Science and Business Media LLC
Date: 18-06-2013
DOI: 10.1038/NRG3457
Publisher: Springer Science and Business Media LLC
Date: 18-11-2013
DOI: 10.1038/NRG3457-C2
Publisher: Springer Science and Business Media LLC
Date: 20-02-2009
Abstract: A high resolution SNP map was constructed for the bovine casein region to identify haplotype structures and study associations with milk traits in Norwegian Red cattle. Our analyses suggest separation of the casein cluster into two haplotype blocks, one consisting of the CSN1S1 , CSN2 and CSN1S2 genes and another one consisting of the CSN3 gene. Highly significant associations with both protein and milk yield were found for both single SNPs and haplotypes within the CSN1S1-CSN2-CSN1S2 haplotype block. In contrast, no significant association was found for single SNPs or haplotypes within the CSN3 block. Our results point towards CSN2 and CSN1S2 as the most likely loci harbouring the underlying causative DNA variation. In our study, the most significant results were found for the SNP CSN2_67 with the C allele consistently associated with both higher protein and milk yields. CSN2_67 calls a C to an A substitution at codon 67 in β-casein gene resulting in histidine replacing proline in the amino acid sequence. This polymorphism determines the protein variants A1/B ( CSN2_67 A allele) versus A2/A3 ( CSN2_67 C allele). Other studies have suggested that a high consumption of A1/B milk may affect human health by increasing the risk of diabetes and heart diseases. Altogether these results argue for an increase in the frequency of the CSN2_67 C allele or haplotypes containing this allele in the Norwegian Red cattle population by selective breeding.
Publisher: Cold Spring Harbor Laboratory
Date: 05-06-2017
DOI: 10.1101/143990
Abstract: Genome sequences for hundreds of mammalian species are available, but an understanding of their genomic regulatory regions, which control gene expression, is only beginning. A comprehensive prediction of potential active regulatory regions is necessary to functionally study the roles of the majority of genomic variants in evolution, domestication, and animal production. We developed a computational method to predict regulatory DNA sequences (promoters, enhancers and transcription factor binding sites) in production animals (cows and pigs) and extended its broad applicability to other mammals. The method utilizes human regulatory features identified from thousands of tissues, cell lines, and experimental assays to find homologous regions that are conserved in sequences and genome organization and are enriched for regulatory elements in the genome sequences of other mammalian species. Importantly, we developed a filtering strategy, including a machine learning classification method, to utilize a very small number of species-specific experimental datasets available to select for the likely active regulatory regions. The method finds the optimal combination of sensitivity and accuracy to unbiasedly predict regulatory regions in mammalian species. Furthermore, we demonstrated the utility of the predicted regulatory datasets in cattle for prioritizing variants associated with multiple production and climate change adaptation traits, and identifying potential genome editing targets.
Publisher: Oxford University Press (OUP)
Date: 10-2019
DOI: 10.1534/GENETICS.119.302336
Abstract: De novo mutations (DNM) create new genetic variance and are an important driver for long-term selection response. We hypothesized that genomic selection exploits mutational variance less than traditional selection methods such as mass selection or selection on pedigree-based breeding values, because DNM in selection candidates are not captured when the selection candidates’ own phenotype is not used in genomic selection, DNM are not on SNP chips and DNM are not in linkage disequilibrium with the SNP on the chip. We tested this hypothesis with Monte Carlo simulation. From whole-genome sequence data, a subset of ∼300,000 variants was used that served as putative markers, quantitative trait loci or DNM. We simulated 20 generations with truncation selection based on breeding values from genomic best linear unbiased prediction without (GBLUP_no_OP) or with own phenotype (GBLUP_OP), pedigree-based BLUP without (BLUP_no_OP) or with own phenotype (BLUP_OP), or directly on phenotype. GBLUP_OP was the best strategy in exploiting mutational variance, while GBLUP_no_OP and BLUP_no_OP were the worst in exploiting mutational variance. The crucial element is that GBLUP_no_OP and BLUP_no_OP puts no selection pressure on DNM in selection candidates. Genetic variance decreased faster with GBLUP_no_OP and GBLUP_OP than with BLUP_no_OP, BLUP_OP or mass selection. The distribution of mutational effects, mutational variance, number of DNM per in idual and nonadditivity had a large impact on mutational selection response and mutational genetic variance, but not on ranking of selection strategies. We advocate that more sustainable genomic selection strategies are required to optimize long-term selection response and to maintain genetic ersity.
Publisher: American Dairy Science Association
Date: 05-2018
Abstract: Genomic prediction is applicable to in iduals of different breeds. Empirical results to date, however, show limited benefits in using information on multiple breeds in the context of genomic prediction. We investigated a multitask Bayesian model, presented previously by others, implemented in a Bayesian stochastic search variable selection (BSSVS) model. This model allowed for evidence of quantitative trait loci (QTL) to be accumulated across breeds or for both QTL that segregate across breeds and breed-specific QTL. In both cases, single nucleotide polymorphism effects were estimated with information from a single breed. Other models considered were a single-trait and multitrait genomic residual maximum likelihood (GREML) model, with breeds considered as different traits, and a single-trait BSSVS model. All single-trait models were applied to each of the 2 breeds separately and to the pooled data of both breeds. The data used included a training data set of 6,278 Holstein and 722 Jersey bulls, as well as 374 Jersey validation bulls. All animals had genotypes for 474,773 single nucleotide polymorphisms after editing and phenotypes for milk, fat, and protein yields. Using the same training data, BSSVS consistently outperformed GREML. The multitask BSSVS, however, did not outperform single-trait BSSVS, which used pooled Holstein and Jersey data for training. Thus, the rigorous assumption that the traits are the same in both breeds yielded a slightly better prediction than a model that had to estimate the correlation between the breeds from the data. Adding the Holstein data significantly increased the accuracy of the single-trait GREML and BSSVS in predicting the Jerseys for milk and protein, in line with estimated correlations between the breeds of 0.66 and 0.47 for milk and protein yields, whereas only the BSSVS model significantly improved the accuracy for fat yield with an estimated correlation between breeds of only 0.05. The relatively high genetic correlations for milk and protein yields, and the superiority of the pooling strategy, is likely the result of the observed admixture between both breeds in our data. The Bayesian model was able to detect several QTL in Holsteins, which likely enabled it to outperform GREML. The inability of the multitask Bayesian models to outperform a simple pooling strategy may be explained by the fact that the pooling strategy assumes equal effects in both breeds furthermore, this assumption may be valid for moderate- to large-sized QTL, which are important for multibreed genomic prediction.
Publisher: Oxford University Press (OUP)
Date: 07-2011
Abstract: Cattle in breeds formed by recent crossing of Bos taurus (Bt) and Bos indicus (Bi) subspecies should contain chromosomes that are a composite of Bt and Bt segments. Using data from a 50K SNP chip, we were able to identify whether a chromosome segment of 11 SNP in a composite animal descended from a Bt or a Bi ancestor. When the method was tested in purebred Bt or Brahman cattle, about 94% of segments were assigned correctly. About 10% of the genome in Australian Brahman cattle appears to be of Bt origin, as might be expected from their history. We then examined the effect of the origin of each chromosome segment on BW in a population of 515 Bt × Bi composite cattle and found 67 chromosome segments with a significant (P<0.01) effect. We confirmed these effects by examining these 67 segments in a population of Brahman cattle and in a population of mixed breeds including composite breeds such as Santa Gertrudis and Brahman cattle. About 66% of the 67 segments had an effect in the same direction in the confirmation analyses as in the discovery population. However, the effect on BW and other traits of chromosome segment origin is small, indicating that we had low power to detect these effects with the number of animals available. Consequently, when chromosome segment origin was used in genomic selection to predict BW, the accuracy was low (0.08). Chromosome segments that had a positive effect on BW tend to be at greater frequency in composite breeds than chromosome segments with a negative effect on BW.
Publisher: Springer Science and Business Media LLC
Date: 24-05-2018
Publisher: Oxford University Press (OUP)
Date: 20-08-2020
DOI: 10.1093/JAS/SKAA262
Abstract: Methane production from rumen methanogenesis contributes approximately 71% of greenhouse gas emissions from the agricultural sector. This study has performed genomic predictions for methane production from 99 sheep across 3 yr using a residual methane phenotype that is log methane yield corrected for live weight, rumen volume, and feed intake. Using genomic relationships, the prediction accuracies (as determined by the correlation between predicted and observed residual methane production) ranged from 0.058 to 0.220 depending on the time point being predicted. The best linear unbiased prediction algorithm was then applied to relationships between animals that were built on the rumen metabolome and microbiome. Prediction accuracies for the metabolome-based relationships for the two available time points were 0.254 and 0.132 the prediction accuracy for the first microbiome time point was 0.142. The second microbiome time point could not successfully predict residual methane production. When the metabolomic relationships were added to the genomic relationships, the accuracy of predictions increased to 0.274 (from 0.201 when only the genomic relationship was used) and 0.158 (from 0.081 when only the genomic relationship was used) for the two time points, respectively. When the microbiome relationships from the first time point were added to the genomic relationships, the maximum prediction accuracy increased to 0.247 (from 0.216 when only the genomic relationship was used), which was achieved by giving the genomic relationships 10 times more weighting than the microbiome relationships. These accuracies were higher than the genomic, metabolomic, and microbiome relationship matrixes achieved alone when identical sets of animals were used.
Publisher: Springer Science and Business Media LLC
Date: 19-12-2019
DOI: 10.1007/S00122-018-3270-8
Abstract: Genomic prediction based on additive genetic effects can accelerate genetic gain. There are opportunities for further improvement by including non-additive effects that access untapped sources of genetic ersity. Several studies have reported a worrying gap between the projected global future demand for plant-based products and the current annual rates of production increase, indicating that enhancing the rate of genetic gain might be critical for future food security. Therefore, new breeding technologies and strategies are required to significantly boost genetic improvement of future crop cultivars. Genomic selection (GS) has delivered considerable genetic gain in animal breeding and is becoming an essential component of many modern plant breeding programmes as well. In this paper, we review the lessons learned from implementing GS in livestock and the impact of GS on crop breeding, and discuss important features for the success of GS under different breeding scenarios. We highlight major challenges associated with GS including rapid genotyping, phenotyping, genotype-by-environment interaction and non-additivity and give ex les for opportunities to overcome these issues. Finally, the potential of combining GS with other modern technologies in order to maximise the rate of crop genetic improvement is discussed, including the potential of increasing prediction accuracy by integration of crop growth models in GS frameworks.
Publisher: Elsevier BV
Date: 05-2018
Publisher: Wiley
Date: 15-08-2019
Publisher: Hindawi Limited
Date: 10-2009
DOI: 10.1017/S0016672309990243
Abstract: Genomic selection describes a selection strategy based on genomic breeding values predicted from dense single nucleotide polymorphism (SNP) data. Multiple methods have been proposed but the critical issue is how to decide whether an SNP should be included in the predictive set to estimate breeding values. One major disadvantage of the traditional Bayes B approach is its high computational demands caused by the changing dimensionality of the models. The use of stochastic search variable selection (SSVS) retains the same assumptions about the distribution of SNP effects as Bayes B, while maintaining constant dimensionality. When Bayesian SSVS was used to predict genomic breeding values for real dairy data over a range of traits it produced accuracies higher or equivalent to other genomic selection methods with significantly decreased computational and time demands than Bayes B.
Publisher: MDPI AG
Date: 08-03-2021
DOI: 10.3390/ANI11030729
Abstract: A limited literature suggests relatively simple feeding regimes and diet formulation strategies for dairy cows in Vietnamese smallholder dairy farms (SDFs). This study aimed to classify and compare feeding regimes and nutrient balance for lactating cows between four typical dairy regions (south lowland, south highland, north lowland, and north highland) in Vietnam and evaluate the possibility of systematic dietary imbalance. Eight SDFs from each of the four regions were visited for two adjacent milking periods per farm. For each visit, frequency and methods of feed and water supply to the lactating cows were recorded, and in idual fat corrected milk yield (ECM) of lactating cows were calculated from milk yield and fat concentration. The amount of each diet ingredient offered and refused by each lactating group was weighed and s led for calculation of dry matter intake per cow (DMI) and analysis of nutrient composition in the component offered. PCDairy, a diet formulation computer model, was used to calculate actual and recommended dietary nutrient concentrations and predict potential milk production. Factor analysis, cluster analysis, and ANOVA were applied to determine grouping effects across as well as between regions. Feeding regimes and diets were grouped into three and nine clusters, respectively. Farmers in the same region tended to apply similar diets and feeding regimes. Across regions, only 47% of all SDFs supplied water ad libitum to the cows. The most used roughages including Napier grass, corn silage, fresh corn with cob, and rice straw were all relatively high in neutral detergent fibre (NDF), acid detergent fibre (ADF), and acid detergent lignin (ADL). The diets in all regions were excessive in crude protein, NDF, ADF, ADL, and most minerals (Ca, P, Mg, K, Na, S, Fe, Zn, Cu, and Mn) but insufficient in net energy and non-fibre carbohydrate. Feed efficiency (1.06 kg FCM/kg DMI) of the diets were sub-optimal. Feeding regimes and dietary nutrient balance of the south lowland SDFs were most problematic. Increasing dietary net energy concentration by increasing the use of starch and fat and decreasing dietary fibre concentration by decreasing the use of Napier grass or rice straw to balance the diets might help improve the milk production and thereby increase feed efficiency.
Publisher: MDPI AG
Date: 09-12-2020
Abstract: Oxford Nanopore Technologies’ MinION has proven to be a valuable tool within human and microbial genetics. Its capacity to produce long reads in real time has opened up unique applications for portable sequencing. Ex les include tracking the recent African swine fever outbreak in China and providing a diagnostic tool for disease in the cassava plant in Eastern Africa. Here we review the current applications of Oxford Nanopore sequencing in livestock, then focus on proposed applications in livestock agriculture for rapid diagnostics, base modification detection, reference genome assembly and genomic prediction. In particular, we propose a future application: ‘crush-side genotyping’ for real-time on-farm genotyping for extensive industries such as northern Australian beef production. An initial in silico experiment to assess the feasibility of crush-side genotyping demonstrated promising results. SNPs were called from simulated Nanopore data, that included the relatively high base call error rate that is characteristic of the data, and calling parameters were varied to understand the feasibility of SNP calling at low coverages in a heterozygous population. With optimised genotype calling parameters, over 85% of the 10,000 simulated SNPs were able to be correctly called with coverages as low as 6×. These results provide preliminary evidence that Oxford Nanopore sequencing has potential to be used for real-time SNP genotyping in extensive livestock operations.
Publisher: Public Library of Science (PLoS)
Date: 15-12-2021
DOI: 10.1371/JOURNAL.PONE.0261274
Abstract: Most traits in livestock, crops and humans are polygenic, that is, a large number of loci contribute to genetic variation. Effects at these loci lie along a continuum ranging from common low-effect to rare high-effect variants that cumulatively contribute to the overall phenotype. Statistical methods to calculate the effect of these loci have been developed and can be used to predict phenotypes in new in iduals. In agriculture, these methods are used to select superior in iduals using genomic breeding values in humans these methods are used to quantitatively measure an in idual’s disease risk, termed polygenic risk scores. Both fields typically use SNP array genotypes for the analysis. Recently, genotyping-by-sequencing has become popular, due to lower cost and greater genome coverage (including structural variants). Oxford Nanopore Technologies’ (ONT) portable sequencers have the potential to combine the benefits genotyping-by-sequencing with portability and decreased turn-around time. This introduces the potential for in-house clinical genetic disease risk screening in humans or calculating genomic breeding values on-farm in agriculture. Here we demonstrate the potential of the later by calculating genomic breeding values for four traits in cattle using low-coverage ONT sequence data and comparing these breeding values to breeding values calculated from SNP arrays. At sequencing coverages between 2X and 4X the correlation between ONT breeding values and SNP array-based breeding values was 0.92 when imputation was used and 0.88 when no imputation was used. With an average sequencing coverage of 0.5x the correlation between the two methods was between 0.85 and 0.92 using imputation, depending on the trait. This suggests that ONT sequencing has potential for in clinic or on-farm genomic prediction, however, further work to validate these findings in a larger population still remains.
Publisher: Springer Science and Business Media LLC
Date: 27-11-2015
DOI: 10.1007/S00335-015-9613-8
Abstract: Dairy cattle are an interesting model for gaining insights into the genes responsible for the large variation between and within mammalian species in the protein and fat content of their milk and their milk volume. Large numbers of phenotypes for these traits are available, as well as full genome sequence of key founders of modern dairy cattle populations. In twenty target QTL regions affecting milk production traits, we imputed full genome sequence variant genotypes into a population of 16,721 Holstein and Jersey cattle with excellent phenotypes. Association testing was used to identify variants within each target region, and gene expression data were used to identify possible gene candidates. There was statistical support for imputed sequence variants in or close to BTRC, MGST1, SLC37A1, STAT5A, STAT5B, PAEP, VDR, CSF2RB, MUC1, NCF4, and GHDC associated with milk production, and EPGN for calving interval. Of these candidates, analysis of RNA-Seq data demonstrated that PAEP, VDR, SLC37A1, GHDC, MUC1, CSF2RB, and STAT5A were highly differentially expressed in mammary gland compared to 15 other tissues. For nine of the other target regions, the most significant variants were in non-coding DNA. Genomic predictions in a third dairy breed (Australian Reds) using sequence variants in only these candidate genes were for some traits more accurate than genomic predictions from 632,003 common SNP on the Bovine HD array. The genes identified in this study are interesting candidates for improving milk production in cattle and could be investigated for novel biological mechanisms driving lactation traits in other mammals.
Publisher: American Dairy Science Association
Date: 07-2018
Abstract: Researching depletions in homozygous genotypes for specific haplotypes among the large cohorts of animals genotyped for genomic selection is a very efficient strategy to map recessive lethal mutations. In this study, by analyzing real or imputed Illumina BovineSNP50 (Illumina Inc., San Diego, CA) genotypes from more than 250,000 Holstein animals, we identified a new locus called HH6 showing significant negative effects on conception rate and nonreturn rate at 56 d in at-risk versus control mating. We fine-mapped this locus in a 1.1-Mb interval and analyzed genome sequence data from 12 carrier and 284 noncarrier Holstein bulls. We report the identification of a strong candidate mutation in the gene encoding SDE2 telomere maintenance homolog (SDE2), a protein essential for genomic stability in eukaryotes. This A-to-G transition changes the initiator ATG (methionine) codon to ACG because the gene is transcribed on the reverse strand. Using RNA sequencing and quantitative reverse-transcription PCR, we demonstrated that this mutation does not significantly affect SDE2 splicing and expression level in heterozygous carriers compared with control animals. Initiation of translation at the closest in-frame methionine codon would truncate the SDE2 precursor by 83 amino acids, including the cleavage site necessary for its activation. Finally, no homozygote for the G allele was observed in a large population of nearly 29,000 in iduals genotyped for the mutation. The low frequency (1.3%) of the derived allele in the French population and the availability of a diagnostic test on the Illumina EuroG10K SNP chip routinely used for genomic evaluation will enable rapid and efficient selection against this deleterious mutation.
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/AN16452
Abstract: The present study determined the ability of a lifetime nutrient-partitioning model to simulate in idual genetic potentials of Australian Holstein cows. The model was initially developed in France and has been shown to be able to accurately simulate performance of in idual cows from various breeds. Generally, it assumes that the curves of cow performance differ only in terms of scaling, but the dynamic shape is universal. In other words, simulations of genetic variability in performance between cow genotypes can be performed using scaling parameters to simply scale the performance curves up or down. Validation of the model used performance data from 63 lactations of Australian Holstein cows offered lucerne cubes plus grain-based supplement. In idual cow records were used to derive genetic scaling parameters for each animal by calibrating the model to minimise root mean-square errors between observed and fitted values, cow by cow. The model was able to accurately fit the curves of bodyweight, milk fat concentration, milk protein concentration and milk lactose concentration with a high degree of accuracy (relative prediction errors %). Daily milk yield and weekly body condition score were satisfactorily predicted, although slight under-predictions of milk yield were identified during the last stage of lactation (relative prediction errors ≈11.1–15.6%). The prediction of feed intake was promising, with the value of relative prediction error of 18.1%. The results also suggest that the current recommendation of energy required for maintenance of pasture-based cows might be under-estimated. In conclusion, this model can be used to simulate genetic variability in the production potential of Australian cows. Thus, it can be used for simulation of consequences of future genetic-selection strategies on lifetime performance and efficiency of in idual cows.
Publisher: Springer Science and Business Media LLC
Date: 2012
Publisher: Springer Science and Business Media LLC
Date: 25-01-2017
Publisher: Elsevier BV
Date: 12-2008
Publisher: Springer Science and Business Media LLC
Date: 15-04-2019
Publisher: Springer Science and Business Media LLC
Date: 04-12-2019
DOI: 10.1038/S41576-018-0082-2
Abstract: The world demand for animal-based food products is anticipated to increase by 70% by 2050. Meeting this demand in a way that has a minimal impact on the environment will require the implementation of advanced technologies, and methods to improve the genetic quality of livestock are expected to play a large part. Over the past 10 years, genomic selection has been introduced in several major livestock species and has more than doubled genetic progress in some. However, additional improvements are required. Genomic information of increasing complexity (including genomic, epigenomic, transcriptomic and microbiome data), combined with technological advances for its cost-effective collection and use, will make a major contribution.
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/AN16449
Abstract: Climate change will have an impact on dairy cow performance. When heat stressed, animals consume less feed, followed by a decline in milk yield. Previously, we have found that there is genetic variation in this decline. Selection for increased milk production, a major breeding objective, is expected to reduce heat tolerance (HT), as these traits are genetically unfavourably correlated. We aimed to develop a future-scenarios selection tool to assist farmers in making selection decisions, that combines the current national dairy selection index, known as the balanced performance index (BPI), with a proposed HT genomic estimated breeding value (GEBV). Heat-tolerance GEBV was estimated for 12 062 genotyped cows and 10 981 bulls, using an established genomic-prediction equation. Publicly available future daily average temperature and humidity data were used to estimate mean daily temperature–humidity index for each dairy herd. An economic estimate of an in idual cow’s heat-tolerance breeding value (BV_HT) was calculated by multiplying head-tolerance GEBVs for milk, fat and protein by their respective economic values that are already used in the BPI. This was scaled for each region by multiplying BV_HT by the heat load, which is the temperature–humidity index units exceeding the threshold per year at a particular location. BV_HT were incorporated into the BPI as: BPI_HT = BPI + BV_HT where BPI_HT is the ‘augmented BPI’ breeding value including HT. A web-based application was developed enabling farmers to predict the future heat load of a herd and take steps to aim at genetic improvement in future generations by selecting bulls and cows that rank high for the ‘augmented BPI’.
Publisher: Wiley
Date: 07-11-2011
DOI: 10.1111/J.1439-0388.2011.00964.X
Abstract: Estimated breeding values (EBVs) using data from genetic markers can be predicted using a genomic relationship matrix, derived from animal's genotypes, and best linear unbiased prediction. However, if the accuracy of the EBVs is calculated in the usual manner (from the inverse element of the coefficient matrix), it is likely to be overestimated owing to s ling errors in elements of the genomic relationship matrix. We show here that the correct accuracy can be obtained by regressing the relationship matrix towards the pedigree relationship matrix so that it is an unbiased estimate of the relationships at the QTL controlling the trait. This method shows how the accuracy increases as the number of markers used increases because the regression coefficient (of genomic relationship towards pedigree relationship) increases. We also present a deterministic method for predicting the accuracy of such genomic EBVs before data on in idual animals are collected. This method estimates the proportion of genetic variance explained by the markers, which is equal to the regression coefficient described above, and the accuracy with which marker effects are estimated. The latter depends on the variance in relationship between pairs of animals, which equals the mean linkage disequilibrium over all pairs of loci. The theory was validated using simulated data and data on fat concentration in the milk of Holstein cattle.
Publisher: Oxford University Press (OUP)
Date: 26-04-2007
DOI: 10.1093/BIOINFORMATICS/BTM154
Abstract: Motivation: Single nucleotide polymorphism (SNP) detection exploiting redundancy in expressed sequence tag (EST) collections that arises from the presence of transcripts of the same gene from different in iduals has been used to generate large collections of SNPs for many species. A second source of redundancy, namely that EST collections can contain multiple transcripts of the same gene from the same in idual, can be exploited to distinguish true SNPs from sequencing error. In this article, we demonstrate with Atlantic salmon and pig EST collections that splitting the EST collection in two, detecting SNPs in both subsets, then accepting only cross-validated SNPs increases validation rates. Results: In the pig data set, 676 cross-validated putative SNPs were detected in a collection of 160 689 ESTs. When validating a subset of these by genotyping on MassARRAY 85.1% of SNPs were polymorphic in successful assays. In the salmon data set, 856 cross-validated putative SNPs were detected in a collection of 243 674 ESTs. Validation by genotyping showed that 81.0% of the cross-validated putative SNPs were polymorphic in successful assays. Availability: Cross-validated SNPs are available at dbSNP (rojects/SNP/), ss69371838-ss69372575 for the salmon SNPs and ss69372587-ss69373226 for the pig SNPs. Contact: ben.hayes@dpi.vic.gov.au
Publisher: Springer Science and Business Media LLC
Date: 15-03-2015
Publisher: Springer Science and Business Media LLC
Date: 25-03-2015
Publisher: Cold Spring Harbor Laboratory
Date: 16-11-2017
DOI: 10.1101/220251
Abstract: Mammalian phenotypes are shaped by numerous genome variants, many of which may regulate gene transcription or RNA splicing. To identify variants with regulatory functions in cattle, an important economic and model species, we used sequence variants to map a type of expression quantitative trait loci (expression QTLs) that are associated with variations in the RNA splicing, i.e., sQTLs. To further the understanding of regulatory variants, sQTLs were compare with other two types of expression QTLs, 1) variants associated with variations in gene expression, i.e., geQTLs and 2) variants associated with variations in exon expression, i.e., eeQTLs, in different tissues. Using whole genome and RNA sequence data from four tissues of over 200 cattle, sQTLs identified using exon inclusion ratios were verified by matching their effects on adjacent intron excision ratios. sQTLs contained the highest percentage of variants that are within the intronic region of genes and contained the lowest percentage of variants that are within intergenic regions, compared to eeQTLs and geQTLs. Many geQTLs and sQTLs are also detected as eeQTLs. Many expression QTLs, including sQTLs, were significant in all four tissues and had a similar effect in each tissue. To verify such expression QTL sharing between tissues, variants surrounding (±1Mb) the exon or gene were used to build local genomic relationship matrices (LGRM) and estimated genetic correlations between tissues. For many exons, the splicing and expression level was determined by the same cis additive genetic variance in different tissues. Thus, an effective but simple-to-implement meta-analysis combining information from three tissues is introduced to increase power to detect and validate sQTLs. sQTLs and eeQTLs together were more enriched for variants associated with cattle complex traits, compared to geQTLs. Several putative causal mutations were identified, including an sQTL at Chr6:87392580 within the 5 th exon of kappa casein ( CSN3 ) associated with milk production traits. Using novel analytical approaches, we report the first identification of numerous bovine sQTLs which are extensively shared between multiple tissue types. The significant overlaps between bovine sQTLs and complex traits QTL highlight the contribution of regulatory mutations to phenotypic variations.
Publisher: Springer Science and Business Media LLC
Date: 03-11-2016
Publisher: Oxford University Press (OUP)
Date: 19-06-2015
DOI: 10.1534/GENETICS.115.178038
Abstract: Doubled haploids are routinely created and phenotypically selected in plant breeding programs to accelerate the breeding cycle. Genomic selection, which makes use of both phenotypes and genotypes, has been shown to further improve genetic gain through prediction of performance before or without phenotypic characterization of novel germplasm. Additional opportunities exist to combine genomic prediction methods with the creation of doubled haploids. Here we propose an extension to genomic selection, optimal haploid value (OHV) selection, which predicts the best doubled haploid that can be produced from a segregating plant. This method focuses selection on the haplotype and optimizes the breeding program toward its end goal of generating an elite fixed line. We rigorously tested OHV selection breeding programs, using computer simulation, and show that it results in up to 0.6 standard deviations more genetic gain than genomic selection. At the same time, OHV selection preserved a substantially greater amount of genetic ersity in the population than genomic selection, which is important to achieve long-term genetic gain in breeding populations.
Publisher: MDPI AG
Date: 30-01-2021
DOI: 10.3390/ANI11020351
Abstract: In smallholder dairy farms (SDFs), farmers often build cowsheds using local materials and based on self-accumulated experience without due consideration to reducing the risk of heat stress. This study aimed to characterise the heat stress abatement strategies and microclimate within SDF cowsheds from four typical dairy regions of Vietnam (south lowland, south highland, north lowland and north highland) and identify the housing parameters most associated with the microclimate. The study was conducted on 32 SDFs (eight SDFs per region) in autumn 2017. Twelve housing management variables, illustrating cowshed design and heat stress abatement methods of each SDF, were collected. Six microclimate parameters, collected within the cowshed, were temperature (AT), humidity, air speed (AS), heat load index (HLI), Temperature-humidity index (THI) and accumulated heat load units (AHLU) during a day (06:00 h to 18:00 h). Factor analysis and cluster analysis was applied to group cowsheds of SDFs into clusters where SDFs in the cluster had the same cowshed characteristics. Multivariable linear models were applied to define the parameters most likely to inform future research into heat stress mitigation on SDF. Averaged from 08:00 h to 18:00 h, microclimate inside the cowsheds was considered hot (HLI 79) in the highland and very hot (HLI 86) in the lowland regions. Cows in the lowland regions accumulated high heat load (AHLU 50) by 18:00 h. Cowsheds of SDFs varied widely and grouped into seven cowshed types, but no type was more effective than others in reducing heat stress conditions within cowsheds. Using roof soakers together with fans decreased AT and HLI by 1.3 °C and 3.2 units, respectively, at 14:00 h compared to 11:00 h. Each 100 m increase in altitude was associated with decreases of 0.4 °C in AT, 1.3 units in HLI and 0.8 units in THI (p 0.001). Each meter increase in the eave height of the cowshed roof was associated with decreases of 0.87 °C in AT, 3.31 units in HLI and 1.42 units in THI, and an increase of 0.14 m/s in AS (p 0.05). The cowshed parameters that should be prioritised for future research into the amelioration of heat stress in SDF cows include using the roof soakers together with fans, increasing altitude, eave roof height and floor area per cow.
Publisher: Springer Science and Business Media LLC
Date: 24-03-2018
Publisher: Public Library of Science (PLoS)
Date: 23-09-2010
Publisher: American Dairy Science Association
Date: 03-2009
Publisher: Elsevier
Date: 2011
Publisher: Research Square Platform LLC
Date: 12-05-2023
DOI: 10.21203/RS.3.RS-2839305/V1
Abstract: Most genetic variants associated with fertility in mammals fall in non-coding regions of the genome and it is unclear how these variants affect fertility. Here we used genome-wide association (GWAS) summary statistics for heifer puberty (pubertal or not at 600 days) from 27,707 cattle multi-trait GWAS signals from 2,119 cattle for four fertility traits, including days to calving, age at first calving, heifer pregnancy status, and foetus age in weeks and expression quantitative trait locus (eQTL) for whole blood from 489 cattle, to identify 87 putatively functional genes affecting cattle fertility. Our analysis revealed a significant overlap between the set of cattle and human fertility-related genes. This finding implies the existence of a shared pool of genes that regulate fertility in mammals. These findings have important implications for the development of novel approaches to improve fertility in cattle and potentially in other mammals as well.
Publisher: Wiley
Date: 20-03-2009
DOI: 10.1111/J.1365-2052.2008.01815.X
Abstract: A number of cattle breeds have become highly specialized for milk or beef production, following strong artificial selection for these traits. In this paper, we compare allele frequencies from 9323 single nucleotide polymorphism (SNP) markers genotyped in dairy and beef cattle breeds averaged in sliding windows across the genome, with the aim of identifying ergently selected regions of the genome between the production types. The value of the method for identifying selection signatures was validated by four sources of evidence. First, differences in allele frequencies between dairy and beef cattle at in idual SNPs were correlated with the effects of those SNPs on production traits. Secondly, large differences in allele frequencies generally occurred in the same location for two independent data sets (correlation 0.45) between sliding window averages. Thirdly, the largest differences in sliding window average difference in allele frequencies were found on chromosome 20 in the region of the growth hormone receptor gene, which carries a mutation known to have an effect on milk production traits in a number of dairy populations. Finally, for the chromosome tested, the location of selection signatures between dairy and beef cattle was correlated with the location of selection signatures within dairy cattle.
Publisher: American Dairy Science Association
Date: 10-2015
Abstract: A new breeding value that combines the amount of feed saved through improved metabolic efficiency with predicted maintenance requirements is described. The breeding value includes a genomic component for residual feed intake (RFI) combined with maintenance requirements calculated from either a genomic or pedigree estimated breeding value (EBV) for body weight (BW) predicted using conformation traits. Residual feed intake is only available for genotyped Holsteins however, BW is available for all breeds. The RFI component of the "feed saved" EBV has 2 parts: Australian calf RFI and Australian lactating cow RFI. Genomic breeding values for RFI were estimated from a reference population of 2,036 in iduals in a multi-trait analysis including Australian calf RFI (n=843), Australian lactating cow RFI (n=234), and UK and Dutch lactating cow RFI (n=958). In all cases, the RFI phenotypes were deviations from a mean of 0, calculated by correcting dry matter intake for BW, growth, and milk yield (in the case of lactating cows). Single nucleotide polymorphism effects were calculated from the output of genomic BLUP and used to predict breeding values of 4,106 Holstein sires that were genotyped but did not have RFI phenotypes themselves. These bulls already had BW breeding values calculated from type traits, from which maintenance requirements in kilograms of feed per year were inferred. Finally, RFI and the feed required for maintenance (through BW) were used to calculate a feed saved breeding value and expressed as the predicted amount of feed saved per year. Animals that were 1 standard deviation above the mean were predicted to eat 66 kg dry matter less per year at the same level of milk production. In a data set of genotyped Holstein sires, the mean reliability of the feed saved breeding value was 0.37. For Holsteins that are not genotyped and for breeds other than Holsteins, feed saved is calculated using BW only. From April 2015, feed saved has been included as part of the Australian national selection index, the Balanced Performance Index (BPI). Selection on the BPI is expected to lead to modest gains in feed efficiency.
Publisher: Elsevier BV
Date: 2008
Publisher: Frontiers Media SA
Date: 05-09-2017
Publisher: Springer Science and Business Media LLC
Date: 20-06-2019
Publisher: CSIRO Publishing
Date: 25-05-2023
DOI: 10.1071/AN22451
Abstract: Context Genotyping-by-sequencing, the use of sequence reads to genotype single-nucleotide polymorphisms (SNPs), has seen an increase in popularity as a tool for genomic prediction. Oxford Nanopore Technologies (Nanopore) sequencing is an emerging technology that produces long sequence reads in real-time. Recent studies have established the ability for low-coverage Nanopore sequence data to be used for genomic prediction. However, the value proposition of Nanopore sequencing for in iduals could be improved if both genotyping and disease diagnosis are achieved from a single s le. Aims This study aimed to demonstrate that Nanopore sequencing can be used for both rapid genotyping and as a disease diagnostic tool using the same s le in livestock. Methods Total DNA extracts from nasal swabs collected from 48 feedlot cattle presenting with clinical signs of bovine respiratory disease (BRD) were sequenced using the Nanopore PromethION sequencer. After 24 h of sequencing, genotypes were imputed and genomic estimated breeding values (GEBVs) for four traits were derived using 641 163 SNPs and corresponding SNP effects. These GEBVs were compared with GEBVs derived from SNP array genotypes and calculated using the same SNP effects. Unmapped sequence reads were classified into taxa using Kraken2 and compared with quantitative real-time polymerase chain reaction (qPCR) results for five BRD-associated pathogens of interest. Key results Sequence-derived genotypes for 46 of the 48 animals were produced in 24 h and GEBV correlations ranged between 0.92 and 0.94 for the four traits. Eleven different BRD-associated pathogens (two viruses and nine bacterial species) were detected in the s les using Nanopore sequence data. A significant (P 0.001) relationship between Nanopore and qPCR results was observed for five overlapping species when a maximum threshold cycle was used. Conclusions The results of this study indicated that 46 cattle genomes can be multiplexed and accurately genotyped for downstream genomic prediction by using a single PromethION flow cell (ver. R9.4) in 24 h. This equates to a cost of AUD35.82 per s le for consumables. The concordance between qPCR results and pathogen proportion estimates also indicated that some pathogenic species, in particular bacterial species, can be accurately identified from the same test. Implications Using Nanopore sequencing, routine genotyping and disease detection in livestock could be combined into one cost-competitive test with a rapid turnaround time.
Publisher: Hindawi Limited
Date: 18-05-2011
DOI: 10.1017/S0016672311000097
Abstract: Genetic resistance to gastrointestinal worms is a complex trait of great importance in both livestock and humans. In order to gain insights into the genetic architecture of this trait, a mixed breed population of sheep was artificially infected with Trichostrongylus colubriformis ( n =3326) and then Haemonchus contortus ( n =2669) to measure faecal worm egg count (WEC). The population was genotyped with the Illumina OvineSNP50 BeadChip and 48 640 single nucleotide polymorphism (SNP) markers passed the quality controls. An independent population of 316 sires of mixed breeds with accurate estimated breeding values for WEC were genotyped for the same SNP to assess the results obtained from the first population. We used principal components from the genomic relationship matrix among genotyped in iduals to account for population stratification, and a novel approach to directly account for the s ling error associated with each SNP marker regression. The largest marker effects were estimated to explain an average of 0·48% ( T. colubriformis ) or 0·08% ( H. contortus ) of the phenotypic variance in WEC. These effects are small but consistent with results from other complex traits. We also demonstrated that methods which use all markers simultaneously can successfully predict genetic merit for resistance to worms, despite the small effects of in idual markers. Correlations of genomic predictions with breeding values of the industry sires reached a maximum of 0·32. We estimate that effective across-breed predictions of genetic merit with multi-breed populations will require an average marker spacing of approximately 10 kbp.
Publisher: Springer Science and Business Media LLC
Date: 2013
Publisher: Springer Science and Business Media LLC
Date: 03-04-2014
DOI: 10.1038/HDY.2013.13
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/AN16472
Abstract: The objective of the present research was to describe the physiological and production responses of lactating dairy cows during and after sudden exposure to temperate-climate heat-wave conditions, compared with cows in thermoneutral conditions. Twelve lactating multiparous Holstein–Friesian dairy cows were housed in controlled-climate chambers for 4 days. Six were exposed to a short-term temperature and humidity challenge (THc, diurnal temperature and humidity fluctuations inducing moderate heat stress temperature humidity index 74–84) and six cows were exposed to thermoneutral conditions (THn, temperatur humidity index 55–61). Cows were also measured during a 7-day pre-experimental and 14-day post-experimental period. Physiological indicators of heat stress were measured, including rectal and vaginal temperature and respiration rate, which indicated that the THc in controlled-climate chambers induced moderate heat stress. The cows exposed to the 4-day THc reduced their milk yield by 53% and their dry-matter intake by 48%, compared with the cows in the THn treatment. Milk yield of THc cows returned to pre-experimental milk yield by Day 7 and dry-matter intake by Day 4 of the post-experimental period. The short-term heat challenge induced metabolic adaptations by mobilising adipose tissue, as indicated by increased non-esterified fatty acids, and amino acids from skeletal muscle, as indicated by increased urea nitrogen to compensate for reduced nutrient intake and increased energy expenditure. Endocrine responses included greater prolactin concentrations, which is associated with thermoregulation and water metabolism. The cows exposed to THc displayed production and physical responses that facilitated lower metabolic heat production and greater heat dissipation in an attempt to maintain homeostasis during the short-term heat exposure. These results indicated that the conditions imposed on the cows in the controlled-climate chambers were sufficient to induce heat-stress responses and adversely affected production in the lactating dairy cow, and the delay between the return to normal feed intake and milk yield following the heat challenge suggests a period of metabolic recovery was occurring.
Publisher: Wiley
Date: 30-03-2015
DOI: 10.1111/JBG.12152
Abstract: The mutations that cause genetic variation in quantitative traits could be old and segregate across many breeds or they could be young and segregate only within one breed. This has implications for our understanding of the evolution of quantitative traits and for genomic prediction to improve livestock. We investigated the age of quantitative trait loci (QTL) for milk production traits identified as segregating in Holstein dairy cattle. We use a multitrait method and found that six of 11 QTL also segregate in Jerseys. Variants identified as Holstein-only QTL were fixed or rare [minor allele frequency (MAF) < 0.05] in Jersey. The age of the QTL mutations appears to vary from perhaps 2000 to 50,000 generations old. The older QTL tend to have high derived allele frequencies and often segregate across both breeds. Holstein-only QTL were often embedded within longer haplotypes, supporting the conclusion that they are typically younger mutations that have occurred more recently than QTL that segregate in both breeds. A reference population for genomic prediction using both Holsteins and Jersey cattle incorrectly predicted a QTL in Jersey cattle when the QTL only segregates in Holsteins. Overcoming this error should help to make genomic prediction more accurate in smaller breeds.
Publisher: American Dairy Science Association
Date: 2014
Abstract: Validating genomic prediction equations in independent populations is an important part of evaluating genomic selection. Published genomic predictions from 2 studies on (1) residual feed intake and (2) dry matter intake (DMI) were validated in a cohort of 78 multiparous Holsteins from Australia. The mean realized accuracy of genomic prediction for residual feed intake was 0.27 when the reference population included phenotypes from 939 New Zealand and 843 Australian growing heifers (aged 5-8 mo) genotyped on high density (770k) single nucleotide polymorphism chips. The 90% bootstrapped confidence interval of this estimate was between 0.16 and 0.36. The mean realized accuracy was slightly lower (0.25) when the reference population comprised only Australian growing heifers. Higher realized accuracies were achieved for DMI in the same validation population and using a multicountry model that included 958 lactating cows from the Netherlands and United Kingdom in addition to 843 growing heifers from Australia. The multicountry analysis for DMI generated 3 sets of genomic predictions for validation animals, one on each country scale. The highest mean accuracy (0.72) was obtained when the genomic breeding values were expressed on the Dutch scale. Although the validation population used in this study was small (n=78), the results illustrate that genomic selection for DMI and residual feed intake is feasible. Multicountry collaboration in the area of dairy cow feed efficiency is the evident pathway to achieving reasonable genomic prediction accuracies for these valuable traits.
Publisher: Frontiers Media SA
Date: 25-03-2022
DOI: 10.3389/FGENE.2022.784663
Abstract: Fertility is a key driver of economic profitability in cattle production. A number of studies have identified genes associated with fertility using genome wide association studies and differential gene expression analysis however, the genes themselves are poorly characterized in cattle. Here, we selected 13 genes from the literature which have previously been shown to have strong evidence for an association with fertility in Brahman cattle ( Bos taurus indicus ) or closely related breeds. We examine the expression variation of the 13 genes that are associated with cattle fertility using RNA-seq, CAGE-seq, and ISO-seq data from 11 different tissue s les from an adult Brahman cow and a Brahman fetus. Tissues examined include blood, liver, lung, kidney, muscle, spleen, ovary, and uterus from the cow and liver and lung from the fetus. The analysis revealed several novel isoforms, including seven from SERPINA7 . The use of three expression characterization methodologies (5′ cap selected ISO-seq, CAGE-seq, and RNA-seq) allowed the identification of isoforms that varied in their length of 5′ and 3′ untranslated regions, variation otherwise undetectable (collapsed as degraded RNA) in generic isoform identification pipelines. The combinations of different sequencing technologies allowed us to overcome the limitations of relatively low sequence depth in the ISO-seq data. The lower sequence depth of the ISO-seq data was also reflected in the lack of observed expression of some genes that were observed in the CAGE-seq and RNA-seq data from the same tissue. We identified allele specific expression that was tissue-specific in AR , IGF1 , SOX9 , STAT3 , and TAF9B . Finally, we characterized an exon of TAF9B as partially nested within the neighboring gene phosphoglycerate kinase 1. As this study only examined two animals, even more transcriptional variation may be present in a genetically erse population. This analysis reveals the large amount of transcriptional variation within mammalian fertility genes and illuminates the fact that the transcriptional landscape cannot be fully characterized using a single technology alone.
Publisher: Springer Science and Business Media LLC
Date: 2014
Publisher: Proceedings of the National Academy of Sciences
Date: 23-04-2012
Abstract: Using a combination of whole-genome resequencing and high-density genotyping arrays, genome-wide haplotypes were reconstructed for two of the most important bulls in the history of the dairy cattle industry, Pawnee Farm Arlinda Chief (“Chief”) and his son Walkway Chief Mark (“Mark”), each accounting for ∼7% of all current genomes. We aligned 20.5 Gbp (∼7.3× coverage) and 37.9 Gbp (∼13.5× coverage) of the Chief and Mark genomic sequences, respectively. More than 1.3 million high-quality SNPs were detected in Chief and Mark sequences. The genome-wide haplotypes inherited by Mark from Chief were reconstructed using ∼1 million informative SNPs. Comparison of a set of 15,826 SNPs that overlapped in the sequence-based and BovineSNP50 SNPs showed the accuracy of the sequence-based haplotype reconstruction to be as high as 97%. By using the BovineSNP50 genotypes, the frequencies of Chief alleles on his two haplotypes then were determined in 1,149 of his descendants, and the distribution was compared with the frequencies that would be expected assuming no selection. We identified 49 chromosomal segments in which Chief alleles showed strong evidence of selection. Candidate polymorphisms for traits that have been under selection in the dairy cattle population then were identified by referencing Chief’s DNA sequence within these selected chromosome blocks. Eleven candidate genes were identified with functions related to milk-production, fertility, and disease-resistance traits. These data demonstrate that haplotype reconstruction of an ancestral proband by whole-genome resequencing in combination with high-density SNP genotyping of descendants can be used for rapid, genome-wide identification of the ancestor’s alleles that have been subjected to artificial selection.
Publisher: Elsevier BV
Date: 07-2011
Publisher: Oxford University Press (OUP)
Date: 15-02-2019
DOI: 10.1534/GENETICS.119.301859
Abstract: Genomic estimated breeding values (GEBVs) in livestock and polygenic risk scores (PRS) in humans are conceptually similar however, the between-species differences in linkage disequilibrium (LD) provide a fundamental point of distinction that impacts approaches to data analyses... In this Review, we focus on the similarity of the concepts underlying prediction of estimated breeding values (EBVs) in livestock and polygenic risk scores (PRS) in humans. Our research spans both fields and so we recognize factors that are very obvious for those in one field, but less so for those in the other. Differences in family size between species is the wedge that drives the different viewpoints and approaches. Large family size achievable in nonhuman species accompanied by selection generates a smaller effective population size, increased linkage disequilibrium and a higher average genetic relationship between in iduals within a population. In human genetic analyses, we select in iduals unrelated in the classical sense (coefficient of relationship & .05) to estimate heritability captured by common SNPs. In livestock data, all animals within a breed are to some extent “related,” and so it is not possible to select unrelated in iduals and retain a data set of sufficient size to analyze. These differences directly or indirectly impact the way data analyses are undertaken. In livestock, genetic segregation variance exposed through s lings of parental genomes within families is directly observable and taken for granted. In humans, this genomic variation is under-recognized for its contribution to variation in polygenic risk of common disease, in both those with and without family history of disease. We explore the equation that predicts the expected proportion of variance explained using PRS, and quantify how GWAS s le size is the key factor for maximizing accuracy of prediction in both humans and livestock. Last, we bring together the concepts discussed to address some frequently asked questions.
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/AN16476
Abstract: Residual feed intake (RFI) is the difference between an animal’s actual and expected feed intake. Two experiments were conducted comparing energy and nitrogen partitioning in mid-lactation, in Holstein–Friesian cows selected for high or low RFI measured previously as growing calves. Each experiment used 16 cows (8 high-RFI and 8 low-RFI) the first used primiparous (PP) cows and the second used multiparous (MP) cows. Cows were housed in idually for 4 days in metabolism stalls, then open-circuit respiration chambers for 3 days. Each cow was offered ad libitum lucerne hay cubes plus 6 kg DM per day of crushed wheat grain. In idual feed intake, milk yield, milk composition and faecal and urine output were measured. Methane and carbon dioxide output and oxygen consumption were measured in the chambers. In MP cows, a greater proportion of energy intake was partitioned to milk and less to heat in low-RFI than high-RFI cows. The proportion of gross-energy intake per kilogram metabolic bodyweight partitioned to milk production was greater and the proportion partitioned to methane and heat production was lower in MP than in PP cows. Energy from tissue mobilisation was not affected by RFI or parity. The amount of nitrogen consumed from feed was greater in MP than PP cows. As a percentage of N intake, N partitioned to milk was greater in PP than in MP cows, but there were no overall effects of RFI on N partitioning. However, there was a trend towards a positive association between N excreted in the urine and RFI, which could have environmental implications. Both RFI and parity were associated with variation in energy and nitrogen partitioning and should be examined in a larger subset of animals in future.
Publisher: Springer Science and Business Media LLC
Date: 04-03-2020
DOI: 10.1186/S12864-020-6575-3
Abstract: Breeding for new macadamia cultivars with high nut yield is expensive in terms of time, labour and cost. Most trees set nuts after four to five years, and candidate varieties for breeding are evaluated for at least eight years for various traits. Genome-wide association studies (GWAS) are promising methods to reduce evaluation and selection cycles by identifying genetic markers linked with key traits, potentially enabling early selection through marker-assisted selection. This study used 295 progeny from 32 full-sib families and 29 parents (18 phenotyped) which were planted across four sites, with each tree genotyped for 4113 SNPs. ASReml-R was used to perform association analyses with linear mixed models including a genomic relationship matrix to account for population structure. Traits investigated were: nut weight (NW), kernel weight (KW), kernel recovery (KR), percentage of whole kernels (WK), tree trunk circumference (TC), percentage of racemes that survived from flowering through to nut set, and number of nuts per raceme. Seven SNPs were significantly associated with NW (at a genome-wide false discovery rate of 0.05), and four with WK. Multiple regression, as well as mapping of markers to genome assembly scaffolds suggested that some SNPs were detecting the same QTL. There were 44 significant SNPs identified for TC although multiple regression suggested detection of 16 separate QTLs. These findings have important implications for macadamia breeding, and highlight the difficulties of heterozygous populations with rapid LD decay. By coupling validated marker-trait associations detected through GWAS with MAS, genetic gain could be increased by reducing the selection time for economically important nut characteristics. Genomic selection may be a more appropriate method to predict complex traits like tree size and yield.
Publisher: Springer Science and Business Media LLC
Date: 27-02-2016
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/CP13361
Abstract: Forage species provide the major feed-base for livestock grazing industries supporting production of dairy products, red meat and animal fibres. Because of the complex, multifactorial and highly environmentally sensitive nature of many key breeders’ traits for forage crops, implementation of genomic selection (GS) is a particularly attractive option. Although basic strategies for GS implementation have been devised, forage species display a broad range of biological factors that may influence the precise design of GS-based programs. These factors are described and exemplified by reference to several temperate and warm-season grass and legume species. Current knowledge with respect to such factors, along with the availability of suitable genomic resources and prospects for future activities, is described for several representative species (white clover, tall fescue and phalaris). Generic issues and benefits associated with GS implementation in forage breeding are also assessed.
Publisher: Oxford University Press (OUP)
Date: 10-07-2013
Publisher: CSIRO Publishing
Date: 2013
DOI: 10.1071/AN12304
Abstract: The New Zealand, Australian and Irish dairy industries have used genomic information to enhance their genetic evaluations over the last 2–4 years. The improvement in the accuracy obtained from including genomic information on thousands of animals in the national evaluation system has revolutionised the dairy breeding programs in the three countries. The genomically enhanced breeding values (GEBV) of young bulls are more reliable than breeding values based on parent average, thus allowing the young bulls to be reliably selected and used in the national herd. Traditionally, the use of young bulls was limited and bulls were not used extensively until they were 5 years old when the more reliable progeny test results became available. Using young sires, as opposed to progeny-tested sires, in the breeding program dramatically reduces the generation interval, thereby facilitating an increase in the rate of genetic gain by 40–50%. Young sires have been marketed on their GEBV in the three countries over the last 2–4 years. Initial results show that the genomic estimates were overestimated in both New Zealand and Ireland. Adjustments have since been introduced into their respective national evaluations to reduce the bias. A bias adjustment has been included in the Australian evaluation since it began however, official genomic evaluations have not been in place as long as in New Zealand and Ireland, so there has been less opportunity to validate if the correction accounts for all bias. Sequencing of the dairy cattle population has commenced in an effort to further improve the genomic predictions and also to detect causative mutations that underlie traits of economic performance.
Publisher: Springer Science and Business Media LLC
Date: 14-01-2011
Publisher: Springer Science and Business Media LLC
Date: 29-09-2016
DOI: 10.1038/SREP34114
Abstract: Dairy products are a key source of valuable proteins and fats for many millions of people worldwide. Dairy cattle are highly susceptible to heat-stress induced decline in milk production, and as the frequency and duration of heat-stress events increases, the long term security of nutrition from dairy products is threatened. Identification of dairy cattle more tolerant of heat stress conditions would be an important progression towards breeding better adapted dairy herds to future climates. Breeding for heat tolerance could be accelerated with genomic selection, using genome wide DNA markers that predict tolerance to heat stress. Here we demonstrate the value of genomic predictions for heat tolerance in cohorts of Holstein cows predicted to be heat tolerant and heat susceptible using controlled-climate chambers simulating a moderate heatwave event. Not only was the heat challenge stimulated decline in milk production less in cows genomically predicted to be heat-tolerant, physiological indicators such as rectal and intra-vaginal temperatures had reduced increases over the 4 day heat challenge. This demonstrates that genomic selection for heat tolerance in dairy cattle is a step towards securing a valuable source of nutrition and improving animal welfare facing a future with predicted increases in heat stress events.
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/CP13363
Abstract: Genomic selection is now being used at an accelerating pace in many plant species. This review first discusses the factors affecting the accuracy of genomic selection, and then interprets results of existing plant genomic selection studies in light of these factors. Differences between genomic breeding strategies for self-pollinated and open-pollinated species, and between-population level v. within-family design, are highlighted. As expected, more training in iduals, higher trait heritability and higher marker density generally lead to better accuracy of genomic breeding values in both self-pollinated and open-pollinated plants. Most published studies to date have artificially limited effective population size by using designs of bi-parental or within-family structure to increase accuracies. The capacity of genomic selection to reduce generation intervals by accurately evaluating traits at an early age makes it an effective tool to deliver more genetic gain from plant breeding in many cases.
Publisher: International Society for Horticultural Science (ISHS)
Date: 06-2018
Publisher: Springer Science and Business Media LLC
Date: 24-11-2009
Publisher: Oxford University Press (OUP)
Date: 09-2008
Abstract: In livestock populations, estimation of breeding values for selection requires a matrix describing the additive relationship between in iduals in the population. This matrix can be derived from pedigree information. In some livestock populations, pedigree information may be unavailable, incomplete, or in error. Here we use simulated data to demonstrate that marker-derived relationship matrices can be used to predict breeding values and estimate additive variance components, provided the markers are sufficiently dense. The approach is demonstrated for an Angus data set with 9,323 SNP markers genotyped.
Publisher: Research Square Platform LLC
Date: 28-10-2022
DOI: 10.21203/RS.3.RS-2165063/V1
Abstract: Many of the world’s agriculturally important plant and animal populations consist of hybrids of subspecies. Cattle in tropical and sub-tropical regions for ex le, originate from two genetically distinct subspecies, Bos indicus and Bos taurus. Methods to derive the underlying genetic architecture for these two subspecies are essential to develop accurate genomic predictions in these hybrid populations. We propose a novel method to achieve this. First, we use haplotypes to assign single nucleotide polymorphism (SNP) alleles to ancestral subspecies-of-origin in a multi-breed and multi-subspecies population. Then we use a BayesR framework to allow SNP alleles originating from the different subspecies to have different effects (unequal variances). Applying this method in a composite population of B. indicus and B. taurus hybrids, our results show that there are underlying genomic differences between the two subspecies, and these effects are not identified in multi-breed genomic evaluations that do not account for subspecies-of-origin effects. The method slightly improved the accuracy of genomic prediction. More significantly, by allocating SNP alleles to ancestral subspecies-of-origin, we were able to identify four SNP with high posterior probabilities of inclusion that have not been previously associated with cattle fertility and were very close to genes associated with fertility in other species. These results show that haplotypes can be used to trace subspecies-of-origin through the genome of this hybrid population and, in conjunction with our novel Bayesian analysis, subspecies SNP allele allocation can be used to increase the accuracy of quantitative trait loci (QTL) association mapping in genetically erse populations.
Publisher: American Dairy Science Association
Date: 07-2017
Abstract: Single nucleotide polymorphisms have been the DNA variant of choice for genomic prediction, largely because of the ease of single nucleotide polymorphism genotype collection. In contrast, structural variants (SV), which include copy number variants (CNV), translocations, insertions, and inversions, have eluded easy detection and characterization, particularly in nonhuman species. However, evidence increasingly shows that SV not only contribute a substantial proportion of genetic variation but also have significant influence on phenotypes. Here we present the discovery of CNV in a prominent New Zealand dairy bull using long-read PacBio (Pacific Biosciences, Menlo Park, CA) sequencing technology and the Sniffles SV discovery tool (version 0.0.1 ritzsedlazeck/Sniffles). The CNV identified from long reads were compared with CNV discovered in the same bull from Illumina sequencing using CNVnator (read depth-based tool Illumina Inc., San Diego, CA) as a means of validation. Subsequently, further validation was undertaken using whole-genome Illumina sequencing of 556 cattle representing the wider New Zealand dairy cattle population. Very limited overlap was observed in CNV discovered from the 2 sequencing platforms, in part because of the differences in size of CNV detected. Only a few CNV were therefore able to be validated using this approach. However, the ability to use CNVnator to genotype the 557 cattle for copy number across all regions identified as putative CNV allowed a genome-wide assessment of transmission level of copy number based on pedigree. The more highly transmissible a putative CNV region was observed to be, the more likely the distribution of copy number was multimodal across the 557 sequenced animals. Furthermore, visual assessment of highly transmissible CNV regions provided evidence supporting the presence of CNV across the sequenced animals. This transmission-based approach was able to confirm a subset of CNV that segregates in the New Zealand dairy cattle population. Genome-wide identification and validation of CNV is an important step toward their inclusion in genomic selection strategies.
Publisher: American Dairy Science Association
Date: 03-2014
Abstract: Combining data from research herds may be advantageous, especially for difficult or expensive-to-measure traits (such as dry matter intake). Cows in research herds are often genotyped using low-density single nucleotide polymorphism (SNP) panels. However, the precision of quantitative trait loci detection in genome-wide association studies and the accuracy of genomic selection may increase when the low-density genotypes are imputed to higher density. Genotype data were available from 10 research herds: 5 from Europe [Denmark, Germany, Ireland, the Netherlands, and the United Kingdom (UK)], 2 from Australasia (Australia and New Zealand), and 3 from North America (Canada and the United States). Heifers from the Australian and New Zealand research herds were already genotyped at high density (approximately 700,000 SNP). The remaining genotypes were imputed from around 50,000 SNP to 700,000 using 2 reference populations. Although it was not possible to use a combined reference population, which would probably result in the highest accuracies of imputation, differences arising from using 2 high-density reference populations on imputing 50,000-marker genotypes of 583 animals (from the UK) were quantified. The European genotypes (n=4,097) were imputed as 1 data set, using a reference population of 3,150 that included genotypes from 835 Australian and 1,053 New Zealand females, with the remainder being males. Imputation was undertaken using population-wide linkage disequilibrium with no family information exploited. The UK animals were also included in the North American data set (n=1,579) that was imputed to high density using a reference population of 2,018 bulls. After editing, 591,213 genotypes on 5,999 animals from 10 research herds remained. The correlation between imputed allele frequencies of the 2 imputed data sets was high (>0.98) and even stronger (>0.99) for the UK animals that were part of each imputation data set. For the UK genotypes, 2.2% were imputed differently in the 2 high-density reference data sets used. Only 0.025% of these were homozygous switches. The number of discordant SNP was lower for animals that had sires that were genotyped. Discordant imputed SNP genotypes were most common when a large difference existed in allele frequency between the 2 imputed genotype data sets. For SNP that had ≥ 20% discordant genotypes, the difference between imputed data sets of allele frequencies of the UK (imputed) genotypes was 0.07, whereas the difference in allele frequencies of the (reference) high-density genotypes was 0.30. In fact, regions existed across the genome where the frequency of discordant SNP was higher. For ex le, on chromosome 10 (centered on 520,948 bp), 52 SNP (out of a total of 103 SNP) had ≥ 20% discordant SNP. Four hundred and eight SNP had more than 20% discordant genotypes and were removed from the final set of imputed genotypes. We concluded that both discordance of imputed SNP genotypes and differences in allele frequencies, after imputation using different reference data sets, may be used to identify and remove poorly imputed SNP.
Publisher: Public Library of Science (PLoS)
Date: 04-09-2013
Publisher: Springer Science and Business Media LLC
Date: 20-06-2022
DOI: 10.1186/S12864-022-08686-3
Abstract: Disease emergence and production loss caused by cattle tick infestations have focused attention on genetic selection strategies to breed beef cattle with increased tick resistance. However, the mechanisms behind host responses to tick infestation have not been fully characterised. Hence, this study examined gene expression profiles of peripheral blood leukocytes from tick-naive Brangus steers ( Bos taurus x Bos indicus ) at 0, 3, and 12 weeks following artificial tick challenge experiments with Rhipicephalus australis larvae. The aim of the study was to investigate the effect of tick infestation on host leukocyte response to explore genes associated with the expression of high and low host resistance to ticks. Animals with high (HR, n = 5) and low (LR, n = 5) host resistance were identified after repeated tick challenge. A total of 3644 unique differentially expressed genes (FDR 0.05) were identified in the comparison of tick-exposed (both HR and LR) and tick-naive steers for the 3-week and 12-week infestation period. Enrichment analyses showed genes were involved in leukocyte chemotaxis, coagulation, and inflammatory response. The IL-17 signalling, and cytokine-cytokine interactions pathways appeared to be relevant in protection and immunopathology to tick challenge. Comparison of HR and LR phenotypes at timepoints of weeks 0, 3, and 12 showed there were 69, 8, and 4 differentially expressed genes, respectively. Most of these genes were related to immune, tissue remodelling, and angiogenesis functions, suggesting this is relevant in the development of resistance or susceptibility to tick challenge. This study showed the effect of tick infestation on Brangus cattle with variable phenotypes of host resistance to R. australis ticks . Steers responded to infestation by expressing leukocyte genes related to chemotaxis, cytokine secretion, and inflammatory response. The altered expression of genes from the bovine MHC complex in highly resistant animals at pre- and post- infestation stages also supports the relevance of this genomic region for disease resilience. Overall, this study offers a resource of leukocyte gene expression data on matched tick-naive and tick-infested steers relevant for the improvement of tick resistance in composite cattle.
Publisher: Wiley
Date: 08-08-2011
DOI: 10.1111/J.1439-0388.2011.00948.X
Abstract: This study aimed to estimate the heritabilities of three economically important traits (total weight, shell shape and meat yield) in Australian blue mussels. The estimates were derived using a pedigree reconstructed from a suite of both published and newly developed microsatellite markers. A total of 135 microsatellite loci were tested, of which 10 loci produced consistent PCR lification and reliable results across all s les (74 full-sibling families including 74 pairs of parents and 2536 offspring). Lack of polymorphism at the non-repetitive region of the adhesive protein gene confirmed that the broodstock were derived from a single species. A total of 1538 progenies (62.5%) could be assigned to single parent pairs, and the remainder were assigned to two families or more, so were discarded from further analysis. Heritabilities for total weight, shell shape and meat yield were low (0.051 ± 0.027, 0.085 ± 0.038 and 0.049 ± 0.028, respectively) but reflected large environmental variation rather than limited genetic variation, suggesting a family-based breeding programme could improve these traits. The genetic correlation between weight and meat yield, expressed as percentage of total mussel which was not shell, was negative, while the genetic correlation between meat yield and shell shape was weakly positive.
Publisher: Elsevier BV
Date: 06-2003
Publisher: Frontiers Media SA
Date: 23-06-2021
DOI: 10.3389/FIMMU.2021.620847
Abstract: Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped henotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV.
Publisher: Springer Science and Business Media LLC
Date: 2011
Publisher: Hindawi Limited
Date: 12-2009
DOI: 10.1017/S0016672309990358
Abstract: The patterns of linkage disequilibrium (LD) between dense polymorphic markers are shaped by the ancestral population history. It is therefore possible to use multilocus predictors of LD to infer past population history and to infer sharing of identical alleles in quantitative trait locus (QTL) studies. We develop a multilocus predictor of LD for pairs of haplotypes, which we term haplotype homozygosity ( HH n ): the probability that any two haplotypes share a given number of n adjacent identical markers or ‘runs of homozygosity’. Our method, based on simplified coalescence theory, accounts for recombination and mutation. We compare our HH n predictions, with HH n in simulated populations and with two published predictors of HH n . Our method performs consistently better across a range of population parameters, including populations with a severe bottleneck followed by expansion, compared to two published methods. We demonstrate that we can predict the pattern of HH n observed in dense single nucleotide polymorphisms (SNPs) genotyped in a cattle population, given appropriate historical changes in population size. Our method is practical for use with very large numbers of in iduals and dense genome wide polymorphic DNA data. It has potential applications in inferring ancestral population history and QTL mapping studies.
Publisher: Oxford University Press (OUP)
Date: 2007
DOI: 10.1534/GENETICS.106.058859
Abstract: Functional dependencies between genes are a defining characteristic of gene networks underlying quantitative traits. However, recent studies show that the proportion of the genetic variation that can be attributed to statistical epistasis varies from almost zero to very high. It is thus of fundamental as well as instrumental importance to better understand whether different functional dependency patterns among polymorphic genes give rise to distinct statistical interaction patterns or not. Here we address this issue by combining a quantitative genetic model approach with genotype–phenotype models capable of translating allelic variation and regulatory principles into phenotypic variation at the level of gene expression. We show that gene regulatory networks with and without feedback motifs can exhibit a wide range of possible statistical genetic architectures with regard to both type of effect explaining phenotypic variance and number of apparent loci underlying the observed phenotypic effect. Although all motifs are capable of harboring significant interactions, positive feedback gives rise to higher amounts and more types of statistical epistasis. The results also suggest that the inclusion of statistical interaction terms in genetic models will increase the chance to detect additional QTL as well as functional dependencies between genetic loci over a broad range of regulatory regimes. This article illustrates how statistical genetic methods can fruitfully be combined with nonlinear systems dynamics to elucidate biological issues beyond reach of each methodology in isolation.
Publisher: Springer Science and Business Media LLC
Date: 2012
Publisher: American Dairy Science Association
Date: 09-2011
Abstract: Feed conversion efficiency of dairy cattle is an important component of the profitability of dairying, given that the cost of feed accounts for much of total farm expenses. Residual feed intake (RFI) is a useful measure of feed conversion efficiency, as it can be used to compare in iduals with the same or differing levels of production during the period of measurement. If genetic variation exists in RFI among dairy cattle, selection for lower RFI could improve profitability. In this experiment, RFI was defined as the difference between an animal's actual feed intake and its expected feed intake, which was determined by regression of dry matter (DM) intake against mean body weight (BW) and growth rate. Nine hundred and three Holstein-Friesian heifer calves, aged between 5 and 7 mo, were measured for RFI in 3 cohorts of approximately 300 animals. Calves were housed under feedlot style conditions in groups of 15 to 20 for 85 to 95 d and had ad libitum access to a cubed alfalfa hay. Intakes of in idual animals were recorded via an electronic feed recording system and BW gain was determined by weighing animals once or twice weekly, over a period of 60 to 70 d. Calves had DM intake (mean ± SD) of 8.3±1.37 kg of DM/d over the measurement period with BW gains of 1.1±0.17 kg/d. In terms of converting feed energy for maintenance and growth, the 10% most efficient calves (lowest RFI) ate 1.7 kg of DM less each day than the 10% least efficient calves (highest RFI) for the same rate of growth. Low-RFI heifers also had a significantly lower rate of intake (g/min) than high-RFI heifers. The heritability estimate of RFI (mean ± SE) was 0.27 (±0.12). These results indicate that substantial genetic variation in RFI exists, and that the magnitude of this variation is large enough to enable this trait to be considered as a candidate trait for future dairy breeding goals. A primary focus of future research should be to ensure that calves that are efficient at converting feed energy for maintenance and growth also become efficient at converting feed energy to milk. Future research will also be necessary to identify the consequences of selection for RFI on other traits (especially fertility and other fitness traits) and if any interactions exist between RFI and feeding level.
Publisher: American Dairy Science Association
Date: 05-2011
Abstract: Three breeds (Fleckvieh, Holstein, and Jersey) were included in a reference population, separately and together, to assess the accuracy of prediction of genomic breeding values in single-breed validation populations. The accuracy of genomic selection was defined as the correlation between estimated breeding values, calculated using phenotypic data, and genomic breeding values. The Holstein and Jersey populations were from Australia, whereas the Fleckvieh population (dual-purpose Simmental) was from Austria and Germany. Both a BLUP with a multi-breed genomic relationship matrix (GBLUP) and a Bayesian method (BayesA) were used to derive the prediction equations. The hypothesis tested was that having a multi-breed reference population increased the accuracy of genomic selection. Minimal advantage existed of either GBLUP or BayesA multi-breed genomic evaluations over single-breed evaluations. However, when the goal was to predict genomic breeding values for a breed with no in iduals in the reference population, using 2 other breeds in the reference was generally better than only 1 breed.
Publisher: Springer Science and Business Media LLC
Date: 14-08-2007
Publisher: Springer Science and Business Media LLC
Date: 16-10-2010
Publisher: Elsevier BV
Date: 11-2015
Publisher: Oxford University Press (OUP)
Date: 16-02-2018
Publisher: CSIRO Publishing
Date: 2012
DOI: 10.1071/AN11229
Abstract: Whole genome association studies in humans have shown a strong relationship between omega-3 levels in plasma and single nucleotide polymorphisms (SNP) located close to genes whose protein products are involved in the biosynthesis of long-chain omega-3 fatty acids. In sheep and other livestock species, the calpain/calpastatin system is the principal influence on natural variation in meat tenderness between animals. Using targeted next generation sequencing, we sequenced the fatty acid desaturase locus (FADS1/2/3), ELOVL2 and SLC26A10 and the calpain/calpastatin (CAPN1/2/3 and CAST) gene loci of 35 industry sires from the Australian flock. A total of 753 SNP were identified and 182 of these SNP were selected for incorporation onto a research SNP panel that represented the genetic variation across the nine genes. A total of 1252 animals were genotyped from the Australian Sheep CRC Information Nucleus Flock for these SNP and the genomic association was calculated for omega-3 fatty acid content and objective meat tenderness in lamb. Six SNP within CAST and CAPN2 showed association with shear force at Day 5 post-mortem at a significance level of P ≤ 0.01. When these were fitted simultaneously in a mixed-model analysis with fixed effects and covariates, three SNP remained significant. These SNP each had an unfavourable effect on shear force of between 1.1 and 1.8 N, with a combined effect of 4.1 N. The frequency of the favourable alleles in the progeny measured indicates that these SNP hold good potential for improving the management of meat tenderness across Merino, Border Leicester and Terminal sire types. No SNP within the FADS1/2/3, ELOVL2 and SLC26A10 gene regions were associated with lamb muscle omega-3 levels. This indicates that genetic variation in the long-chain omega-3 biosynthesis pathway genes analysed here may not be important for omega-3 content in lamb within the Information Nucleus Flock population.
Publisher: Springer-Verlag
Date: 2005
Publisher: Wiley
Date: 11-04-2012
Publisher: American Dairy Science Association
Date: 05-2015
Abstract: In dairy cattle, the rate of genetic gain from genomic selection depends on reliability of direct genomic values (DGV). One option to increase reliabilities could be to increase the size of the reference set used for prediction, by using genotyped bulls with daughter information in countries other than the evaluating country. The increase in reliabilities of DGV from using this information will depend on the extent of genotype by environment interaction between the evaluating country and countries contributing information, and whether this is correctly accounted for in the prediction method. As the genotype by environment interaction between Australia and Europe or North America is greater than between Europe and North America for most dairy traits, ways of including information from other countries in Australian genomic evaluations were examined. Thus, alternative approaches for including information from other countries and their effect on the reliability and bias of DGV of selection candidates were assessed. We also investigated the effect of including overseas (OS) information on reliabilities of DGV for selection candidates that had weaker relationships to the current Australian reference set. The DGV were predicted either using daughter trait deviations (DTD) for the bulls with daughters in Australia, or using this information as well as OS information by including deregressed proofs (DRP) from Interbull for bulls with only OS daughters in either single trait or bivariate models. In the bivariate models, DTD and DRP were considered as different traits. Analyses were performed for Holstein and Jersey bulls for milk yield traits, fertility, cell count, survival, and some type traits. For Holsteins, the data used included up to 3,580 bulls with DTD and up to 5,720 bulls with only DRP. For Jersey, about 900 bulls with DTD and 1,820 bulls with DRP were used. Bulls born after 2003 and genotyped cows that were not dams of genotyped bulls were used for validation. The results showed that the combined use of DRP on bulls with OS daughters only and DTD for Australian bulls in either the single trait or bivariate model increased the coefficient of determination [(R(2)) (DGV,DTD)] in the validation set, averaged across 6 main traits, by 3% in Holstein and by 5% in Jersey validation bulls relative to the use of DTD only. Gains in reliability and unbiasedness of DGV were similar for the single trait and bivariate models for production traits, whereas the bivariate model performed slightly better for somatic cell count in Holstein. The increase in R(2) (DGV,DTD) as a result of using bulls with OS daughters was relatively higher for those bulls and cows in the validation sets that were less related to the current reference set. For ex le, in Holstein, the average increase in R(2) for milk yield traits when DTD and DRP were used in a single trait model was 23% in the least-related cow group, but only 3% in the most-related cow group. In general, for both breeds the use of DTD from domestic sources and DRP from Interbull in a single trait or bivariate model can increase reliability of DGV for selection candidates.
Start Date: 12-2017
End Date: 12-2020
Amount: $420,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 09-2018
End Date: 03-2023
Amount: $345,465.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2023
End Date: 12-2027
Amount: $5,000,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 04-2022
End Date: 04-2026
Amount: $785,312.00
Funder: Australian Research Council
View Funded ActivityStart Date: 09-2021
End Date: 08-2026
Amount: $4,996,503.00
Funder: Australian Research Council
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