ORCID Profile
0000-0003-2512-1696
Current Organisation
University of New England
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Research Topics
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.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Genomics | Genetics | Animal Breeding | Quantitative Genetics (incl. Disease and Trait Mapping Genetics) | Crop and pasture production | Animal reproduction and breeding | Horticultural crop improvement (incl. selection and breeding) | Crop and pasture improvement (incl. selection and breeding) |
ANZSRC Socio-Economic Objective (SEO)
Application Software Packages (excl. Computer Games) | Environmentally Sustainable Animal Production not elsewhere classified | Pigs | Expanding Knowledge in the Biological Sciences | Beef cattle
Related Links
Publications
Using dominance relationship coefficients based on linkage disequilibrium and linkage with a general complex pedigree to increase mapping resolution
Publisher: Oxford University Press (OUP)
Date: 10-2006
DOI: 10.1534/GENETICS.106.060806
Abstract: Dominance (intralocus allelic interactions) plays often an important role in quantitative trait variation. However, few studies about dominance in QTL mapping have been reported in outbred animal or human populations. This is because common dominance effects can be predicted mainly for many full sibs, which do not often occur in outbred or natural populations with a general pedigree. Moreover, incomplete genotypes for such a pedigree make it infeasible to estimate dominance relationship coefficients between in iduals. In this study, identity-by-descent (IBD) coefficients are estimated on the basis of populationwide linkage disequilibrium (LD), which makes it possible to track dominance relationships between unrelated founders. Therefore, it is possible to use dominance effects in QTL mapping without full sibs. Incomplete genotypes with a complex pedigree and many markers can be efficiently dealt with by a Markov chain Monte Carlo method for estimating IBD and dominance relationship matrices ($\\batchmode \\documentclass[fleqn,10pt,legalpaper]{article} \\usepackage{amssymb} \\usepackage{amsfonts} \\usepackage{amsmath} \\pagestyle{empty} \\begin{document} \\(D_{\\mathrm{RM}}\\) \\end{document}$). It is shown by simulation that the use of $\\batchmode \\documentclass[fleqn,10pt,legalpaper]{article} \\usepackage{amssymb} \\usepackage{amsfonts} \\usepackage{amsmath} \\pagestyle{empty} \\begin{document} \\(D_{\\mathrm{RM}}\\) \\end{document}$ increases the likelihood ratio at the true QTL position and the mapping accuracy and power with complete dominance, overdominance, and recessive inheritance modes when using 200 genotyped and phenotyped in iduals.
Methods and experimental designs for detection of QTL in sheep and goats
Publisher: Elsevier BV
Date: 06-2007
Using an evolutionary algorithm and parallel computing for haplotyping in a general complex pedigree with multiple marker loci
Publisher: Springer Science and Business Media LLC
Date: 11-04-2008
Genomic analysis of the slope of the reaction norm for body weight in Australian sheep
Publisher: Springer Science and Business Media LLC
Date: 03-06-2022
DOI: 10.1186/S12711-022-00734-6
Abstract: Selection of livestock based on their robustness or sensitivity to environmental variation could help improve the efficiency of production systems, particularly in the light of climate change. Genetic variation in robustness arises from genotype-by-environment (G × E) interactions, with genotypes performing differently when animals are raised in contrasted environments. Understanding the nature of this genetic variation is essential to implement strategies to improve robustness. In this study, our aim was to explore the genetics of robustness in Australian sheep to different growth environments using linear reaction norm models (RNM), with post-weaning weight records of 22,513 lambs and 60 k single nucleotide polymorphisms (SNPs). The use of scale-corrected genomic estimated breeding values (GEBV) for the slope to account for scale-type G × E interactions was also investigated. Additive genetic variance was observed for the slope of the RNM, with genetic correlations between low- and high-growth environments indicating substantial re-ranking of genotypes (0.44–0.49). The genetic variance increased from low- to high-growth environments. The heritability of post-weaning body weight ranged from 0.28 to 0.39. The genetic correlation between intercept and slope of the reaction norm for post-weaning body weight was low to moderate when based on the estimated (co)variance components but was much higher when based on back-solved SNP effects. An initial analysis suggested that a region on chromosome 11 affected both the intercept and the slope, but when the GEBV for the slope were conditioned on the GEBV for the intercept to remove the effect of scale-type G × E interactions on SNP effects for robustness, a single genomic region on chromosome 7 was found to be associated with robustness. This region included genes previously associated with growth traits and disease susceptibility in livestock. This study shows a significant genetic variation in the slope of RNM that could be used for selecting for increased robustness of sheep. Both scale-type and rank-type G × E interactions contributed to variation in the slope. The correction for scale effects of GEBV for the slope should be considered when analysing robustness using RNM. Overall, robustness appears to be a highly polygenic trait.
Detailed phenotyping identifies genes with pleiotropic effects on body composition
Publisher: Springer Science and Business Media LLC
Date: 12-03-2016
35 Software Development for Deterministic Prediction of Selection Response in Livestock Breeding Programs Using Genomic Information.
Publisher: Oxford University Press (OUP)
Date: 04-2018
Accuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validation
Publisher: Springer Science and Business Media LLC
Date: 12-11-2012
Design and role of an information nucleus in sheep breeding programs
Publisher: CSIRO Publishing
Date: 2010
DOI: 10.1071/AN10151
Abstract: The Australian sheep Cooperative Research Centre has initiated an information nucleus with the aim to estimate genetic parameters for new traits, to undertake a large-scale whole-genome association study and to enhance the breeding values of breeding animals in commercial studs. This paper presents the rationale behind the current design factors to meet the main objectives. It then discusses the potential design of an information nucleus if it were a sustainable part of commercial sheep-breeding programs in the long term. Advantages of such an information nucleus are summarised and quantified where possible.
Industry benefits from using genomic information in two- and three-tier sheep breeding systems
Publisher: CSIRO Publishing
Date: 2015
DOI: 10.1071/AN13265
Abstract: A model of the sheep breeding industry with nucleus flocks, multiplier flocks and commercial sheep flocks was used to examine the value of genomic selection. The model reflected a dual-purpose Merino breeding objective, with genomic information improving selection accuracy by 39% for rams at 6 months of age and by 17% at 18 months. The current level of net dollar benefit to the sheep industry from selection, but without genomic testing, can be improved by 10–14% for a closed three-tiered breeding structure with rams used at 18 months. If the rams are first used at 6–7 months then the dollar gains can be improved by 15–17%, since genomic information can provide proportionately greater gains for young animals that have limited phenotypic information. In a two-tiered breeding system, with nucleus flocks selling rams direct to commercial producers, rather than through multiplier flocks, the dollar gains to industry from genomic testing increased to ~12–13% for rams bred at 18 months, and 20–22% if nucleus rams are used at 6–7 months. The optimal structure requires two-stage selection, with an initial selection based on information available without genomic testing, to limit the cost of testing to only the superior rams. However, the optimum proportion of rams tested depends on the system and the cost of testing. In order to recover the cost of genomic testing, the nucleus flocks must recover up to 5% of the extra genetic gain as extra profit from sale of rams to commercial sheep producers.
Increased genetic gains in multi-trait sheep indices using female reproductive technologies combined with optimal contribution selection and genomic breeding values
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/AN15440
Abstract: Female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro fertilisation and embryo transfer (JIVET) can produce multiple offspring per mating in sheep and cattle. In breeding programs this allows for higher female selection intensity and, in the case of JIVET, a reduction in generation interval, resulting in higher rates of genetic gain. Low selection accuracy of young females entering JIVET has often dissuaded producers from using this technology. However, genomic selection (GS) could increase selection accuracy of candidates at a younger age to help increase rates of genetic gain. This increase might vary for different traits in multiple trait breeding programs depending on genetic parameters and the practicality of recording, particularly for hard to measure traits. This study used both stochastic (animals) and deterministic (GS) simulation to evaluate the effect of reproductive technologies on the genetic gain for various traits in sheep breeding programs, both with and without GS. Optimal contribution selection was used to manage inbreeding and to optimally assign reproductive technologies to in idual selection candidates. Two Australian sheep industry indexes were used – a terminal sire index that focussed on growth and carcass traits (the ‘Lamb 2020’ index) and a Merino index that focuses on wool traits, bodyweight, and reproduction (MP+). We observed that breeding programs using artificial insemination or natural mating (AI/N) + MOET, compared with AI/N alone, yielded an extra 39% and 27% genetic gain for terminal and Merino indexes without GS, respectively. However, the addition of JIVET to AI/N + MOET without GS only yielded an extra 1% genetic gain for terminal index and no extra gain in the Merino index. When GS was used in breeding programs, we observed AI/N + MOET + JIVET outperformed AI/N + MOET by 21% and 33% for terminal and Merino indexes, respectively. The implementation of GS increased genetic gain where reproductive technologies were used by 9–34% in Lamb 2020 and 37–98% in MP+. In idual trait response to selection varied in each breeding program. The combination of GS and reproductive technologies allowed for greater genetic gain in both indexes especially for hard to measure traits, but had limited effect on the traits that already had a large amount of early age records.
Estimates of genetic and phenotypic parameters for production, haematological and gastrointestinal nematode-associated traits in Australian cashmere goats
Publisher: CSIRO Publishing
Date: 2011
DOI: 10.1071/AN10035
Abstract: The present study was designed to estimate genetic parameters of 17 production, parasite-associated and haematological traits in Australian cashmere goats. It comprised 796 records of female progeny of 532 dams sired by 29 bucks over a 4-year period. Measurement of haematological and parasite-associated traits was carried out on female kids during low-level natural gastrointestinal nematode challenge at 3 and 5 months of age and at 28 and/or 35 days after artificial challenge with 10 000 infective larvae of Trichostrongylus colubriformis administered 1 week after the 5-month measurement. Production traits were measured up to 18 months of age. Year of birth significantly affected all traits apart from cashmere diameter (CSD). Twin kids had significantly lower liveweight (up to 10 months), packed cell volume and mean corpuscular volume (at 3 and 5 months) but higher specific IgG levels and mean corpuscular haemoglobin content at 3 months. Paddock of birth and early rearing and its interaction with year of birth had significant effects on worm egg count (WEC) during natural challenge, on IgG at both natural and post-artificial challenge measurements and on liveweight at early ages. The level of gastrointestinal nematode challenge in the nine different paddocks clearly influenced both WEC and IgG during natural and subsequent artificial challenge. Maternal permanent environmental effects were important only for liveweights at 3 month of age and for IgG at 5 months of age. For other traits, a simple animal model without maternal permanent environmental effects gave the best fit. Estimates of heritability (h2) of WEC and IgG were low (0.06–0.22) with the highest h2 estimates occurring after 5 months of natural infection or 35 days after artificial challenge. The majority of fleece traits were moderately to highly heritable, ranging from 0.38 to 0.78. The h2 estimates for mean fibre curvature are novel for cashmere goats and were moderate, varying from 0.32 to 0.48. Heritability estimates for erythrocyte traits were uniformly high (0.49–0.98) while those for leukocyte traits varied from low to moderate (0.09–0.43). Strong genetic and phenotypic correlations existed between major production traits. Due to the comparatively small dataset, the standard errors of genetic correlations were relatively high. CSD was positively correlated with cashmere weight and yield, an unfavourable direction. CSD was negatively correlated with fibre curvature, indicating that animals producing finer fibres produce cashmere with a higher crimp count. No phenotypic relationships were observed between WEC and fleece traits. Liveweight was weakly but negatively correlated with WEC and circulating neutrophils, while it was positively associated with eosinophils, lymphocytes and packed cell volume. This study has shown that selection for increased resistance to gastrointestinal nematode infection cashmere goats is possible but progress will be slow. WEC should remain the phenotypic marker of choice and the additional cost of alternative measures of resistance is not justified. Many of the parasite-associated traits appear to under independent genetic control.
Genotype × birth type or rearing-type interactions for growth and ultrasound scanning traits in Merino sheep
Publisher: CSIRO Publishing
Date: 2019
DOI: 10.1071/AN17464
Abstract: This study explores the interaction between genetic potential for growth in Merino lambs and their birth type (BT) or rearing type (RT). Data on birthweight (BWT), weaning weight (WWT), post-weaning weight (PWWT), scan fat (PFAT) and eye muscle depth (PEMD) were used from 3920 single and 4492 twin-born lambs from 285 sires and 5279 dams. Univariate analysis showed a significant sire × BT interaction accounting for 1.59% and 2.49% of the phenotypic variation for BWT and WWT, respectively, and no significant effect for PWWT, PFAT and PEMD. Sire × RT interaction effects were much smaller and only significant for PEMD. Bivariate analysis indicated that the genetic correlation (rg) between trait expression in lambs born and reared as singles versus those born and reared as twins were high for BWT, WWT, PWWT (0.91 ± 0.02 – 0.96 ± 0.01), whereas rg for PFAT and PEMD were lower (0.81 ± 0.03 and 0.86 ± 0.02). The rg between traits expressed in lambs born and reared as singles versus those born as twins but reared as singles were lower: 0.77 ± 0.08, 0.88 ± 0.03, 0.66 ± 0.06 and 0.61 ± 0.08 for WWT, PWWT, PFAT and PEMD, respectively. A different RT only affected the expression of breeding values for PFAT and PEMD (rg 0.62 ± 0.04 and 0.47 ± 0.03, respectively). This study showed genotype × environment interaction for BWT and WWT (sire × BT interaction) and for PEMD (sire by RT interaction). However, sires’ breeding value of a model that accounts for sire × BT interaction provides a very similar ranking of sires compared with a model that ignores it, implying that there is no need to correct for the effect in models for genetic evaluation.
Impact of young ewe fertility rate on risk and genetic gain in sheep-breeding programs using genomic selection
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/AN15321
Abstract: Genomic selection could be useful in sheep-breeding programs, especially if rams and ewes are first mated at an earlier age than is the current industry practice. However, young-ewe (1 year old) fertility rates are known to be lower and more variable than those of mature ewes. The aim of the present study was to evaluate how young-ewe fertility rate affects risk and expected genetic gain in Australian sheep-breeding programs that use genomic information and select ewes and rams at different ages. The study used stochastic simulation to model different flock age structures and young-ewe fertility levels with and without genomic information for Merino and maternal sheep-breeding programs. The results from 10 years of selection were used to compare breeding programs on the basis of the mean and variation in genetic gain. Ram and ewe age, availability of genomic information on males and young-ewe fertility level all significantly (P & 0.05) affected expected genetic gain. Higher young-ewe fertility rates significantly increased expected genetic gain. Low fertility rate of young ewes (10%) resulted in net genetic gain similar to not selecting ewes until they were 19 months old and did not increase breeding-program risk, as the likelihood of genetic gain being lower than the range of possible solutions from a breeding program with late selection of both sexes was zero. Genomic information was of significantly (P & 0.05) more value for 1-year-old rams than for 2-year-old rams. Unless genomic information was available, early mating of rams offered no greater gain in Merino breeding programs and increased breeding-program risk. It is concluded that genomic information decreases the risk associated with selecting replacements at 7 months of age. Genetic progress is unlikely to be adversely affected if fertility levels above 10% can be achieved. Whether the joining of young ewes is a viable management decision for a breeder will depend on the fertility level that can be achieved in their young ewes and on other costs associated with the early mating of ewes.
Simultaneous fine mapping of closely linked epistatic quantitative trait loci using combined linkage disequilibrium and linkage with a general pedigree
Publisher: Springer Science and Business Media LLC
Date: 15-05-2008
DOI: 10.1186/1297-9686-40-3-265
Abstract: Causal mutations and their intra- and inter-locus interactions play a critical role in complex trait variation. It is often not easy to detect epistatic quantitative trait loci (QTL) due to complicated population structure requirements for detecting epistatic effects in linkage analysis studies and due to main effects often being hidden by interaction effects. Mapping their positions is even harder when they are closely linked. The data structure requirement may be overcome when information on linkage disequilibrium is used. We present an approach using a mixed linear model nested in an empirical Bayesian approach, which simultaneously takes into account additive, dominance and epistatic effects due to multiple QTL. The covariance structure used in the mixed linear model is based on combined linkage disequilibrium and linkage information. In a simulation study where there are complex epistatic interactions between QTL, it is possible to simultaneously map interacting QTL into a small region using the proposed approach. The estimated variance components are accurate and less biased with the proposed approach compared with traditional models.
Comparing genomic prediction accuracy from purebred, crossbred and combined purebred and crossbred reference populations in sheep
Publisher: Springer Science and Business Media LLC
Date: 30-09-2014
Accuracy of genotype imputation in sheep breeds
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.
Optimising the proportion of selection candidates measured for feed intake for a beef cattle breeding objective that includes methane emissions
Publisher: Oxford University Press (OUP)
Date: 03-2017
Abstract: Reducing daily methane production (DMP) via selection for lower estimated daily (pasture) feed intake (DFI) has the potential to be more cost effective than direct selection for DMP. Daily feed intake has a high heritability and high genetic correlation to DMP and has a potential lower cost of measurement. This study's main aim was to determine for a breeding nucleus the optimal proportion of randomly selected young male and female cattle in which to estimate DFI. This optimum proportion was determined by modeling the measurement costs and response to selection of Angus cattle on a (standard industry) Angus breeding index (ABI) augmented with DFI and DMP in a combined breeding objective (BO), but without DMP being measured. For the assumed herd structure and considering a 20 yr planning horizon, the highest net present value (NPV) occurred when 64% of males and no females were measured for DFI. The highest breakeven DFI test cost (A$41.51/head) and highest returns on investment (ROI) occurred when 36% of males and no females had DFI estimates. Higher ROI were achieved when all males had DFI estimates before any females had DFI estimates. There was a diminishing increase in rate of genetic gain when moving from 36% to 64% of males with DFI estimates, thus ROI decreased from 29.7% to 23.1%. When 36% of males had DFI estimates (and no females), herd DMP genetic gain was slightly positive as the DMP reduction per generation from male selection (-0.086) was more than offset by the DMP increase per generation from female selection (+0.110). The selection response for DMP only became negative when at least 40% of males had DFI estimates. Having 64% of males with DFI estimates resulted in a predicted genetic decrease in DMP (-0.018 kgCOe/head per yr), compared to an increase of 0.052 kgCOe/head per yr when no animals had DFI estimates. The optimum proportion of males with DFI estimates (36 to 64%) depends on the breeders attitude toward ROI and the value of genetic change for DMP. Sensitivity analysis showed that the economic value (EV), heritability and genetic variance of DFI had a higher impact on the NPV and ROI outcomes than parameters related to ABI and DMP, so future work should focus on obtaining robust estimates for DFI parameters. Higher EV for feed intake and DMP would result in higher percentages of animals being profitably measured for DFI, leading to larger reductions in DMP.
Contrast Effects and Sex Influence Maternal and Self-Report Dimensional Measures of Attention-Deficit Hyperactivity Disorder
Publisher: Springer Science and Business Media LLC
Date: 24-08-2015
DOI: 10.1007/S10519-014-9670-X
Abstract: The heritability of attention-deficit/hyperactivity disorder (ADHD) is higher for children than adults. This may be due to increasing importance of environment in symptom variation, measurement inaccuracy when two raters report behavior of a twin-pair, a contrast effect resulting from parental comparison of siblings and/or dimensionality of measures. We examine rater contrast and sex effects in ADHD subtypes using a dimensional scale and compare the aetiology of self, versus maternal-report. Data were collected using the Strengths and Weaknesses of ADHD and Normal Behaviour Scale (SWAN): maternal-report for 3,223 twins and siblings (mean age 21.2, SD = 6.3) and self-report for 1,617 twins and siblings (mean age 25.5, SD = 3.2). Contrast effects and magnitude of genetic and environmental contributions to variance of ADHD phenotypes (inattention, hyperactivity-impulsivity, combined behaviours) were examined using structural equation modeling. Contrast effects were evident for maternal-report hyperactivity-impulsivity (b = -0.04) and self-report inattention (-0.09) and combined ADHD (-0.08). Dominant genetic effects were shared by raters for inattention, hyperactivity-impulsivity and combined ADHD. Broad-sense heritability was equal across sex for maternal-report inattention, hyperactivity-impulsivity and combined ADHD (0.72, 0.83, 0.80). Heritability for corresponding subtypes in self-reported data were best represented by sex (0.46, 0.30, 0.39 for males 0.69, 0.41, 0.65 for females). Heritability difference between maternal and self-report ADHD was due to greater variance of male specific environment in self-report data. Self-reported ADHD differed across sex by magnitude of specific environment and genetic effects.
Using random regression models to estimate genetic variation in growth pattern and its association with sexual maturity of Thai native chickens
Publisher: Informa UK Limited
Date: 14-08-2020
MTG2: an efficient algorithm for multivariate linear mixed model analysis based on genomic information
Publisher: Oxford University Press (OUP)
Date: 10-01-2016
DOI: 10.1093/BIOINFORMATICS/BTW012
Abstract: Summary: We have developed an algorithm for genetic analysis of complex traits using genome-wide SNPs in a linear mixed model framework. Compared to current standard REML software based on the mixed model equation, our method is substantially faster. The advantage is largest when there is only a single genetic covariance structure. The method is particularly useful for multivariate analysis, including multi-trait models and random regression models for studying reaction norms. We applied our proposed method to publicly available mice and human data and discuss the advantages and limitations. Availability and implementation: MTG2 is available in ite/honglee0707/mtg2. Contact: hong.lee@une.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.
Use of gene expression and whole-genome sequence information to improve the accuracy of genomic prediction for carcass traits in Hanwoo cattle
Publisher: Springer Science and Business Media LLC
Date: 29-09-2020
DOI: 10.1186/S12711-020-00574-2
Abstract: In this study, we assessed the accuracy of genomic prediction for carcass weight (CWT), marbling score (MS), eye muscle area (EMA) and back fat thickness (BFT) in Hanwoo cattle when using genomic best linear unbiased prediction (GBLUP), weighted GBLUP (wGBLUP), and a BayesR model. For these models, we investigated the potential gain from using pre-selected single nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) on imputed sequence data and from gene expression information. We used data on 13,717 animals with carcass phenotypes and imputed sequence genotypes that were split in an independent GWAS discovery set of varying size and a remaining set for validation of prediction. Expression data were used from a Hanwoo gene expression experiment based on 45 animals. Using a larger number of animals in the reference set increased the accuracy of genomic prediction whereas a larger independent GWAS discovery dataset improved identification of predictive SNPs. Using pre-selected SNPs from GWAS in GBLUP improved accuracy of prediction by 0.02 for EMA and up to 0.05 for BFT, CWT, and MS, compared to a 50 k standard SNP array that gave accuracies of 0.50, 0.47, 0.58, and 0.47, respectively. Accuracy of prediction of BFT and CWT increased when BayesR was applied with the 50 k SNP array (0.02 and 0.03, respectively) and was further improved by combining the 50 k array with the top-SNPs (0.06 and 0.04, respectively). By contrast, using BayesR resulted in limited improvement for EMA and MS. wGBLUP did not improve accuracy but increased prediction bias. Based on the RNA-seq experiment, we identified informative expression quantitative trait loci, which, when used in GBLUP, improved the accuracy of prediction slightly, i.e. between 0.01 and 0.02. SNPs that were located in genes, the expression of which was associated with differences in trait phenotype, did not contribute to a higher prediction accuracy. Our results show that, in Hanwoo beef cattle, when SNPs are pre-selected from GWAS on imputed sequence data, the accuracy of prediction improves only slightly whereas the contribution of SNPs that are selected based on gene expression is not significant. The benefit of statistical models to prioritize selected SNPs for estimating genomic breeding values is trait-specific and depends on the genetic architecture of each trait.
Genome-wide association study of inattention and hyperactivity-impulsivity measured as quantitative traits
Publisher: Cambridge University Press (CUP)
Date: 25-03-2013
DOI: 10.1017/THG.2013.12
Abstract: Genome-wide association studies (GWAS) of attention-deficit/hyperactivity disorder (ADHD) offer the benefit of a hypothesis-free approach to measuring the quantitative effect of genetic variants on affection status. Generally the findings of GWAS relying on ADHD status have been non-significant, but the one study using quantitative measures of symptoms found SLC9A9 and SLC6A1 were associated with inattention and hyperactivity–impulsivity. Accordingly, we performed a GWAS using quantitative measures of each ADHD subtype measured with the Strengths and Weaknesses of ADHD and Normal Behaviour (SWAN) scale in two community-based s les. This scale captures the full range of attention and kinetic behavior from high levels of attention and appropriate activity to the inattention and hyperactivity–impulsivity associated with ADHD within two community-based s les. Our discovery s le comprised 1,851 participants (mean age = 22.8 years [4.8] 50.6% female), while our replication s le comprised 155 participants (mean age = 26.3 years [3.1] 68.4% females). Age, sex, age × sex, and age 2 were included as covariates and the results from each s le were combined using meta-analysis, then analyzed with a gene-based test to estimate the combined effect of markers within genes. We compare our results with markers that have previously been found to have a strong association with ADHD symptoms. Neither the GWAS nor subsequent meta-analyses yielded genome-wide significant results the strongest effect was observed at rs2110267 (4.62 × 10 −7 ) for symptoms of hyperactivity–impulsivity. The strongest effect in the gene-based test was for GPR139 on symptoms of inattention (6.40 × 10 −5 ). Replication of this study with larger s les will add to our understanding of the genetic etiology of ADHD.
Using information of relatives in genomic prediction to apply effective stratified medicine
Publisher: Springer Science and Business Media LLC
Date: 09-02-2017
DOI: 10.1038/SREP42091
Abstract: Genomic prediction shows promise for personalised medicine in which diagnosis and treatment are tailored to in iduals based on their genetic profiles for complex diseases. We present a theoretical framework to demonstrate that prediction accuracy can be improved by targeting more informative in iduals in the data set used to generate the predictors (“discovery s le”) to include those with genetically close relationships with the subjects put forward for risk prediction. Increase of prediction accuracy from closer relationships is achieved under an additive model and does not rely on any family or interaction effects. Using theory, simulations and real data analyses, we show that the predictive accuracy or the area under the receiver operating characteristic curve (AUC) increased exponentially with decreasing effective size ( N e ), i.e. when in iduals are closely related. For ex le, with the s le size of discovery set N = 3000, heritability h 2 = 0.5 and population prevalence K = 0.1, AUC value approached to 0.9 and the top percentile of the estimated genetic profile scores had 23 times higher proportion of cases than the general population. This suggests that there is considerable room to increase prediction accuracy by using a design that does not exclude closer relationships.
Genetic parameters for milk yield in imported Jersey and Jersey-Friesian cows using daily milk records in Sri Lanka
Publisher: Asian Australasian Association of Animal Production Societies
Date: 11-2020
DOI: 10.5713/AJAS.19.0798
Abstract: Objective: This study was conducted to estimate genetic parameters for milk yield traits using daily milk yield records from parlour data generated in an intensively managed commercial dairy farm with Jersey and Jersey-Friesian cows in Sri Lanka.Methods: Genetic parameters were estimated for first and second lactation predicted and realized 305-day milk yield using univariate animal models. Genetic parameters were also estimated for total milk yield for each 30-day intervals of the first lactation using univariate animal models and for daily milk yield using random regression models fitting second-order Legendre polynomials and assuming heterogeneous residual variances. Breeding values for predicted 305-day milk yield were estimated using an animal model.Results: For the first lactation, the heritability of predicted 305-day milk yield in Jersey cows (0.08±0.03) was higher than that of Jersey-Friesian cows (0.02±0.01). The second lactation heritability estimates were similar to that of first lactation. The repeatability of the daily milk records was 0.28±0.01 and the heritability ranged from 0.002±0.05 to 0.19±0.02 depending on day of milk. Pearson product-moment correlations between the bull estimated breeding values (EBVs) in Australia and bull EBVs in Sri Lanka for 305-day milk yield were 0.39 in Jersey cows and –0.35 in Jersey-Friesian cows.Conclusion: The heritabilities estimated for milk yield in Jersey and Jersey-Friesian cows in Sri Lanka were low, and were associated with low additive genetic variances for the traits. Sire differences in Australia were not expressed in the tropical low-country of Sri Lanka. Therefore, genetic progress achieved by importing genetic material from Australia can be expected to be slow. This emphasizes the need for a within-country evaluation of bulls to produce locally adapted dairy cows.
Improvement of meat and carcase quality traits using genomics in pig sire lines
Publisher: Elsevier BV
Date: 11-2021
Accuracy of genotype imputation based on random and selected reference sets in purebred and crossbred sheep populations and its effect on accuracy of genomic prediction
Publisher: Springer Science and Business Media LLC
Date: 12-2015
A genome-wide association study (GWAS) for carcass traits in Hanwoo cattle using imputed whole genome sequence data
Publisher: Wageningen Academic Publishers
Date: 31-12-2022
The value of using DNA markers for beef bull selection in the seedstock sector1,2
Publisher: Oxford University Press (OUP)
Date: 02-2011
Abstract: The objective of this study was to estimate the value derived from using DNA information to increase the accuracy of beef sire selection in a closed seedstock herd. Breeding objectives for commercial production systems targeting 2 erse markets were examined using multiple-trait selection indexes developed for the Australian cattle industry. Indexes included those for both maternal (self-replacing) and terminal herds targeting either a domestic market, where steers are finished on pasture, or the export market, where steers are finished on concentrate rations in feedlots and marbling has a large value. Selection index theory was used to predict the response to conventional selection based on phenotypic performance records, and this was compared with including information from 2 hypothetical marker panels. In 1 case the marker panel explained a percentage of additive genetic variance equal to the heritability for all traits in the breeding objective and selection criteria, and in the other case to one-half of this amount. Discounted gene flow methodology was used to calculate the value derived from the use of superior bulls selected using DNA test information and performance recording over that derived from conventional selection using performance recording alone. Results were ultimately calculated as discounted returns per DNA test purchased by the seedstock operator. The DNA testing using these hypothetical marker panels increased the selection response between 29 to 158%. The value of this improvement above that obtained using traditional performance recording ranged from $89 to 565 per commercial bull, and $5,332 to 27,910 per stud bull. Assuming that the entire bull calf crop was tested to achieve these gains, the value of the genetic gain derived from DNA testing ranged from $204 to 1,119 per test. All values assumed that the benefits derived from using superior bulls were efficiently transferred along the production chain to the seedstock producer incurring the costs of genotyping. These results suggest that the development of greater-accuracy DNA tests for beef cattle selection could be beneficial from an industry-wide perspective, but the commercial viability will strongly depend on price signaling throughout the production chain.
Genomic regions in Australian cattle associated with consumer satisfaction of beef
Publisher: Wageningen Academic Publishers
Date: 31-12-2023
Estimation of genetic parameters for BW and body measurements in Brahman cattle
Publisher: Elsevier BV
Date: 2019
Manipulating response to selection on many traits
Publisher: Wageningen Academic Publishers
Date: 31-12-2023
Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP)
Publisher: Wageningen Academic Publishers
Date: 31-12-2022
Analysis of culling reasons and age at culling in Australian dairy cattle
Publisher: CSIRO Publishing
Date: 02-02-2021
DOI: 10.1071/AN20195
Abstract: Context A thorough analysis of the reasons for culling was made to understand the phenotypic trend in herd life. In addition, identification of culling reasons could enable to develop a strategy for further evaluation of longevity in Australian dairy cows. Aims The aim of this study was to investigate the main causes of culling in Australian dairy herds and thereby to assess the trend of reason-specific culling over time. Methods Culling reasons in Australian dairy cattle were studied based on culling records from 1995 through 2016. A total of 2 452 124 in idual cow culling observations were obtained from Datagene, Australia, of which 2 140 337 were Holstein and 311 787 were from Jersey cows. A binary logistic regression model was used to estimate effects of breed and age and the trend of a particular culling reason over time. Key results The most important culling reasons identified over the 21-year period were infertility (17.0%), mastitis (12.9%), low production (9.3%), sold for dairy purpose (6.4%) and old age (6.2%), whereas 37.4% were ‘other reasons not reported’. The average age at culling was nearly the same for Holstein (6.75 years) and Jersey (6.73 years) cows. The estimated age at culling was slightly increased for Holstein cows (by 3.7 days) and somewhat decreased for Jersey cows (by 11 days) over the last two decades. The probability of culling cows for infertility and low production was high in early parities and consistently declined as age advanced, and culling due to mastitis was higher in older cows. The trend of main culling reasons over time was evaluated, indicating that the probability of culling due to infertility has progressively increased over the years in both breeds, and culling for mastitis in Jersey cows has also increased. Culling of cows due to low production sharply decreased from 2.5 to –8% for Holstein and from 73 to 60% for Jersey cows over the 21-year period. Conclusions Culling age has changed only little in both breeds whereas culling reasons have changed over the last two decades, with low production becoming a less important reason for culling and infertility becoming more important for Holstein and Jersey breeds. Implications Due to changes of culling reasons, there could be a change in the meaning of survival over time as well. As a result, genetic correlation with survival and other traits might be changed and accuracy and bias of genetic evaluations could be affected.
Fine mapping of multiple interacting quantitative trait loci using combined linkage disequilibrium and linkage information.
Publisher: Zhejiang University Press
Date: 10-2007
Genetic mapping of quantitative trait loci for resistance to Haemonchus contortus in sheep
Publisher: Wiley
Date: 06-2009
DOI: 10.1111/J.1365-2052.2008.01836.X
Abstract: This paper presents results from a mapping experiment to detect quantitative trait loci (QTL) for resistance to Haemonchus contortus infestation in merino sheep. The primary trait analysed was faecal worm egg count in response to artificial challenge at 6 months of age. In the first stage of the experiment, whole genome linkage analysis was used for broad-scale mapping. The animal resource used was a designed flock comprising 571 in iduals from four half-sib families. The average marker spacing was about 20 cM. For the primary trait, 11 QTL (as chromosomal/family combinations) were significant at the 5% chromosome-wide level, with allelic substitution effects of between 0.19 and 0.38 phenotypic standard deviation units. In general, these QTL did not have a significant effect on faecal worm egg count recorded at 13 months of age. In the second stage of the experiment, three promising regions (located on chromosomes 1, 3 and 4) were fine-mapped. This involved typing more closely spaced markers on in iduals from the designed flock as well as an additional 495 in iduals selected from a related population with a deeper pedigree. Analysis was performed using a linkage disequilibrium-linkage approach, under additive, dominant and multiple QTL models. Of these, the multiple QTL model resulted in the most refined QTL positions, with resolutions of <10 cM achieved for two regions. Because of the moderate size of effect of the QTL, and the apparent age and/or immune status specificity of the QTL, it is suggested that a panel of QTL will be required for significant genetic gains to be achieved within industry via marker-assisted selection.
Genetic correlations between wool traits and meat quality traits in Merino sheep1
Publisher: Oxford University Press (OUP)
Date: 10-2017
DOI: 10.2527/JAS2017.1628
Abstract: Genetic correlations between 29 wool production and quality traits and 25 meat quality and nutritional value traits were estimated for Merino sheep from an Information Nucleus (IN). Genetic correlations among the meat quality and nutritional value traits are also reported. The IN comprised 8 flocks linked genetically and managed across a range of sheep production environments in Australia. The wool traits included over 5,000 yearling and 3,700 adult records for fleece weight, fiber diameter, staple length, staple strength, fiber diameter variation, scoured wool color, and visual scores for breech and body wrinkle. The meat quality traits were measured on s les from the and included over 1,200 records from progeny of over 170 sires for intramuscular fat (IMF), shear force of meat aged for 5 d (SF5), 24 h postmortem pH (pHLL also measured in the , pHST), fresh and retail meat color and meat nutritional value traits such as iron and zinc levels, and long-chain omega-3 and omega-6 polyunsaturated fatty acid levels. Estimated heritabilities for IMF, SF5, pHLL, pHST, retail meat color lightness (), myoglobin, iron, zinc and across the range of long-chain fatty acids were 0.58 ± 0.11, 0.10 ± 0.09, 0.15 ± 0.07, 0.20 ± 0.10, 0.59 ± 0.15, 0.31 ± 0.09, 0.20 ± 0.09, 0.11 ± 0.09, and range of 0.00 (eicosapentaenoic, docosapentaenoic, and arachidonic acids) to 0.14 ± 0.07 (linoleic acid), respectively. The genetic correlations between the wool production and meat quality traits were low to negligible and indicate that wool breeding programs will have little or no effect on meat quality. There were moderately favorable genetic correlations between important yearling wool production traits and the omega-3 fatty acids that were reduced for corresponding adult wool production traits, but these correlations are unlikely to be important in wool/meat breeding programs because they have high SE, and the omega-3 traits have little or no genetic variance. Significant genetic correlations among the meat quality traits included IMF with SF5 (-0.76 ± 0.24), fresh meat color * (0.50 ± 0.18), and zinc (0.41 ± 0.19). Selection to increase IMF will improve meat tenderness and color which may address some of the issues with Merino meat quality. These estimated parameters allow Merino breeders to combine wool and meat objectives without compromising meat quality.
The importance of accounting for maternal genetic effects in Australian fine-wool Merino breeding
Publisher: CSIRO Publishing
Date: 2005
DOI: 10.1071/AR05006
Abstract: (Co) variances for greasy fleece weight (GFW), clean fleece weight (CFW), mean fibre diameter (MFD), staple strength (SS), coefficient of variation of fibre diameter (CVFD), birthweight (BW), weaning weight (WW), and yearling weight (YW) were estimated for 5108 Australian Merino sheep from the CSIRO Fine Wool Project, born between 1990 and 1994. Covariances between these traits and number of lambs weaned per ewe joined (NLW) were also estimated. Significant maternal genetic effects were found for GFW, CFW, BW, WW, and YW. Estimates of heritability were biased upwardly when maternal effects were ignored. The maternal heritability estimates for GFW, CFW, BW, WW, and YW were 0.17, 0.15, 0.38, 0.28, and 0.13, respectively. Maternal effects were not important for MFD, CVFD, SS, and NLW. Direct-maternal genetic correlations within each fleece weight and bodyweight trait were estimated to be moderately negative (–0.26 to –0.48). The effect of ignoring maternal genetic effect was explored using selection index theory. Accounting for the maternal effects in both the selection criteria and breeding objective increased the overall response by 14.3%, 4.8%, 2.6%, 1.4%, and 0.0% in 3, 6, 12, 20 and 30% micron premium scenarios, respectively, compared with when the maternal effects were only included in breeding objective. Complete ignorance of the maternal effects led to overestimation in overall response of 2.8–35.7% for different micron premium scenarios in contrast to when the maternal effects were ignored in the selection index weight, but were included in the breeding objective. The results indicate that the maternal genetic effects of fleece weight and bodyweight should be considered in Merino breeding programs.
Components of the accuracy of genomic prediction in a multi-breed sheep population1
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.
Redefining residual feed intake to account for marbling fat in beef breeding programs
Publisher: CSIRO Publishing
Date: 21-07-2021
DOI: 10.1071/AN21107
Abstract: Context Improving meat quality traits such as marbling is a well established breeding objective for many beef producers. More recently, the inclusion of feed efficiency is being considered. The main driving factors being the direct feed cost, as well as consumer concerns related to environmental sustainability of beef production. Aims The main aim of this study was to examine modifying the definition of residual feed intake (RFI), by including an adjustment for intramuscular fat (IMF). The secondary aim was to further understand the genetic relationships between feed intake and a range of carcass traits. Methods Using a population of 4034 Australian Angus animals, feed intake and carcass traits, along with pedigree and fixed effects, were analysed. This included the calculation of three definitions of RFI, being the standard definition, accounting for average daily gain and metabolic mid-weight, and two amended versions accounting for ultrasound IMF (RFIu), or carcass IMF (RFIi). Variance components, heritabilities, and genetic and phenotypic correlations were estimated and compared. Key results All three definitions of RFI were moderately heritable (0.30–0.32) and highly correlated, both genetically (0.99) and phenotypically (0.99). Unfavourable genetic correlations were observed between RFI and carcass IMF (CIMF), and between RFIu and CIMF at 0.29 and 0.24 respectively. Similarly, there were unfavourable genetic correlations between RFI and ultrasound IMF (UIMF), between RFIi and UIMF, and between RFIu and UIMF at 0.30, 0,21 and 0.23 respectively. Conclusions RFI can be redefined to account for traits, other than average daily gain and metabolic mid-weight, such as IMF. However due to limitations of phenotypic linear regression, and only small amounts of variation in feed intake being explained by the IMF traits, the redefinition of RFI was a suboptimal approach to breeding candidate selection. Furthermore, the present study confirmed the challenges with selecting for both feed efficiency and meat quality traits as they are generally genetically antagonist. Implications For beef cattle breeding programs, the investigation of alternative selection approaches is warranted. This may include further understanding the genetic correlations among traits in the breeding objective and, according to their economic value, optimally weighting the related estimated breeding value.
Genome-Wide Association Studies and Genomic Prediction
Publisher: Humana Press
Date: 2013
A quantitative trait locus for faecal worm egg and blood eosinophil counts on chromosome 23 in Australian goats
Publisher: Wiley
Date: 13-11-2009
DOI: 10.1111/J.1439-0388.2009.00824.X
Abstract: Three microsatellite markers on goat chromosome 23 adjacent to the MHC were used to test for quantitative trait loci (QTL) affecting faecal worm egg count (WEC) and leukocyte traits in ten Australian Angora and twelve Australian Cashmere half-sib families (n = 16-57 per family). Data were collected from 280 Angora and 347 Cashmere kids over a 3- and 4-year period. A putative QTL affecting trichostrongyle WEC was found in two small families at the 5% chromosome-wise threshold level. The biggest QTL effect for WEC of 1.65 standard deviations (sigma(p)) was found within the region of OarCP73-BM1258. A significant QTL affecting blood eosinophil counts at the 1% chromosome-wise threshold level was detected at marker BM1258 (at 26 cM) in two Angora and Cashmere families. The magnitude of the putative QTL was 0.69 and 0.85 sigma(p) in Angora and Cashmere families, respectively. Due to the comparatively low power of the study these findings should be viewed as indicative rather than definitive.
The accuracy of genomic prediction for meat quality traits in Hanwoo cattle when using genotypes from different SNP densities and preselected variants from imputed whole genome sequence
Publisher: CSIRO Publishing
Date: 05-11-2022
DOI: 10.1071/AN20659
Abstract: Context Genomic prediction is the use of genomic data in the estimation of genomic breeding values (GEBV) in animal breeding. In beef cattle breeding programs, genomic prediction increases the rates of genetic gain by increasing the accuracy of selection at earlier ages. Aims The objectives of the study were to examine the effect of single-nucleotide polymorphism (SNP) density and to evaluate the effect of using SNPs preselected from imputed whole-genome sequence for genomic prediction. Methods Genomic and phenotypic data from 2110 Hanwoo steers were used to predict GEBV for marbling score (MS), meat texture (MT), and meat colour (MC) traits. Three types of SNP densities including 50k, high-density (HD), and whole-genome sequence data and preselected SNPs from genome-wide association study (GWAS) were used for genomic prediction analyses. Two scenarios (independent and dependent discovery populations) were used to select top significant SNPs. The accuracy of GEBV was assessed using random cross-validation. Genomic best linear unbiased prediction (GBLUP) was used to predict the breeding values for each trait. Key results Our result showed that very similar prediction accuracies were observed across all SNP densities used in the study. The prediction accuracy among traits ranged from 0.29 ± 0.05 for MC to 0.46 ± 0.04 for MS. Depending on the studied traits, up to 5% of prediction accuracy improvement was obtained when the preselected SNPs from GWAS analysis were included in the prediction analysis. Conclusions High SNP density such as HD and the whole-genome sequence data yielded a similar prediction accuracy in Hanwoo beef cattle. Therefore, the 50K SNP chip panel is sufficient to capture the relationships in a breed with a small effective population size such as the Hanwoo cattle population. Preselected variants improved prediction accuracy when they were included in the genomic prediction model. Implications The estimated genomic prediction accuracies are moderately accurate in Hanwoo cattle and for searching for SNPs that are more productive could increase the accuracy of estimated breeding values for the studied traits.
Variation in Latent Classes of Adult Attention-Deficit Hyperactivity Disorder by Sex and Environmental Adversity.
Publisher: SAGE Publications
Date: 28-07-2013
Abstract: Objective: The findings of genetic, imaging and neuropsychological studies of attention-deficit hyperactivity disorder (ADHD) are mixed. To understand why this might be the case we use both dimensional and categorical symptom measurement to provide alternate and detailed perspectives of symptom expression. Method: Interviewers collected ADHD, conduct problems (CP) and sociodemographic data from 3793 twins and their siblings aged 22 to 49 ( M = 32.6). We estimate linear weighting of symptoms across ADHD and CP items. Latent class analyses and regression describe associations between measured variables, environmental risk factors and subsequent disadvantage. Additionally, the clinical relevance of each class was estimated. Results: Five classes were found for women and men few symptoms, hyperactive-impulsive, CP, inattentive, combined symptoms with CP. Women within the inattentive class reported more symptoms and reduced emotional health when compared to men and to women within other latent classes. Women and men with combined ADHD symptoms reported comorbid conduct problems but those with either inattention or hyperactivity-impulsivity only did not. Conclusion: The dual perspective of dimensional and categorical measurement of ADHD provides important detail about symptom variation across sex and with environmental covariates.
10th WCGALP in beautiful Vancouver
Publisher: Wiley
Date: 16-09-2014
DOI: 10.1111/JBG.12119
Genetic and economic benefits of selection based on performance recording and genotyping in lower tiers of multi-tiered sheep breeding schemes
Publisher: Springer Science and Business Media LLC
Date: 17-01-2017
Genetic parameters for carcass and meat quality traits and their relationships to liveweight and wool production in hogget Merino rams
Publisher: Wiley
Date: 06-2008
DOI: 10.1111/J.1439-0388.2007.00711.X
Abstract: Genetic parameters for carcass and meat quality traits of about 18-month-old Merino rams (n = 5870), the progeny of 543 sires from three research resource flocks, were estimated. The estimates of heritability for hot carcass weight (HCW) and the various fat and muscle dimension measurements were moderate and ranged from 0.20 to 0.37. The brightness of meat (colour L*, 0.18 +/- 0.03 standard error) and meat pH (0.22 +/- 0.03) also had moderate estimates of heritability, although meat relative redness (colour a*, 0.10 +/- 0.03) and relative yellowness (colour b*, 0.10 +/- 0.03) were lower. Heritability estimates for live weights were moderate and ranged from 0.29 to 0.41 with significant permanent maternal environmental effects (0.13 to 0.10). The heritability estimates for the hogget wool traits were moderate to high and ranged from 0.27 to 0.60. The ultrasound measurements of fat depth (FATUS) and eye muscle depth (EMDUS) on live animals were highly genetically correlated with the corresponding carcass measurements (0.69 +/- 0.09 FATC and 0.77 +/- 0.07 EMD). Carcass tissue depth (FATGR) had moderate to low genetic correlations with carcass muscle measurements [0.18 +/- 0.10 EMD and 0.05 +/- 0.10 eye muscle area (EMA)], while those with FATC were negative. The genetic correlation between EMD and eye muscle width (EMW) was 0.41 +/- 0.08, while EMA was highly correlated with EMD (0.89 +/- 0.0) and EMW (0.78 +/- 0.04). The genetic correlations for muscle colour with muscle measurements were moderately negative, while those with fat measurements were close to zero. Meat pH was positively correlated with muscle measurements (0.14 to 0.17) and negatively correlated with fat measurements (-0.06 to -0.18). EMDUS also showed a similar pattern of correlations to EMD with meat quality indicator traits, although FATUS had positive correlations with these traits which were generally smaller than their standard error. The genetic correlations among the meat colour traits were high and positive while those with meat pH were high and negative, which were all in the favourable direction. Generally, phenotypic correlations were similar or slightly lower than the corresponding genetic correlations. There were generally small to moderate negative genetic correlations between clean fleece weight (CFW) and carcass fat traits while those with muscle traits were close to zero. As the Merino is already a relatively lean breed, this implies that particular attention should be given to this relationship in Merino breeding programmes to prevent the reduction of fat reserves as a correlated response to selection for increased fleece weight. The ultrasound scan traits generally showed a similar pattern to the corresponding carcass fat and muscle traits. There was a small unfavourable genetic correlation between CFW and meat pH (0.19 +/- 0.07).
Genomic prediction in a numerically small breed population using prioritized genetic markers from whole‐genome sequence data
Publisher: Wiley
Date: 10-08-2021
DOI: 10.1111/JBG.12638
Abstract: The objective of this study was to investigate the accuracy of genomic prediction of body weight and eating quality traits in a numerically small sheep population (Dorper sheep). Prediction was based on a large multi‐breed/admixed reference population and using (a) 50k or 500k single nucleotide polymorphism (SNP) genotypes, (b) imputed whole‐genome sequencing data (~31 million), (c) selected SNPs from whole genome sequence data and (d) 50k SNP genotypes plus selected SNPs from whole‐genome sequence data. Furthermore, the impact of using a breed‐adjusted genomic relationship matrix on accuracy of genomic breeding value was assessed. The selection of genetic variants was based on an association study performed on imputed whole‐genome sequence data in an independent population, which was chosen either randomly from the base population or according to higher genetic proximity to the target population. Genomic prediction was based on genomic best linear unbiased prediction (GBLUP), and the accuracy of genomic prediction was assessed according to the correlation between genomic breeding value and corrected phenotypes ided by the square root of trait heritability. The accuracy of genomic prediction was between 0.20 and 0.30 across different traits based on common 50k SNP genotypes, which improved on average by 0.06 (absolute value) on average based on using prioritized genetic markers from whole‐genome sequence data. Using prioritized genetic markers from a genetically more related GWAS population resulted in slightly higher prediction accuracy (0.02 absolute value) compared to genetic markers derived from a random GWAS population. Using high‐density SNP genotypes or imputed whole‐genome sequence data in GBLUP showed almost no improvement in genomic prediction accuracy however, accounting for different marker allele frequencies in reference population according to a breed‐adjusted GRM resulted to on average 0.024 (absolute value) increase in accuracy of genomic prediction.
321. Variance component estimation for single-step genomic BLUP for Australian terminal sire sheep
Publisher: Wageningen Academic Publishers
Date: 31-12-2022
Effects of truncation and false positives in selection of markers for genomic prediction
Publisher: Wageningen Academic Publishers
Date: 31-12-2023
Use of a bovine genome array to identify new biological pathways for beef marbling in Hanwoo (Korean Cattle)
Publisher: Springer Science and Business Media LLC
Date: 09-11-2010
Adaptation and Fitness in Animal Populations: Evolutionary and Breeding Perspectives on Genetic Resource Management
Publisher: Springer Netherlands
Date: 2008
Optimization of a crossing system using mate selection
Publisher: Springer Science and Business Media LLC
Date: 24-02-2006
DOI: 10.1051/GSE:2005033
DNA-based parentage verification in two Australian goat herds
Publisher: Elsevier BV
Date: 11-2008
Inclusion of skin follicle traits in selection indices in breeding programs improves genetic gain in Australian fine-wool Merinos
Publisher: CSIRO Publishing
Date: 2007
DOI: 10.1071/AR06347
Abstract: Genetic parameters for skin follicle traits, wool traits, body weight, and number of lambs weaned per ewe joined were estimated for 5108 10-month-old Australian fine-wool Merinos born between 1990 and 1996. These animals were descended from 261 sires and 2508 dams. The skin follicle number index that is based on skin surface area, and primary, secondary, or total follicle density were introduced as possible early-age selection criteria estimated at 6 months of age. Heritability estimates for total, secondary, and primary follicle number index were 0.45 ± 0.04, 0.46 ± 0.04, and 0.38 ± 0.04, respectively. The genetic correlations of total follicle number index with clean fleece weight, mean fibre diameter, staple strength, coefficient of variation of fibre diameter, body weight, and number of lambs weaned were 0.16, –0.67, 0.00, 0.03, 0.22, and 0.22, respectively. Responses to selection on indices including and excluding follicle traits were calculated based on the genetic parameters estimated, and with annual responses calculated using an optimised age structure. On average, 10% greater response was predicted when total follicle number index was used as an additional selection criterion in different micron premium scenarios. In comparison, skin follicle density had a smaller effect on genetic improvement. The extra response was ~1%. Similar index responses were obtained when total follicle number index was used as a replacement selection criterion for clean fleece weight, mean fibre diameter, and coefficient of variation of fibre diameter for breeding objectives with low emphasis on fibre diameter. In objectives with high emphasis on fibre diameter, unfavourable correlated responses in staple strength and CV of fibre diameter limited the effectiveness of using total follicle number index as a selection criterion. Although the use of total follicle number index as an additional selection criterion can be favourable for some breeding objectives, measuring this trait is currently cost prohibitive to inclusion in Merino breeding programs.
Response to selection in beef cattle using IGF-1 as a selection criterion for residual feed intake under different Australian breeding objectives
Publisher: Elsevier BV
Date: 12-2004
Genetic polymorphisms of the bovine Fatty acid binding protein 4 gene are significantly associated with marbling and carcass weight in Hanwoo (Korean Cattle)
Publisher: Wiley
Date: 03-2010
DOI: 10.1111/J.1365-2052.2010.02024.X
Abstract: The objective of this study was to investigate an association between polymorphisms in the FABP4 gene and phenotypic variation for marbling and carcass weight (CWT) in a population of Hanwoo steers. We re-sequenced 4.3 kb of the FABP4 gene region in 24 Hanwoo bulls and identified 16 SNPs and 1 microsatellite polymorphism. Of these 16 SNPs, three SNPs [g.2774G>C (intron I), g.3473A>T (intron II) and g.3631G>A (exon III, creating a p.Met >Val amino acid substitution)] were genotyped in 583 steers to assess their association with carcass traits. The g.3473A allele showed a significant increasing effect on CWT (P = 0.01) and the g.3631G allele was associated with higher marbling score (P = 0.006). One haplotype of these three SNPs (CAG) was significantly associated with CWT (P = 0.02) and marbling score (P = 0.05) and could potentially be of value for marker assisted selection in Hanwoo cattle. The CAG haplotype effect for CWT was larger (11.14 +/- 5.03 kg) than the largest single locus effect of g.3473A>T (5.01 +/- 2.2 kg).
Design of reference populations for genomic selection in crossbreeding programs
Publisher: Springer Science and Business Media LLC
Date: 2015
Genetic parameters for wool traits, live weight, and ultrasound carcass traits in Merino sheep
Publisher: Oxford University Press (OUP)
Date: 2017
DOI: 10.2527/JAS2016.1234
Multiple-trait QTL mapping and genomic prediction for wool traits in sheep
Publisher: Springer Science and Business Media LLC
Date: 15-08-2017
Genetic parameters for egg production traits in purebred and hybrid chicken in a tropical environment
Publisher: Informa UK Limited
Date: 02-11-2015
DOI: 10.1080/00071668.2015.1099614
Abstract: Genetic parameters were estimated for 5 economically important egg production traits using records collected over 9 years in chickens reared under tropical conditions in Thailand. The data were from two purebred lines and two hybrid lines of layer parent stocks. The two purebred lines were Rhode Island Red (RIR) and White Plymouth Rock (WPR) and the hybrid lines were formed by crossing a commercial brown egg laying strain to Rhode Island Red (RC) and White Plymouth Rock (WC), respectively. Five egg production traits were analysed, including age at first egg (AFE), body weight at first egg (BWT), egg weight at first egg (EWFE), number of eggs from the first 17 weeks of lay (EN) and average egg weight over the 17th week of lay (EW). Fixed effects of year and hatch within year were significant for all 5 traits and were included in the model. Maternal genetic and permanent environmental effects of the dam were not significant, except for EN and EW in RIR and BWT and EW in WPR. Estimated heritability of AFE, BWT, EWFE, EN and EW were 0.45, 0.50, 0.29, 0.19 and 0.43 in RIR 0.44, 0.38, 0.33, 0.20 and 0.38 in WPR 0.37, 0.41, 0.38, 0.18 and 0.36 in RC and 0.46, 0.53, 0.36, 0.38 and 0.45 in WC lines, respectively. The EN was negatively correlated with other traits, except for BWT in RC and AFE and BWT in WC. It was concluded that selection for increased EN will reduce other egg production traits in purebred and hybrid chicken and therefore EN needs to be combined with other egg production traits in a multi-trait selection index to improve all traits optimally according to a defined breeding objective.
457. Response to index selection for temperate dairy cattle breeds in tropical Sri Lanka
Publisher: Wageningen Academic Publishers
Date: 31-12-2022
Book of Abstracts of the 70th Annual Meeting of the European Federation of Animal Science
Publisher: Wageningen Academic Publishers
Date: 26-08-2019
730. Value of data from ram breeding flocks as an industry reference population for Australian sheep
Publisher: Wageningen Academic Publishers
Date: 31-12-2022
Genetic parameters for meat quality traits of Australian lamb meat
Publisher: Elsevier BV
Date: 02-2014
DOI: 10.1016/J.MEATSCI.2013.09.007
Abstract: Genetic parameters were estimated for a range of meat quality traits recorded on Australian lamb meat. Data were collected from Merino and crossbred progeny of Merino, terminal and maternal meat breed sires of the Information Nucleus programme. Lambs born between 2007 and 2010 (n=8968) were slaughtered, these being the progeny of 372 sires and 5309 dams. Meat quality traits were found generally to be of moderate heritability (estimates between 0.15 and 0.30 for measures of meat tenderness, meat colour, polyunsaturated fat content, mineral content and muscle oxidative capacity), with notable exceptions of intramuscular fat (0.48), ultimate pH (0.08) and fresh meat colour a* (0.08) and b* (0.10) values. Genetic correlations between hot carcass weight and the meat quality traits were low. The genetic correlation between intramuscular fat and shear force was high (-0.62). Several measures of meat quality (fresh meat redness, retail meat redness, retail oxy/met value and iron content) appear to have potential for inclusion in meat sheep breeding objectives.
Genetic evaluation of Australian dairy cattle for somatic cell scores using multi-trait random regression test-day model
Publisher: Wiley
Date: 06-2009
DOI: 10.1111/J.1439-0388.2008.00762.X
Abstract: A multi-trait (MT) random regression (RR) test day (TD) model has been developed for genetic evaluation of somatic cell scores for Australian dairy cattle, where first, second and third lactations were considered as three different but correlated traits. The model includes herd-test-day, year-season, age at calving, heterosis and lactation curves modelled with Legendre polynomials as fixed effects, and random genetic and permanent environmental effects modelled with Legendre polynomials. Residual variance varied across the lactation trajectory. The genetic parameters were estimated using asreml. The heritability estimates ranged from 0.05 to 0.16. The genetic correlations between lactations and between test days within lactations were consistent with most of the published results. Preconditioned conjugate gradient algorithm with iteration on data was implemented for solving the system of equations. For reliability approximation, the method of Tier and Meyer was used. The genetic evaluation system was validated with Interbull validation method III by comparing proofs from a complete evaluation with those from an evaluation based on a data set excluding the most recent 4 years. The genetic trend estimate was in the allowed range and correlations between the two sets of proofs were very high. Additionally, the RR model was compared to the previous test day model. The correlations of proofs between both models were high (0.97) for bulls with high reliabilities. The correlations of bulls decreased with increasing incompleteness of daughter performance information. The correlations between the breeding values from two consecutive runs were high ranging from 0.97 to 0.99. The MT RR TD model was able to make effective use of available information on young bulls and cows, and could offer an opportunity to breeders to utilize estimated breeding values for first and later lactations.
Effective breeding programmes down under
Publisher: Wiley
Date: 10-01-2017
DOI: 10.1111/JBG.12252
Genome-wide association study for carcass traits in Hanwoo cattle using additional relatives' information of non-genotyped animals.
Publisher: Wiley
Date: 22-08-2022
DOI: 10.1111/AGE.13251
Abstract: The aim of this study was to find significant genomic regions associated with carcass traits in Hanwoo cattle and to compare the benefit of using additional information from non-genotyped animals. Imputed whole-genome sequence data were used along with phenotypic data on 13 715 genotyped animals as well as phenotypes of 440 284 non-genotyped animals that were offspring of 454 genotyped sires. For carcass weight, 15 083 SNPs in 33 QTL regions and 313 candidate genes were identified. We found 410 SNPs in 17 QTL regions containing 122 candidate genes for back fat thickness. In total, 656 SNPs in 19 QTLs with 137 candidate genes for eye muscle area and 79 SNPs in 12 QTL regions with 77 candidate genes were identified for marbling score. The most important candidate genes included ZFAT, TG, PLAG1, CHCHD7, and TOX for carcass weight and eye muscle area, NOG for back fat thickness, and EVOVL5 for marbling score. This study showed that the use of phenotypic records on non-genotyped progeny along with imputed whole-genome sequence data increased the power of detecting new significant genomic regions.
Genetic analysis of weight, fat and muscle depth in growing lambs using random regression models
Publisher: Cambridge University Press (CUP)
Date: 02-2006
DOI: 10.1079/ASC200511
Abstract: Genetic parameters were estimated using uni- and bi-variate random regression models for weight, eye-muscle depth and fat depth measures between 60 and 360 days of age. Each trait was measured up to five times in 50-day intervals following weaning on approximately 4000 Australian Poll Dorset Sheep. The model accounted for rearing type, dam age, management group and age of recording. The model used for analysing weight included quadratic, orthogonal polynomials for direct genetic and environmental effects, a linear polynomial for maternal genetic effects and heterogeneous error variance across ages. The fat and muscle analysis used linear orthogonal polynomials for direct genetic and environmental effects and heterogeneous error variance. Throughout the 300-day trajectory heritability for weight traits ranged from 0·20 to 0·31, while heritability for fat depth ranged from 0·24 to 0·34 and heritability for eye-muscle depth ranged from 0·24 to 0·40. Genetic correlations between repeated measures of the same trait at different ages were positive and declined as the age interval increased, to minimum values of 0·60, 0·31 and 0·50 for weight, fat and muscle respectively between 60 and 360 days of age. Genetic correlations between weight and fat and weight and eye muscle were moderate to high (0·6 to 0·8) and positive but decreased slightly with age. The genetic correlations between fat and muscle were moderate to high (0·5 to 0·7) throughout the 300-day trajectory. In all cases, the estimates produced in this study were reasonably consistent with the limited number of studies that exist in the reported literature. This study demonstrated the relationships that exist between repeated measures of weight, fat and muscle measures over time, which is of interest to prime lamb producers looking to select for specific breeding objectives or market end points requiring precise weight, fat and muscle combinations at certain ages.
The effect of genomic information on optimal contribution selection in livestock breeding programs
Publisher: Springer Science and Business Media LLC
Date: 2013
Combining the meiosis Gibbs sampler with the random walk approach for linkage and association studies with a general complex pedigree and multimarker loci
Publisher: Oxford University Press (OUP)
Date: 12-2005
DOI: 10.1534/GENETICS.104.037028
Abstract: A linkage analysis for finding inheritance states and haplotype configurations is an essential process for linkage and association mapping. The linkage analysis is routinely based upon observed pedigree information and marker genotypes for in iduals in the pedigree. It is not feasible for exact methods to use all such information for a large complex pedigree especially when there are many missing genotypic data. Proposed Markov chain Monte Carlo approaches such as a single-site Gibbs s ler or the meiosis Gibbs s ler are able to handle a complex pedigree with sparse genotypic data however, they often have reducibility problems, causing biased estimates. We present a combined method, applying the random walk approach to the reducible sites in the meiosis s ler. Therefore, one can efficiently obtain reliable estimates such as identity-by-descent coefficients between in iduals based on inheritance states or haplotype configurations, and a wider range of data can be used for mapping of quantitative trait loci within a reasonable time.
Description of lamb growth using random regression on field data
Publisher: Elsevier BV
Date: 09-2004
Evidence for multiple alleles effecting muscling and fatness at the Ovine GDF8 locus
Publisher: Springer Science and Business Media LLC
Date: 08-11-2007
Across flock (co)variance components for faecal worm egg count, live weight, and fleece traits for Australian merinos
Publisher: Elsevier BV
Date: 12-2004
Genomic prediction from observed and imputed high-density ovine genotypes
Publisher: Springer Science and Business Media LLC
Date: 20-04-2017
Different models of genetic variation and their effect on genomic evaluation
Publisher: Springer Science and Business Media LLC
Date: 17-05-2011
Parameter Estimation and Assessment of Bias in Genetic Evaluation of Carcass Traits in Hanwoo Cattle Using Real and Simulated Data
Publisher: Korean Society of Animal Science and Technology
Date: 13-04-2023
A combined long-range phasing and long haplotype imputation method to impute phase for SNP genotypes
Publisher: Springer Science and Business Media LLC
Date: 10-03-2011
Random regression test day models to estimate genetic parameters for milk yield and milk components in Philippine dairy buffaloes
Publisher: Wiley
Date: 02-03-2015
DOI: 10.1111/JBG.12133
Abstract: Heritabilities and genetic correlations for milk production traits were estimated from first-parity test day records on 1022 Philippine dairy buffalo cows. Traits analysed included milk (MY), fat (FY) and protein (PY) yields, and fat (Fat%) and protein (Prot%) concentrations. Varying orders of Legendre polynomials (Leg(m)) as well as the Wilmink function (Wil) were used in random regression models. These various models were compared based on log likelihood, Akaike's information criterion, Bayesian information criterion and genetic variance estimates. Six residual variance classes were sufficient for MY, FY, PY and Fat%, while seven residual classes for Prot%. Multivariate analysis gave higher estimates of genetic variance and heritability compared with univariate analysis for all traits. Heritability estimates ranged from 0.25 to 0.44, 0.13 to 0.31 and 0.21 to 0.36 for MY, FY and PY, respectively. Wilmink's function was the better fitting function for additive genetic effects for all traits. It was also the preferred function for permanent environment effects for Fat% and Prot%, but for MY, FY and PY, the Legm was the appropriate function. Genetic correlations of MY with FY and PY were high and they were moderately negative with Fat% and Prot%. To prevent deterioration in Fat% and Prot% and improve milk quality, more weight should be applied to milk component traits.
Reaction-norm analysis of neonatal lamb mortality suggests heritability varies with cold-stress: an example in the Elsenburg Merino selection lines
Publisher: CSIRO Publishing
Date: 13-04-2023
DOI: 10.1071/AN22464
Abstract: Context Coping with high levels of cold stress should be beneficial to survival of lambs, given the high mortality rate associated with severe winter storms. The Elsenburg Merino selection experiment involved ergent selection for reproduction. Phenotypic results comparing the positively selected H-Lines and negatively selected L-Lines suggested that cold-stress adaption could have contributed to the favourable genetic trends for survival of H-Line lambs. However, observing the genetic merit of better adapted animals depends on the presence of cold stress at the time of recording. A genotype by environment component (G × E) could, thus, be important when assessing survival/mortality phenotypes. Aim This study proposed the genetic analysis of this possible G × E component and compared the H- and L-Lines in this regard. Methods The sire model allowed the use of progeny phenotypes for neonatal mortality recorded during different levels of cold stress, and the possible G × E could be investigated through the reaction-norm approach. Genetic parameters were evaluated as random regression components by implementing a Gibbs s ling approach. A data set of 5723 in idual lamb records was analysed as the progeny of 213 sires. Results A modelled G × E component played an important role in mortality outcomes, with the mean estimate (and 95% confidence interval) for the slope ( σ s b 2 = 0.113 [ 0.0019 – 0.28 ] AN22464_IE1.gif) only marginally smaller than the corresponding estimate for the intercept ( σ s a 2 = 0.124 [ 0.003 – 0.26 ] AN22464_IE2.gif). The reaction-norm model showed a higher heritability (h2 ± posterior standard deviation) for mortality at 3 days of age during high cold-stress (0.22 ± 0.16 at ~1100 KJm−2h−1) than during mild (0.13 ± 0.10 at ~960 KJm−2h−1) conditions, suggesting a greater ability to discriminate between sires at increasing stress levels. Conclusions Failure to account for this G × E component putatively contributes to the low h2 commonly reported for survival traits. The higher h2 at increased levels of cold stress could have played an important part in the higher survival of the H-Line progeny, who were better at coping with cold, wet and windy conditions. Implications Larger studies representing a wider environmental trajectory are recommended. This should be very feasible since cold stress can be derived from commonly available weather-station data.
Genetic parameters for racing records in trotters using linear and generalized linear models1
Publisher: Oxford University Press (OUP)
Date: 09-2012
Abstract: Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success.
Genomic evaluations using similarity between haplotypes
Publisher: Wiley
Date: 29-12-2012
DOI: 10.1111/JBG.12020
Abstract: Long-range phasing and haplotype library imputation methodologies are accurate and efficient methods to provide haplotype information that could be used in prediction of breeding value or phenotype. Modelling long haplotypes as independent effects in genomic prediction would be inefficient due to the many effects that need to be estimated and phasing errors, even if relatively low in frequency, exacerbate this problem. One approach to overcome this is to use similarity between haplotypes to model covariance of genomic effects by region or of animal breeding values. We developed a simple method to do this and tested impact on genomic prediction by simulation. Results show that the diagonal and off-diagonal elements of a genomic relationship matrix constructed using the haplotype similarity method had higher correlations with the true relationship between pairs of in iduals than genomic relationship matrices built using unphased genotypes or assumed unrelated haplotypes. However, the prediction accuracy of such haplotype-based prediction methods was not higher than those based on unphased genotype information.
Genetic correlations between wool traits and carcass traits in Merino sheep
Publisher: Oxford University Press (OUP)
Date: 2017
DOI: 10.2527/JAS2017.1385
Genetic parameters for faecal worm egg count at different ages in Australian sheep under natural challenge
Publisher: CSIRO Publishing
Date: 2019
DOI: 10.1071/AN17833
Abstract: The data used in the present study consisted of 24535 worm egg count records on sheep observed from 63 to 560 days of age under conditions of the natural challenge of trichostrongylid species. Records were extracted from the Information Nucleus Flock database of the Australia Sheep Cooperative Research Centre program from 2007 to 2011. Records were observed at various ages and sub ided into weaning (W, ~3 months), post-weaning (P, ~4 months), yearling (Y, ~12 months) and hogget (H, ~18 months) age stages and were used to investigate genetic variation at different age stages in univariate analyses and estimate genetic correlations between age stages in multi-trait analyses. The full data were also analysed by random regression models to study how heritability and genetic correlations varied with age. Heritability estimates from univariate analyses were 0.20 ± 0.05, 0.15 ± 0.02, 0.36 ± 0.09, 0.22 ± 0.06 for W, P, Y and H age stages respectively. A similar trend of heritability over ages was found from random regression analyses, which decreased from 0.16 at 90 days to 0.09 at 120 days, following a steady increase to 0.32 at ~410 days, and then decreased afterwards to 0.24 at 520 days. Strong genetic correlations (& .8) were found between W and P age stages, along with Y and H age stages. Sire by flock interaction effects were significant, and accounted for the reduced estimates of heritability and increased genetic correlations between age stages. The results indicated that a multiple-trait approach is required for genetic evaluation of worm egg count when measurements are at different ages, and the accuracy of evaluations would benefit from recording at least two separate age stages.
Genetic variation within and between subpopulations of the Australian Merino breed
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/AN14560
Abstract: Genetic variation within and between Australian Merino subpopulations was estimated from a large breeding nucleus in which up to 8500 progeny from over 300 sires were recorded at eight sites across Australia. Subpopulations were defined as genetic groups using the Westell–Quaas model in which base animals with unknown pedigree were allocated to groups based on their flock of origin if there were sufficient ‘expressions’ for the flock, or to one of four broad sheep-type groups otherwise (Ultra/Superfine, Fine/Fine-medium, Medium/Strong, or unknown). Linear models including genetic groups and additive genetic breeding values as random effects were used to estimate variance components for 12 traits: yearling greasy and clean fleece weight (ygfw and ycfw), yearling mean and coefficient of variation of fibre diameter (yfd and ydcv), yearling staple length and staple strength (ysl and yss), yearling fibre curvature (ycuv), yearling body wrinkle (ybdwr), post-weaning weight (pwt), muscle (pemd) and fat depth (pfat), and post-weaning worm egg count (pwec). For the majority of traits, the genetic group variance ranged from approximately equal to two times larger than the additive genetic (within group) variance. The exceptions were pfat and ydcv where the genetic group to additive variance ratios were 0.58 and 0.22, respectively, and pwec and yss where there was no variation between genetic groups. Genetic group correlations between traits were generally the same sign as corresponding additive genetic correlations, but were stronger in magnitude (either more positive or more negative). These large differences between genetic groups have long been exploited by Merino ram breeders, to the extent that the animals in the present study represent a significantly admixed population of the founding groups. The relativities observed between genetic group and additive genetic variance components in this study can be used to refine the models used to estimate breeding values for the Australian Merino industry.
Genetic parameters and inbreeding effects for production traits of Thai native chickens
Publisher: Asian Australasian Association of Animal Production Societies
Date: 07-2019
DOI: 10.5713/AJAS.18.0690
The role of pedigree information in combined linkage disequilibrium and linkage mapping of quantitative trait loci in a general complex pedigree
Publisher: Oxford University Press (OUP)
Date: 2005
DOI: 10.1534/GENETICS.104.033233
Abstract: Combined linkage disequilibrium and linkage (LDL) mapping can exploit historical as well as recent and observed recombinations in a recorded pedigree. We investigated the role of pedigree information in LDL mapping and the performance of LDL mapping in general complex pedigrees. We compared using complete and incomplete genotypic data, spanning 5 or 10 generations of known pedigree, and we used bi- or multiallelic markers that were positioned at 1- or 5-cM intervals. Analyses carried out with or without pedigree information were compared. Results were compared with linkage mapping in some of the data sets. Linkage mapping or LDL mapping with sparse marker spacing (∼5 cM) gave a poorer mapping resolution without considering pedigree information compared to that with considering pedigree information. The difference was bigger in a pedigree of more generations. However, LDL mapping with closely linked markers (∼1 cM) gave a much higher mapping resolution regardless of using pedigree information. This study shows that when marker spacing is dense and there is considerable linkage disequilibrium generated from historical recombinations between flanking markers and QTL, the loss of power due to ignoring pedigree information is negligible and mapping resolution is very high.
Genomic Selection in Animal Breeding Programs
Publisher: Humana Press
Date: 2013
DOI: 10.1007/978-1-62703-447-0_26
Abstract: Genomic selection can have a major impact on animal breeding programs, especially where traits that are important in the breeding objective are hard to select for otherwise. Genomic selection provides more accurate estimates for breeding value earlier in the life of breeding animals, giving more selection accuracy and allowing lower generation intervals. From sheep to dairy cattle, the rates of genetic improvement could increase from 20 to 100 % and hard-to-measure traits can be improved more effectively.Reference populations for genomic selection need to be large, with thousands of animals measured for phenotype and genotype. The smaller the effective size of the breeding population, the larger the DNA segments they potentially share and the more accurate genomic prediction will be. The relative contribution of information from relatives in the reference population will be larger if the baseline accuracy is low, but such information is limited to closely related in iduals and does not last over generations.
Modelling genetic covariance structure across ages of mean fibre diameter in sheep using multivariate and random regression analysis
Publisher: CSIRO Publishing
Date: 2012
DOI: 10.1071/AN12139
Abstract: Mean fibre diameter measurements from yearling to 5-year-old Australian fine- and medium-wool Merino sheep were analysed using several multivariate models that varied in covariance structure. A pre-structured multivariate model was found to be the most parsimonious model in comparison with the other models fitted such as banded, autoregressive and random regression. In the preferred model, the ages of mean fibre diameter for fine-wool data were genetically partitioned into yearling, 2 years, 3 years and later ages and for medium-wool data into hogget, 2 years and later ages. The estimates of genetic correlations between mean fibre diameter measured at different ages for medium-wool sheep were higher (0.89–1.00) than those for fine-wool Merino (0.75–1.00).
Reproductive performance in the Sheep CRC Information Nucleus using artificial insemination across different sheep-production environments in southern Australia
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/AN11323
Abstract: The present paper covers reproductive performance in an artificial-insemination (AI) program of the Sheep CRC Information Nucleus with 24 699 lambs born at eight locations in southern Australia across five lambings between 2007 and 2011. Results from AI with frozen semen compared well with industry standards for natural mating. Conception rates averaged 72%, and 1.45 lambs were born per ewe pregnant for Merino ewes and 1.67 for crossbreds. Lamb deaths averaged 21% for Merino ewes and 15% for crossbreds and 19%, 22% and 20% for lambs from ewes that were mated to terminal, Merino and maternal sire types, respectively. Net reproductive rates were 82% for Merino ewes and 102% for crossbreds. From 3198 necropsies across 4 years, dystocia and starvation-mismothering accounted for 72% of lamb deaths within 5 days of lambing. Major risk factors for lamb mortality were birth type (single, twin or higher order), birthweight and dam breed. Losses were higher for twin and triplet lambs than for singles and there was greater mortality at relatively lighter and heavier birthweights. We conclude that reproductive rate in this AI program compared favourably with natural mating. Lamb birthweight for optimum survival was in the 4–8-kg range. Crossbred ewes had greater reproductive efficiency than did Merinos.
Across population genetic parameters for wool, growth, and reproduction traits in Australian Merino sheep. 1. Data structure and non-genetic effects
Publisher: CSIRO Publishing
Date: 2007
DOI: 10.1071/AR06161
Abstract: Accurate estimates of adjustment factors for systematic environmental effects are required for genetic evaluation systems. This study combined data from 7 research resource flocks across Australia to estimate genetic parameters and investigate the significance of various environmental factors for production traits in Australian Merino sheep. The flocks were maintained for several generations and represented contemporary Australian Merino fine, medium, and broad wool bloodlines over the past 30 years. Over 110 000 records were available for analysis for each of the major wool traits, with over 2700 sires and 25 000 dams. Univariate linear mixed animal models were used to analyse 6 wool, 4 growth, and 4 reproduction traits. This first paper outlines the data structure and the non-genetic effects of age of the animal, age of dam, birth-rearing type, sex, flock, bloodline, and year, which were significant with few exceptions for all production traits. Age of dam was not significant for reproduction traits and fleece yield. Generally, wool, growth, and reproduction traits need to be adjusted for age, birth-rearing type, and age of dam before the estimation of breeding values for pragmatic and operational reasons. Adjustment for animal age in wool traits needs to be applied for clean fleece weight (CFW), greasy fleece weight (GFW), and fibre diameter (FD) with inclusion of 2 age groups (2 years old and years old), but for reproduction traits, inclusion of all age groups is more appropriate. For GFW, CFW, and hogget weight (HWT), adjustment for only 2 dam age groups of maiden and mature ewes seems sufficient, whereas for birth (BWT), weaning (WWT), and yearling (YWT) weights, adjustments need to be applied for all dam age groups. Adjustment for birth-rearing type (single-single, multiple-single, multiple-multiple) is appropriate for wool, growth, and reproduction traits. The implications of adjustment for non-genetic effects are discussed.
Across population genetic parameters for wool, growth, and reproduction traits in Australian Merino sheep. 2. Estimates of heritability and variance components
Publisher: CSIRO Publishing
Date: 2007
DOI: 10.1071/AR06162
Abstract: Precise estimates of genetic parameters are required for genetic evaluation systems. This study combined data from 7 research resource flocks across Australia to estimate variance components and genetic parameters for production traits in the Australian Merino sheep. The flocks were maintained for several generations and represented contemporary Australian Merino fine, medium, and broad wool bloodlines over the past 30 years. Over 110 000 records were available for analysis for each of the major wool traits, and 50 000 records for reproduction and growth traits with over 2700 sires and 25 000 dams. A linear mixed animal model was used to analyse 6 wool traits comprising clean fleece weight (CFW), greasy fleece weight (GFW), fibre diameter (FD), yield (YLD), coefficient of variation of fibre diameter (CVFD), and standard deviation of fibre diameter (SDFD), 4 growth traits comprising birth weight (BWT), weaning weight (WWT), yearling weight (YWT), and hogget weight (HWT), and 4 reproduction traits comprising fertility (FER), litter size (LS), lambs born per ewe joined (LB/EJ), and lambs weaned per ewe joined (LW/EJ). The range of direct heritability estimates for the wool traits was 0.42 ± 0.01 for CFW to 0.68 ± 0.01 for FD. For growth traits the range was 0.18 ± 0.01 for BWT to 0.38 ± 0.01 for HWT, and for reproduction traits 0.045 ± 0.01 for FER to 0.074 ± 0.01 for LS. Significant maternal effects were found for wool and growth, but not reproduction traits. There was significant covariance between direct and maternal genetic effects for all wool and growth traits except for YWT. The correlations between direct and maternal effects ranged from –0.60 ± 0.02 for GFW to –0.21 ± 0.10 for SDFD in the wool traits and from –0.21 ± 0.03 for WWT to 0.25 ± 0.08 for HWT in the growth traits. Litter effects were significant for all wool and growth traits and only for LS in reproduction traits. The mating sire was fitted in the models for reproduction traits and this variance component accounted for 21, 17, and 8% of the total phenotypic variation for FER, LB/EJ, and LW/EJ, respectively. The implications of additional significant variance components for the estimation of heritability are discussed.
QTL and gene expression analyses identify genes affecting carcass weight and marbling on BTA14 in Hanwoo (Korean Cattle)
Publisher: Springer Science and Business Media LLC
Date: 30-07-2011
DOI: 10.1007/S00335-011-9331-9
Abstract: Causal mutations affecting quantitative trait variation can be good targets for marker-assisted selection for carcass traits in beef cattle. In this study, linkage and linkage disequilibrium analysis (LDLA) for four carcass traits was undertaken using 19 markers on bovine chromosome 14. The LDLA analysis detected quantitative trait loci (QTL) for carcass weight (CWT) and eye muscle area (EMA) at the same position at around 50 cM and surrounded by the markers FABP4SNP2774C>G and FABP4_μsat3237. The QTL for marbling (MAR) was identified at the midpoint of markers BMS4513 and RM137 in a 3.5-cM marker interval. The most likely position for a second QTL for CWT was found at the midpoint of tenth marker bracket (FABP4SNP2774C>G and FABP4_μsat3237). For this marker bracket, the total number of haplotypes was 34 with a most common frequency of 0.118. Effects of haplotypes on CWT varied from a -5-kg deviation for haplotype 6 to +8 kg for haplotype 23. To determine which genes contribute to the QTL effect, gene expression analysis was performed in muscle for a wide range of phenotypes. The results demonstrate that two genes, LOC781182 (p = 0.002) and TRPS1 (p = 0.006) were upregulated with increasing CWT and EMA, whereas only LOC614744 (p = 0.04) has a significant effect on intramuscular fat (IMF) content. Two genetic markers detected in FABP4 were the most likely QTL position in this QTL study, but FABP4 did not show a significant effect on both traits (CWT and EMA) in gene expression analysis. We conclude that three genes could be potential causal genes affecting carcass traits CWT, EMA, and IMF in Hanwoo.
Attention deficit hyperactivity disorder in Australian adults: prevalence, persistence, conduct problems and disadvantage
Publisher: Public Library of Science (PLoS)
Date: 10-10-2012
The possibilities of estimating relationships between traits with and without micro-genetic environmental sensitivity
Publisher: Wageningen Academic Publishers
Date: 31-12-2023
Economic values for production, fertility and mastitis traits for temperate dairy cattle breeds in tropical Sri Lanka.
Publisher: Wiley
Date: 24-01-2022
DOI: 10.1111/JBG.12667
Abstract: Economic values for annual milk yield (MY, kg), annual fat yield (FY, kg), annual protein yield (PY, kg), age at first calving (AFC, days), number of services per conception (NSC), calving interval (CI, days) and mastitis episodes (MS) were derived for temperate dairy cattle breeds in tropical Sri Lanka using a bio-economic model. Economic values were calculated on a per cow per year basis. Derived economic values in rupees (LKR) for MY, FY and PY were 107, -162 and -15, while for AFC, NSC, CI and MS, economic values were -59, -270, -84 and -8,303. Economic values for FY and PY further decreased with higher feed prices, and a less negative economic value for FY was obtained with increased price for fat. Negative economic values for FY and PY show that genetic improvement for these traits is not economical due to the high feed costs and/or the insufficient payment for fat and protein. Therefore, revision of milk fat and protein payments is recommended. Furthermore, the breeding objective developed in this study was dominated by milk production and fertility traits. Adaptability and functional traits that are important in a temperate dairy cattle breeding programme in tropical Sri Lanka, such as longevity, feed efficiency, disease resistance and heat tolerance should be recorded to incorporate them in the breeding objective. Continued trait recording of all traits is recommended to ensure dairy cows can be selected more effectively in a tropical environment based on a breeding objective that also includes adaptability and functional traits.
Genomic prediction of reproduction traits for Merino sheep
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.
Valuing DNA tested bulls for commercial beef production
Publisher: CSIRO Publishing
Date: 2004
DOI: 10.1071/AR03268
Abstract: This paper quantifies the benefits of using a sire genotyped for a single recessive gene in a commercial beef herd. A modified gene-flow method was used to account for changing allele frequency over time. The benefits to a commercial breeder of using a genotyped sire were highest when initial allele frequency was moderate and when the sire was used in a self-replacing herd that had increased allele frequency over time. An ex le of the thyroglobulin gene affecting marbling in beef cattle was used. The value to a self-replacing herd of a sire homozygous for the favourable allele of the thyroglobulin gene was shown to be up to $338 more than of an ungenotyped sire, in a population where the initial gene frequency was 0.3 and the genotype accounted for 0.5 standard deviations of phenotypic variation.
Investigation of methods for inclusion of systematic environmental effects in weaning and post-weaning weights for meat sheep in large-scale genetic evaluation
Publisher: CSIRO Publishing
Date: 15-07-2022
DOI: 10.1071/AN21300
Abstract: Context Genetic evaluation of Australian sheep is conducted for millions of animals for more than 100 traits. Currently, the Australian sheep genetic-analysis software (OVIS) applies a pre-adjustment of phenotype for fixed effects rather than fitting all fixed and random effects jointly in a linear mixed model to estimate breeding values. However, the current correction factors might be outdated and potential interactions among fixed effects not accounted for, which could lead to bias in estimated breeding values (EBVs). Aims This study aimed to assess whether correction factors used in OVIS for early bodyweights recorded in meat sheep breeds are appropriate, so as to explore whether the pre-adjustment method is still suitable and how this compares with a linear mixed model, and to estimate the significance of interactions between fixed effects. Methods Correlations between EBVs from different models and regression slopes from forward prediction were calculated, using weaning-weight data on 365 956 White Suffolk and 370 649 Poll Dorset sheep and post-weaning weight data on 292 538 White Suffolk and 303 864 Poll Dorset sheep. Key results The current OVIS procedure resulted in regression slopes of progeny performance on sire EBVs (averaged over breeds) of 0.37 and 0.35 for weaning and post-weaning weights respectively. Updated pre-adjustment factors improved the regression slopes to 0.40 and 0.38 respectively. Analysis with a linear mixed model produced significantly better regression slopes than did pre-adjustment (0.47 and 0.44 respectively). Further, regression slopes obtained from the linear mixed model with flock by sex by age interaction averaged over breeds were 0.48 for weaning and 0.46 for post-weaning weight respectively, which was a moderate improvement over the current OVIS model. Including a flock by sex by age interaction produced significantly better improvement in Poll Dorset sheep and modest improvement in White Suffolk sheep than did linear mixed model without interaction. Conclusions Using a linear mixed model with a flock by sex by age interaction significantly improves the utility of estimated breeding values for weaning and post-weaning weight in predicting the performance of future progeny. Implications To account for systematic environmental effects, a linear mixed model should be used in OVIS to jointly estimate the fixed effects and EBVs.
Design of a low-density SNP chip for the main Australian sheep breeds and its effect on imputation and genomic prediction accuracy
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%.
The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes
Publisher: Springer Science and Business Media LLC
Date: 09-02-2012
Genotype-environment interaction on human cognitive function conditioned on the status of breastfeeding and maternal smoking around birth
Publisher: Springer Science and Business Media LLC
Date: 20-07-2017
DOI: 10.1038/S41598-017-06214-Y
Abstract: We estimated genotype by environment interaction (G × E) on later cognitive performance and educational attainment across four unique environments, i.e. 1) breastfed without maternal smoking, 2) breastfed with maternal smoking, 3) non-breastfed without maternal smoking and 4) non-breastfed with maternal smoking, using a novel design and statistical approach that was facilitated by the availability of datasets with the genome-wide single nucleotide polymorphisms (SNPs). There was significant G × E for both fluid intelligence (p-value = 1.0E-03) and educational attainment (p-value = 8.3E-05) when comparing genetic effects in the group of in iduals who were breastfed without maternal smoking with those not breastfed without maternal smoking. There was also significant G × E for fluid intelligence (p-value = 3.9E-05) when comparing the group of in iduals who were breastfed with maternal smoking with those not breastfed without maternal smoking. Genome-wide significant SNPs were different between different environmental groups. Genomic prediction accuracies were significantly higher when using the target and discovery s le from the same environmental group than when using those from the different environmental groups. This finding demonstrates G × E has important implications for future studies on the genetic architecture, genome-wide association studies and genomic predictions.
Predicting lactation yields in dairy buffaloes by interpolation and multiple trait prediction
Publisher: Elsevier BV
Date: 02-2013
Marker-based selection within smallholder production systems in developing countries
Publisher: Elsevier BV
Date: 03-2011
Accuracy of estimated genomic breeding values for wool and meat traits in a multi-breed sheep population
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.
Simultaneous fine mapping of multiple closely linked quantitative trait loci using combined linkage disequilibrium and linkage with a general pedigree
Publisher: Oxford University Press (OUP)
Date: 08-2006
DOI: 10.1534/GENETICS.106.057653
Abstract: Within a small region (e.g., & cM), there can be multiple quantitative trait loci (QTL) underlying phenotypes of a trait. Simultaneous fine mapping of closely linked QTL needs an efficient tool to remove confounded shade effects among QTL within such a small region. We propose a variance component method using combined linkage disequilibrium (LD) and linkage information and a reversible jump Markov chain Monte Carlo (MCMC) s ling for model selection. QTL identity-by-descent (IBD) coefficients between in iduals are estimated by a hybrid MCMC combining the random walk and the meiosis Gibbs s ler. These coefficients are used in a mixed linear model and an empirical Bayesian procedure combines residual maximum likelihood (REML) to estimate QTL effects and a reversible jump MCMC that s les the number of QTL and the posterior QTL intensities across the tested region. Note that two MCMC processes are used, i.e., an (internal) MCMC for IBD estimation and an (external) MCMC for model selection. In a simulation study, the use of the multiple-QTL model clearly removes the shade effects between three closely linked QTL located at 1.125, 3.875, and 7.875 cM across the region of 10 cM, using 40 markers at 0.25-cM intervals. It is shown that the use of combined LD and linkage information gives much more useful information compared to using linkage information alone for both single- and multiple-QTL analyses. When using a lower marker density (11 markers at 1-cM intervals), the signal of the second QTL can disappear. Extreme values of past effective size (resulting in extreme levels of LD) decrease the mapping accuracy.
Genetic and phenotypic parameters between yearling, hoggetand adult reproductive performance and age of first oestrus in sheep
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/AN13245
Abstract: The aims of this study were to quantify the relationship between age of first oestrus and yearling reproductive performance in maternal-cross ewes in the Information Nucleus Flock data and to estimate genetic and phenotypic correlations between early and later reproductive performance defined as three ages, yearling, hogget and adult in both Merino and maternal-cross ewes. Information on 2218 yearling records, 2047 hogget records and 910 age of first oestrus records were used in the analysis of maternal-cross ewes, whereas 3286 hogget and 2518 adult reproductive records were used in analysis of Merino ewes. Heritability estimates for yearling reproductive performance in maternal-cross ewes ranged from 0.08 ± 0.09 for ewe fecundity to 0.16 ± 0.05 for number of lambs born and were generally higher than hogget heritability estimates for both maternal-cross and Merino ewes. Age at first oestrus was found to have a low heritability, 0.02 with standard errors of 0.07 and 0.06 with and without weight fitted as a covariate. Genetic correlations between age at first oestrus with and without weight fitted as a covariate and yearling reproductive performance were positive, ranging from 0.07 ± 0.49 with lamb survival to 0.94 ± 0.39 with number of lambs born, which was unexpected. Correlations between traits from the same age class were high in both breed groups. Genetic correlations between yearling and hogget performance in maternal-cross ewes were generally lower than one, ranging from 0.46 ± 0.68 for lamb survival and 0.79 ± 0.50 for fertility suggesting that yearling and later reproductive performance are related but genetically different traits. In Merino ewes, the genetic correlations between hogget and adult performance followed a similar pattern. The small number of records in this study generated high standard errors for estimates, which restricts the conclusions that can be drawn. Overall, this study supports current practice used by ‘Sheep Genetics’, the Australian genetic evaluation system for sheep, in considering yearling reproductive performance as a trait separate from later parities for genetic evaluation purposes.
Strategies and cost-benefit of selecting for a polled sheep nucleus by using DNA testing
Publisher: CSIRO Publishing
Date: 2019
DOI: 10.1071/AN17720
Abstract: The present study assessed the effectiveness and cost–benefit of several genotyping strategies for breeding poll Merino sheep in a closed nucleus with different initial allele frequencies and assuming a single-gene responsible for the horn or poll phenotype. We assumed that selection was based on phenotypes or genotypes for a single gene conferring polledness via a complete-dominance model. Under such a model, a complete fixation of the ‘polled allele’ (P) requires genotyping of the ewe-selection candidates. Testing a higher proportion of female candidates resulted in a faster fixation of the P-allele. Fixation ranged from 1 year of selection with a high starting P-allele frequency of 0.9, to 7 years for low starting P-allele frequencies of 0.3. When premiums of AU$50 or AU$100 were paid for rams with a PP genotype, breeding for PP genotypes was not profitable when the starting P-allele frequency was below 0.7. If the starting allele frequency was above 0.7, net profitability was positive over 10 years when premiums of AU$200 were paid for known PP-genotype rams. While fixing the P-allele, genetic gain for production traits was slowed down in the first 5 years of selection by up to 23% and 3% for initial P allele-frequencies of 0.3 and 0.9 respectively. Lost genetic gain due to fixing the P-allele, which can never be recovered in a closed nucleus, incurred 200–800% higher costs than the DNA testing costs. Rates of genetic gain recovered to pre-P-allele selection level rates of genetic gain once the P-allele was fixed. Testing a maximum of 25% ewe-selection candidates was the least expensive strategy across all starting allele frequencies and premiums. To avoid large losses of genetic gain in a closed nucleus with low P-allele starting frequencies, opening the nucleus should be considered to increase starting P-allele frequencies and also to potentially increase rates of genetic gain to offset the economic loss caused by P-selection.
Preliminary estimates of genetic parameters for carcass and meat quality traits in Australian sheep
Publisher: CSIRO Publishing
Date: 2010
DOI: 10.1071/AN10126
Abstract: Using performance from progeny born in 2007 and 2008 generated by the Information Nucleus program of the Cooperative Research Centre for Sheep Industry Innovation, preliminary estimates of heritability were obtained for a range of novel carcass and meat attributes of lamb relevant to consumers, including carcass characteristics, meat quality and nutritional value of lamb. Phenotypic and genetic correlations of live animal traits with carcass composition and meat quality traits were also estimated. The data were from progeny located at eight sites, sired by 183 rams from Merino, maternal and terminal meat breeds and were representative of the Merino, Border Leicester × Merino, Terminal × Merino and Terminal × Border Leicester-Merino production types of the Australian sheep industry. Data were available from 7176 lambs for weaning weight, 6771 lambs for ultrasound scanning and 4110 lambs for slaughter traits. For the novel meat quality traits, generally moderate to high heritability estimates were obtained for meat quality measures of shear force (0.27 aged 1 day, 0.38 aged 5 days), intramuscular fat (0.39), retail meat colour (range of 0.09 to 0.44) and myoglobin content (0.22). The nutritional value traits of omega-3 fatty acids and iron and zinc contents tended to have low to moderate heritabilities (0.11–0.37), although these were based on fewer records. Fresh meat colour traits were of low to moderate heritability (0.06–0.21) whereas measures of meat pH were of low heritability (~0.10). For the carcass traits, estimates of heritability were moderate to high for the various measures of carcass fat (0.18–0.50), muscle weight (0.22–0.35), meat yield (0.24–0.35), carcass muscle dimensions (0.25–0.34) and bone weight (0.27). Results indicate that for most lamb carcass and meat quality traits there is sufficient genetic variation for selection to alter successfully these characteristics. Additionally, most genetic correlations of live animal assessments of bodyweight, muscle and subcutaneous fat with the carcass and meat quality traits were favourable. Appropriate definition of breeding objectives and design of selection indexes should be able to account for the small unfavourable relationships that exist and achieve the desired outcomes from breeding programs.
Genetic correlations among and between wool, growth and reproduction traits in Merino sheep
Publisher: Wiley
Date: 04-2007
DOI: 10.1111/J.1439-0388.2007.00641.X
Abstract: Data from seven research resource flocks across Australia were combined to provide accurate estimates of genetic correlations among production traits in Merino sheep. The flocks represented contemporary Australian Merino fine, medium and broad wool strains over the past 30 years. Over 110,000 records were available for analysis for each of the major wool traits, and 50,000 records for reproduction and growth traits with over 2700 sires and 25,000 dams. In idual models developed from the single trait analyses were extended to the various combinations of two-trait models to obtain genetic correlations among six wool traits [clean fleece weight (CFW), greasy fleece weight, fibre diameter (FD), yield, coefficient of variation of fibre diameter and standard deviation of fibre diameter], four growth traits [birth weight, weaning weight, yearling weight (YWT), and hogget weight] and four reproduction traits [fertility, litter size, lambs born per ewe joined, lambs weaned per ewe joined (LW/EJ)]. This study has provided for the first time a comprehensive matrix of genetic correlations among these 14 wool, growth and reproduction traits. The large size of the data set has also provided estimates with very low standard errors. A moderate positive genetic correlation was observed between CFW and FD (0.29 +/- 0.02). YWT was positively correlated with CFW (0.23 +/- 0.04), FD (0.17 +/- 0.04) and LWEJ (0.58 +/- 0.06), while LW/EJ was negatively correlated with CFW (-0.26 +/- 0.05) and positively correlated with FD (0.06 +/- 0.04) and LS (0.68 +/- 0.04). These genetic correlations, together with the estimates of heritability and other parameters provide the basis for more accurate prediction of outcomes in complex sheep-breeding programmes designed to improve several traits.
Genomic prediction based on selected variants from imputed whole-genome sequence data in Australian sheep populations
Publisher: Springer Science and Business Media LLC
Date: 12-2019
DOI: 10.1186/S12711-019-0514-2
Abstract: Whole-genome sequence (WGS) data could contain information on genetic variants at or in high linkage disequilibrium with causative mutations that underlie the genetic variation of polygenic traits. Thus far, genomic prediction accuracy has shown limited increase when using such information in dairy cattle studies, in which one or few breeds with limited ersity predominate. The objective of our study was to evaluate the accuracy of genomic prediction in a multi-breed Australian sheep population of relatively less related target in iduals, when using information on imputed WGS genotypes. Between 9626 and 26,657 animals with phenotypes were available for nine economically important sheep production traits and all had WGS imputed genotypes. About 30% of the data were used to discover predictive single nucleotide polymorphism (SNPs) based on a genome-wide association study (GWAS) and the remaining data were used for training and validation of genomic prediction. Prediction accuracy using selected variants from imputed sequence data was compared to that using a standard array of 50k SNP genotypes, thereby comparing genomic best linear prediction (GBLUP) and Bayesian methods (BayesR/BayesRC). Accuracy of genomic prediction was evaluated in two independent populations that were each lowly related to the training set, one being purebred Merino and the other crossbred Border Leicester x Merino sheep. A substantial improvement in prediction accuracy was observed when selected sequence variants were fitted alongside 50k genotypes as a separate variance component in GBLUP (2GBLUP) or in Bayesian analysis as a separate category of SNPs (BayesRC). From an average accuracy of 0.27 in both validation sets for the 50k array, the average absolute increase in accuracy across traits with 2GBLUP was 0.083 and 0.073 for purebred and crossbred animals, respectively, whereas with BayesRC it was 0.102 and 0.087. The average gain in accuracy was smaller when selected sequence variants were treated in the same category as 50k SNPs. Very little improvement over 50k prediction was observed when using all WGS variants. Accuracy of genomic prediction in erse sheep populations increased substantially by using variants selected from whole-genome sequence data based on an independent multi-breed GWAS, when compared to genomic prediction using standard 50K genotypes.
Using the realized relationship matrix to disentangle confounding factors for the estimation of genetic variance components of complex traits
Publisher: Springer Science and Business Media LLC
Date: 15-06-2010
Genetic parameters for methane emissions in Australian sheep measured in portable accumulation chambers in grazing and controlled environments
Publisher: CSIRO Publishing
Date: 10-03-2022
DOI: 10.1071/AN21270
Abstract: Context Genotype by environment interaction or sire re-ranking between measurements of methane emission in different environments or from using different measurement protocols can affect the efficiency of selection strategies to abate methane emission. Aim This study tested the hypothesis that measurements of methane emission from grazing sheep under field conditions, where the feed intake is unknown, are genetically correlated to measurements in a controlled environment where feed intake is known. Methods Data on emission of methane and carbon dioxide and uptake of oxygen were measured using portable accumulation chambers from 499 animals in a controlled environment in New South Wales and 1382 animals in a grazing environment in Western Australia were analysed. Genetic linkage between both environments was provided by 140 sires with progeny in both environments. Multi-variate animal models were used to estimate genetic parameters for the three gas traits corrected for liveweight. Genetic groups were fitted in the models to account for breed differences. Genetic correlations between the field and controlled environments for the three traits were estimated using bivariate models. Key results Animals in the controlled environment had higher methane emission compared to the animals in the field environment (37.0 ± s.d 9.3 and 35.3 ± s.d 9.4 for two protocols vs 12.9 ± s.d 5.1 and 14.6 ± s.d 4.8 mL/min for lambs and ewes (±s.d) P 0.05) but carbon dioxide emission and oxygen uptake did not significantly differ. The heritability estimates for methane emission, carbon dioxide emission and oxygen uptake were 0.15, 0.06 and 0.11 for the controlled environment and 0.17, 0.27 and 0.35 for the field environment. The repeatability for the traits in the controlled environment ranged from 0.51 to 0.59 and from 0.24 to 0.38 in the field environment. Genetic correlations were high (0.85–0.99) but with high standard errors. Conclusion Methane emission phenotypes measured using portable accumulation chambers in grazing sheep can be used in genetic evaluation to estimate breeding values for genetic improvement of emission related traits. The combined measurement protocol-environment did not lead to re-ranking of sires. Implication These results suggest that both phenotypes could be used in selection for reduced methane emission in grazing sheep. However, this needs to be consolidated using a larger number of animals and sires with larger progeny groups in different environments.
Optimization of Dairy Cattle Breeding Programs with Genotype by Environment Interaction in Kenya
Publisher: MDPI AG
Date: 21-08-2022
DOI: 10.3390/AGRICULTURE12081274
Abstract: Genotype by environment interaction influences the effectiveness of dairy cattle breeding programs in developing countries. This study aimed to investigate the optimization of dairy cattle breeding programs for three different environments within Kenya. Multi-trait selection index theory was applied using deterministic simulation in SelAction software to determine the optimum strategy that would maximize genetic response for dairy cattle under low, medium, and high production systems. Four different breeding strategies were simulated: a single production system breeding program with progeny testing bulls in the high production system environment (HIGH) one joint breeding program with progeny testing bulls in three environments (JOINT) three environment-specific breeding programs each with testing of bulls within each environment (IND) and three environment-specific breeding programs each with testing of bulls within each environment using both phenotypic and genomic information (IND-GS). Breeding strategies were evaluated for the whole industry based on the predicted genetic response weighted by the relative size of each environment. The effect of increasing the size of the nucleus was also evaluated for all four strategies using 500, 1500, 2500, and 3000 cows in the nucleus. Correlated responses in the low and medium production systems when using a HIGH strategy were 18% and 3% lower, respectively, compared to direct responses achieved by progeny testing within each production system. The JOINT strategy with one joint breeding program with bull testing within the three production systems produced the highest response among the strategies using phenotypes only. The IND-GS strategy using phenotypic and genomic information produced extra responses compared to a similar strategy (IND) using phenotypes only, mainly due to a lower generation interval. Going forward, the dairy industry in Kenya would benefit from a breeding strategy involving progeny testing bulls within each production system.
A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation
Publisher: Springer Science and Business Media LLC
Date: 19-06-2012
Is it useful to define residual feed intake as a trait in animal breeding programs?
Publisher: CSIRO Publishing
Date: 2004
DOI: 10.1071/EA02105
Abstract: Residual feed intake is a linear function of feed intake, production and maintenance of liveweight, and as such is an attractive characteristic to use to represent production efficiency. The phenotypic and genetic parameters of residual feed intake can be written as a function of its constituent traits. Moreover, selection indices containing the constituent traits are equivalent with an index that includes residual feed intake. Therefore, definition of the term residual feed intake may be useful to interpret variation in production efficiency, but it does not help in obtaining a better selection response than selection on constituent traits alone. In fact, multiple trait genetic evaluation of constituent traits rather than residual feed intake is likely to be more accurate as this more appropriately accommodates different models for the constituent traits and missing data. For residual feed intake to reflect true biological efficiency in growing animals, it is important that feed intake and liveweight are accurately measured. Accounting for growth and body composition would significantly help in revealing between-animal variation in feed utilisation. Random regression models can be helpful in indicating variation in feed efficiency over the growth trajectory.
The CHRNE 470del20 mutation causing congenital myasthenic syndrome in South African Brahman cattle: Prevalence, origin, and association with performance traits1
Publisher: Oxford University Press (OUP)
Date: 03-2007
DOI: 10.2527/JAS.2006-379
Abstract: Genotyping of the South African, registered, Brahman cattle population for the 470del20 mutation in the CHRNE gene causing congenital myasthenic syndrome (CMS) was carried out in 1,453 animals. Overall prevalence of carriers was 0.97% (0.50 to 1.68%, 95% confidence interval). Carrier prevalence among breeding bulls in 2004 was 1.22% (0.65 to 2.15%, 95% confidence interval), and had not changed significantly since 2000. Using segregation analysis, CMS genotype probabilities were calculated for all 612,219 animals in the pedigree, leading to the identification of 2 founder animals as the most likely original carriers. Pedigree analysis revealed no ancestors common to all known carriers, but rather that the mutation had been introduced at least twice into the South African Brahman population, probably via animals imported from the United States. The effects of CMS genotype probability on adjusted birth, 200-d, 400-d, and 600-d BW, as well as on EBV for birth, 200-d, 400-d, and 600-d BW, and milk, were estimated, accounting for effects of sire. Heterozygosity for the CHRNE 470del20 mutation was associated with a 13.3-kg increase in adjusted 600-d BW (P = 0.03). Positive effects of CMS carrier status on all BW EBV were found, but no effect was found on milk EBV. We conclude that CMS carriers have a BW advantage at 600 d and possibly also at birth, 200 d, and 400 d. This may confer a selective advantage and tend to increase the frequency of the mutation.
Increased genetic gains in sheep, beef and dairy breeding programs from using female reproductive technologies combined with optimal contribution selection and genomic breeding values
Publisher: Springer Science and Business Media LLC
Date: 14-09-2015
The use of foal and studbook traits in the breeding programmes of Finnhorse and Standardbred trotters
Publisher: Wiley
Date: 27-01-2011
DOI: 10.1111/J.1439-0388.2010.00886.X
Abstract: Genetic correlations for body measurements and subjectively scored traits between foals and studbook horses were estimated using bivariate linear mixed models. Observations for nine foal and eleven studbook traits in Finnhorses on 6529 foals and 6596 studbook horses and in Standardbred trotters on 3069 foals and 2112 studbook horses were available from the Finnish horse breeding shows. The number of sires with progeny in both foal and studbook data was 203 in Finnhorse and 145 in Standardbred trotters. Estimates of heritability for body measurements in foals and studbook horses using univariate models were high in both breeds (0.41-0.84). Heritability estimates for subjectively scored traits using univariate models were generally higher for foals (0.08-0.46) than for studbook horses (0.06-0.21) in both breeds. Genetic correlations between foals and studbook horses for body measurements were highly positive ranging from 0.74 to 0.96 in Finnhorses and from 0.79 to 0.99 in Standardbred trotters. Low to highly positive genetic correlations between foals and studbook horses for subjectively scored traits were obtained in Finnhorse trotters, whereas in Standardbred trotters genetic correlations for subjectively scored traits varied from moderately negative to highly positive. Higher estimates of heritability for foal traits and generally high genetic correlations between the foal and studbook traits indicate that an early selection for conformation traits would be efficient in the breeding programmes.
Genetic correlations for foal and studbook traits with racing traits and implications for selection strategies in the Finnhorse and Standardbred trotter
Publisher: Wiley
Date: 04-07-2012
DOI: 10.1111/J.1439-0388.2012.01011.X
Abstract: Genetic correlations for body measurements and conformation and functional traits in foals and studbook horses with racing traits were estimated in the Finnhorse and Standardbred. Genetic response and accuracy were estimated using records of animal, half-sibs and parents in selection scenarios for racing traits, for foal and racing traits, for studbook and racing traits, and using records of animal, half-sibs and parents for foal traits and racing traits of parents. Racing time and earnings were the breeding objective. Low-to-moderate genetic correlations for body measurements and racing traits indicated that selection favours bigger horses at all ages. Being mainly favourable for the breeding objective, genetic correlations for conformation and functional traits with racing traits were highest for the foal traits of type, trot and overall grade and for the studbook traits of character and movements. Genetic correlations for foal and studbook conformation with racing traits were low in the Finnhorse and moderate to high in the Standardbred. In foals, the highest genetic correlations were for trot with racing time (-0.54) and with earnings (0.52) in the Finnhorse, and for overall grade with racing time (-0.54) and with earnings (0.54) in the Standardbred. In studbook horses, genetic correlations were high for character with racing time and earnings in the Finnhorse (-0.68, 0.61) and in the Standardbred (-0.63, 0.70), and for movements with racing time and earnings in the Finnhorse (-0.70, 0.69) and in the Standardbred (-0.90, 0.88). To increase accuracy of conformation and functional traits, foal traits would be more useful in the index with racing traits, as being less preselected than studbook traits. The foal traits (type, trot, overall grade) having moderate heritability and genetic correlations with racing traits would be useful in multi-trait index before a racing career, where the greatest gain is because of a shorter generation interval. It would be feasible to implement for AI stallions.
Genomic Best Linear Unbiased Prediction (gBLUP) for the Estimation of Genomic Breeding Values
Publisher: Humana Press
Date: 2013
DOI: 10.1007/978-1-62703-447-0_13
Abstract: Genomic best linear unbiased prediction (gBLUP) is a method that utilizes genomic relationships to estimate the genetic merit of an in idual. For this purpose, a genomic relationship matrix is used, estimated from DNA marker information. The matrix defines the covariance between in iduals based on observed similarity at the genomic level, rather than on expected similarity based on pedigree, so that more accurate predictions of merit can be made. gBLUP has been used for the prediction of merit in livestock breeding, may also have some applications to the prediction of disease risk, and is also useful in the estimation of variance components and genomic heritabilities.
Genome wide QTL mapping to identify candidate genes for carcass traits in Hanwoo (Korean Cattle)
Publisher: Springer Science and Business Media LLC
Date: 31-01-2012
Genomic prediction of weight and wool traits in a multi-breed sheep population
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/AN13129
Abstract: The objective of this study was to predict the accuracy of genomic prediction for 26 traits, including weight, muscle, fat, and wool quantity and quality traits, in Australian sheep based on a large, multi-breed reference population. The reference population consisted of two research flocks, with the main breeds being Merino, Border Leicester (BL), Poll Dorset (PD), and White Suffolk (WS). The genomic estimated breeding value (GEBV) was based on GBLUP (genomic best linear unbiased prediction), applying a genomic relationship matrix calculated from the 50K Ovine SNP chip marker genotypes. The accuracy of GEBV was evaluated as the Pearson correlation coefficient between GEBV and accurate estimated breeding value based on progeny records in a set of genotyped industry animals. The accuracies of weight traits were relatively low to moderate in PD and WS breeds (0.11–0.27) and moderate to relatively high in BL and Merino (0.25–0.63). The accuracy of muscle and fat traits was moderate to relatively high across all breeds (between 0.21 and 0.55). The accuracy of GEBV of yearling and adult wool traits in Merino was, on average, high (0.33–0.75). The results showed the accuracy of genomic prediction depends on trait heritability and the effective size of the reference population, whereas the observed GEBV accuracies were more related to the breed proportions in the multi-breed reference population. No extra gain in within-breed GEBV accuracy was observed based on across breed information. More investigations are required to determine the precise effect of across-breed information on within-breed genomic prediction.
Building on Falconer's work on environmental sensitivity and scale
Publisher: Wageningen Academic Publishers
Date: 31-12-2022
Genetic correlations between ewe reproduction and carcass and meat quality traits in Merino sheep
Publisher: Wiley
Date: 12-2008
DOI: 10.1111/J.1439-0388.2008.00745.X
Abstract: Genetic correlations between reproduction traits in ewes and carcass and meat quality traits in Merino rams were obtained using restricted maximum likelihood procedures. The carcass data were from 5870 Merino rams slaughtered at approximately 18 months of age that were the progeny of 543 sires from three research resource flocks over 7 years. The carcass traits included ultrasound scan fat and eye muscle depth (EMDUS) measured on live animals, dressing percentage and carcass tissue depth (at the GR site FATGR and C site FATC), eye muscle depth, width and area and the meat quality indicator traits of muscle final pH and colour (L*, a*, b*). The reproduction data consisted of 13 464 ewe joining records for number of lambs born and weaned and 9015 records for LS. The genetic correlations between reproduction and fat measurements were negative (range -0.06 +/- 0.12 to -0.37 +/- 0.12), with smaller correlations for live measurement than carcass traits. There were small favourable genetic correlations between reproduction traits and muscle depth in live rams (EMDUS, 0.10 +/- 0.12 to 0.20 +/- 0.12), although those with carcass muscle traits were close to zero. The reproduction traits were independent of meat colour L* (relative brightness), but tended to be favourably correlated with meat colour a* (relative redness, 0.12 +/- 0.17 to 0.19 +/- 0.16). There was a tendency for meat final pH to have small negative favourable genetic correlations with reproduction traits (0.05 +/- 0.11 to -0.17 +/- 0.12). This study indicates that there is no antagonism between reproduction traits and carcass and meat quality indicator traits, with scope for joint improvement of reproduction, carcass and meat quality traits in Merino sheep.
Predicting Unobserved Phenotypes for Complex Traits from Whole-Genome SNP Data
Publisher: Public Library of Science (PLoS)
Date: 24-10-2008
Genomic estimation of additive and dominance effects and impact of accounting for dominance on accuracy of genomic evaluation in sheep populations.
Publisher: Wiley
Date: 17-08-2017
DOI: 10.1111/JBG.12287
Abstract: The objectives of this study were to estimate the additive and dominance variance component of several weight and ultrasound scanned body composition traits in purebred and combined cross-bred sheep populations based on single nucleotide polymorphism (SNP) marker genotypes and then to investigate the effect of fitting additive and dominance effects on accuracy of genomic evaluation. Additive and dominance variance components were estimated in a mixed model equation based on "average information restricted maximum likelihood" using additive and dominance (co)variances between animals calculated from 48,599 SNP marker genotypes. Genomic prediction was based on genomic best linear unbiased prediction (GBLUP), and the accuracy of prediction was assessed based on a random 10-fold cross-validation. Across different weight and scanned body composition traits, dominance variance ranged from 0.0% to 7.3% of the phenotypic variance in the purebred population and from 7.1% to 19.2% in the combined cross-bred population. In the combined cross-bred population, the range of dominance variance decreased to 3.1% and 9.9% after accounting for heterosis effects. Accounting for dominance effects significantly improved the likelihood of the fitting model in the combined cross-bred population. This study showed a substantial dominance genetic variance for weight and ultrasound scanned body composition traits particularly in cross-bred population however, improvement in the accuracy of genomic breeding values was small and statistically not significant. Dominance variance estimates in combined cross-bred population could be overestimated if heterosis is not fitted in the model.
Optimal utilization of non-additive quantitative trait locus in animal breeding programs
Publisher: Wiley
Date: 10-2008
DOI: 10.1111/J.1439-0388.2008.00741.X
Abstract: Optimal selection on a single identified quantitative trait locus (QTL) with four modes of inheritance: normal autosomal, sex-limited, imprinting and X-linked, was evaluated in four breeding structures: single line selection (SLS), two-way crossing (2WC), three-way crossing (3WC) and reciprocal crossing (RC) by comparing extra benefit from mate selection over index selection to demonstrate effectiveness of mate selection in exploiting non-additive QTL. The results showed that the superiority varied at different QTL inheritance modes, initial favourable allele frequencies and breeding structures. The superiority tended to decrease with the increase of the favourable allele frequency except for over-dominant QTL and imprinted QTL in all breeding structures. Less superiority (below 9%) was observed for a recessive and a fully dominant QTL than for an over-dominant QTL (up to 27.11%). Normal autosomal and sex-linked QTL led to a similar trend of superiority from mate selection but the magnitude of the superiority with the latter was slightly higher than with the former for most combinations of the parameters. A high superiority (6.41-41.54%) was observed from mate selection over index selection for an imprinted QTL. A maternally imprinted QTL tended to lead to higher superiority from mate selection than a paternally imprinted QTL. X-linked QTL led to less superiority from mate selection than the other modes of QTL. A larger superiority from mate selection was observed for a recessive and a fully dominant QTL in structures 3WC and 2WC than structures RC and SLS. The superiority from autosomal QTL and X-linked QTL was lower in the structure RC than in other structures examined.
Estimates of genetic and phenotypic parameters for production, haematological and gastrointestinal nematode-associated traits in Australian Angora goats
Publisher: CSIRO Publishing
Date: 2010
DOI: 10.1071/AN09035
Abstract: Genetic parameters for liveweight (LWT), greasy fleece weight (GFW), mean fibre diameter (MFD), standard deviation of MFD (MFD-s.d.), mean fibre curvature (CURVE) percentage of medullated (%MED) and kemp (%KEMP) fibres, faecal worm egg count (WEC), packed cell volume (PCV), mean corpuscular volume (MCV) mean corpuscular haemoglobin content (MCHC), circulating anti-nematode IgG (IgG) and counts of circulating eosinophils (EOS), lymphocytes (LYM), neutrophils (NEU), basophils (BASO) and monocytes (MONO) up to 18 months of age were estimated in Australian Angora goats (608 animals, 14 sires 3 years of birth). Measurements were made during a period of natural parasite challenge up to 5 months of age, or following artificial challenge with 10 000 infective larvae of Trichostrongylus colubriformis at 5.25 months of age. Year of birth had a significant impact on production and parasite-associated traits at all ages studied. Sex had a marked effect on production and erythrocyte traits. Birth type had no effect on any traits in animals older than 6 months. Maternal effects were not significant except for LWT at 3, 5 and 6 months and for IgG at 3 months. Most production traits were highly (LWT, GFW, MFD, %MED) or moderately (CURVE, MFD-s.d.) heritable (range 0.17–0.59) with only %KEMP having a low heritability (0.02–0.14). The heritability estimates (±s.e.) for CURVE are novel for goats and ranged from 0.18 ± 0.09 at first shearing to 0.44 ± 0.14 at third shearing. Heritability estimates were low for WEC (0.02–0.16) and for specific IgG during natural infection (0.14–0.15) but higher for IgG following artificial challenge with T. colubriformis (0.42 ± 0.13). Of the haematological variables NEU and all red cell traits were highly heritable (0.45–0.71), LYM and MONO were moderately to highly heritable (0.31–0.55), and EOS was weakly to moderately heritable (0.06–0.28). Strong phenotypic correlations existed between production traits. MFD was positively correlated with GFW and negatively correlated with CURVE, indicating that finer fibres have a higher crimp or wave count. WEC had consistent negative phenotypic correlations with PCV, LYM and EOS, and positive correlations with NEU. Correlations with IgG were positive up to 5 months and negative thereafter. Phenotypic correlations between WEC and LWT as well as with GFW and MFD were negative. Heritability estimates for production traits were generally consistent with other studies. Haematological and fibre curvature findings are completely novel for Angora goats. Estimates of heritability for WEC fell in mid range of published findings for other goat breeds, and these results suggest that there is some scope for breeding for worm resistance in Angoras but the response is likely to be slow.
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