ORCID Profile
0000-0001-8359-5318
Current Organisations
University of Queensland
,
Queensland Department of Agriculture and Fisheries
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Springer Science and Business Media LLC
Date: 09-11-2013
Publisher: Springer Science and Business Media LLC
Date: 06-01-2020
DOI: 10.1007/S00122-019-03526-7
Abstract: Multi-environment models using marker-based kinship information for both additive and dominance effects can accurately predict hybrid performance in different environments. Sorghum is an important hybrid crop that is grown extensively in many subtropical and tropical regions including Northern NSW and Queensland in Australia. The highly varying weather patterns in the Australian summer months mean that sorghum hybrids exhibit a great deal of variation in yield between locations. To ultimately enable prediction of the outcome of crossing parental lines, both additive effects on yield performance and dominance interaction effects need to be characterised. This paper demonstrates that fitting a linear mixed model that includes both types of effects calculated using genetic markers in relationship matrices improves predictions. Genotype by environment interactions was investigated by comparing FA1 (single-factor analytic) and FA2 (two-factor analytic) structures. The G×E causes a change in hybrid rankings between trials with a difference of up to 25% of the hybrids in the top 10% of each trial. The prediction accuracies increased with the addition of the dominance term (over and above that achieved with an additive effect alone) by an average of 15% and a maximum of 60%. The percentage of dominance of the total genetic variance varied between trials with the trials with higher broad-sense heritability having the greater percentage of dominance. The inclusion of dominance in the factor analytic models improves the accuracy of the additive effects. Breeders selecting high yielding parents for crossing need to be aware of effects due to environment and dominance.
Publisher: Wiley
Date: 03-2018
DOI: 10.2135/CROPSCI2017.08.0469
Abstract: Genomic selection can increase the rate of genetic gain in plant breeding programs by shortening the breeding cycle. Gain can also be increased through higher selection intensities, as the size of the population available for selection can be increased by predicting performance of non‐phenotyped, but genotyped, lines. This paper demonstrates the application of genomic prediction in a sorghum [ Sorghum bicolor (L.) Moench] breeding program and compares different genomic prediction models incorporating relationship information derived from molecular markers and pedigree information. In cross‐validation, the models using marker‐based relationships had higher selection accuracy than the selection accuracy for models that used pedigree‐based relationships. It was demonstrated that genotypes that have not been included in the trials could be predicted quite accurately using marker information alone. The accuracy of prediction declined as the genomic relationship of the predicted in idual to the training population declined. We also demonstrate that the accuracy of genomic breeding values from the prediction error variance derived from the mixed model equations is a useful indicator of the accuracy of prediction. This will be useful to plant breeders, as the accuracy of the genomic predictions can be assessed with confidence before phenotypes are available. Four distinct environments were studied and shown to perform very differently with respect to the accuracy of predictions and the composition of estimated breeding values. This paper shows that there is considerable potential for sorghum breeding programs to benefit from the implementation of genomic selection.
Publisher: Wiley
Date: 13-08-2021
DOI: 10.1111/TPJ.15437
Abstract: Variation in grain size, a major determinant of grain yield and quality in cereal crops, is determined by both the plant’s genetic potential and the available assimilate to fill the grain in the absence of stress. This study investigated grain size variation in response to variation in assimilate supply in sorghum using a ersity panel ( n = 837) and a backcross‐nested association mapping population ( n = 1421) across four experiments. To explore the effects of genetic potential and assimilate availability on grain size, the top half of selected panicles was removed at anthesis. Results showed substantial variation in five grain size parameters with high heritability. Artificial reduction in grain number resulted in a general increase in grain weight, with the extent of the increase varying across genotypes. Genome‐wide association studies identified 44 grain size quantitative trait locus (QTL) that were likely to act on assimilate availability and 50 QTL that were likely to act on genetic potential. This finding was further supported by functional enrichment analysis and co‐location analysis with known grain number QTL and candidate genes. RNA interference and overexpression experiments were conducted to validate the function of one of the identified gene, SbDEP1 , showing that SbDEP1 positively regulates grain number and negatively regulates grain size by controlling primary branching in sorghum. Haplotype analysis of SbDEP1 suggested a possible role in racial differentiation. The enhanced understanding of grain size variation in relation to assimilate availability presented in this study will benefit sorghum improvement and have implications for other cereal crops.
Publisher: Springer Science and Business Media LLC
Date: 19-12-2021
DOI: 10.1007/S00122-020-03727-5
Abstract: A large collection of Ethiopian sorghum landraces, characterized by agro-ecology and racial-group, was found to contain high levels of ersity and admixture, with significant SNP associations identified for environmental adaptation. Sorghum [Sorghum bicolor L. (Moench)] is a major staple food crop in Ethiopia, exhibiting extensive genetic ersity with adaptations to erse agroecologies. The environmental and climatic drivers, as well as the genomic basis of adaptation, are poorly understood in Ethiopian sorghum and are critical elements for the development of climate-resilient crops. Exploration of the genome-environment association (GEA) is important for identifying adaptive loci and predicting phenotypic variation. The current study aimed to better understand the GEA of a large collection of Ethiopian sorghum landraces (n = 940), characterized with genome-wide SNP markers, to investigate key traits related to adaptation to temperature, precipitation and altitude. The Ethiopian sorghum landrace collection was found to consist of 12 subpopulations with high levels of admixture (47%), representing all the major racial groups of cultivated sorghum with the exception of kafir. Redundancy analysis indicated that agroecology explained up to 10% of the total SNP variation, and geographical location up to 6%. GEA identified 18 significant SNP markers for environmental variables. These SNPs were found to be significantly enriched (P < 0.05) for a priori QTL for drought and cold adaptation. The findings from this study improve our understanding of the genetic control of adaptive traits in Ethiopian sorghum. Further, the Ethiopian sorghum germplasm collection provides sources of adaptation to harsh environments (cold and/or drought) that could be deployed in breeding programs globally for abiotic stress adaptation.
Publisher: University of Queensland Library
Date: 2021
DOI: 10.14264/06B268C
Publisher: Springer Science and Business Media LLC
Date: 16-09-2023
Publisher: Oxford University Press (OUP)
Date: 13-08-2022
DOI: 10.1093/JXB/ERAC336
Abstract: The stay-green trait is recognized as a key drought adaptation mechanism in cereals worldwide. Stay-green sorghum plants exhibit delayed senescence of leaves and stems, leading to prolonged growth, a reduced risk of lodging, and higher grain yield under end-of-season drought stress. More than 45 quantitative trait loci (QTL) associated with stay-green have been identified, including two major QTL (Stg1 and Stg2). However, the contributing genes that regulate functional stay-green are not known. Here we show that the PIN FORMED family of auxin efflux carrier genes induce some of the causal mechanisms driving the stay-green phenotype in sorghum, with SbPIN4 and SbPIN2 located in Stg1 and Stg2, respectively. We found that nine of 11 sorghum PIN genes aligned with known stay-green QTL. In transgenic studies, we demonstrated that PIN genes located within the Stg1 (SbPIN4), Stg2 (SbPIN2), and Stg3b (SbPIN1) QTL regions acted pleiotropically to modulate canopy development, root architecture, and panicle growth in sorghum, with SbPIN1, SbPIN2, and SbPIN4 differentially expressed in various organs relative to the non-stay-green control. The emergent consequence of such modifications in canopy and root architecture is a stay-green phenotype. Crop simulation modelling shows that the SbPIN2 phenotype can increase grain yield under drought.
Location: Australia
Location: United Kingdom of Great Britain and Northern Ireland
Location: Australia
No related grants have been discovered for Colleen Hunt.