Methods to infer dense genomic information from sparsely genotyped populations. Prediction of phenotype based on DNA polymorphisms or sequence has important applications such as prediction of disease risk in human medicine and prediction of genetic value in plant or animal breeding. This project will enhance precision and lower the cost of association studies leading to substantial increase in accuracy of such predictions. This will allow more effective genetic improvement, particularly of diff ....Methods to infer dense genomic information from sparsely genotyped populations. Prediction of phenotype based on DNA polymorphisms or sequence has important applications such as prediction of disease risk in human medicine and prediction of genetic value in plant or animal breeding. This project will enhance precision and lower the cost of association studies leading to substantial increase in accuracy of such predictions. This will allow more effective genetic improvement, particularly of difficult but important traits such as disease resistance, reduced green-house gas emissions and product quality. The same methods can be extended to improve genetic improvement in plants and better prediction of human disease risk. Read moreRead less
Identifying the diversity and evolution of loci associated with adaptation to aridity/heat and salinity in ancient cereal crops. This project will use ancient grains of wheat, barley and rye to find 'lost' genetic diversity at key genes associated with resistance to aridity, salt and disease. This project will make the proteins of key genes, and study their interaction with the environment over time by measuring ions in the grains to reveal the ancient environmental conditions.
Discovery Early Career Researcher Award - Grant ID: DE130100614
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Novel statistical algorithms and methods to quantify and partition pleiotropy between complex traits in populations. A fundamental question in biology is how common genetic effects are shared between traits or groups. For example, is cognition or human behaviour genetically identical across genders or across human population groups? This project will address these questions using multiple independent genome-wide association studies.
Phenotypic profiling from DNA using genetic and epigenetic information. The project intends to quantify how much information about a person can be inferred from a DNA sample. A DNA sample contains epigenomic information additional to the genome sequence. This information can reflect age and the past and present lifestyle of the individual whose sample it is. The project aims to quantify the accuracy of lifestyle and phenotypic prediction from DNA. Existing genome-wide genotype and methylation ar ....Phenotypic profiling from DNA using genetic and epigenetic information. The project intends to quantify how much information about a person can be inferred from a DNA sample. A DNA sample contains epigenomic information additional to the genome sequence. This information can reflect age and the past and present lifestyle of the individual whose sample it is. The project aims to quantify the accuracy of lifestyle and phenotypic prediction from DNA. Existing genome-wide genotype and methylation array data from thousands of blood samples from human subjects will be statistically analysed to develop and validate predictors for chronological age, smoking, caffeine use, pesticide exposure, diet and body mass index. Potential applications of epigenomic prediction are widespread, ranging from forensics to ecology.Read moreRead less
Estimating genotype-environment interaction using genomic information. This project aims to develop statistical methods that can explore genotype–environment interaction at the genomic level using genome-wide single nucleotide polymorphisms or sequence data. It plans to estimate how the effects of genetic variants change with changing environmental conditions and how overall genetic variance changes due to changing effects in specific gene regions. It plans to deliver statistical models and meth ....Estimating genotype-environment interaction using genomic information. This project aims to develop statistical methods that can explore genotype–environment interaction at the genomic level using genome-wide single nucleotide polymorphisms or sequence data. It plans to estimate how the effects of genetic variants change with changing environmental conditions and how overall genetic variance changes due to changing effects in specific gene regions. It plans to deliver statistical models and methods and an efficient algorithm implemented in software, which would broadly benefit the field of complex trait genetics. Methods to estimate genotype–environment interaction effects at the genomic level would help elucidate complex biological systems, including human genetic response to changing environmental factors and the potential adaptation of animals to changing environmental conditions.Read moreRead less
Genome-wide determination of Puccinia psidii s.l. rust resistance in eucalypts. Recently, guava rust was detected in Australia, posing significant risks to native flora, plantations, and timber exports. Scientists from The University of Melbourne and Victorian Department of Primary Industries together with tree breeders, forest growers and forest managers aim to use tree genomics rust resistance breeding to enable management and operational responses and inform policy development.
Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, populat ....Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, population samples or from different populations (e.g. multi-ethnicities or multi-breeds). The expected outcome is to better understand the dynamic architecture of complex traits and develop methods with improved power, precision and accuracy in genomic analyses.Read moreRead less
TraitCapture: Genomic modelling for plant phenomics under environmental stress. This project aims to develop software to integrate new hyper-spectral and 3D growth models of plant phenomics with population genomics to identify heritable developmental traits across varied environments. Genome wide association studies aim to then be used to identify causal genes. Functional structural plant models incorporating genetic variation will be used to predict growth under simulated stress environments. ....TraitCapture: Genomic modelling for plant phenomics under environmental stress. This project aims to develop software to integrate new hyper-spectral and 3D growth models of plant phenomics with population genomics to identify heritable developmental traits across varied environments. Genome wide association studies aim to then be used to identify causal genes. Functional structural plant models incorporating genetic variation will be used to predict growth under simulated stress environments. The research team unites international industry, the Australian Plant Phenomics Facility, and university statistical geneticists. TraitCapture software will use open standards applicable to both controlled and field environments enabling plant breeders to pre-select adaptive traits to increase crop productivity under environmental stress.Read moreRead less
Establishing novel breeding methods for canola improvement. It is imperative to ensure reliable food production in the coming years of climate change and increasing population. Genomics offers the greatest potential to increase food production. This project will apply genomic selection methods to accelerate canola oilseed breeding to ensure continued increases in production of this important food and national export.
Fertility crisis: harnessing the genomic tension behind pollen fertility in sorghum. Hybrid sorghum varieties yield more grain than inbred varieties but the production seed for farmers can be difficult. This project will identify the genes responsible for a trait that makes hybrid seed production possible and this knowledge will help raise sorghum yields in Australian and in some of the world’s poorest countries.