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
The extent, causes and implications of pleiotropy among complex traits. The project seeks to understand how a DNA mutation can affect many characters or traits. Many traits are called complex because they are controlled by a very large number of genes, most of which have small effects. Complex traits include traits important in medicine (such as susceptibility to heart disease) and in agriculture (such as tenderness of meat). Because there are many genes affecting each trait, most genes have sma ....The extent, causes and implications of pleiotropy among complex traits. The project seeks to understand how a DNA mutation can affect many characters or traits. Many traits are called complex because they are controlled by a very large number of genes, most of which have small effects. Complex traits include traits important in medicine (such as susceptibility to heart disease) and in agriculture (such as tenderness of meat). Because there are many genes affecting each trait, most genes have small effects which makes them hard to identify. The fact that a mutation that has a small effect on a complex trait also has a larger effect on a less complex trait may help us to identify the mutation and use it in agriculture or medicine.Read moreRead less
Evolution, selection and estimation of polygenic epistatic networks in quantitative traits. Traits observed in organisms, such as height, are the result of an individual's genes and how they relate to the environment. But genes do not act alone; they work together in complex interactions. This project aims to understand these interactions and their role in animal production and human disease.
Breeding super black soldier flies at scale for sustainable food production. This project aims to address the current challenges impeding the industrial scale-up of Australian Black Soldier Fly (BSF) farming across diverse feed waste substrates by generating critical on-farm knowledge. This project expects to generate fundamental knowledge in commercial BSF breeding designs whilst also developing and testing new animal evaluation technologies (ie, genetic & spectroscopy) through interdisciplinar ....Breeding super black soldier flies at scale for sustainable food production. This project aims to address the current challenges impeding the industrial scale-up of Australian Black Soldier Fly (BSF) farming across diverse feed waste substrates by generating critical on-farm knowledge. This project expects to generate fundamental knowledge in commercial BSF breeding designs whilst also developing and testing new animal evaluation technologies (ie, genetic & spectroscopy) through interdisciplinary approaches that will accelerate industry productivity. Expected outcomes of this project include the long-term growth and competitive advantage of the Australian insect farming industry, as well as promoting the benefits of a circular economy through bioconversion of organic waste into commercially viable products.Read moreRead less
Prediction of phenotype for multiple traits from multi-omic data. This project aims to develop better methods for predicting traits in an individual based on their genome sequence. This method will be tested in agricultural animals and plants and in humans. The prediction formula is derived from a training dataset that has information on the traits and genome sequence of a sample of individuals. The prediction formula can then be applied to predict the trait in individuals where the trait is un ....Prediction of phenotype for multiple traits from multi-omic data. This project aims to develop better methods for predicting traits in an individual based on their genome sequence. This method will be tested in agricultural animals and plants and in humans. The prediction formula is derived from a training dataset that has information on the traits and genome sequence of a sample of individuals. The prediction formula can then be applied to predict the trait in individuals where the trait is unknown. This is useful for selecting the best parents for breeding in agriculture and for predicting the future phenotype of animals, crops and people. The proposed method uses data on very many traits to identify sequence variants that have a function and to predict the traits affected by each variant.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
Whole-genome multivariate reaction norm model for complex traits. This project aims to develop a multivariate whole-genome genotype-covariate correlation and interaction model that can be applied to a wide range of existing genome-wide association study (GWAS) datasets. Genotype-covariate correlation and interaction (GCCI) are fundamental in biology but there is no standard approach to disentangle interaction from correlation in the whole-genome analyses. This project will address the key featur ....Whole-genome multivariate reaction norm model for complex traits. This project aims to develop a multivariate whole-genome genotype-covariate correlation and interaction model that can be applied to a wide range of existing genome-wide association study (GWAS) datasets. Genotype-covariate correlation and interaction (GCCI) are fundamental in biology but there is no standard approach to disentangle interaction from correlation in the whole-genome analyses. This project will address the key feature in biology, which relates to dissecting the complex mechanism of association and interaction. The proposed statistical model implemented in a context of a novel design based on multiple GWAS data sets is a paradigm shifting-tool with applications to multiple industries.Read moreRead less
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
Advanced animal breeding in aquaculture: using genome-wide molecular breeding values for rapid animal improvement in the silver-lipped pearl oyster. The primary impediment to achieving rapid genetic progress in aquaculture is an inability to accurately and rapidly identify high-performance animals for selection as parents in animal breeding programs. This project aims to develop an innovative genomic selection breeding system for the silver-lipped pearl oyster to overcome current limitations ass ....Advanced animal breeding in aquaculture: using genome-wide molecular breeding values for rapid animal improvement in the silver-lipped pearl oyster. The primary impediment to achieving rapid genetic progress in aquaculture is an inability to accurately and rapidly identify high-performance animals for selection as parents in animal breeding programs. This project aims to develop an innovative genomic selection breeding system for the silver-lipped pearl oyster to overcome current limitations associated with traditional animal improvement methods. The use of genomic selection will not only transform the Australian pearl oyster industry, but it will also showcase the potential of genomic selection in aquaculture globally. Furthermore, knowledge gained from this project can also be applied to a variety of other Australian aquaculture species to accelerate the uptake of this technology.Read moreRead less