Novel genomic technologies to improve fertility in northern beef cattle. This project aims to develop new genomic technologies to enable accelerated improvement of cow fertility. Increased global demand for beef is driving northern Australian beef enterprises to develop innovative ways to increase productivity. A substantial industry challenge is poor fertility of cows, with weaning rates frequently less than 40%. The expected outcomes of this project are an improvement in weaning rates to enabl ....Novel genomic technologies to improve fertility in northern beef cattle. This project aims to develop new genomic technologies to enable accelerated improvement of cow fertility. Increased global demand for beef is driving northern Australian beef enterprises to develop innovative ways to increase productivity. A substantial industry challenge is poor fertility of cows, with weaning rates frequently less than 40%. The expected outcomes of this project are an improvement in weaning rates to enable accelerated genetic gain for fertility in these enterprises by delivering a low cost array, which assays thousands of DNA variants affecting fertility simultaneously. This should provide significant benefits such as a new genomic prediction method informed by gene expression data from a unique resource of Brahman cattle with exceptionally high fertility, generating significant industry benefits.Read moreRead less
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
Beyond pineal melatonin: sensing the seasons without the eye. The project will identify the causal connection between seasonal breeding in animals and a recently recognised brain biochemical pathway by applying experimental treatments mimicking seasonal environmental changes in a mutant and wild-type nematode worm model. Through experimentation we will identify useful biological targets that might be manipulated to enhance control of seasonal breeding in managed animals. With better control of r ....Beyond pineal melatonin: sensing the seasons without the eye. The project will identify the causal connection between seasonal breeding in animals and a recently recognised brain biochemical pathway by applying experimental treatments mimicking seasonal environmental changes in a mutant and wild-type nematode worm model. Through experimentation we will identify useful biological targets that might be manipulated to enhance control of seasonal breeding in managed animals. With better control of reproductive output in animals, farmers and managers can increase and/or decrease reproductive output as needed in managed species including livestock and vertebrate pests. This will enhance the use of precious land resources and minimize ecological damage from overbreeding.Read moreRead less
Mapping recombination blocks in Brassica. DNA technology provides new ways to study genomes. Understanding how the genome behaves during plant breeding will help design strategies for the breeding and selection of improved crop plants.
Defining the Brassica pan-genome and establishing methods for gene conversion based crop improvement. Gene content varies between individual varieties. The project aims to apply novel genomic tools to identify and characterise the fixed and variable gene content in the important crop canola and use this to understand genome evolution as well as develop tools to accelerate canola breeding. The project team have developed and used a high-resolution genotyping approach to demonstrate that gene conv ....Defining the Brassica pan-genome and establishing methods for gene conversion based crop improvement. Gene content varies between individual varieties. The project aims to apply novel genomic tools to identify and characterise the fixed and variable gene content in the important crop canola and use this to understand genome evolution as well as develop tools to accelerate canola breeding. The project team have developed and used a high-resolution genotyping approach to demonstrate that gene conversions, short recombination events which lead to the non-reciprocal exchange of genomic regions during meiosis, are abundant in crop genomes. The project aims to develop methods and resources to characterise gene conversion in canola and establish a basis for gene conversion based crop improvement.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
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.