Genomics to rust proof the humble oat. This project aims to reduce the impact of the damaging and currently intractable fungal pathogen crown rust (OCR) in Australian oat production. The expected project outcomes are: new sources of enduring high value resistance to OCR, tools to accelerate the use of these resistances, and locally adapted OCR resistant oat germplasm for use in developing profitable oat varieties. The project will use new approaches to tap very recently released genomic resource ....Genomics to rust proof the humble oat. This project aims to reduce the impact of the damaging and currently intractable fungal pathogen crown rust (OCR) in Australian oat production. The expected project outcomes are: new sources of enduring high value resistance to OCR, tools to accelerate the use of these resistances, and locally adapted OCR resistant oat germplasm for use in developing profitable oat varieties. The project will use new approaches to tap very recently released genomic resources and unique oat/ OCR resources assembled over many years. It will lead to responsible stewardship of broadly effective OCR resistance in grazing/milling/hay oats, increasing grower profitability, reducing reliance on fungicides, and underpinning planned growth in our export oat market. 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