Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statis ....Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statistical methods provide the opportunity to close this gap. The outcome will be identification of many genomic variants causing variation in complex traits. This will benefit scientific understanding of complex traits and the ability to predict traits for individuals from their genome sequence.Read moreRead less
Early Career Industry Fellowships - Grant ID: IE230100263
Funder
Australian Research Council
Funding Amount
$477,037.00
Summary
Improve genomic testing tools for fertility traits in beef cattle. Fertility is a key driver of productivity and profitability for beef industry; however, a substantial industry challenge is poor fertility and the difficulty and expense of measuring fertility in remote Australia. By integrating multiple omics datasets and fifty thousand fertility phenotypes recorded on beef cattle, the project will identify sequence variation, including structural variants, that underpin genetic variation in cat ....Improve genomic testing tools for fertility traits in beef cattle. Fertility is a key driver of productivity and profitability for beef industry; however, a substantial industry challenge is poor fertility and the difficulty and expense of measuring fertility in remote Australia. By integrating multiple omics datasets and fifty thousand fertility phenotypes recorded on beef cattle, the project will identify sequence variation, including structural variants, that underpin genetic variation in cattle fertility. Our industry partner, which genotypes hundreds of thousands of cattle a year, will produce new genotype arrays and novel low-cost sequencing approaches including these variants, enabling selection that could potentially increase herd reproductive rate by 4%, returning $40M per annum to the farmers.Read moreRead less
A next-generation whole parasite bovine Babesia vaccine. . In Australia, Babesia parasites cause most of the severe and often fatal cases of cattle-tick fever, a globally significant tick-borne disease. It can be prevented by a live-attenuated parasite vaccine which has critical limitations of a 4-day shelf-life and risk of severe disease if administered to adult cattle. This project aims to evaluate in cattle a novel whole parasite Babesia bovis vaccine that cannot cause disease and can be pres ....A next-generation whole parasite bovine Babesia vaccine. . In Australia, Babesia parasites cause most of the severe and often fatal cases of cattle-tick fever, a globally significant tick-borne disease. It can be prevented by a live-attenuated parasite vaccine which has critical limitations of a 4-day shelf-life and risk of severe disease if administered to adult cattle. This project aims to evaluate in cattle a novel whole parasite Babesia bovis vaccine that cannot cause disease and can be preserved as an off-the-shelf product without losing efficacy. The expected outcome is a significantly improved vaccine for a major infectious disease that affects primary food production. As the disease imposes a major economic burden, it will have great benefit for the Australian livestock industry.
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Improving dairy cow fertility: targeting exosome-responsive cell pathways. . This project aims to assist the dairy industry to achieve its goal of increasing the six-week in-calf pregnancy rate in dairy cows by at least 10 per cent within five years via the identification of circulating exosomal biomarkers of improved fertility that will be used to develop superior breeding stock to deliver higher industry productivity. The impact of novel biomarkers will permit the Australian and New Zealand da ....Improving dairy cow fertility: targeting exosome-responsive cell pathways. . This project aims to assist the dairy industry to achieve its goal of increasing the six-week in-calf pregnancy rate in dairy cows by at least 10 per cent within five years via the identification of circulating exosomal biomarkers of improved fertility that will be used to develop superior breeding stock to deliver higher industry productivity. The impact of novel biomarkers will permit the Australian and New Zealand dairy industries to meet their targets and provide economic benefit to the respective industries, whilst ensuring availability of low cost milk to Australian citizens.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