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
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