PREDICTION OF PHENOTYPE FOR MULTIPLE TRAITS FROM MULTI-OMIC DATA
Grant number: DP200100499 | Funding period: 2020 - 2023
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 ..View full description
Related publications (1)
Genome-wide fine-mapping identifies pleiotropic and functional variants that predict many traits across global cattle populations
Ruidong Xiang, Iona M MacLeod, Hans D Daetwyler, Gerben de Jong, Erin O'Connor, Chris Schrooten, Amanda J Chamberlain, Michael E Goddard
The difficulty in finding causative mutations has hampered their use in genomic prediction. Here, we present a methodology to fine..