PREDICTION OF PHENOTYPE FOR MULTIPLE TRAITS FROM MULTI-OMIC DATA

Grant number: DP200100499 | Funding period: 2020 - 2023

Completed

Abstract

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 ..

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Related publications (4)

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A multi-tissue atlas of regulatory variants in cattle.

Shuli Liu, Yahui Gao, Oriol Canela-Xandri, Sheng Wang, Ying Yu, Wentao Cai, Bingjie Li, Ruidong Xiang, Amanda J Chamberlain, Erola Pairo-Castineira, Kenton D'Mellow, Konrad Rawlik, Charley Xia, Yuelin Yao, Pau Navarro, Dominique Rocha, Xiujin Li, Ze Yan, Congjun Li, Benjamin D Rosen

2022-09-01

Characterization of genetic regulatory variants acting on livestock gene expression is essential for interpreting the molecular me..

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Mutant alleles differentially shape fitness and other complex traits in cattle

Ruidong Xiang, Ed J Breen, Sunduimijid Bolormaa, Christy J Vander Jagt, Amanda J Chamberlain, Iona M Macleod, Michael E Goddard

2021-12-02

Mutant alleles (MAs) that have been classically recognised have large effects on phenotype and tend to be deleterious to traits an..

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Bayesian genome-wide analysis of cattle traits using variants with functional and evolutionary significance

Ruidong Xiang, Ed J Breen, Claire P Prowse-Wilkins, Amanda J Chamberlain, Michael E Goddard

2021-07-21

Context: Functional genomics studies have highlighted genomic regions with regulatory and evolutionary significance. Such informat..

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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

2021-02-08

The difficulty in finding causative mutations has hampered their use in genomic prediction. Here, we present a methodology to fine..

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