Journal article

On the use of whole-genome sequence data for across-breed genomic prediction and fine-scale mapping of QTL

Theo Meuwissen, Irene van den Berg, Mike Goddard

GENETICS SELECTION EVOLUTION | BMC | Published : 2021

Abstract

BACKGROUND: Whole-genome sequence (WGS) data are increasingly available on large numbers of individuals in animal and plant breeding and in human genetics through second-generation resequencing technologies, 1000 genomes projects, and large-scale genotype imputation from lower marker densities. Here, we present a computationally fast implementation of a variable selection genomic prediction method, that could handle WGS data on more than 35,000 individuals, test its accuracy for across-breed predictions and assess its quantitative trait locus (QTL) mapping precision. METHODS: The Monte Carlo Markov chain (MCMC) variable selection model (Bayes GC) fits simultaneously a genomic best linear unb..

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University of Melbourne Researchers