Identification of key contributors to increase phasing accuracy in complex population structures

Abstract

Knowledge of the genetic contribution of individuals is essential to select informative individuals for genotype imputation. Based on the Eigen Value Decomposition (EVD) of a relationship matrix we describe a novel approach to determine the genetic contribution of individuals within populations. The approach was applied and validated in four disparate datasets including simulated population, a highly structured experimental sheep population and two large complex pedigreed populations namely horse and cattle. In the simulated and sheep datasets, we identified all known key contributors within the populations, whilst in the horse and cattle dataset we applied the method to select small reference populations that increased phasing accuracy. Compared to commonly applied strategies to select informative individuals for genotype imputation including the identification of marginal gene contributions (PEDIG) and the optimization of genetic relatedness (REL) the selection of key contributors provided the highest phasing accuracies within the selected reference populations. Therefore, this method provides a valuable complement to common applied tools to select individuals for re-sequencing.

Published in

Annual meeting of the European Association for Animal Production
2016, number: 22, pages: 341-341
Title: Book of Abstracts of the 67th Annual Meeting of the European Federation of Animal Science
Publisher: Wageningen Academic Publishers

Conference

67th Annual Meeting of the European Federation of Animal Science

SLU Authors

• Jonas, Elisabeth

  • Department of Animal Biosciences, Swedish University of Agricultural Sciences
    
  • University of Sydney

UKÄ Subject classification

Genetics and Breeding in Agricultural Sciences

Publication identifier

• ISBN: 978-90-8686-284-9
• eISBN: 978-90-8686-830-8

Permanent link to this page (URI)

https://res.slu.se/id/publ/79529