Predicting Genomic Selection Accuracy from Hetergeneous Sources

2015

Van Der Werf, Julius H

Clark, Sam A

Lee, Sang Hong

Editor(s): Kim Bunter, Tim Byrne, Hans Daetwyler, Susanne Hermesch, Kathryn Kemper, James Kijas, David Nation, Wayne Pitchford, Suzanne Rowe, Matt Shaffer, Alison van Eenennaam

Conference Publication

en

Publication

Association for the Advancement of Animal Breeding and Genetics (AAABG)

Armidale, Australia

une:19631

We predict genomic selection accuracy from a heterogeneous reference population that contains close relatives, herd- or flock mates and individuals from the wider population, using an established theory. The various sources of information were modeled as different and independent reference populations with different effective sizes. We show that information on close relatives can have a substantial effect on genomic prediction accuracy. We also show the increase of the genomic prediction accuracy to be less reliant on higher marker density or total reference population size when there are more closely related individuals to predict from. Conversely, the value of close relatives is smaller when the total reference population size is larger. Our modelling is useful to assess the value of a population reference versus a breeder's own reference, based on own animals genotyped.

link

Proceedings of the Association for the Advancement of Animal Breeding and Genetics, v.21, p. 161-164

1328-3227

9780646945545

161

164