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Article
Accuracy and Training Population Design for Genomic Selection on Quantitative Traits in Elite North American Oats
The Plant Genome
  • Franco G. Asoro, Iowa State University
  • Mark A. Newell, Iowa State University
  • William D. Beavis, Iowa State University
  • Marvin Paul Scott, United States Department of Agriculture
  • Jean-Luc Jannink, United States Department of Agriculture
Document Type
Article
Publication Version
Published Version
Publication Date
7-1-2011
DOI
10.3835/plantgenome2011.02.0007
Abstract

Genomic selection (GS) is a method to estimate the breeding values of individuals by using markers throughout the genome. We evaluated the accuracies of GS using data from five traits on 446 oat (Avena sativa L.) lines genotyped with 1005 Diversity Array Technology (DArT) markers and two GS methods (ridge regression–best linear unbiased prediction [RR-BLUP] and BayesCπ) under various training designs. Our objectives were to (i) determine accuracy under increasing marker density and training population size, (ii) assess accuracies when data is divided over time, and (iii) examine accuracy in the presence of population structure. Accuracy increased as the number of markers and training size become larger. Including older lines in the training population increased or maintained accuracy, indicating that older generations retained information useful for predicting validation populations. The presence of population structure affected accuracy: when training and validation subpopulations were closely related accuracy was greater than when they were distantly related, implying that linkage disequilibrium (LD) relationships changed across subpopulations. Across many scenarios involving large training populations, the accuracy of BayesCπ and RR-BLUP did not differ. This empirical study provided evidence regarding the application of GS to hasten the delivery of cultivars through the use of inexpensive and abundant molecular markers available to the public sector.

Comments

This article is from The Plant Genome 4 (2011): 132, doi: 10.3835/plantgenome2011.02.0007.

Rights
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.
Language
en
File Format
application/pdf
Citation Information
Franco G. Asoro, Mark A. Newell, William D. Beavis, Marvin Paul Scott, et al.. "Accuracy and Training Population Design for Genomic Selection on Quantitative Traits in Elite North American Oats" The Plant Genome Vol. 4 Iss. 2 (2011) p. 132 - 144
Available at: http://works.bepress.com/paul-scott/14/