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  1. Vol. 51 No. 6, p. 2597-2606
     
    Received: May 5, 2011
    Published: Nov, 2011


    * Corresponding author(s): mes12@cornell.edu
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doi:10.2135/cropsci2011.05.0253

Genomic Selection Accuracy for Grain Quality Traits in Biparental Wheat Populations

  1. Elliot L. Heffnera,
  2. Jean-Luc Janninkab,
  3. Hiroyoshi Iwatac,
  4. Edward Souzad and
  5. Mark E. Sorrells *a
  1. a Cornell Univ., Dep. of Plant Breeding and Genetics, 240 Emerson Hall, Ithaca, NY 14853
    b USDA-ARS, R.W. Holley Center for Agriculture and Health, Cornell Univ., Ithaca, NY 14853
    c The Univ. of Tokyo, Graduate School of Agricultural and Life Sciences, Dep. of Agricultural and Environmental Biology, Bunkyo, Tokyo 113-8657, Japan
    d USDA-ARS Soft Wheat Quality Lab., Ohio Agricultural Research and Extension Center (OARDC), 1680 Madison Ave., Wooster OH 44691

Abstract

Genomic selection (GS) is a promising tool for plant and animal breeding that uses genome-wide molecular marker data to capture small and large effect quantitative trait loci and predict the genetic value of selection candidates. Genomic selection has been shown previously to have higher prediction accuracies than conventional marker-assisted selection (MAS) for quantitative traits. In this study, we compared phenotypic and marker-based prediction accuracy of genetic value for nine different grain quality traits within two biparental soft winter wheat (Triticum aestivum L.) populations. We used a cross-validation approach that trained and validated prediction accuracy across years to evaluate effects of model training population size, training population replication, and marker density. Results showed that prediction accuracy was significantly greater using GS versus MAS for all traits studied and that accuracy for GS reached a plateau at low marker densities (128–256).The average ratio of GS accuracy to phenotypic selection accuracy was 0.66, 0.54, and 0.42 for training population sizes of 96, 48, and 24, respectively. These results provide further empirical evidence that GS could produce greater genetic gain per unit time and cost than both phenotypic selection and conventional MAS in plant breeding with use of year-round nurseries and inexpensive, high-throughput genotyping technology.

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Copyright © 2011. Copyright © by the Crop Science Society of America, Inc.