General combining ability model for genomewide selection in a biparental cross

Amy Jacobson, Lian Lian, Shengqiang Zhong, Rex Bernardo

Research output: Contribution to journalArticlepeer-review

66 Scopus citations

Abstract

Genomewide selection within an A/B biparental cross is most advantageous if it could be effectively done before the cross is phenotyped. Our objectives were to determine if a general combining ability (GCA) model is useful for genomewide selection in an A/B cross, and to assess the influence of training population size (NGCA), number of crosses pooled into the training population (N×), linkage disequilibrium (r2), and heritability (h2) on the prediction accuracy with the GCA model. The GCA model involved pooling 4 to 38 maize crosses with A and B as one of the parents into the training population for an A/B cross, whereas the same background (SB) model involved pooling crosses between random inbreds. Across 30 A/B test populations, the mean response to selection (R) with the GCA model was 0.19 Mg ha-1 for testcross grain yield, -6 g kg-1 for moisture, and 0.38 kg hL-1 for test weight. These R values with the GCA model were 68 to 76% of the corresponding R values with phenotypic selection (PS). The R values with the SB model were only 15 to 28% of the R values with PS. Increasing the size of the training population with random crosses from the same heterotic group was less important than including crosses with A and B as one of the parents. Prediction accuracy was most highly correlated with h2r2 √NGCA and h2r2 √N×. Our results indicated that the GCA model is routinely effective for genomewide selection within A/B crosses, before phenotyping the progeny in the cross.

Original languageEnglish (US)
Pages (from-to)895-905
Number of pages11
JournalCrop Science
Volume54
Issue number3
DOIs
StatePublished - Apr 2014

Fingerprint

Dive into the research topics of 'General combining ability model for genomewide selection in a biparental cross'. Together they form a unique fingerprint.

Cite this