Genomic selection for grain yield and quality traits in durum wheat

Jemanesh K. Haile, Amidou N’Diaye, Fran Clarke, John Clarke, Ron Knox, Jessica Rutkoski, Filippo M. Bassi, Curtis J. Pozniak

Research output: Contribution to journalArticle

Abstract

The prediction accuracies of genomic selection depend on several factors, including the genetic architecture of target traits, the number of traits considered at a given time, and the statistical models. Here, we assessed the potential of single-trait (ST) and multi-trait (MT) genomic prediction models for durum wheat on yield and quality traits using a breeding panel (BP) of 170 varieties and advanced breeding lines, and a doubled-haploid (DH) population of 154 lines. The two populations were genotyped with the Infinium iSelect 90K SNP assay and phenotyped for various traits. Six ST-GS models (RR-BLUP, G-BLUP, BayesA, BayesB, Bayesian LASSO, and RKHS) and three MT prediction approaches (MT-BayesA, MT-Matrix, and MT-SI approaches which use economic selection index as a trait value) were applied for predicting yield, protein content, gluten index, and alveograph measures. The ST prediction accuracies ranged from 0.5 to 0.8 for the various traits and models and revealed comparable prediction accuracies for most of the traits in both populations, except BayesA and BayesB, which better predicted gluten index, tenacity, and strength in the DH population. The MT-GS models were more accurate than the ST-GS models only for grain yield in the BP. Using BP as a training set to predict the DH population resulted in poor predictions. Overall, all the six ST-GS models appear to be applicable for GS of yield and gluten strength traits in durum wheat, but we recommend the simple computational models RR-BLUP or G-BLUP for predicating single trait and MT-SI for predicting yield and protein simultaneously.

Original languageEnglish (US)
Article number75
JournalMolecular Breeding
Volume38
Issue number6
DOIs
StatePublished - Jun 1 2018
Externally publishedYes

Keywords

  • Genomic selection
  • GS models
  • Multi-trait
  • Quality traits
  • Selection index
  • Triticum turgidum L. var. durum

ASJC Scopus subject areas

  • Biotechnology
  • Molecular Biology
  • Agronomy and Crop Science
  • Genetics
  • Plant Science

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  • Cite this

    Haile, J. K., N’Diaye, A., Clarke, F., Clarke, J., Knox, R., Rutkoski, J., Bassi, F. M., & Pozniak, C. J. (2018). Genomic selection for grain yield and quality traits in durum wheat. Molecular Breeding, 38(6), [75]. https://doi.org/10.1007/s11032-018-0818-x