Open AccessGenome‐Wide Association and Prediction of Grain and Semolina Quality Traits in Durum Wheat Breeding Populations
Author(s) -
Fiedler Jason D.,
Salsman Evan,
Liu Yuan,
Michalak de Jiménez Monika,
Hegstad Justin B.,
Chen Bingcan,
Manthey Frank A.,
Chao Shiaoman,
Xu Steven,
Elias Elias M.,
Li Xuehui
Publication year - 2017
Publication title -
the plant genome
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 41
ISSN - 1940-3372
DOI - 10.3835/plantgenome2017.05.0038
Subject(s) - biology , selection (genetic algorithm) , quantitative trait locus , trait , marker assisted selection , plant breeding , genomic selection , microbiology and biotechnology , breeding program , grain quality , cultivar , grain yield , agronomy , genetic gain , genetic variation , genetics , genotype , gene , single nucleotide polymorphism , machine learning , computer science , programming language
Grain yield and semolina quality traits are essential selection criteria in durum wheat breeding. However, high phenotypic screening costs limit selection to relatively few breeding lines in late generations. This selection paradigm confers relatively low selection efficiency due to the advancement of undesirable lines into expensive yield trials for grain yield and quality trait testing. Marker‐aided selection can enhance selection efficiency, especially for traits that are difficult or costly to phenotype. The aim of this study was to identify major quality trait quantitative trait loci (QTL) for marker‐assisted selection (MAS) and to explore potential application of genomic selection (GS) in a durum wheat breeding program. In this study, genome‐wide association mapping was conducted for five quality traits using 1184 lines from the North Dakota State University (NDSU) durum wheat breeding program. Several QTL associated with test weight, semolina color, and gluten strength were identified. Genomic selection models were developed and forward prediction accuracies of 0.27 to 0.66 were obtained for the five quality traits. Our results show the potential for grain and semolina quality traits to be selected more efficiently through MAS and GS with further refinement. Considerable opportunity exists to extend these techniques to other traits such as grain yield and agronomic characteristics, further improving breeding efficiency in durum cultivar development.