Association Mapping of Kernel Size and Milling Quality in Wheat (<i>Triticum aestivum</i> L.) Cultivars

TLDR

Association mapping uses linkage disequilibrium to detect gene effects and complements QTL analysis for developing molecular breeding tools. The study applied association mapping to 95 soft winter wheat cultivars, estimating population structure with 36 SSR markers, assessing LD on chromosomes 2D and 5A, and testing 62 SSR loci on 2D, 5A, and 5B for kernel morphology and milling quality using a mixed‑effects model with permutation‑adjusted significance thresholds. The analysis revealed strong LD (<1 cM) on chromosome 2D and ~5 cM in the centromeric region of 5A, identified significant markers for kernel size on all three chromosomes, and demonstrated that association mapping can complement and enhance QTL information for marker‑assisted selection.

Abstract

Association mapping is a method for detection of gene effects based on linkage disequilibrium (LD) that complements QTL analysis in the development of tools for molecular plant breeding. In this study, association mapping was performed on a selected sample of 95 cultivars of soft winter wheat. Population structure was estimated on the basis of 36 unlinked simple-sequence repeat (SSR) markers. The extent of LD was estimated on chromosomes 2D and part of 5A, relative to the LD observed among unlinked markers. Consistent LD on chromosome 2D was <1 cM, whereas in the centromeric region of 5A, LD extended for approximately 5 cM. Association of 62 SSR loci on chromosomes 2D, 5A, and 5B with kernel morphology and milling quality was analyzed through a mixed-effects model, where subpopulation was considered as a random factor and the marker tested was considered as a fixed factor. Permutations were used to adjust the threshold of significance for multiple testing within chromosomes. In agreement with previous QTL analysis, significant markers for kernel size were detected on the three chromosomes tested, and alleles potentially useful for selection were identified. Our results demonstrated that association mapping could complement and enhance previous QTL information for marker-assisted selection.