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 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.
T HE basic objective of association mapping (AM)studies is to detect correlations between genotypes and phenotypes in a sample of individuals on the basis of linkage disequilibrium (LD) (Zondervan and Cardon 2004). In the study of genetics of complex diseases in humans, AM offers the important advantage of sampling unrelated individuals in the population, as compared to other experimental designs that require sampling within families (Risch 2000). In contrast to humans, plants can be manipulated to develop large experimental populations with desirable characteristics for genetic mapping, so in principle use of the association approach might not seem as appealing as it is in humans.However, sampling unrelated genotypes presents a number of advantages for the development of tools for marker-assisted selection in plant breeding ( Jannink et al. 2001). First, the experimental population can be a representative sample of the population to which inference is desired. Examples are a core collection from a gene bank, varieties representing the elite germplasm of a breeding program or inbred lines representing a synthetic outcrossing population. In this way, information derived from the experiments should be readily applicable to crop improvement. Second, AM can be more efficient in the use of resources. A group of unrelated individuals normally presents variation for many phenotypic aspects; thus several traits can be studied in the same population using the same genotypic data. A higher proportion of molecular markers are likely to be polymorphic, providing better genome coverage than any biparental map. Furthermore, if elite lines are used for study, multi-year and multi-location phenotypic data may be available at no additional cost (Ra...