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

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 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...

Rapid linkage disequilibrium decay in the Lr10 gene in wild emmer wheat (Triticum dicoccoides) populations

“…This approach is somewhat similar to the method implemented by Breseghello and Sorrells (2006), even though they have removed only very similar haplotypes and in the current study only distant haplotypes were selected. Taking into account that T. dicoccoides is a selfer, LD decay in Lr10 was very rapid, within 1-2 kb.…”

Association between Grain Size and Shape and Quality Traits, and Path Analysis of Thousand Grain Weight in Iranian Bread Wheat Landraces from Different Geographic Regions

“…However, some components such as TGW are characterized by a higher heritability than grain yield itself (Bezant et al, 1997;Huang et al, 2006;Tsilo et al, 2010;Deng et al, 2011). TGW is positively correlated with agronomic yield (Baril 1992;Fuller, 2007;Maccaferri et al, 2011) and flour yield (Chasten et al, 1995;Breseghello and Sorrells, 2006;Williams et al, 2013). Moreover, the high heritability values (59% to 96%) in most of the cultivars studied so far have proved that this character is phenotypically the most-stable yield component (Giura and Saulescu, 1996;Huang et al, 2006;Sun et al, 2009;Tsilo et al, 2010;Patil et al, 2013).…”

“…While, grain shape is generally estimated by length, width, vertical perimeter, sphericity and horizontal axes proportion (Breseghello and Sorrells, 2007). Many studies have been shown that wheat grain size and shape is positively correlated with TGW and they have affected flour yield, end-use quality and market price (Evers et al, 1990;Breseghello and Sorrells, 2006;Tsilo et al, 2010;Cui et al, 2011;Blanco et al, 2012;Williams et al, 2013;Rasheed et al, 2014). Theoretical models predict that milling yield could be increased by optimizing grain size and shape with large and spherical grains being the optimum grain morphology (Evers et al, 1990).…”

Evaluation of multi-locus models for genome-wide association studies: a case study in sugar beet

“…It has successfully been used to detect quantitative trait loci (QTL) for agronomically important traits in many crop species including maize (for example, Harjes et al, 2008), wheat (for example, Breseghello and Sorrells, 2006;Reif et al, 2011a, b), barley (for example, Wang et al, 2012;Berger et al, 2013) and rice (for example, Huang et al, 2010). Traditional approaches for QTL detection in plants are based on linkage mapping in bi-parental populations.…”