Association Analysis of Historical Bread Wheat Germplasm Using Additive Genetic Covariance of Relatives and Population Structure

Abstract

Linkage disequilibrium can be used for identifying associations between traits of interest and genetic markers. This study used mapped diversity array technology (DArT) markers to find associations with resistance to stem rust, leaf rust, yellow rust, and powdery mildew, plus grain yield in five historical wheat international multienvironment trials from the International Maize and Wheat Improvement Center (CIMMYT). Two linear mixed models were used to assess marker-trait associations incorporating information on population structure and covariance between relatives. An integrated map containing 813 DArT markers and 831 other markers was constructed. Several linkage disequilibrium clusters bearing multiple host plant resistance genes were found. Most of the associated markers were found in genomic regions where previous reports had found genes or quantitative trait loci (QTL) influencing the same traits, providing an independent validation of this approach. In addition, many new chromosome regions for disease resistance and grain yield were identified in the wheat genome. Phenotyping across up to 60 environments and years allowed modeling of genotype 3 environment interaction, thereby making possible the identification of markers contributing to both additive and additive 3 additive interaction effects of traits.A useful new tool for crop genetic improvement is the identification of polymorphic markers associated with phenotypic variation for important traits by means of linkage disequilibrium (LD) between loci ( Thornsberry et al. 2001;Flint-Garcia et al. 2003). A major advantage of this approach over conventional linkage mapping is that it does not require the timeconsuming and expensive generation of specific genetic populations. LD is determined by the physical distance of the loci across chromosomes and has proven useful for dissecting complex traits because it offers fine-scale mapping due to the inclusion of historical recombination (Lynch and Walsh 1998). However, false positive correlation between markers and traits can arise in the absence of physical proximity due to population structure caused by admixture, mating system, and genetic drift or by artificial or natural selection during evolution, domestication, or plant improvement ( Jannink and Walsh 2002). False associations can also be caused by alleles occurring at very low frequencies in the initial population (Breseghello and Sorrells 2006a,b). These factors create LD between loci that are not physically linked and cause a high rate of false positives when relating polymorphic markers to phenotypic trait variation. Thus, separating LD due to physical linkage from LD due to population structure is a critical prerequisite in association analyses.Population structure can be quantified using Bayesian analysis, which has been effective for assigning individuals to subpopulations (Q matrix) using unlinked markers (Pritchard et al. 2000). Other multivariate statistical analyses such as classification (clustering) and ordination (scaling) can al...

Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers

“…The results obtained here with W-GY are consistent with those reported by Crossa et al (2007) and indicate that markers such as wPt.6047, wPt.3393, wPt3462, and wPt.3904 (located in chromosome 3B, the long arm of chromosome 7A, chromosome 1A, and the short arm of chromosome 1A, respectively) are indeed associated with GY in wheat.…”

Array-based high-throughput DNA markers for crop improvement

“…Constructed a framework linkage map of 93 DH lines using DArT, AFLP and SSR markers. Inferred origin of DArT markers from gene-rich regions Semagn et al (2006) Used 41000 DArT markers and developed a linkage map with 90 SSR and 543 DArT (278 bread wheat-derived probes and 265 durum wheat probes) markers using 176 RILs Wenzl et al (2007b) 242 DArT markers were used to study association with resistance against stem rust, leaf rust, yellow rust, powdery mildew, yield and yield-contributing traits Crossa et al (2007) Studied genetic diversity of UK, US and Australian wheat varieties using DArT markers White et al (2008) Cassava 734 Tested three complexity reduction methods to select the two that generated largest frequency of polymorphic clones (PstI/TaqI: 14.6%, PstI/BstNI: 17.2%) to produce large genotyping arrays. Detected B1000 polymorphic clones on two arrays; PstI/TaqI array was validated using 38 accessions …”

Bayesian QTL mapping for multiple families derived from crossing a set of inbred lines to a reference line

“…In some crop species such as maize, rice and wheat, germplasm collections that include accessions consisting of traditional landraces, modern cultivars and wild species have recently been established (Flint-Garcia et al, 2005;Kojima et al, 2005;Crossa et al, 2007), and used for evaluation of the genetic diversity present in a species. Such collections are also useful as stocks of genes for breeding programs.…”