Association Analysis For Yield Traits With Molecular Markers In Huang-huai River Valley Winter Wheat Region

Wheat is one of dominant crops and plays an important role in grain production.Huang-Huai river valley winter wheat region is one of the most important regions ofagricultural production in China. With the great efforts of many breeders, the region has bredand popularized a lot of new wheat varieties for a long time. With the rapid development ofthe modern molecular biology, the application of marker-assisted selection not onlymaximizes the rate of improvement in quantitative characters, but provides a more reliableapproach in wheat breeding programs. In this study, the yield and yield-related traits of128wheat varieties/lines from the Huang-Huai River Valley Winter Wheat Region were evaluatedin2years at three locations. And they were genotyped with64SSR,27EST-SSR and47functional markers distributing on the21chromosomes. Based on population structureanalysis, association mapping between the genotyping data with phenotypic data wereperformed to identify some loci and favorable alleles that are responsible to yield traits. Themajor results are as follows:1. A total of64SSR,27EST-SSR and47functional markers produced a total of422alleles among the128accessions. Ninety-one SSR and EST-SSR markers produced315alleles, with2–7alleles on each locus and an average of3.5. Forty-seven functional markersproduced107alleles, with2–5alleles per locus and an average of2.3. The polymorphisminformation content (PIC) of SSR and EST-SSR markers ranged from0.075to0.705, with anaverage of0.392. An average PIC of functional markers was0.241(range of0.059–0.702).The results showed that the genetic diversity was relatively high among the assecions used inthis study. By population structure analysis, the128assecions were clustered into three maingroups, and most of wheat lines are of admixture kinship.2. Marker-trait association was tested through the mixed linear model using the softwareTASSEL2.1. Besides genotyping data and phenotypic data, both Q and K matrices were used in the MLM to correct for both population and family structure. A total of78marker-traitassociations were identified (P≤0.005) with49different markers, and the R2ranged of2.3–18.9%. In which, seventeen loci are associated with plant height, six loci are associatedwith spike length, five loci are associated with fertile spikelet number per spike, fourteen lociare associated with spikelet number per spike, fifteen loci are associated with spike number,five loci are associated with kernel number per spike, thirteen loci are associated withthousand-kernel weight. Of which,38marker-trait associations were associated with the sametrait when analyzed by using the phenotypic values in multiple environments or using theaverage values, and16markers were associated with at least two traits simultaneously.3. On the basis of our results of loci associated with the traits, alleles of loci significantlyassociated with the traits were analyzed further in this study. Some favorable allelesassociated with yield traits in multiple environments were discovered, such as Ax2*-null andUMN19*-A362for reducing plant height, barc21-A220for increasing spike length,gpw2111-A156for increasing fertile spikelet number per spike, swes65-A120for increasingspikelet number per spike, VRN-A1*-A1068for increasing spike number, cfd5-A215forincreasing kernel number per spike, and wmc626-A170for increasing thousand-kernel weight.These results may provide useful information for marker-assisted selection in wheat breedingprograms for yield traits.