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a USDA-ARS Biosciences Research Lab., 1605 Albrecht Blvd., Fargo, ND 58105
b Dep. of Plant Sciences, Univ. of California, Davis, CA 95616
c Dep. of Plant Breeding and Genetics, Cornell Univ., 240 Emerson Hall, Ithaca, NY 14853
* Corresponding author (chaos{at}fargo.ars.usda.gov).
Genetic diversity and genome-wide linkage disequilibrium (LD) were investigated among 43 U.S. wheat (Triticum aestivum L.) elite cultivars and breeding lines representing seven U.S. wheat market classes using 242 wheat genomic simple sequence repeat (SSR) markers distributed throughout the wheat genome. Genetic diversity among these lines was examined using genetic distance-based and model-based clustering methods, and analysis of molecular variance. Four populations were identified from the model-based analysis, which partitioned each of the spring and winter populations into two subpopulations, corresponding largely to major geographic regions of wheat production in the United States. This suggests that the genetic diversity existing among these U.S. wheat germplasm was influenced more by regional adaptation than by market class, and that the individuals clustered in the same model-based population likely shared related ancestral lines in their breeding history. For this germplasm collection, genome-wide LD estimates were generally less than 1 cM for the genetically linked loci pairs. This may result from the population stratification and small sample size that reduced statistical power. Most of the LD regions observed were between loci less than 10 cM apart. However, the distribution of LD was not uniform based on linkage distance and was independent of marker density. Consequently, LD is likely to vary widely among wheat populations.
Abbreviations: AMOVA, analysis of molecular variance CS, Chinese Spring EST, expressed sequence tag Fst, Wright's fixation index HRS, hard red spring HRW, hard red winter HWS, hard white spring HWW, hard white winter LD, linkage disequilibrium PCR, polymerase chain reaction PIC, polymorphism information content QTL, quantitative trait loci SSR, simple sequence repeat SRW, soft red winter SWS, soft white spring SWW, soft white winter UPGMA, unweighted pair-group method with arithmetic mean.
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