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Identification of Associated SSR Markers for Yield Component and Fiber Quality Traits Based on Frame Map and Upland Cotton Collections
Authors:Qin Hongde  Chen Min  Yi Xianda  Bie Shu  Zhang Cheng  Zhang Youchang  Lan Jiayang  Meng Yanyan  Yuan Youlu  Jiao Chunhai
Affiliation:1. Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, China.; 2. Key Laboratory of Cotton Biology and Breeding in the Middle Reaches of the Changjiang River (Wuhan), Ministry of Agriculture, Wuhan, P. R. China.; 3. Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyan, China.; 4. Hubei Academy of Agricultural Sciences, Wuhan, China.; USDA-ARS-SRRC, UNITED STATES,
Abstract:Detecting QTLs (quantitative trait loci) that enhance cotton yield and fiber quality traits and accelerate breeding has been the focus of many cotton breeders. In the present study, 359 SSR (simple sequence repeat) markers were used for the association mapping of 241 Upland cotton collections. A total of 333 markers, representing 733 polymorphic loci, were detected. The average linkage disequilibrium (LD) decay distances were 8.58 cM (r2 > 0.1) and 5.76 cM (r2 > 0.2). 241 collections were arranged into two subgroups using STRUCTURE software. Mixed linear modeling (MLM) methods (with population structure (Q) and relative kinship matrix (K)) were applied to analyze four phenotypic datasets obtained from four environments (two different locations and two years). Forty-six markers associated with the number of bolls per plant (NB), boll weight (BW), lint percentage (LP), fiber length (FL), fiber strength (FS) and fiber micornaire value (FM) were repeatedly detected in at least two environments. Of 46 associated markers, 32 were identified as new association markers, and 14 had been previously reported in the literature. Nine association markers were near QTLs (at a distance of less than 1–2 LD decay on the reference map) that had been previously described. These results provide new useful markers for marker-assisted selection in breeding programs and new insights for understanding the genetic basis of Upland cotton yields and fiber quality traits at the whole-genome level.
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