Construction of high-density SNP- and SSR-based genetic map and identification of candidate genes for fiber quality and yield traits using an introgressed recombinant inbred line population of Upland cotton

Working group session: 
Breeding and Applied Genomics
Presentation type: 
5 minute Oral and Poster
Authors: 
Furong, Wang
Yu, Chen
Chunyun, Zhang
Jingxia, Zhang
Zhangqiang, Song
Jun, Zhang
Author Affliation: 
Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan 250100, People’s Republic of China
Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan 250100, People’s Republic of China
Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan 250100, People’s Republic of China
Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan 250100, People’s Republic of China
Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan 250100, People’s Republic of China
Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Ministry of Agriculture, Cotton Research Center of Shandong Academy of Agricultural Sciences, Jinan 250100, People’s Republic of China
Abstract: 
Fiber quality and yield are two main improved target traits in cotton breeding. QTL fine mapping and candidate genes identifying for these important agronomic traits would be beneficial to cotton breeding. In this present work, we constructed a high-density genetic map to identify QTLs associated with fiber quality and yield traits using an introgressed recombinant in-bred line (RIL) population consisting of 254 individuals. This map spanned a total distance of 3,426.57cM including 3556 SLAF-based SNP and 199 SSR markers. QTLs mapping were conducted with the phenotypic data collected from 7 environments. A total of 104 QTLs including 67 QTLs for fiber quality and 37 QTLs for yield traits were identified. Some of the QTLs were co-located in 19 QTL-clusters and distributed on 12 chromosomes. Twenty-four of the QTLs were detected in three or more environments and determined as stable QTLs. Further, by combining DNA re-sequence, RNA-seq and qPCR analysis, we identified six candidate genes for stable QTLs, including Gh_A03G1147 (GhPEL5), Gh_D07G1598 (GhCSLC6) and Gh_D13G1921 (GhTBL5) for fiber-length QTLs, Gh_D03G0919 (GhCOBL4), Gh_D09G1659 (GhMYB4) and Gh_D09G1690 (GhMYB85) for lint-percentage QTL. Our results provide comprehensive insight for understanding the genetic base of formation of fiber quality and yield traits and would be helpful for MAS-assisted cotton genetic improvement.