SSR-based association mapping of fiber quality in upland cotton using an eight-way MAGIC population
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The quality of fiber is significant in the upland cotton industry. As complex quantitative traits, fiber quality traits are worth studying at a genetic level. To investigate the genetic architecture of fiber quality traits, we conducted an association analysis using a multi-parent advanced generation inter-cross (MAGIC) population developed from eight parents and comprised of 960 lines. The reliable phenotypic data for six major fiber traits of the MAGIC population were collected from five environments in three locations. Phenotypic analysis showed that the MAGIC lines have a wider variation amplitude and coefficient than the founders. A total of 284 polymorphic SSR markers among eight parents screened from a high-density genetic map were used to genotype the MAGIC population. The MAGIC population showed abundant genetic variation and fast linkage disequilibrium (LD) decay (0.76 cM, r2 > 0.1), which revealed the advantages of high efficiency and power in QTL exploration. Association mapping via a mixed linear model identified 52 significant loci associated with six fiber quality traits; 14 of them were mapped in reported QTL regions with fiber-related or other agronomic traits. Nine markers demonstrated the pleiotropism that controls more than two fiber traits. Furthermore, two SSR markers, BNL1231 and BNL3452, were authenticated as hotspots that were mapped with multi-traits. In addition, we provided candidate regions and screened six candidate genes for identified loci according to the LD decay distance. Our results provide valuable QTL for further genetic mapping and will facilitate marker-based breeding for fiber quality in cotton.
KeywordsCotton MAGIC population Fiber quality SSR Association mapping
We would like to thank Dingguo Li and Xiaofang Li for developing the MAGIC population as well as thank Wu Li, Chao Shen, Tianwang Wen, Bin Gao, De Zhu, and Muhammad Mahmood Ahmed for their assistance with collection of trait data. This research was supported by the National Natural Science Foundation of China (Grant No. 31371674) and the Special Fund for Agro-scientific Research in the Public Interest (Grant No. 201303008).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflicts of interest.
The authors declare that this study complies with the current laws of the country in which the experiments were performed. This article does not contain any studies with human participants or animals performed by any of the authors.
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