Identification of stable QTLs controlling fiber traits properties in multi-environment using recombinant inbred lines in Upland cotton (Gossypium hirsutum L.)
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Cotton fiber is widely used as the raw materials for the textile industry. With the development in spinning technology, the improvement of cotton fiber quality is becoming more and more important. However, negative correlation between yield and fiber quality is an obstacle for cotton improvement. Molecular marker assisted selection provides a potential methodology to break the negative correlation. The main objective of this research was to construct a genetic linkage map and mapping QTL for fiber quality, further to facilitate marker assisted selection for fiber quality traits in Upland cotton (Gossypium hirsutum L.). A genetic linkage map, consisting of 581 loci and spanning 3714.4 cM of the cotton genome, was constructed using recombinant inbred lines population derived from the cross GX1135 × GX100-2, with an average interval of 6.39 cM between adjacent loci. Fiber quality traits were investigated in recombinant inbred lines population sampled by lines from three environments respectively, and each followed a randomized complete block design with two replications. Twenty quantitative trait loci were detected for four fiber quality traits: eight for fiber length, three for fiber strength, five for fiber elongation, and four for fiber micronaire. Among these QTLs, qFL-chr5-2 and qFL-chr10-1 for fiber length, qFS-chr1-1 for fiber strength, and qFM-chr19-1 for fiber micronaire were detected again, which verified the previous results in F2, F2:3 and F2:4 populations (four environments), therefore these major QTLs were stable and especially useful for marker assisted selection to improve fiber quality in Upland cotton.
KeywordsQTLs Fiber quality traits Recombinant inbred lines Upland cotton (Gossypium hirsutum L.)
We thank Dr. Youlu Yuan (Chinese Academy of Agricultural Sciences) and Dr. Zhengsheng Zhang (Southwestern University) for providing SWU SSR primers. Thanks to Xianhui Yan and Yihua Rong (Xiangyang Academy of Agricultural Sciences, Hubei Province), and Yuhua Li (China Agricultural University) for their contributions on field experiments, sampling and data acquisition. This research was supported by the National Natural Science Foundation of China (31171591), and a grant from the National High Technology Research and Development Program (2011AA10A102) to J HUA.
Conflict of interest
We have no conflict of interests.
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