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Candidate quantitative trait loci and genes for fiber quality in Gossypium hirsutum L. detected using single- and multi-locus association mapping
- Yuan, Yanchao, Zhang, Haijun, Wang, Liyuan, Xing, Huixian, Mao, Lili, Tao, Jincai, Wang, Xianlin, Feng, Wei, Wang, Qingkang, Wang, Haoran, Wei, Ze, Zhang, Guihua, Song, Xian-Liang, Sun, Xue-Zhen
- Industrial crops and products 2019 v.134 pp. 356-369
- Gossypium hirsutum, breeding, chromosome mapping, cottonseed, discriminant analysis, fiber quality, gene expression, genes, genetic variation, genome-wide association study, loci, models, ovules, pleiotropy, quantitative polymerase chain reaction, quantitative trait loci, single nucleotide polymorphism, textile industry
- Upland cotton makes an important contribution to natural fiber production worldwide. Given the necessity to high quality fiber required in the textile industry, the genomic variation of diverse accessions and the loci underpinning fiber quality should be extensively investigated. Here, a panel of 196 upland cottons and 41,815 single-nucleotide polymorphism (SNP) markers were examined for detection of candidate quantitative trait loci (QTL) for five fiber quality traits in six environments using both single- and multi-locus genome-wide association studies (GWAS) models. With discriminant analysis of principal components (DAPC), the accessions were divided into four subpopulations, and among these, 40 SNPs and 38 QTL were significant in at least three environments and at least two models. Reference to the TM-1 genome and related gene expression data, 89 candidate genes preferentially expressed in fiber or ovules were identified. In this study, 23 candidate QTL and 71 candidate genes were also identified in previous studies, and of them, five promising QTL and 13 promising genes may have pleiotropic effects. In addition, nine putative genes were identified with quantitative real-time PCR. Furthermore, 17 common genes between fiber quality traits and cottonseed nutritional traits were identified. All of the SNP markers and promising genes detected in this study could be used in future breeding practices and for putative gene functional studies.