Unraveling the genetic basis of superior traits in Gossypium barbadense: From phenotype to genotype

被引:0
|
作者
Cai, Yongsheng [1 ]
Qu, Yanying [1 ]
Yang, Long [1 ]
Liu, Jun [2 ]
Huo, Peng [3 ]
Duan, Yajie [1 ]
Guo, Dongcai [1 ]
Zhou, Qiang [1 ]
Li, Ying [1 ]
Chen, Quanjia [1 ]
Zheng, Kai [1 ]
机构
[1] Xinjiang Agr Univ, Coll Agr, Engn Res Ctr Cotton, Minist Educ, Urumqi 830052, Peoples R China
[2] Xinjiang Jinfengyuan Seeds Co Ltd, Aksu 843100, Peoples R China
[3] Dept Agr & Rural Affairs Xinjiang, Urumqi 830000, Peoples R China
基金
中国国家自然科学基金;
关键词
G; barbadense; Genetic map; QTLs; RNA-seq; Candidate gene; Genetic correlation; PROVIDES INSIGHTS; UPLAND COTTON; LINKAGE MAPS; R PACKAGE; GENOME; HIRSUTUM; EVOLUTION; ALIGNMENT; DATABASE;
D O I
10.1016/j.indcrop.2024.118663
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
G. barbadense is renowned for its high-quality fiber and is highly regarded as a natural material in the textile industry. However, research on cotton has mainly focused on G. hirsutum, and progress in sea island cotton has been relatively slow. There was limited understanding of the genetic loci and transcriptional regulatory mechanisms of important traits, and the genetic basis for the development of superior traits remains unclear. In this study, a recombinant inbred line (RIL) population was constructed using two sea island cotton parents from different cotton regions. The phenotypic characteristics of the two parents and the RIL population, as well as the phenotypic correlations, heritability, and genetic models of the RIL population, were comprehensively analyzed. The RIL population was genotyped using whole-genome resequencing technology, and a high-density intraspecific linkage map was constructed, consisting of 5295 bin markers and a total genetic map distance of 2721.79 centimorgans (cM). Phenotypic data collected from five different environments were used to detect 169 quantitative trait loci (QTLs) using the composite interval mapping method. Among these QTLs, 30 were related to agronomic traits, 61 were related to yield traits, and 78 were related to fiber quality traits. Additionally, 17 QTL clusters were detected, and the additive effects of these clusters explained the correlation between different phenotypic traits. Candidate genes for stable QTLs related to agronomic and yield traits were identified through variant annotation and functional prediction. Two bin markers associated with lint percentage (LP) were validated as potential breeding markers. Furthermore, using RNA-seq data of cotton fiber from the RIL population parents, the dynamic changes in gene expression during different developmental stages of cotton fiber were revealed, and important differentially expressed genes in the secondary cell wall development and metabolism network of fibers were identified. Importantly, through the combined analysis of fiber trait QTLs and transcriptomes, eight candidate genes involved in regulating fiber quality traits were predicted, and the genetic basis of the excellent allele site qFL_D04_1 in the breeding history of Chinese sea island cotton was elucidated. In summary, this study provides new genetic resources and potential breeding markers for cotton variety improvement, valuable theoretical information for understanding the genetic basis of important traits in sea island cotton, and effectively promotes the development of cotton biotechnology breeding.
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页数:19
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