Yang Yanlong, Sun Fenglei, Wei Xin, Wang Zhengzheng, Ma Jun, Zhang Dawei, Li Chunping, Lai Chengxia, Fu Guoyong, Li Youzhong
Xinjiang Key Laboratory of Cotton Genetic Improvement and Intelligent Production, National Cotton Engineering Technology Research Center, Cotton Research Institute of Xinjiang Uyghur Autonomous Region Academy of Agricultural Sciences, Urumqi 830091, China.
Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Key Laboratory of Cotton Biology and Genetic Breeding in the Northwest Inland Cotton Production Region, Ministry of Agriculture and Rural Affairs, Shihezi 832000, China.
Plants (Basel). 2025 Sep 7;14(17):2804. doi: 10.3390/plants14172804.
Cotton fiber quality improvement remains a fundamental challenge in breeding programs due to the complex genetic architecture underlying fiber development. The narrow genetic base of upland cotton ( L.) and the quantitative nature of fiber quality traits necessitate innovative approaches for identifying and incorporating superior alleles from related species. We developed a BCF population by introgressing chromosome segments from the sea island cotton variety Xinhai 36 () into the upland cotton variety Xinluzhong 60 (). Based on fiber strength phenotyping, we constructed two DNA bulks representing extreme phenotypes (20 superior and 12 inferior individuals) for bulked segregant analysis sequencing (BSA-Seq). High-throughput sequencing generated 225.13 Gb of raw data with average depths of 20× for parents and 30× for bulks. SNP calling and annotation were performed using GATK and ANNOVAR against the upland cotton reference genome (TM-1). BSA-Seq analysis identified 13 QTLs primarily clustered within a 1.6 Mb region (20.6-22.2 Mb) on chromosome A10. Within this region, we detected nonsynonymous mutation genes involving a total of six genes. GO and KEGG enrichment analyses revealed significant enrichment for carbohydrate metabolic processes, protein modification, and secondary metabolite biosynthesis pathways. Integration with transcriptome data prioritized , encoding a β-amylase family protein, as the key candidate gene. Functional validation through overexpression and RNAi knockdown in demonstrated that significantly regulates starch content and β-amylase activity, though without visible morphological alterations. This study successfully identified potential genomic regions and candidate genes associated with cotton fiber strength using chromosome segment substitution lines combined with BSA-Seq. The key candidate gene provides a valuable target for marker-assisted selection in cotton breeding programs. Our findings establish a foundation for understanding the molecular mechanisms of fiber quality formation and offer genetic resources for developing superior cotton varieties with enhanced fiber strength.
由于棉花纤维发育的遗传结构复杂，棉花纤维品质改良仍是育种计划中的一项基本挑战。陆地棉（Gossypium hirsutum L.）遗传基础狭窄，且纤维品质性状具有数量遗传特性，因此需要创新方法来鉴定和导入相关物种的优良等位基因。我们通过将海岛棉品种新海36（Gossypium barbadense L.）的染色体片段渗入陆地棉品种新陆中60（Gossypium hirsutum L.）中，构建了一个染色体片段代换系群体（BCF）。基于纤维强度表型分析，我们构建了两个代表极端表型的DNA混合池（20个纤维强度高的个体和12个纤维强度低的个体）用于分离群体分组分析法测序（BSA-Seq）。高通量测序产生了225.13 Gb的原始数据，亲本的平均测序深度为20×，混合池的平均测序深度为30×。使用GATK和ANNOVAR针对陆地棉参考基因组（TM-1）进行单核苷酸多态性（SNP）的检测和注释。BSA-Seq分析在A10染色体上一个1.6 Mb的区域（20.6 - 22.2 Mb）内鉴定出13个数量性状基因座（QTL），主要聚集在该区域。在这个区域内，我们检测到总共6个涉及非同义突变的基因。基因本体（GO）和京都基因与基因组百科全书（KEGG）富集分析表明，碳水化合物代谢过程、蛋白质修饰和次生代谢物生物合成途径显著富集。与转录组数据整合后，优先选择了编码β-淀粉酶家族蛋白的Gh_A10G0807作为关键候选基因。通过在棉花中过表达和RNA干扰敲低进行功能验证表明，Gh_A10G0807显著调节淀粉含量和β-淀粉酶活性，尽管没有明显的形态改变。本研究利用染色体片段代换系结合BSA-Seq成功鉴定了与棉花纤维强度相关的潜在基因组区域和候选基因。关键候选基因Gh_A10G0807为棉花育种计划中的标记辅助选择提供了有价值的靶点。我们的研究结果为理解纤维品质形成的分子机制奠定了基础，并为培育具有增强纤维强度的优良棉花品种提供了遗传资源。
