Key Laboratory of Cotton Breeding and Cultivation in Huang-Huai-Hai Plain, Institute of Industrial Crops, Ministry of Agriculture and Rural Affairs of China, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Nanjing, 210095, China.
Theor Appl Genet. 2022 Jul;135(7):2279-2295. doi: 10.1007/s00122-022-04111-1. Epub 2022 May 16.
Thirty-four SNPs corresponding with 22 QTLs for lint percentage, including 13 novel QTLs, was detected via GWAS. Two candidate genes underlying this trait were also identified. Cotton (Gossypium spp.) is an important natural textile fiber and oilseed crop cultivated worldwide. Lint percentage (LP, %) is one of the important yield components, and increasing LP is a core goal of cotton breeding improvement. However, the genetic and molecular mechanisms underlying LP in upland cotton remain unclear. Here, we performed a genome-wide association study (GWAS) for LP based on 254 upland cotton accessions in four environments as well as the best linear unbiased predictors using the high-density CottonSNP80K array. In total, 41,413 high-quality single-nucleotide polymorphisms (SNPs) were screened, and 34 SNPs within 22 quantitative trait loci (QTLs) were significantly associated with LP. In total, 175 candidate genes were identified from two major genomic loci (GR1 and GR2), and 50 hub genes were identified through GO enrichment and weighted gene co-expression network analysis. Two candidate genes (Gh_D01G0162 and Gh_D07G0463), which may participate in early fiber development to affect the number of fiber protrusions and LP, were also identified. Their genetic variation and expression were verified by linkage disequilibrium blocks, haplotypes, and quantitative real-time polymerase chain reaction, respectively. The weighted gene interaction network analysis showed that the expression of Gh_D07G0463 was significantly correlated with that of Gh_D01G0162. These identified SNPs, QTLs and candidate genes provide important insights into the genetic and molecular mechanisms underlying variations in LP and serve as a foundation for LP improvement via marker-assisted breeding.
通过全基因组关联研究(GWAS),在四个环境中对 254 个陆地棉品种进行了基于皮棉百分率(LP,%)的GWAS,使用高密度的 CottonSNP80K 阵列作为最佳线性无偏预测。共筛选出 41413 个高质量的单核苷酸多态性(SNP),其中 34 个 SNP 与 22 个数量性状位点(QTL)显著相关。从两个主要基因组区域(GR1 和 GR2)共鉴定出 175 个候选基因,并通过 GO 富集和加权基因共表达网络分析鉴定出 50 个枢纽基因。还鉴定出两个候选基因(Gh_D01G0162 和 Gh_D07G0463),它们可能参与早期纤维发育,影响纤维突起的数量和 LP。通过连锁不平衡块、单倍型和定量实时聚合酶链反应分别验证了它们的遗传变异和表达。加权基因互作网络分析表明,Gh_D07G0463 的表达与 Gh_D01G0162 的表达显著相关。这些鉴定出的 SNP、QTL 和候选基因为 LP 变异的遗传和分子机制提供了重要的见解,并为通过标记辅助选择进行 LP 改良奠定了基础。