Cottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement. A genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines. This study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.

The β-amylase (BAM) gene family encodes important enzymes that catalyze the conversion of starch to maltose in various biological processes of plants and play essential roles in regulating the growth and development of multiple plants. So far, BAMs have been extensively studied in Arabidopsis thaliana (A. thaliana). However, the characteristics of the BAM gene family in the crucial economic crop, cotton, have not been reported. In this study, 27 GhBAM genes in the genome of Gossypium hirsutum L (G. hirsutum) were identified by genome-wide identification, and they were divided into three groups according to sequence similarity and phylogenetic relationship. The gene structure, chromosome distribution, and collinearity of all GhBAM genes identified in the genome of G. hirsutum were analyzed. Further sequence alignment of the core domain of glucosyl hydrolase showed that all GhBAM family genes had the glycosyl hydrolase family 14 domain. We identified the BAM gene GhBAM7 and preliminarily investigated its function by transcriptional sequencing analysis, qRT-PCR, and subcellular localization. These results suggested that the GhBAM7 gene may influence fiber strength during fiber development. This systematic analysis provides new insight into the transcriptional characteristics of BAM genes in G. hirsutum. It may lay the foundation for further study of the function of these genes.

Cotton is an important commercial crop whose growth and yield are severely affected by drought. S-adenosylmethionine (SAM) is widely involved in the plant stress response and growth regulation; however, the role of the S-adenosylmethionine synthase (SAMS) gene family in this process is poorly understood. Here, we systematically analyzed the expression of SAMS genes in Upland Cotton (Gossypium hirsutum L.). A total of 16 SAMS genes were identified, each with a similar predicted structure. A large number of cis-acting elements involved in the response to abiotic stress were predicted based on promoter analysis, indicating a likely important role in abiotic stress responses. The results of qRT-PCR validation showed that GhSAMS genes had different expression patterns after drought stress and in response to drought stress. Analysis of a selected subset of GhSAMS genes showed increased expression in cultivar Xinluzhong 39 (drought resistant) when compared to cultivar Xinluzao 26 (drought-sensitive) upland cotton. This study provides important relevant information for further study of SAMS genes in drought resistance research of upland cotton, which is helpful for drought-resistance improvement of upland cotton.

Cotton is the most widely planted fiber crop in the world, and improving cotton fiber quality has long been a research hotspot. The development of cotton fibers is a complex process that includes four consecutive and overlapping stages, and although many studies on cotton fiber development have been reported, most of the studies have been based on cultivars that are promoted in production or based on lines that are used in breeding. Here, we report a phenotypic evaluation of Gossypium hirsutum based on immature fiber mutant (xin w 139) and wild-type (Xin W 139) lines and a comparative transcriptomic study at seven time points during fiber development. The results of the two-year study showed that the fiber length, fiber strength, single-boll weight and lint percentage of xin w 139 were significantly lower than those of Xin W 139, and there were no significant differences in the other traits. Principal component analysis (PCA) and cluster analysis of the RNA-sequencing (RNA-seq) data revealed that these seven time points could be clearly divided into three different groups corresponding to the initiation, elongation and secondary cell wall (SCW) synthesis stages of fiber development, and the differences in fiber development between the two lines were mainly due to developmental differences after twenty days post anthesis (DPA). Differential expression analysis revealed a total of 5131 unique differentially expressed genes (DEGs), including 290 transcription factors (TFs), between the 2 lines. These DEGs were divided into five clusters. Each cluster functional category was annotated based on the KEGG database, and different clusters could describe different stages of fiber development. In addition, we constructed a gene regulatory network by weighted correlation network analysis (WGCNA) and identified 15 key genes that determined the differences in fiber development between the 2 lines. We also screened seven candidate genes related to cotton fiber development through comparative sequence analysis and qRT–PCR; these genes included three TFs (GH_A08G1821 (bHLH), GH_D05G3074 (Dof), and GH_D13G0161 (C3H)). These results provide a theoretical basis for obtaining an in-depth understanding of the molecular mechanism of cotton fiber development and provide new genetic resources for cotton fiber research.

Currently, developing cotton cultivation in saline–alkali soils is a vital focus for restructuring the cotton industry in China. The seedling stage, specifically the three-leaf stage, is a crucial period for assessing the salt tolerance of cotton. This research examined 430 natural populations of upland cotton, including 45 semi-wild germlines of Gossypium purpurascens. We measured the phenotypic responses of salt stress injury on seedlings as well as potassium (K), calcium (Ca), sodium (Na), and magnesium (Mg) concentrations in the roots, stems, and leaves following a 72 h exposure. The comprehensive salt tolerance index (CSTI) was determined using a membership function, principal component analysis, and cluster analysis based on 48 phenotypic traits related to salt tolerance. The results revealed significant variations in the phenotypic traits of the ion group under salt stress. Salt stress greatly affected the relative contents of Mg, K, and Ca ions in the aboveground parts of cotton, and correlations were observed among the 48 indices. The CSTI was calculated using seven principal component indexes, identifying 30 salt-tolerant, 114 weakly salt-tolerant, 39 salt-sensitive, and 4 highly sensitive materials based on cluster analysis. Among the 45 G. purpurascens cotton resources, 28 were weakly salt-tolerant, while 17 were salt-sensitive. Through TMT (Tandem Mass Tag)-based quantitative analysis, we identified 3107 unique peptides among 28,642 detected peptides, resulting in 203,869 secondary mass spectra, with 50,039 spectra successfully matched to peptides. Additionally, we identified several salt tolerance-related pathways (carbon metabolism; glutathione metabolism; the biosynthesis of amino acids, etc.) and proteins classified within the CAZy (Carbohydrate-Active EnZYme) family and expansin proteins. The results of this study concerning salt-tolerant materials provide a crucial theoretical foundation for the identification and evaluation of salt-tolerant breeding parents in cultivated cotton.

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 (Gossypium hirsutum L.) and the quantitative nature of fiber quality traits necessitate innovative approaches for identifying and incorporating superior alleles from related species. We developed a BC₆F₂ population by introgressing chromosome segments from the sea island cotton variety Xinhai 36 (G. barbadense) into the upland cotton variety Xinluzhong 60 (G. hirsutum). 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 GH_A10G1043, encoding a β-amylase family protein, as the key candidate gene. Functional validation through overexpression and RNAi knockdown in Arabidopsis thaliana demonstrated that GH_A10G1043 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 GH_A10G1043 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.