Juwu Gong

The DUF538 gene family, harboring unknown functional proteins, has been reported to take active roles in plant development and response to adversities, while few studies of genome-wide identification and functional verification have been performed in cotton. Hence, two ancestral diploid species, G. arboretum and G. raimondii, and two cultivated tetraploid ones, G. hirsutum and G. barbadense, were chosen in this study to investigate the cotton DUF538 gene family, resulting in 37, 37, 70, and 70 members identified, respectively. A phylogenetic tree was constructed on these cotton DUF538 genes, together with 22 A. thaliana ones, which were divided into seven groups unevenly distributed across nearly all chromosomes. High-degree conservatism, while rich in diversity, was separately observed in gene structure and conserved motif analyses between the same groups and different groups, and a great number of gene-replication events were detected from intraspecific and interspecific collinearity analyses, implying this was the driving force for DUF538 family expansion. Multiple cis-acting elements relevant to adversity-stress responses were found in the promoter region, which were consistent with the transcriptome expression analyses in response to low-temperature and drought stress and Verticillium wilt infection. Coincidentally, GhDUF538-7 showed the core position in the protein–protein interaction network and was identified in the overlapping region of the interval of four reported VW resistance-related QTLs. The gene function of GhDUF538-7 was verified via gene cloning, relative expression-pattern detection, and virus-induced gene silencing (VIGS) experiment. The TRV:DUF538-7 plants showed more serious VW symptoms, significantly severe disease indices, relatively higher fungal biomass, and increased brown vascular bundles compared with TRV:00 plants. Significantly lower expression levels of marker genes PR4 and MYC2 in jasmonate signaling pathways indicated GhDUF538-7 as a potentially positive regulatory factor in plant defense via hormone signal transduction. This study not only broadened the research perspective of evolution and functional differentiation of the cotton DUF538 gene family, but it also revealed the cooperative relationship between DUF538-7 and the JA pathway for further molecular mechanisms of cotton resistance to VW infection.

Plant height is a key agronomic trait that influences plant architecture and mechanical harvesting suitability in cotton; however, the molecular mechanisms underlying its dynamic development remain unclear. In this study, two recombinant inbred line (RIL) populations sharing CCRI127 as a common paternal parent (RIL-GH07, n = 150; RIL-2358B, n = 276) were developed. Based on stable plant-height performance across multiple environments, tall and short extreme lines were selected from the two RIL populations for transcriptome sequencing. By integrating differential expression analysis with weighted gene co-expression network analysis (WGCNA), we identified hub genes associated with cotton plant height development, characterized the molecular features and core pathways governing dynamic stem elongation at different growth stages, thereby providing insights into the transcriptional regulation of plant height development in cotton. The two RIL populations showed broadly similar plant-height growth patterns, with slow elongation at 15 DOS, rapid elongation during 30–60 DOS, and reduced growth after 70 DOS. Transcriptome differential expression analysis identified 15,052 non-redundant DEGs, which exhibited clear population- and stage-specific expression patterns. In the GH07 population, the largest number of DEGs was detected at 15 DOS (7193), whereas in the 2358B population relatively large numbers of DEGs were maintained at both 30 DOS (3839) and 70 DOS (3118). Analysis of DEGs shared by the two populations across four developmental stages showed that, in addition to genes with consistent expression trends, each stage also contained a substantial number of DEGs with opposite expression directions. WGCNA identified 25 gene expression modules, among which the green and yellow modules were significantly positively correlated with plant height. Functional enrichment analysis indicated that genes in these two modules were mainly enriched in hormone regulation and signal transduction, protein modification and degradation, and intracellular transport. Seven hub genes were identified by integrating intramodular connectivity and kME values. Functional prediction suggested that these genes may play important roles in cotton plant height development. This study provides genetic resources and a theoretical basis for subsequent functional validation of cotton plant height-related genes and the improvement of plant architecture in cotton.

Ammonium transporters (AMTs) represent a class of proteins within the ammonium transporter domain, which play an important role in mediating the transmembrane transport of NH₄⁺ in plants. However, research on AMT genes in foxtail millet remains limited. In this study, members of the AMT gene family in foxtail millet were identified at the whole genome level through bioinformatic analysis. The gene structure, evolutionary relationships, chromosomal localization, interspecies collinearity, cis-acting elements, and expression patterns of SiAMT members were systematically analyzed. The results revealed that there were nine SiAMT family members in foxtail millet, with molecular weights ranging from 49.5 to 53.8 kDa. Phylogenetic analysis classified them into three groups, which were unevenly distributed across chromosomes. The analysis of promoter cis-acting elements identified multiple regulatory elements, including light-, anaerobic-, and hormone-responsive elements. Collinearity analysis showed that the divergence time of AMT family members in foxtail millet and rice was more recent compared to Arabidopsis thaliana. The expression levels of SiAMT members varied across different tissues of foxtail millet, with most SiAMT family members showing high expression in roots, while SiAMT7 was significantly expressed in leaves. qRT-PCR analysis showed that SiAMT1 was significantly down-regulated in roots, stems, and leaves under salt stress. This study provides a theoretical foundation for further investigation into the functions of the AMT gene family.

Leucine-rich repeat extensins (LRXs) are essential regulators of plant development, cell wall integrity, and stress responses. However, genome-wide LRX studies in cotton are limited. Analysis of four Gossypium species identified 29, 28, 16, and 16 LRX genes in G. hirsutum, G. barbadense, G. arboreum, and G. raimondii, respectively. Phylogenetic analysis resolved these 89 genes into four subfamilies (I–IV). Structural annotation revealed that cotton LRX family members exhibit conserved domain architectures. This finding was corroborated by motif analysis, which revealed notable conservation in the motif compositions of most cotton LRX proteins, suggesting functional conservation across evolutionary lineages. Distinct spatiotemporal expression patterns were uncovered between G. hirsutum and G. barbadense. Prolonged exposure to extreme temperatures induced widespread down-regulation of most GhLRX genes, whereas genes in subgroup IV were significantly up-regulated under salt and drought stress conditions, respectively. Notably, GhLRX7 showed a more proactive responding profile to Verticillium wilt (VW) infection, which was therefore selected for functional validation employing virus-induced gene silencing in the cotton cultivars MBI9626 and CCRI36. Phenotypic analysis of silenced plants revealed exacerbated disease symptoms compared to wild-type controls, providing direct evidence implicating GhLRX7 as a key contributor to defense against VW.

Cotton fiber quality—defined by length, strength, and fineness—directly influences the commercial value of textile products, with fiber length being one of the most critical parameters in industrial procurement. In upland cotton ( Gossypium hirsutum ), fiber development occurs through four overlapping stages, of which the elongation phase (2–20 d post‐anthesis, DPA) is pivotal for determining final fiber length. Recent studies have identified a diverse set of genes regulating fiber elongation via distinct molecular mechanisms, categorized into six functional classes: Phytohormone‐associated genes; transcription factor‐associated genes; cellulose‐, lignin‐, and sucrose‐associated genes; lipid‐associated genes; cytoskeleton‐associated genes; and other functionally diverse genes. By synthesizing their roles and hierarchical interactions, this review constructs comprehensive genetic networks governing fiber elongation. This work provides a molecular blueprint for precision breeding strategies to enhance cotton fiber length, offering actionable insights for breeding programs aimed at improving fiber quality.

Gibberellins (GAs) play a crucial regulatory role in the growth and development of cotton (Gossypium hirsutum L.). Through bioinformatics analyses, we identified a total of 39 GA2ox genes (encoding gibberellin 2-oxidases) in the cotton genome, designated GhGA2ox1 to GhGA2ox39. Based on phylogenetic analysis, these genes were classified into five groups. We further examined their gene structures, conserved motifs, and chromosomal distributions, revealing that members within the same group shared similar structural and motif organizations. Collinearity and cis-element analyses provided important insights into the evolutionary history and regulatory potential of the GA2ox gene family in cotton. Notably, using nucleotide diversity (π) and population differentiation (F_ST) analyses across the entire family, we screened and identified nine candidate genes that underwent strong artificial selection during cotton domestication and improvement. Further haplotype-phenotype association analysis identified GH_D09G0919 (GhGA2ox31) as a key regulator of Plant Height (PH). To validate their regulatory roles, we analyzed the genotype distribution in accessions with extreme phenotypes. The results revealed divergent selection histories for these two loci: the favorable allele of GH_D01G0720 (GhGA2ox23) was already fixed in the tested population, whereas GH_D09G0919 maintained significant natural variation. Specifically, the Hap2 allele of GH_D09G0919 was significantly enriched in the shortest accessions compared to the tallest ones. Importantly, quantitative real-time polymerase chain reaction (qRT-PCR) analysis confirmed that the Hap2 allele drives significantly higher gene expression in leaves, suggesting that enhanced GA catabolism underlies the compact phenotype. Additionally, transcriptomic profiling revealed the tissue-specific expression patterns of candidate genes, implying their functional roles in development. Furthermore, functional validation using the Arabidopsis mutant of the homologous gene (AtGA2ox8) confirmed its conserved role in regulating plant height, as the mutant exhibited a distinct short-stature phenotype. These results uncover valuable genetic resources for molecular breeding to shape compact cotton architecture. Collectively, this study aims to analyze the evolutionary patterns of the cotton GA2ox gene family and to identify key genes that regulate plant height under artificial selection, providing theoretical support for molecular breeding of compact plant types.

Verticillium wilt (VW) severely limits the cotton yield and fiber quality. Marker-assisted selection is an efficient strategy for breeding resistant varieties. In this study, a high-density genetic map was constructed by using an F8:9 recombinant inbred line (RIL) population derived from CCRI70. Phenotypic data on disease incidence (DINC) and disease index (DI) were collected across six environments. A total of 59 QTLs for DINC and 60 QTLs for DI were identified, with three and six stable across multiple environments, respectively. These QTLs formed 18 clusters across 13 chromosomes, showing consistent additive effects. Transcriptome analysis revealed eight differentially expressed candidate genes within stable QTL regions. Among them, GH_D05G1495, GH_A09G1013, and GH_D05G1683 were further validated by virus-induced gene silencing as key genes conferring V. dahliae resistance in cotton. This study provides valuable genetic resources for improving Verticillium wilt resistance in cotton breeding.

Cottonseed oil is rich in unsaturated fatty acids (UFAs), making it suitable for use as edible oil. Fatty acid desaturases (FADs) play a major role in the conversion of monounsaturated fatty acids (MUFAs) to polyunsaturated fatty acids (PUFAs). In total, 39 GhFAD genes were detected in upland cotton and divided into five groups in the present study. Gene structure and domain analysis showed that GhFAD members within each group were highly conserved. Cis-elements associated with environmental stress and hormone responses were identified in GhFAD promoters. The predicted transcription factors and miRNAs targeting these genes suggest extensive roles for GhFADs in diverse stress conditions. Analysis of expression profiles indicated that GhFAD genes participate extensively in developmental processes and stress adaptation in cotton. Among these, the concurrent high expression of GhFAD2-1 and low expression of GhFAD3 are consistent with the typical fatty acid profile of cottonseed oil. GhFAD3-2 and GhFAD3-1 exhibit a complementary expression profiles, suggesting they may operate in a relay manner during fiber development. Additionally, experimental evidence established that GhFAD2-3 is involved in the cold stress response. This research delivers a thorough characterization of the GhFAD genes in upland cotton, thereby establishing a solid groundwork for future functional genomics studies.

Understanding the influence of environmental factors on cotton performance is crucial for enhancing yield and fiber quality in the context of climate change. This study investigates genotype-by-environment (G×E) interactions in cotton, using data from 250 recombinant inbred lines (CCRI70 RILs) cultivated across 14 diverse environments in China’s major cotton cultivation areas. Our findings reveal that environmental effects predominantly influenced yield-related traits (boll weight, lint percentage, and the seed index), contributing to 34.7% to 55.7% of their variance. In contrast fiber quality traits showed lower environmental sensitivity (12.3–27.0%), with notable phenotypic plasticity observed in the boll weight, lint percentage, and fiber micronaire. Employing six machine learning models, Random Forest demonstrated superior predictive ability (R² = 0.40–0.72; predictive Pearson correlation = 0.63–0.86). Through SHAP-based interpretation and sliding-window regression, we identified key environmental drivers primarily active during mid-to-late growth stages. This approach effectively reduced the number of influential input variables to just 0.1–2.4% of the original dataset, spanning 2–9 critical time windows per trait. Incorporating these identified drivers significantly improved cross-environment predictions, enhancing Random Forest accuracy by 0.02–0.15. These results underscore the strong potential of machine learning to uncover critical temporal environmental factors underlying G×E interactions and to substantially improve predictive modeling in cotton breeding programs, ultimately contributing to more resilient and productive cotton cultivation.