Salt stress is an environmental factor that limits plant seed germination, growth, and survival. We performed a comparative RNA sequencing transcriptome analysis during germination of the seeds from two cultivars with contrasting salt tolerance responses. A transcriptomic comparison between salt-tolerant cotton cv Jin-mian 25 and salt-sensitive cotton cv Su-mian 3 revealed both similar and differential expression patterns between the two genotypes during salt stress. The expression of genes related to aquaporins, kinases, reactive oxygen species (ROS) scavenging, trehalose biosynthesis, and phytohormone biosynthesis and signaling that include ethylene (ET), gibberellin (GA), abscisic acid (ABA), jasmonic acid (JA), and brassinosteroid (BR) were systematically investigated between the cultivars. Despite the involvement of these genes in cotton’s response to salt stress in positive or negative ways, their expression levels were mostly similar in both genotypes. Interestingly, a PXC2 gene (Ghir_D08G025150) was identified, which encodes a leucine-rich repeat receptor-like protein kinase (LRR-RLK). This gene showed an induced expression pattern after salt stress treatment in salt-tolerant cv Jin-mian 25 but not salt-sensitive cv Su-mian 3. Our multifaceted transcriptome approach illustrated a differential response to salt stress between salt-tolerant and salt-sensitive cotton.

Drought stress has a significant impact on cotton growth, development, and productivity. This study conducted drought stress treatment and normal water treatment (control group) on 502 cotton accessions and analyzed data on eight phenotypic traits closely related to drought stress tolerance. The results showed that all indicators changed significantly under drought stress conditions compared to the control group, with varying degrees of response among different indicators. To comprehensively evaluate the drought resistance of cotton during the germination period, the values of drought resistance comprehensive evaluation (D-value), weight drought resistance coefficient (WDC-value), and comprehensive drought resistance coefficient (CDC-value) were calculated based on membership function analysis and principal component analysis. Cluster analysis based on the D-value divided the germplasm into five drought-resistant grades, followed by the selection of one extreme material, each from the strongly drought-resistant and strongly drought-sensitive groups. An evaluation model was established using stepwise regression analysis, including the following effective indicators: Relative Fresh Weight (RFW), Relative Hypocotyl Length (RHL), Relative Seeds Water Absorption Rate (RAR), Relative Germination Rate (RGR), Relative Germination Potential (RGP), and Relative Drought Tolerance Index (RDT). The validation of the D-value prediction model based on the Best Linear Unbiased Prediction (BLUP) showed that the results obtained from two independent biological replicates were highly consistent. The comprehensive evaluation system and screening indicators established in this study provide a reliable method for identifying drought tolerance during the germination period.

Plant height (PH) is a vital agronomic trait that significantly affects cotton yield and facilitates mechanized harvesting. Gaining insights into the genetic regulatory mechanisms governing plant height is fundamental to advancing cotton breeding. In this study, cotton plants were treated with varying concentrations of mepiquat chloride, resulting in significant differences in plant height compared to the control group. Transcriptome data from 18 treated cotton stem tissue samples were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), leading to the identification of 21 gene co-expression modules. Of these, eight modules exhibited positive correlations, while 13 modules showed negative correlations with plant height. A co-expression network comprising 20,409 valid genes was constructed and visualized using Cytoscape 3.9.1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that these modules are associated with biologically significant pathways, including oxidoreductase activity, transcriptional regulator activity, catalytic activity, and phosphate hydrolase activity. Further analysis of gene connectivity within these modules identified 10 core genes (Gohir.D03G105600, Gohir.A03G060400, Gohir.A05G333400, Gohir.D09G243300, Gohir.D12G213500, Gohir.A04G065185, Gohir.A04G039105, Gohir.D08G127760, Gohir.A09G103348, and Gohir.A04G039120) and enabled the establishment of a gene interaction regulation network. Functional predictions suggest that these candidate genes may play key roles in the regulation of cotton plant height. This study offers theoretical insights into the molecular mechanisms underlying cotton plant height and provides valuable references for breeding new cotton varieties with optimized plant heights.