Integrating RNA-Seq, Transcription Factor Annotation, and WGCNA Identifies Key Candidate Genes in Upland Cotton Seedlings Under Short-Term Drought Stress

Abstract

Background: Drought is one of the major abiotic stresses that affect and limit cotton growth and production. However, transcriptome differences between drought-tolerant and drought-susceptible cotton lines remain largely unknown. Methods and Results: In this study, two upland cotton cultivars, the drought-tolerant XLZ80 and drought-sensitive XLZ61, were subjected to comparative phenotypic and transcriptomic analyses under drought stress. Phenotypic evaluation showed that XLZ80 exhibited only mild leaf wilting, whereas XLZ61 displayed severe wilting symptoms after drought stress. RNA-seq analysis revealed that differentially expressed genes in XLZ80 were specifically enriched in pathways related to phosphatidylinositol signaling, phenylalanine metabolism, MAPK signaling, and betaine biosynthesis, while DEGs in XLZ61 were primarily involved in basal metabolic processes. A total of 9302 core DEGs were identified across and between the cultivars and were grouped into eight dynamic expression clusters containing 841 transcription factors. Weighted gene co-expression network analysis further identified three key modules associated with drought tolerance. Twelve hub genes, including GH_D02G2153 (MADS-box) and GH_A05G1087 (bZIP), were identified as central regulators. qRT-PCR validation confirmed that these genes exhibited faster and stronger induction in the tolerant cultivar. In summary, this study deepens the transcriptional-level understanding of drought stress responses in cotton and provides valuable gene resources for breeding drought-resistant cultivars.