Integrated Transcriptomic and Metabolomic Analyses Provide New Insights into Alkaline Stress Tolerance in Gossypium hirsutum

Jieyin Zhao^1*Shiwei Geng²Wenju Gao³Fenglei Sun²Yang Ni²Teng Ma²Tingwei Wang¹Bingyue Wang²Junhao Wang²Shuaishuai Qian²Shengmei Li⁴

• ¹Xinjiang Agricultural University, Ürümqi, China
• ²Cotton Research Institute of Xinjiang Uyghur Autonomous Region Academy of Agricultural Sciences, Urumqi, China
• ³Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan Province, China
• ⁴Xinjiang Agricultural Vocational and Technical University, Changji, China

Cotton, one of the most important economic crops worldwide, has long been bred mainly for improvements in yield and quality, with relatively little focus on salt-alkali resistance. In this study, transcriptomic and metabolomic sequencing were performed on Gossypium hirsutum exposed to alkaline stress for different durations.The results of sample clustering, principal component analysis (PCA), and the number of differentially expressed genes (DEGs) revealed that 12 hours and 24 hours were the periods during which upland cotton presented the strongest response to salt stress, with flavonoid biosynthesis and alpha-linolenic acid metabolism playing significant roles during this time. A total of 6,610 DEGs were identified via comparison to the 0 h time point, including 579 transcription factors (TFs) that were significantly enriched in pathways such as flavonoid biosynthesis, the cell cycle, the cytochrome P450 pathway, phenylalanine metabolism, phototransduction, and alpha-linolenic acid metabolism. Through ultrahigh-performance liquid chromatography-MS (UPLC-MS), 4,225 metabolites were identified, and 1,684 differentially accumulated metabolites (DAMs) were identified by comparison to the levels at 0 h. A joint analysis of RNA-seq and metabolomic data revealed that the flavonoid biosynthesis and alpha-linolenic acid metabolism pathways play key roles in the response of G. hirsutum to alkaline stress, and the key genes in these pathways were identified. The weighted gene correlation network analysis (WGCNA) revealed 15 candidate genes associated with alkali tolerance in cotton, including 4 TFs and 4 genes related to flavonoid and anthocyanin biosynthesis. In conclusion, our study provides a theoretical foundation for understanding the molecular mechanisms underlying alkali tolerance in cotton and offers new gene resources for future research.