Integrated transcriptomic and metabolomic analyses provide new insights into alkaline stress tolerance in Gossypium hirsutum
IntroductionCotton, 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.MethodsIn this study, transcriptomic and metabolomic sequencing were performed on Gossypium hirsutum exposed...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Plant Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2025.1604606/full |
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| author | Shiwei Geng Wenju Gao Fenglei Sun Ni Yang Teng Ma Tingwei Wang Bingyue Wang Junhao Wang Shuaishuai Qian Shengmei Li Jieyin Zhao |
| author_facet | Shiwei Geng Wenju Gao Fenglei Sun Ni Yang Teng Ma Tingwei Wang Bingyue Wang Junhao Wang Shuaishuai Qian Shengmei Li Jieyin Zhao |
| author_sort | Shiwei Geng |
| collection | DOAJ |
| description | IntroductionCotton, 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.MethodsIn this study, transcriptomic and metabolomic sequencing were performed on Gossypium hirsutum exposed to alkaline stress for different durations.ResultsThe 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.ConclusionIn 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. |
| format | Article |
| id | doaj-art-7747dd4f606f4b8697f498c49c2ba736 |
| institution | DOAJ |
| issn | 1664-462X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj-art-7747dd4f606f4b8697f498c49c2ba7362025-08-20T03:07:17ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2025-06-011610.3389/fpls.2025.16046061604606Integrated transcriptomic and metabolomic analyses provide new insights into alkaline stress tolerance in Gossypium hirsutumShiwei Geng0Wenju Gao1Fenglei Sun2Ni Yang3Teng Ma4Tingwei Wang5Bingyue Wang6Junhao Wang7Shuaishuai Qian8Shengmei Li9Jieyin Zhao10Xinjiang Cotton Technology Innovation Center/Xinjiang Key Laboratory of Cotton Genetic Improvement and Intelligent Production/National Cotton Engineering Technology Research Center, Cotton Research Institute of Xinjiang Uyghur Autonomous Region Academy of Agricultural Sciences, Wulumuqi, Xinjiang, ChinaNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, ChinaXinjiang Cotton Technology Innovation Center/Xinjiang Key Laboratory of Cotton Genetic Improvement and Intelligent Production/National Cotton Engineering Technology Research Center, Cotton Research Institute of Xinjiang Uyghur Autonomous Region Academy of Agricultural Sciences, Wulumuqi, Xinjiang, ChinaXinjiang Cotton Technology Innovation Center/Xinjiang Key Laboratory of Cotton Genetic Improvement and Intelligent Production/National Cotton Engineering Technology Research Center, Cotton Research Institute of Xinjiang Uyghur Autonomous Region Academy of Agricultural Sciences, Wulumuqi, Xinjiang, ChinaXinjiang Cotton Technology Innovation Center/Xinjiang Key Laboratory of Cotton Genetic Improvement and Intelligent Production/National Cotton Engineering Technology Research Center, Cotton Research Institute of Xinjiang Uyghur Autonomous Region Academy of Agricultural Sciences, Wulumuqi, Xinjiang, ChinaEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, Urumqi, ChinaXinjiang Cotton Technology Innovation Center/Xinjiang Key Laboratory of Cotton Genetic Improvement and Intelligent Production/National Cotton Engineering Technology Research Center, Cotton Research Institute of Xinjiang Uyghur Autonomous Region Academy of Agricultural Sciences, Wulumuqi, Xinjiang, ChinaXinjiang Cotton Technology Innovation Center/Xinjiang Key Laboratory of Cotton Genetic Improvement and Intelligent Production/National Cotton Engineering Technology Research Center, Cotton Research Institute of Xinjiang Uyghur Autonomous Region Academy of Agricultural Sciences, Wulumuqi, Xinjiang, ChinaXinjiang Cotton Technology Innovation Center/Xinjiang Key Laboratory of Cotton Genetic Improvement and Intelligent Production/National Cotton Engineering Technology Research Center, Cotton Research Institute of Xinjiang Uyghur Autonomous Region Academy of Agricultural Sciences, Wulumuqi, Xinjiang, ChinaCollege of Biotechnology, Xinjiang Agricultural Vocational and Technical University, Changji, Xinjiang, ChinaEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, Urumqi, ChinaIntroductionCotton, 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.MethodsIn this study, transcriptomic and metabolomic sequencing were performed on Gossypium hirsutum exposed to alkaline stress for different durations.ResultsThe 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.ConclusionIn 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.https://www.frontiersin.org/articles/10.3389/fpls.2025.1604606/fullGossypium hirsutumalkaline stressRNA-seqmetabolomecandidate genes |
| spellingShingle | Shiwei Geng Wenju Gao Fenglei Sun Ni Yang Teng Ma Tingwei Wang Bingyue Wang Junhao Wang Shuaishuai Qian Shengmei Li Jieyin Zhao Integrated transcriptomic and metabolomic analyses provide new insights into alkaline stress tolerance in Gossypium hirsutum Frontiers in Plant Science Gossypium hirsutum alkaline stress RNA-seq metabolome candidate genes |
| title | Integrated transcriptomic and metabolomic analyses provide new insights into alkaline stress tolerance in Gossypium hirsutum |
| title_full | Integrated transcriptomic and metabolomic analyses provide new insights into alkaline stress tolerance in Gossypium hirsutum |
| title_fullStr | Integrated transcriptomic and metabolomic analyses provide new insights into alkaline stress tolerance in Gossypium hirsutum |
| title_full_unstemmed | Integrated transcriptomic and metabolomic analyses provide new insights into alkaline stress tolerance in Gossypium hirsutum |
| title_short | Integrated transcriptomic and metabolomic analyses provide new insights into alkaline stress tolerance in Gossypium hirsutum |
| title_sort | integrated transcriptomic and metabolomic analyses provide new insights into alkaline stress tolerance in gossypium hirsutum |
| topic | Gossypium hirsutum alkaline stress RNA-seq metabolome candidate genes |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2025.1604606/full |
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