Evidence map›Paper›PMID 40530291›Full record

ArticleFrontiers in plant science2025

Integrated transcriptomic and metabolomic analyses provide new insights into alkaline stress tolerance in

Shiwei Geng, Wenju Gao, Fenglei Sun, Ni Yang, Teng Ma, Tingwei Wang, Bingyue Wang, Junhao Wang, Shuaishuai Qian, Shengmei Li and 1 more

Abstract read
In one paragraph

Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Shiwei Geng *Xinjiang 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, China.
Wenju Gao *National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, China.
Fenglei Sun *Xinjiang 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, China.
Ni YangXinjiang 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, China.
Teng MaXinjiang 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, China.
Tingwei WangEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, Urumqi, China.
Bingyue WangXinjiang 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, China.
Junhao WangXinjiang 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, China.
Shuaishuai QianXinjiang 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, China.
Shengmei LiCollege of Biotechnology, Xinjiang Agricultural Vocational and Technical University, Changji, Xinjiang, China.
Jieyin ZhaoEngineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, Urumqi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: 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. Methods: In this study, transcriptomic and metabolomic sequencing were performed on Results: 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 Conclusion: 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.

Indexed as

alkaline stresscandidate genesGossypium hirsutummetabolomeRNA-seq

Identifiers

PMID40530291
PMCPMC12170613

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.