Evidence map›Paper›PMID 30991750›Full record

ArticleInternational journal of molecular sciences2019

Deep Transcriptome Analysis Reveals Reactive Oxygen Species (ROS) Network Evolution, Response to Abiotic Stress, and Regulation of Fiber Development in Cotton.

Yanchao Xu, Richard Odongo Magwanga, Xiaoyan Cai, Zhongli Zhou, Xingxing Wang, Yuhong Wang, Zhenmei Zhang, Dingsha Jin, Xinlei Guo, Yangyang Wei and 3 more

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
10.2field-weighted citation impact, top 2% of its field
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

32 citing papers in PubMed, 58 citations in OpenAlex.

  1. Article
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  5. Genetic basis and role of exotic accessions in cultivated cotton fiber quality improvement.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Review
  6. Review
  7. Analysis of the genetic basis of fiber-related traits and flowering time in upland cotton using machine learning.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
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  19. Characterization ofAntioxidants (Basel, Switzerland) · 2022
    Article
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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

13 authors at 2 institutions in 2 countries.

Yanchao XuState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. xuyanchao2016@163.com.
Richard Odongo MagwangaState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. magwangarichard@yahoo.com.
Xiaoyan CaiState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. caixy@cricaas.com.cn.
Zhongli ZhouState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. zhouzl@cricaas.com.cn.
Xingxing WangState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. wangxx@cricaas.com.cn.
Yuhong WangState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. wangyh2525377@163.com.
Zhenmei ZhangState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. jindingsha@163.com.
Dingsha JinState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. jindingsha@163.com.
Xinlei GuoState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. lizhenqing2019@163.com.
Yangyang WeiState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. liufang@caas.cn.
Zhenqing LiState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. lizhenqing2019@163.com.
Kunbo WangState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. wkbcri@cricaas.com.cn.
Fang LiuState Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang 455000, China. liufang@caas.cn.
Cotton Research Institute · CNJaramogi Oginga Odinga University of Science and Technology · KE

Funding

National key research and development plan 2016YFD0100306, 2016YFD0101401National Natural Science Foundation of China 31671745, 31601352, and 31530053
6 · The paper itself

Abstract

Reactive oxygen species (ROS) are important molecules in the plant, which are involved in many biological processes, including fiber development and adaptation to abiotic stress in cotton. We carried out transcription analysis to determine the evolution of the ROS genes and analyzed their expression levels in various tissues of cotton plant under abiotic stress conditions. There were 515, 260, and 261 genes of ROS network that were identified in

Indexed as

Stress, PhysiologicalTranscriptomeGene Expression ProfilingGene Expression Regulation, PlantGenome, PlantGossypiumPhylogenyReactive Oxygen SpeciesReactive Oxygen Speciesabiotic stressfiber developmentROS genestranscription analysis

Identifiers

PMID30991750
PMCPMC6514600
OpenAlexW2937907798

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.