Evidence map›Paper›PMID 36293038›Full record

ArticleInternational journal of molecular sciences2022

A Comprehensive Gene Co-Expression Network Analysis Reveals a Role of

Pengyun Chen, Fei Wei, Hongliang Jian, Tingli Hu, Baoquan Wang, Xiaoyan Lv, Hantao Wang, Xiaokang Fu, Shuxun Yu, Hengling Wei and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2022. 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
1.9field-weighted citation impact, top 14% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Emerging Horizons in Plant Genetics and Breeding.International journal of molecular sciences · 2023
    Article
  3. Article
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 at 3 institutions in 1 country.

Pengyun ChenState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.
Fei WeiState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.
Hongliang JianState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.
Tingli HuState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.
Baoquan WangState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.
Xiaoyan LvState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.
Hantao WangState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.
Xiaokang FuState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.
Shuxun YuState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.ORCID 0000-0002-9715-3462
Hengling WeiState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.
Liang MaState Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China.
Cotton Research Institute · CNHenan University · CNZhengzhou University · CN

Funding

China Agriculture Research System CARS-15-06
6 · The paper itself

Abstract

Abiotic stress, such as drought and salinity stress, seriously inhibit the growth and development of plants. Therefore, it is vital to understand the drought and salinity resistance mechanisms to enable cotton to provide more production under drought and salt conditions. In this study, we identified 8806 and 9108 differentially expressed genes (DEGs) through a comprehensive analysis of transcriptomic data related to the PEG-induced osmotic and salt stress in cotton. By performing weighted gene co-expression network analysis (WGCNA), we identified four co-expression modules in PEG treatment and five co-expression modules in salinity stress, which included 346 and 324 predicted transcription factors (TFs) in these modules, respectively. Correspondingly, whole genome duplication (WGD) events mainly contribute to the expansion of those TFs. Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) analyses revealed those different modules were associated with stress resistance, including regulating macromolecule metabolic process, peptidase activity, transporter activity, lipid metabolic process, and responses to stimulus. Quantitative RT-PCR analysis was used to confirm the expression levels of 15 hub TFs in PEG6000 and salinity treatments. We found that the hub gene

Indexed as

DroughtsGene Expression Regulation, PlantGossypiumLipidsPeptide HydrolasesPlant BreedingSalt StressStress, PhysiologicalTranscription FactorsLipidsPeptide HydrolasesTranscription Factorsabiotic stressescottonGhWRKY46transcriptomicVIGSWGCNA

Identifiers

PMID36293038
PMCPMC9603583
OpenAlexW4304807045

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.