Evidence map›Paper›PMID 34512689›Full record

ArticleFrontiers in plant science2021

Combining Genome and Gene Co-expression Network Analyses for the Identification of Genes Potentially Regulating Salt Tolerance in Rice.

Panita Chutimanukul, Triono Bagus Saputro, Puriphot Mahaprom, Kitiporn Plaimas, Luca Comai, Teerapong Buaboocha, Meechai Siangliw, Theerayut Toojinda, Supachitra Chadchawan

Abstract read
In one paragraph

Article in Frontiers in plant science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. International journal of molecular sciences · 2026
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  2. FScientific reports · 2025
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  8. Association of a SpecificInternational journal of molecular sciences · 2024
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  10. International journal of molecular sciences · 2023
    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

9 authors.

Panita ChutimanukulCenter of Excellence in Environment and Plant Physiology, Department of Botany, Faculty of Science, Chulalongkorn University, Bangkok, Thailand.
Triono Bagus SaputroCenter of Excellence in Environment and Plant Physiology, Department of Botany, Faculty of Science, Chulalongkorn University, Bangkok, Thailand.
Puriphot MahapromCenter of Excellence in Environment and Plant Physiology, Department of Botany, Faculty of Science, Chulalongkorn University, Bangkok, Thailand.
Kitiporn PlaimasAdvanced Virtual and Intelligent Computing Research Center, Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok, Thailand.
Luca ComaiGenome Center and Department of Plant Biology, University of California Davis Genome Center, UC Davis, Davis, CA, United States.
Teerapong BuaboochaOmics Science and Bioinformatics Center, Faculty of Science, Chulalongkorn University, Bangkok, Thailand.
Meechai SiangliwNational Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Luang, Thailand.
Theerayut ToojindaNational Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Luang, Thailand.
Supachitra ChadchawanCenter of Excellence in Environment and Plant Physiology, Department of Botany, Faculty of Science, Chulalongkorn University, Bangkok, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Salinity stress tolerance is a complex polygenic trait involving multi-molecular pathways. This study aims to demonstrate an effective transcriptomic approach for identifying genes regulating salt tolerance in rice. The chromosome segment substitution lines (CSSLs) of "Khao Dawk Mali 105 (KDML105)" rice containing various regions of DH212 between markers RM1003 and RM3362 displayed differential salt tolerance at the booting stage. CSSL16 and its nearly isogenic parent, KDML105, were used for transcriptome analysis. Differentially expressed genes in the leaves of seedlings, flag leaves, and second leaves of CSSL16 and KDML105 under normal and salt stress conditions were subjected to analyses based on gene co-expression network (GCN), on two-state co-expression with clustering coefficient (CC), and on weighted gene co-expression network (WGCN). GCN identified 57 genes, while 30 and 59 genes were identified using CC and WGCN, respectively. With the three methods, some of the identified genes overlapped, bringing the maximum number of predicted salt tolerance genes to 92. Among the 92 genes, nine genes,

Indexed as

clustering co-efficientgene co-expression networkricesalt-tolerant genestranscriptome analysis

Identifiers

PMID34512689
PMCPMC8427287

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.