Evidence map›Paper›PMID 30501128›Full record

ArticleGenes2018

Two-State Co-Expression Network Analysis to Identify Genes Related to Salt Tolerance in Thai rice.

Apichat Suratanee, Chidchanok Chokrathok, Panita Chutimanukul, Nopphawitchayaphong Khrueasan, Teerapong Buaboocha, Supachitra Chadchawan, Kitiporn Plaimas

Abstract read
In one paragraph

Article in Genes, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Association of a SpecificInternational journal of molecular sciences · 2024
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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

7 authors.

Apichat SurataneeDepartment of Mathematics, Faculty of Applied Science, King Mongkut's University of Technology North Bangkok 10800, Thailand. apichat.s@sci.kmutnb.ac.th.
Chidchanok ChokrathokAdvanced Virtual and Intelligent Computing (AVIC) Center, Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand. chorn.chid@gmail.com.
Panita ChutimanukulDepartment of Botany, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand. priggerr@gmail.com.
Nopphawitchayaphong KhrueasanDepartment of Botany, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand. sharesci@gmail.com.
Teerapong BuaboochaDepartment of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand. teerapong.b@chula.ac.th.
Supachitra ChadchawanDepartment of Botany, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand. supachitra.c@chula.ac.th.
Kitiporn PlaimasAdvanced Virtual and Intelligent Computing (AVIC) Center, Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand. kitiporn.p@chula.ac.th.

Funding

King Mongkut's University of Technology North Bangkok KMUTNB-ART-60-061Ratchadaphiseksompoj Research Fund, Chulalongkorn University CU-59-012-FW
6 · The paper itself

Abstract

Khao Dawk Mali 105 (KDML105) rice is one of the most important crops of Thailand. It is a challenging task to identify the genes responding to salinity in KDML105 rice. The analysis of the gene co-expression network has been widely performed to prioritize significant genes, in order to select the key genes in a specific condition. In this work, we analyzed the two-state co-expression networks of KDML105 rice under salt-stress and normal grown conditions. The clustering coefficient was applied to both networks and exhibited significantly different structures between the salt-stress state network and the original (normal-grown) network. With higher clustering coefficients, the genes that responded to the salt stress formed a dense cluster. To prioritize and select the genes responding to the salinity, we investigated genes with small partners under normal conditions that were highly expressed and were co-working with many more partners under salt-stress conditions. The results showed that the genes responding to the abiotic stimulus and relating to the generation of the precursor metabolites and energy were the great candidates, as salt tolerant marker genes. In conclusion, in the case of the complexity of the environmental conditions, gaining more information in order to deal with the co-expression network provides better candidates for further analysis.

Indexed as

clustering coefficientsgene co-expression network‘Khao Dawk Mali 105’network analysisrice genomeRNA sequencingsalt stresssalt-tolerant genestwo-state networks

Identifiers

PMID30501128
PMCPMC6316690

What OpenQuestion 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 OpenQuestion graph.