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

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 ke...

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Autores principales: Suratanee, Apichat, Chokrathok, Chidchanok, Chutimanukul, Panita, Khrueasan, Nopphawitchayaphong, Buaboocha, Teerapong, Chadchawan, Supachitra, Plaimas, Kitiporn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6316690/
https://www.ncbi.nlm.nih.gov/pubmed/30501128
http://dx.doi.org/10.3390/genes9120594
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author Suratanee, Apichat
Chokrathok, Chidchanok
Chutimanukul, Panita
Khrueasan, Nopphawitchayaphong
Buaboocha, Teerapong
Chadchawan, Supachitra
Plaimas, Kitiporn
author_facet Suratanee, Apichat
Chokrathok, Chidchanok
Chutimanukul, Panita
Khrueasan, Nopphawitchayaphong
Buaboocha, Teerapong
Chadchawan, Supachitra
Plaimas, Kitiporn
author_sort Suratanee, Apichat
collection PubMed
description 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.
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spelling pubmed-63166902019-01-09 Two-State Co-Expression Network Analysis to Identify Genes Related to Salt Tolerance in Thai Rice Suratanee, Apichat Chokrathok, Chidchanok Chutimanukul, Panita Khrueasan, Nopphawitchayaphong Buaboocha, Teerapong Chadchawan, Supachitra Plaimas, Kitiporn Genes (Basel) Article 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. MDPI 2018-11-29 /pmc/articles/PMC6316690/ /pubmed/30501128 http://dx.doi.org/10.3390/genes9120594 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Suratanee, Apichat
Chokrathok, Chidchanok
Chutimanukul, Panita
Khrueasan, Nopphawitchayaphong
Buaboocha, Teerapong
Chadchawan, Supachitra
Plaimas, Kitiporn
Two-State Co-Expression Network Analysis to Identify Genes Related to Salt Tolerance in Thai Rice
title Two-State Co-Expression Network Analysis to Identify Genes Related to Salt Tolerance in Thai Rice
title_full Two-State Co-Expression Network Analysis to Identify Genes Related to Salt Tolerance in Thai Rice
title_fullStr Two-State Co-Expression Network Analysis to Identify Genes Related to Salt Tolerance in Thai Rice
title_full_unstemmed Two-State Co-Expression Network Analysis to Identify Genes Related to Salt Tolerance in Thai Rice
title_short Two-State Co-Expression Network Analysis to Identify Genes Related to Salt Tolerance in Thai Rice
title_sort two-state co-expression network analysis to identify genes related to salt tolerance in thai rice
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6316690/
https://www.ncbi.nlm.nih.gov/pubmed/30501128
http://dx.doi.org/10.3390/genes9120594
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