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Genes 2018, 9(12), 594; https://doi.org/10.3390/genes9120594

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

1
Department of Mathematics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bangkok 10800, Thailand
2
Advanced Virtual and Intelligent Computing (AVIC) Center, Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
3
Department of Botany, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
4
Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
*
Author to whom correspondence should be addressed.
Received: 4 October 2018 / Revised: 8 November 2018 / Accepted: 19 November 2018 / Published: 29 November 2018
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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. View Full-Text
Keywords: salt-tolerant genes; gene co-expression network; RNA sequencing; network analysis; ‘Khao Dawk Mali 105’; clustering coefficients; two-state networks; salt stress; rice genome salt-tolerant genes; gene co-expression network; RNA sequencing; network analysis; ‘Khao Dawk Mali 105’; clustering coefficients; two-state networks; salt stress; rice genome
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Suratanee, A.; Chokrathok, C.; Chutimanukul, P.; Khrueasan, N.; Buaboocha, T.; Chadchawan, S.; Plaimas, K. Two-State Co-Expression Network Analysis to Identify Genes Related to Salt Tolerance in Thai Rice. Genes 2018, 9, 594.

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