Evidence map›Paper›PMID 39456877›Full record

ArticleInternational journal of molecular sciences2024

Profiling of Key Hub Genes Using a Two-State Weighted Gene Co-Expression Network of 'Jao Khao' Rice under Soil Salinity Stress Based on Time-Series Transcriptome Data.

Prasit Khunsanit, Kitiporn Plaimas, Supachitra Chadchawan, Teerapong Buaboocha

Abstract read
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Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Leveraging Genetic Diversity for Abiotic Stress Tolerance.International journal of molecular sciences · 2026
    Article
  2. FScientific reports · 2025
    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

4 authors.

Prasit KhunsanitProgram in Biotechnology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.
Kitiporn PlaimasDepartment of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.ORCID 0000-0002-0416-8316
Supachitra ChadchawanCenter of Excellence in Environment and Plant Physiology, Department of Botany, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.
Teerapong BuaboochaCenter of Excellence in Molecular Crop, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.

Funding

NSRF through the Program Management Unit for Human Resources & Institutional Development, Re-search and Innovation B05F640097
6 · The paper itself

Abstract

RNA-sequencing enables the comprehensive detection of gene expression levels at specific time points and facilitates the identification of stress-related genes through co-expression network analysis. Understanding the molecular mechanisms and identifying key genes associated with salt tolerance is crucial for developing rice varieties that can thrive in saline environments, particularly in regions affected by soil salinization. In this study, we conducted an RNA-sequencing-based time-course transcriptome analysis of 'Jao Khao', a salt-tolerant Thai rice variety, grown under normal or saline (160 mM NaCl) soil conditions. Leaf samples were collected at 0, 3, 6, 12, 24, and 48 h. In total, 36 RNA libraries were sequenced. 'Jao Khao' was found to be highly salt-tolerant, as indicated by the non-significant differences in relative water content, cell membrane stability, leaf greenness, and chlorophyll fluorescence over a 9-day period under saline conditions. Plant growth was slightly retarded during days 3-6 but recovered by day 9. Based on time-series transcriptome data, we conducted differential gene expression and weighted gene co-expression network analyses. Through centrality change from normal to salinity network, 111 key hub genes were identified among 1,950 highly variable genes. Enriched genes were involved in ATP-driven transport, light reactions and response to light, ATP synthesis and carbon fixation, disease resistance and proteinase inhibitor activity. These genes were upregulated early during salt stress and RT-qPCR showed that 'Jao Khao' exhibited an early upregulation trend of two important genes in energy metabolism: RuBisCo (

Indexed as

Gene Expression ProfilingGene Expression Regulation, PlantGene Regulatory NetworksOryzaSalt StressTranscriptomePlant LeavesPlant ProteinsSalinitySalt ToleranceSoilPlant ProteinsSoilnetwork-based analysisriceRNA-sequencingsalt tolerancetranscriptomictwo-state co-expression networkweighted co-expression network

Identifiers

PMID39456877
PMCPMC11508143

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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.