Sonsungsan Pajaree, Chantanakool Pheerawat, Suratanee Apichat, Buaboocha Teerapong, Comai Luca, Chadchawan Supachitra, Plaimas Kitiporn
Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok, Thailand.
Center of Excellence in Environment and Plant Physiology, Department of Botany, Faculty of Science, Chulalongkorn University, Bangkok, Thailand.
Front Plant Sci. 2021 Dec 2;12:744654. doi: 10.3389/fpls.2021.744654. eCollection 2021.
Salinity is an important environmental factor causing a negative effect on rice production. To prevent salinity effects on rice yields, genetic diversity concerning salt tolerance must be evaluated. In this study, we investigated the salinity responses of rice () to determine the critical genes. The transcriptomes of 'Luang Pratahn' rice, a local Thai rice variety with high salt tolerance, were used as a model for analyzing and identifying the key genes responsible for salt-stress tolerance. Based on 3' Tag-Seq data from the time course of salt-stress treatment, weighted gene co-expression network analysis was used to identify key genes in gene modules. We obtained 1,386 significantly differentially expressed genes in eight modules. Among them, six modules indicated a significant correlation within 6, 12, or 48h after salt stress. Functional and pathway enrichment analysis was performed on the co-expressed genes of interesting modules to reveal which genes were mainly enriched within important functions for salt-stress responses. To identify the key genes in salt-stress responses, we considered the two-state co-expression networks, normal growth conditions, and salt stress to investigate which genes were less important in a normal situation but gained more impact under stress. We identified key genes for the response to biotic and abiotic stimuli and tolerance to salt stress. Thus, these novel genes may play important roles in salinity tolerance and serve as potential biomarkers to improve salt tolerance cultivars.
盐度是对水稻生产产生负面影响的重要环境因素。为防止盐度对水稻产量的影响，必须评估与耐盐性相关的遗传多样性。在本研究中，我们调查了水稻（）的盐度响应以确定关键基因。将具有高耐盐性的泰国当地水稻品种“Luang Pratahn”的转录组用作分析和鉴定负责耐盐胁迫的关键基因的模型。基于盐胁迫处理时间进程的3'标签测序数据，使用加权基因共表达网络分析来鉴定基因模块中的关键基因。我们在八个模块中获得了1386个显著差异表达的基因。其中，六个模块在盐胁迫后6、12或48小时内显示出显著相关性。对感兴趣模块的共表达基因进行功能和通路富集分析，以揭示哪些基因主要富集在盐胁迫响应的重要功能中。为了鉴定盐胁迫响应中的关键基因，我们考虑了两种状态的共表达网络、正常生长条件和盐胁迫，以研究哪些基因在正常情况下不太重要，但在胁迫下获得了更大的影响。我们鉴定了对生物和非生物刺激的响应以及对盐胁迫的耐受性的关键基因。因此，这些新基因可能在耐盐性中发挥重要作用，并可作为改善耐盐品种的潜在生物标志物。
