Abstract:
Studies on Oryza sativa (rice) are crucial for improving agricultural productivity and ensuring global sustenance security, especially considering the increasing drought and heat stress caused by extreme climate change. Currently, the genes and mechanisms underlying drought and heat resistance in rice are not fully understood, and the scope for enhancing the development of new strains remains considerable. To accurately identify the key genes related to drought and heat stress responses in rice, multiple datasets from the Gene Expression Omnibus (GEO) database were integrated in this study. A co-expression network was constructed using a Weighted Correlation Network Analysis (WGCNA) algorithm. We further distinguished the core network and intersected it with differentially expressed genes and multiple expression datasets for screening. Differences in gene expression levels were verified using quantitative real-time polymerase chain reaction (PCR). OsDjC53, MBF1C, BAG6, HSP23.2, and HSP21.9 were found to be associated with the heat stress response, and it is also possible that UGT83A1 and OsCPn60a1, although not directly related, are affected by drought stress. This study offers significant insights into the molecular mechanisms underlying stress responses in rice, which could promote the development of stress-tolerant rice breeds.
摘要:
水稻研究对提高农业生产力和确保全球生计安全至关重要,特别是考虑到极端气候变化导致的干旱和热胁迫的增加。目前,水稻抗旱性和耐热性的基因和机制还不完全清楚,加强新菌株开发的空间仍然很大。为了准确鉴定水稻干旱和高温胁迫响应的关键基因,本研究整合了来自基因表达综合(GEO)数据库的多个数据集.使用加权相关网络分析(WGCNA)算法构建共表达网络。我们进一步区分了核心网络,并将其与差异表达的基因和多个表达数据集相交以进行筛选。使用定量实时聚合酶链反应(PCR)验证基因表达水平的差异。OsDjC53,MBF1C,发现BAG6,HSP23.2和HSP21.9与热应激反应有关,UGT83A1和OsCPn60a1虽然没有直接关系,受干旱胁迫的影响。这项研究为水稻胁迫反应的分子机制提供了重要的见解,从而促进耐逆性水稻品种的发展。