Transcriptional survey of abiotic stress response in maize (Zea mays L.) in the level of gene co-expression network and differential gene correlation analysis

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-12-22 DOI:10.1093/aobpla/plad087
Leyla Nazari, Z. Zinati
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Abstract

Maize may be exposed to several abiotic stresses in the field. Therefore, identifying the tolerance mechanisms of naturally field stress is mandatory. Gene expression data of maize upon abiotic stress were collected, and 560 differentially expressed genes (DEGs) were identified through meta-analysis. The most significant gene ontology terms in up-regulated genes were “response to abiotic stress” and “chitinase activity”. “Phosphorelay signal transduction system” was the most significant enriched biological process in down-regulated DEGs. The co-expression analysis unveiled seven modules of DEGs, with a notable positive correlation between the modules and abiotic stress. Furthermore, the statistical significance was strikingly high for the turquoise, green, and yellow modules. The turquoise group played a central role in orchestrating crucial adaptations in metabolic and stress response pathways in maize when exposed to abiotic stress. Within three up-regulated modules, Zm.7361.1.A1_at, Zm.10386.1.A1_a_at, and Zm.10151.1.A1_at emerged as hub genes. These genes might introduce novel candidates implicated in stress tolerance mechanisms, warranting further comprehensive investigation and research. In parallel, the R package glmnet was applied to fit a logistic LASSO regression model on the DEGs profile to select candidate genes associated with abiotic responses in maize. The identified hub genes and LASSO regression genes were validated on an independent microarray dataset. Additionally, Differential Gene Correlation Analysis (DGCA) was performed on LASSO and hub genes to investigate the gene-gene regulatory relationship. The p-value of DGCA of 16 pairwise gene comparisons was lower than 0.01, indicating a gene-gene significant change in correlation between control and abiotic stress. Integrated WGCNA and logistic LASSO analysis revealed Zm.11185.1.S1_at, Zm.2331.1.S1_x_at, and Zm.17003.1.S1_at. Notably, these three genes were identified in the 16 gene-pair comparisons. This finding highlights the notable significance of these genes in the abiotic stress response. Additional research into maize stress tolerance may focus on these three genes.
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基因共表达网络和差异基因相关性分析水平上的玉米(Zea mays L.)非生物胁迫响应转录调查
玉米在田间可能会受到多种非生物胁迫。因此,必须找出玉米对田间自然胁迫的耐受机制。本研究收集了玉米在非生物胁迫下的基因表达数据,并通过元分析确定了 560 个差异表达基因(DEGs)。上调基因中最重要的基因本体术语是 "对非生物胁迫的响应 "和 "几丁质酶活性"。在下调的 DEGs 中,"磷酸链信号转导系统 "是最重要的富集生物过程。共表达分析揭示了七个 DEGs 模块,这些模块与非生物胁迫显著正相关。此外,绿松石、绿色和黄色模块的统计显著性也很高。绿松石组在协调玉米暴露于非生物胁迫时的代谢和胁迫响应途径的关键适应中发挥了核心作用。在三个上调模块中,Zm.7361.1.A1_at、Zm.10386.1.A1_a_at 和 Zm.10151.1.A1_at 成为枢纽基因。这些基因可能会引入与胁迫耐受机制有关的新候选基因,值得进一步全面调查和研究。同时,应用 R 软件包 glmnet 对 DEGs 图谱拟合逻辑 LASSO 回归模型,以筛选出与玉米非生物反应相关的候选基因。确定的中心基因和 LASSO 回归基因在独立的微阵列数据集上进行了验证。此外,还对 LASSO 和中心基因进行了差异基因相关分析(DGCA),以研究基因与基因之间的调控关系。16 个成对基因比较的 DGCA p 值小于 0.01,表明对照与非生物胁迫之间的基因-基因相关性发生了显著变化。综合 WGCNA 和逻辑 LASSO 分析发现了 Zm.11185.1.S1_at、Zm.2331.1.S1_x_at 和 Zm.17003.1.S1_at。值得注意的是,这三个基因是在 16 个基因对比较中发现的。这一发现凸显了这些基因在非生物胁迫响应中的重要作用。有关玉米抗逆性的其他研究可重点关注这三个基因。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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