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利用共表达网络分析鉴定伽马辐照水稻中的候选放射性标记基因。

The identification of candidate radio marker genes using a coexpression network analysis in gamma-irradiated rice.

机构信息

Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongeup, Jeonbuk, 580-185, Republic of Korea.

Plant Genomics Lab, Department of Applied Plant Sciences, Kangwon National University, Chuncheon, 200-713, Republic of Korea.

出版信息

Physiol Plant. 2013 Dec;149(4):554-70. doi: 10.1111/ppl.12058. Epub 2013 Apr 26.

DOI:10.1111/ppl.12058
PMID:23617399
Abstract

Plant physiological and biochemical processes are significantly affected by gamma irradiation stress. In addition, gamma-ray (GA) differentially affects gene expression across the whole genome. In this study, we identified radio marker genes (RMGs) responding only to GA stress compared with six abiotic stresses (chilling, cold, anoxia, heat, drought and salt) in rice. To analyze the expression patterns of differentially expressed genes (DEGs) in gamma-irradiated rice plants against six abiotic stresses, we conducted a hierarchical clustering analysis by using a complete linkage algorithm. The up- and downregulated DEGs were observed against six abiotic stresses in three and four clusters among a total of 31 clusters, respectively. The common gene ontology functions of upregulated DEGs in clusters 9 and 19 are associated with oxidative stress. In a Pearson's correlation coefficient analysis, GA stress showed highly negative correlation with salt stress. On the basis of specific data about the upregulated DEGs, we identified the 40 candidate RMGs that are induced by gamma irradiation. These candidate RMGs, except two genes, were more highly induced in rice roots than in other tissues. In addition, we obtained other 38 root-induced genes by using a coexpression network analysis of the specific upregulated candidate RMGs in an ARACNE algorithm. Among these genes, we selected 16 RMGs and 11 genes coexpressed with three RMGs to validate coexpression network results. RT-PCR assay confirmed that these genes were highly upregulated in GA treatment. All 76 genes (38 root-induced genes and 38 candidate RMGs) might be useful for the detection of GA sensitivity in rice roots.

摘要

植物生理生化过程受伽马辐射胁迫的显著影响。此外,伽马射线(GA)会在整个基因组水平上对基因表达产生差异影响。在这项研究中,我们鉴定了仅对 GA 胁迫有响应而对六种非生物胁迫(冷胁迫、冷胁迫、缺氧胁迫、热胁迫、干旱胁迫和盐胁迫)无响应的放射性标记基因(RMG)。为了分析受伽马射线照射的水稻植株在六种非生物胁迫下差异表达基因(DEGs)的表达模式,我们使用完全链接算法进行了层次聚类分析。在总共 31 个聚类中,观察到 3 个和 4 个聚类中受六种非生物胁迫上调和下调的 DEGs。聚类 9 和 19 中上调 DEGs 的共同基因本体功能与氧化应激有关。在 Pearson 相关系数分析中,GA 胁迫与盐胁迫呈高度负相关。基于上调 DEGs 的特定数据,我们鉴定了 40 个候选 RMG,它们受到伽马辐射的诱导。这些候选 RMG 中,除了两个基因,在水稻根中比在其他组织中诱导程度更高。此外,我们还通过在 ARACNE 算法中使用特定上调候选 RMG 的共表达网络分析获得了另外 38 个根诱导基因。在这些基因中,我们选择了 16 个 RMG 和 11 个与三个 RMG 共表达的基因来验证共表达网络结果。RT-PCR 检测证实这些基因在 GA 处理中高度上调。所有 76 个基因(38 个根诱导基因和 38 个候选 RMG)可能有助于检测水稻根中的 GA 敏感性。

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