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Comprehensive meta-analysis and co-expression network analysis identify candidate genes for salt stress response in Arabidopsis

机译:综合性荟萃分析和共表达网络分析识别拟南芥盐应激反应的候选基因

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摘要

Salinity is one of the major environmental limitations to agricultural productivity throughout the world. To overcome the defects of microarray sequencing analyses caused by heterogeneity among individual studies, the effect size (ES) analysis based on the NetworkAnalyst web tool was conducted to synthesize 13 salt stress-related microarray data-sets, filtered from over 2000 data-sets and publications. A total of 3811 differently expressed (DE) genes were identified with 1476 up-regulated and 2335 down-regulated genes in NaCl-treated samples. A total of 172 biological processes were enriched by the over-expressed genes, like response to jasmonic acid, positive regulation of transcription, DNA-templated, and insulin resistance. The co-expression network construction yielded 15,630 nodes and 73,125 edges, further clustered into 178 co-expressed clusters based on the Heuristic Cluster Chiseling Algorithm (HCCA) method. A total of 1036 genes with the top 5% of clusters were treated as hub genes. The identification of DE genes, gene-gene co-expressing relations, and hub genes may contribute to uncover the mechanisms of salinity stress tolerance in Arabidopsis.
机译:盐度是全世界农业生产力的主要环境局限之一。为了克服各个研究中的异质性引起的微阵列测序分析的缺陷,进行了基于NetworkAnalyst Web工具的效果大小分析,以合成13个盐应力相关的微阵列数据集,从2000多个数据集中过滤出版物。在NaCl处理的样品中用1476个上调和2335个下调基因鉴定了总共3811种不同表达(DE)基因。通过对茉莉酸的响应,转录,转录的正调节,DNA模板和胰岛素抗性的响应,共富集了172种生物过程。共表达网络施工产生了15,630个节点和73,125边,进一步聚集到基于启发式群集凿子算法(HCCA)方法的178个共表达集群。总共1036个基因具有前5%的簇被视为枢纽基因。 De基因,基因基因共同关系的鉴定和枢纽基因可能有助于揭示拟南芥中盐度胁迫耐受的机制。

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