Kim Jiye, Jun Kyong Mi, Kim Joung Sug, Chae Songhwa, Pahk Yoon-Mok, Lee Tae-Ho, Sohn Soo-In, Lee Soo In, Lim Myung-Ho, Kim Chang-Kug, Hur Yoonkang, Nahm Baek Hie, Kim Yeon-Ki
Insilicogen, Inc., Suwon-si, Republic of Korea.
GreenGene Biotech Inc., Yongin, Republic of Korea.
Evol Bioinform Online. 2017 Jun 19;13:1176934317715421. doi: 10.1177/1176934317715421. eCollection 2017.
Accumulated microarray data are used for assessing gene function by providing statistical values for co-expressed genes; however, only a limited number of Web tools are available for analyzing the co-expression of genes of . We have developed a Web tool called RapaNet (http://bioinfo.mju.ac.kr/arraynet/brassica300k/query/), which is based on a data set of 143 microarrays compiled from various organs and at different developmental stages during exposure to biotic or abiotic stress. RapaNet visualizes correlated gene expression information via correlational networks and phylogenetic trees using Pearson correlation coefficient (). In addition, RapaNet provides hierarchical clustering diagrams, scatterplots of log ratio intensities, related pathway maps, and -element lists of promoter regions. To ascertain the functionality of RapaNet, the correlated genes encoding ribosomal protein (L7Ae), photosystem II protein D1 (psbA), and cytochrome P450 monooxygenase in glucosinolate biosynthesis (CYP79F1) were retrieved from RapaNet and compared with their homologues. An analysis of the co-expressed genes revealed their shared and unique features.
积累的微阵列数据通过为共表达基因提供统计值来用于评估基因功能;然而,仅有有限数量的网络工具可用于分析油菜基因的共表达。我们开发了一个名为RapaNet的网络工具(http://bioinfo.mju.ac.kr/arraynet/brassica300k/query/),它基于从各种器官以及在生物或非生物胁迫下不同发育阶段汇编的143个微阵列数据集。RapaNet使用皮尔逊相关系数通过相关网络和系统发育树可视化相关基因表达信息。此外,RapaNet提供层次聚类图、对数比率强度散点图、相关通路图以及启动子区域的顺式作用元件列表。为确定RapaNet的功能,从RapaNet中检索了编码核糖体蛋白(L7Ae)、光系统II蛋白D1(psbA)以及硫代葡萄糖苷生物合成中的细胞色素P450单加氧酶(CYP79F1)的相关基因,并与其同源物进行比较。对共表达基因的分析揭示了它们的共同和独特特征。