Wei Liu1, Liping Lin2, Zhiyuan Zhang2, Siqi Liu2, Kuan Gao2, Yanbin Lv2, Huan Tao2, Huaqin He3. 1. School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, People's Republic of China. weilau@fafu.edu.cn. 2. School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, People's Republic of China. 3. School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, People's Republic of China. hehq3@fafu.edu.cn.
Abstract
MAIN CONCLUSION: A comprehensive network of the Arabidopsis transcriptome was analyzed and may serve as a valuable resource for candidate gene function investigations. A web tool to explore module information was also provided. Arabidopsis thaliana is a widely studied model plant whose transcriptome has been substantially profiled in various tissues, development stages and other conditions. These data can be reused for research on gene function through a systematic analysis of gene co-expression relationships. We collected microarray data from National Center for Biotechnology Information Gene Expression Omnibus, identified modules of co-expressed genes and annotated module functions. These modules were associated with experiments/traits, which provided potential signature modules for phenotypes. Novel heat shock proteins were implicated according to guilt by association. A higher-order module networks analysis suggested that the Arabidopsis network can be further organized into 15 meta-modules and that a chloroplast meta-module has a distinct gene expression pattern from the other 14 meta-modules. A comparison with the rice transcriptome revealed preserved modules and KEGG pathways. All the module gene information was available from an online tool at http://bioinformatics.fafu.edu.cn/arabi/ . Our findings provide a new source for future gene discovery in Arabidopsis.
MAIN CONCLUSION: A comprehensive network of the Arabidopsis transcriptome was analyzed and may serve as a valuable resource for candidate gene function investigations. A web tool to explore module information was also provided. Arabidopsis thaliana is a widely studied model plant whose transcriptome has been substantially profiled in various tissues, development stages and other conditions. These data can be reused for research on gene function through a systematic analysis of gene co-expression relationships. We collected microarray data from National Center for Biotechnology Information Gene Expression Omnibus, identified modules of co-expressed genes and annotated module functions. These modules were associated with experiments/traits, which provided potential signature modules for phenotypes. Novel heat shock proteins were implicated according to guilt by association. A higher-order module networks analysis suggested that the Arabidopsis network can be further organized into 15 meta-modules and that a chloroplast meta-module has a distinct gene expression pattern from the other 14 meta-modules. A comparison with the rice transcriptome revealed preserved modules and KEGG pathways. All the module gene information was available from an online tool at http://bioinformatics.fafu.edu.cn/arabi/ . Our findings provide a new source for future gene discovery in Arabidopsis.
Authors: Joshua M Gendron; José L Pruneda-Paz; Colleen J Doherty; Andrew M Gross; S Earl Kang; Steve A Kay Journal: Proc Natl Acad Sci U S A Date: 2012-02-06 Impact factor: 11.205
Authors: Björn Usadel; Takeshi Obayashi; Marek Mutwil; Federico M Giorgi; George W Bassel; Mimi Tanimoto; Amanda Chow; Dirk Steinhauser; Staffan Persson; Nicholas J Provart Journal: Plant Cell Environ Date: 2009-08-27 Impact factor: 7.228
Authors: Wolfgang Huber; Vincent J Carey; Robert Gentleman; Simon Anders; Marc Carlson; Benilton S Carvalho; Hector Corrada Bravo; Sean Davis; Laurent Gatto; Thomas Girke; Raphael Gottardo; Florian Hahne; Kasper D Hansen; Rafael A Irizarry; Michael Lawrence; Michael I Love; James MacDonald; Valerie Obenchain; Andrzej K Oleś; Hervé Pagès; Alejandro Reyes; Paul Shannon; Gordon K Smyth; Dan Tenenbaum; Levi Waldron; Martin Morgan Journal: Nat Methods Date: 2015-02 Impact factor: 28.547
Authors: Katleen De Preter; Roland Barriot; Frank Speleman; Jo Vandesompele; Yves Moreau Journal: Nucleic Acids Res Date: 2008-03-16 Impact factor: 16.971
Authors: Abdul Kader Alabdullah; Philippa Borrill; Azahara C Martin; Ricardo H Ramirez-Gonzalez; Keywan Hassani-Pak; Cristobal Uauy; Peter Shaw; Graham Moore Journal: Front Plant Sci Date: 2019-10-18 Impact factor: 5.753