Gene co-expression network analysis identifies trait-related modules in Arabidopsis thaliana.
Liping LinLiping LinZhiyuan ZhangSiqi LiuKuan GaoYanbin LvHuan TaoHuaqin HePublished in: Planta (2019)
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.
Keyphrases
- genome wide
- network analysis
- gene expression
- dna methylation
- arabidopsis thaliana
- copy number
- genome wide identification
- transcription factor
- heat shock
- poor prognosis
- single cell
- machine learning
- risk assessment
- genome wide analysis
- rna seq
- lymph node metastasis
- heat stress
- climate change
- long non coding rna
- oxidative stress
- artificial intelligence