Thursday 10 January 2017
From gene expression modeling to gene network to investigate Arabidopsis thaliana stress response
Institute of Plant Sciences Paris-Saclay IPS2, UMR MIA-Paris, AgroParisTech,Orsay, France
Transcriptome data allow investigating the gene behaviors and co-expression studies have rapidly been considered as a way to identify sets of candidate gene modules. Generally co-expression is established by analyzing correlations between all gene pairs in multiple microarray experiments collected from public repositories. Such approaches may suffer from both heterogeneity of data and the choice of the clustering method, usually based on gene pairs.
Tackling these limitations, we propose an analysis based on a large and homogeneous set of transcriptome data extracted from CATdb: 387 stress conditions organized into 9 biotic and 9 abiotic stress categories. Instead of correlation analysis, a model-based clustering was applied to identify clusters of co-expressed genes per stress category. Various resources were then analyzed and integrated to characterize functions associated with genes in these clusters. Protein–protein interactions and transcription factors-targets interactions were exploited to display gene networks. All the results are stored and managed in GEM2Net, a new module of CATdb (Zaag et al., 2015). We are currently using this resource to identify a coregulation network and possible determinants of expression regulation. We are also proposing a high-throughput functional annotation of Arabidopsis thaliana. During my talk, I will present these different projects.
Contact : Antoine Martin