Comparing Time Series Transcriptome Data Between Plants Using A Network Module Finding Algorithm

Comparative transcriptome analysis is the comparison of expression patterns between homologous genes in different species. Since most molecular mechanistic studies in plants have been performed in model species including Arabidopsis and rice, comparative transcriptome analysis is particularly important for functional annotation of genes in other plant species. Many biological processes, such as embryo development, are highly conserved between different plant species. The challenge is to establish one-to-one mapping of the developmental stages between two species. In this protocol, we solve this problem by converting the gene expression patterns into a co-expression network and then apply network module-finding algorithms to the cross-species co-expression network. We describe how to perform such analysis using bash scripts for preliminary data processing and R programming language, which implemented simulated annealing method for module finding. We also provide instructions on how to visualize the resulting co-expression networks across species.