Application of MapMan and RiceNet Drives Systematic Analyses of the Early Heat Stress Transcriptome in Rice Seedlings

High-throughput transcriptome analyses such as oligonucleotide microarray technology are powerful tools for identifying an entire set of transcripts under given experimental conditions. However, it is not a simple process to interpret which information is important from those large gene sets. Using oligonucleotide arrays, more than 3000 rice microarray data have been produced; all are available for public users from the NCBI gene expression omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/). In this study, we employed MapMan and RiceNet tools to drive systematic analyses of the early heat stress transcriptome in rice seedlings. We generated transcriptome data to identify 589 genes that respond to early during heat stress, and uploaded the list to various overviews installed in the MapMan tool. In the cellular-response overview, this investigation revealed that the heat stress MapMan term is the most dominant, fitting well to the purpose of transcriptome analysis for examining the early heat stress response. When we applied the regulation overview, we learned that genes associated with transcription factors, protein modification, and calcium regulation are more significantly coupled with early heat stress in rice seedlings. This suggests that essential components, comprising signaling pathways, are mediated by such stress. We also used RiceNet to determine the functional gene network mediated by this stress. This network development was based on genes with enriched MapMan terms, i.e., heat stress, transcription factors, protein modification, and calcium regulation. We expect that applications of MapMan and RiceNet to genome-wide transcriptome data will guide users to identify key elements for further analyses.