Development of KaPPA-View4 for omics studies on Jatropha and a database system KaPPA-Loader for construction of local omics databases

Abstract

The publication of the whole genome sequence of Jatropha curcas L. has contributed to the study of gene functions of this plant, especially in data-driven investigations such as transcriptome and proteome analyses. Metabolomics analyses of Jatropha have also been reported in recent years. However, the analytical tools for omics data from Jatropha are limited. We prepared a set of pathway maps where the predicted genes of Jatropha were assigned based on KEGG pathway maps, and developed an omics viewer named KaPPA-View4-Jatropha where the pathway maps were implemented. Out of 40,929 predicted genes, 8085 genes were mapped on the KEGG Metabolism maps, other KEGG maps, or gene category maps that were generated from gene classification data of KEGG BRITE. Two transcriptome datasets, four metabolome datasets and one gene co-expression dataset were registered in the viewer. To facilitate data sharing of unpublished omics data among research collaborators, we developed a local database system, KaPPA-Loader. These data mining environments and the supporting database system will help Jatropha researchers to discover key genes such as those involved in oil production, biosynthesis of toxic compounds, and stress resistance. KaPPA-View4-Jatropha and KaPPA-Loader are available from the KaPPA-View portal site (http://kpv.kazusa.or.jp/).