Plant Omics Data Center: An Integrated Web Repository for Interspecies Gene Expression Networks with NLP-based Curation

Large-scale omics information is an important source for a clue to gain insight into gene functions. To provide a platform for seamless access to the omics information across multiple plant species, we have developed and been maintaining a web-database Plant Omics Data Center (PODC;http://bioinf.mind.meiji.ac.jp/podc/). PODC stores information such as NGS-based gene expression profile, gene expression networks (GENs), orthologous relationships, and literature-based functional annotations. Here, we report about recent major updates in PODC.

    For species, information on Nicotiana tabacum and Zea mays become available in addition to 8 species in the previous version (Arabidopsis thaliana, Solanum lycopersicum, Solanum tuberosum, Oryza sativa, Sorghum bicolor, Vitis vinifera, Medicago truncatula, and Glycine max). PODC has been greatly improved in the database functions for data mining (e.g., GEN construction with an arbitrary gene(s), a statistical test for gene sets and gene expression data). Since the original descriptions of experimental conditions (e.g., developmental stages, treatments, organs) for each RNA-seq dataset in SRA are not practically controlled, we also organized the descriptions into easily accessed and manipulated formats. In PODC, the controlled descriptions of experimental conditions are provided to easily compare gene expressions among experimental conditions. The records for highly-reliable functional annotations, obtained from NLP and manual curation processes, for genes have considerably increased (approximately 18,000 records). With the comprehensive omics and knowledge-based information, PODC provides a powerful platform for identification of novel genes and biological functions.

    This research was supported by Research Funding for Computational Software Supporting Program from Meiji University.