P1122Plant Omics Data Center (PODC) : The Integrated Web Repository for Intra- and Interspecies Gene Expression Networks
Similarity in expression profile of genes is an important clue to estimate their physiological function and a mechanism underlying regulation of the gene expression. Analysis of Gene Expression Network (GEN), which is built based on the gene expression similarity, has contributed to a comprehensive understanding of functional characterization of genes in the genome. With recent innovation in DNA sequencing technique, transcriptome analysis (RNA-Seq) has been widely employed in not only a model plant, such as Arabidopsis, but also non-model plants such as grain crops, horticultural crops and fruit trees. The integrated analysis against the large-scale omics data from many different species open a whole new field of systems biology, for-making new discovery of biological mechanism.
We have incorporated mRNA-Seq samples from eight plant species (Arabidopsis thaliana, Solanum lycopersicum, Solanum tuberosum, Oryza sativa, Sorghum bicolor, Vitis vinifera, Medicago truncatula, and Glycine max) from the public sequence read archive, digitally profiled the entire gene expression profiles, and drawn GENs, which were constructed by Correspondence Analysis (CA). In order to understand the evolutionary conservation of GENs in multiple species, GENs were linked according to the orthology relationships among gene across different species. In addition to the gene expression data, high-quality functional annotations for genes are required to understand biological roles of the genes. To provide information on GEN and precise functional annotations, we have improved functional annotations by automated (Natural Language Processing; NLP) and manual curation. The omics and knowledge information are freely available from out web-database Plant Omics Data Center (http://bioinf.mind.meiji.ac.jp/podc/)