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BackgroundProtein-protein interactions play a fundamental role in elucidating the molecular mechanisms of biomolecular function, signal transductions and metabolic pathways of living organisms. Although high-throughput technologies such as yeast two-hybrid system and affinity purification followed by mass spectrometry are widely used in model organisms, the progress of protein-protein interactions detection in plants is rather slow. With this motivation, our work presents a computational approach to predict protein-protein interactions in Oryza sativa.ResultsTo better understand the interactions of proteins in Oryza sativa, we have developed PRIN, a Predicted Rice Interactome Network. Protein-protein interaction data of PRIN are based on the interologs of six model organisms where large-scale protein-protein interaction experiments have been applied: yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans), fruit fly (Drosophila melanogaster), human (Homo sapiens), Escherichia coli K12 and Arabidopsis thaliana. With certain quality controls, altogether we obtained 76,585 non-redundant rice protein interaction pairs among 5,049 rice proteins. Further analysis showed that the topology properties of predicted rice protein interaction network are more similar to yeast than to the other 5 organisms. This may not be surprising as the interologs based on yeast contribute nearly 74% of total interactions. In addition, GO annotation, subcellular localization information and gene expression data are also mapped to our network for validation. Finally, a user-friendly web interface was developed to offer convenient database search and network visualization.ConclusionsPRIN is the first well annotated protein interaction database for the important model plant Oryza sativa. It has greatly extended the current available protein-protein interaction data of rice with a computational approach, which will certainly provide further insights into rice functional genomics and systems biology.PRIN is available online at http://bis.zju.edu.cn/prin/.

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Dendrobium officinale L. is an important traditional herb with high commercial value in China. Several bioactive constituents, including polysaccharides and alkaloids, reportedly make major contributions toward the excellent medicinal effect of D. officinale. In this study, the contents of polysaccharides and alkaloids in various organs of D. officinale were measured and compared. We took advantage of transcriptomes from four organs to explore biological mechanisms in the organ-specific distribution of active ingredients in D. officinale. Based on Kyoto Encyclopedia of Genes and Genomes pathways, unigenes related to the enzymes involved in fructose and mannose metabolism and unigenes associated with putative upstream elements of the alkaloid biosynthetic pathway were identified. A large number of candidates, including 35 full-length glycosyltransferase genes and 49 full-length P450 genes, were also identified based on the transcriptome data, and the organ-specific expression pattern of these genes was determined. Furthermore, differential expression of all candidate genes was analyzed in two Dendrobium species, D. nobile L. and D. officinale. The data will supply important clues to exploit useful genes involved in polysaccharide and alkaloid synthesis.