MPIC: a mitochondrial protein import components database for plant and non-plant species.

In the 2 billion years since the endosymbiotic event that gave rise to mitochondria, variations in mitochondrial protein import have evolved across different species. With the genomes of an increasing number of plant species sequenced, it is possible to gain novel insights into mitochondrial protein import pathways. We have generated the Mitochondrial Protein Import Components (MPIC) Database (DB; http://www.plantenergy.uwa.edu.au/applications/mpic) providing searchable information on the protein import apparatus of plant and non-plant mitochondria. An in silico analysis was carried out, comparing the mitochondrial protein import apparatus from 24 species representing various lineages from Saccharomyces cerevisiae (yeast) and algae to Homo sapiens (human) and higher plants, including Arabidopsis thaliana (Arabidopsis), Oryza sativa (rice) and other more recently sequenced plant species. Each of these species was extensively searched and manually assembled for analysis in the MPIC DB. The database presents an interactive diagram in a user-friendly manner, allowing users to select their import component of interest. The MPIC DB presents an extensive resource facilitating detailed investigation of the mitochondrial protein import machinery and allowing patterns of conservation and divergence to be recognized that would otherwise have been missed. To demonstrate the usefulness of the MPIC DB, we present a comparative analysis of the mitochondrial protein import machinery in plants and non-plant species, revealing plant-specific features that have evolved.

Rice DB: an Oryza Information Portal linking annotation, subcellular location, function, expression, regulation, and evolutionary information for rice and Arabidopsis.

Omics research in Oryza sativa (rice) relies on the use of multiple databases to obtain different types of information to define gene function. We present Rice DB, an Oryza information portal that is a functional genomics database, linking gene loci to comprehensive annotations, expression data and the subcellular location of encoded proteins. Rice DB has been designed to integrate the direct comparison of rice with Arabidopsis (Arabidopsis thaliana), based on orthology or 'expressology', thus using and combining available information from two pre-eminent plant models. To establish Rice DB, gene identifiers (more than 40 types) and annotations from a variety of sources were compiled, functional information based on large-scale and individual studies was manually collated, hundreds of microarrays were analysed to generate expression annotations, and the occurrences of potential functional regulatory motifs in promoter regions were calculated. A range of computational subcellular localization predictions were also run for all putative proteins encoded in the rice genome, and experimentally confirmed protein localizations have been collated, curated and linked to functional studies in rice. A single search box allows anything from gene identifiers (for rice and/or Arabidopsis), motif sequences, subcellular location, to keyword searches to be entered, with the capability of Boolean searches (such as AND/OR). To demonstrate the utility of Rice DB, several examples are presented including a rice mitochondrial proteome, which draws on a variety of sources for subcellular location data within Rice DB. Comparisons of subcellular location, functional annotations, as well as transcript expression in parallel with Arabidopsis reveals examples of conservation between rice and Arabidopsis, using Rice DB (http://ricedb.plantenergy.uwa.edu.au).