Chisato Yamasaki

Towards BioDBcore: a community-defined information specification for biological databases

The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources; and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.

BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains

The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data. In this review, we briefly introduce the themes covered by these sub-groups. The observations made, conclusions drawn, and software development projects that emerged from these activities are discussed.

Comparative Genome Analysis of Three Eukaryotic Parasites with Differing Abilities To Transform Leukocytes Reveals Key Mediators of Theileria-Induced Leukocyte Transformation

ABSTRACT We sequenced the genome of Theileria orientalis, a tick-borne apicomplexan protozoan parasite of cattle. The focus of this study was a comparative genome analysis of T. orientalis relative to other highly pathogenic Theileria species, T. parva and T. annulata. T. parva and T. annulata induce transformation of infected cells of lymphocyte or macrophage/monocyte lineages; in contrast, T. orientalis does not induce uncontrolled proliferation of infected leukocytes and multiplies predominantly within infected erythrocytes. While synteny across homologous chromosomes of the three Theileria species was found to be well conserved overall, subtelomeric structures were found to differ substantially, as T. orientalis lacks the large tandemly arrayed subtelomere-encoded variable secreted protein-encoding gene family. Moreover, expansion of particular gene families by gene duplication was found in the genomes of the two transforming Theileria species, most notably, the TashAT/TpHN and Tar/Tpr gene families. Gene families that are present only in T. parva and T. annulata and not in T. orientalis, Babesia bovis, or Plasmodium were also identified. Identification of differences between the genome sequences of Theileria species with different abilities to transform and immortalize bovine leukocytes will provide insight into proteins and mechanisms that have evolved to induce and regulate this process. The T. orientalis genome database is available at http://totdb.czc.hokudai.ac.jp/. IMPORTANCE Cancer-like growth of leukocytes infected with malignant Theileria parasites is a unique cellular event, as it involves the transformation and immortalization of one eukaryotic cell by another. In this study, we sequenced the whole genome of a nontransforming Theileria species, Theileria orientalis, and compared it to the published sequences representative of two malignant, transforming species, T. parva and T. annulata. The genome-wide comparison of these parasite species highlights significant genetic diversity that may be associated with evolution of the mechanism(s) deployed by an intracellular eukaryotic parasite to transform its host cell. Cancer-like growth of leukocytes infected with malignant Theileria parasites is a unique cellular event, as it involves the transformation and immortalization of one eukaryotic cell by another. In this study, we sequenced the whole genome of a nontransforming Theileria species, Theileria orientalis, and compared it to the published sequences representative of two malignant, transforming species, T. parva and T. annulata. The genome-wide comparison of these parasite species highlights significant genetic diversity that may be associated with evolution of the mechanism(s) deployed by an intracellular eukaryotic parasite to transform its host cell.

H-InvDB in 2009: extended database and data mining resources for human genes and transcripts

We report the extended database and data mining resources newly released in the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). H-InvDB is a comprehensive annotation resource of human genes and transcripts, and consists of two main views and six sub-databases. The latest release of H-InvDB (release 6.2) provides the annotation for 219 765 human transcripts in 43 159 human gene clusters based on human full-length cDNAs and mRNAs. H-InvDB now provides several new annotation features, such as mapping of microarray probes, new gene models, relation to known ncRNAs and information from the Glycogene database. H-InvDB also provides useful data mining resources—‘Navigation search’, ‘H-InvDB Enrichment Analysis Tool (HEAT)’ and web service APIs. ‘Navigation search’ is an extended search system that enables complicated searches by combining 16 different search options. HEAT is a data mining tool for automatically identifying features specific to a given human gene set. HEAT searches for H-InvDB annotations that are significantly enriched in a user-defined gene set, as compared with the entire H-InvDB representative transcripts. H-InvDB now has web service APIs of SOAP and REST to allow the use of H-InvDB data in programs, providing the users extended data accessibility.

Evola : Ortholog database of all human genes in H-InvDB with manual curation of phylogenetic trees

Orthologs are genes in different species that evolved from a common ancestral gene by speciation. Currently, with the rapid growth of transcriptome data of various species, more reliable orthology information is prerequisite for further studies. However, detection of orthologs could be erroneous if pairwise distance-based methods, such as reciprocal BLAST searches, are utilized. Thus, as a sub-database of H-InvDB, an integrated database of annotated human genes (http://h-invitational.jp/), we constructed a fully curated database of evolutionary features of human genes, called ‘Evola’. In the process of the ortholog detection, computational analysis based on conserved genome synteny and transcript sequence similarity was followed by manual curation by researchers examining phylogenetic trees. In total, 18 968 human genes have orthologs among 11 vertebrates (chimpanzee, mouse, cow, chicken, zebrafish, etc.), either computationally detected or manually curated orthologs. Evola provides amino acid sequence alignments and phylogenetic trees of orthologs and homologs. In ‘dN/dS view’, natural selection on genes can be analyzed between human and other species. In ‘Locus maps’, all transcript variants and their exon/intron structures can be compared among orthologous gene loci. We expect the Evola to serve as a comprehensive and reliable database to be utilized in comparative analyses for obtaining new knowledge about human genes. Evola is available at http://www.h-invitational.jp/evola/.

CIPRO 2.5: Ciona intestinalis protein database, a unique integrated repository of large-scale omics data, bioinformatic analyses and curated annotation, with user rating and reviewing functionality

The Ciona intestinalis protein database (CIPRO) is an integrated protein database for the tunicate species C. intestinalis. The database is unique in two respects: first, because of its phylogenetic position, Ciona is suitable model for understanding vertebrate evolution; and second, the database includes original large-scale transcriptomic and proteomic data. Ciona intestinalis has also been a favorite of developmental biologists. Therefore, large amounts of data exist on its development and morphology, along with a recent genome sequence and gene expression data. The CIPRO database is aimed at collecting those published data as well as providing unique information from unpublished experimental data, such as 3D expression profiling, 2D-PAGE and mass spectrometry-based large-scale analyses at various developmental stages, curated annotation data and various bioinformatic data, to facilitate research in diverse areas, including developmental, comparative and evolutionary biology. For medical and evolutionary research, homologs in humans and major model organisms are intentionally included. The current database is based on a recently developed KH model containing 36 034 unique sequences, but for higher usability it covers 89 683 all known and predicted proteins from all gene models for this species. Of these sequences, more than 10 000 proteins have been manually annotated. Furthermore, to establish a community-supported protein database, these annotations are open to evaluation by users through the CIPRO website. CIPRO 2.5 is freely accessible at http://cipro.ibio.jp/2.5.

H-InvDB in 2013: an omics study platform for human functional gene and transcript discovery

H-InvDB (http://www.h-invitational.jp/) is a comprehensive human gene database started in 2004. In the latest version, H-InvDB 8.0, a total of 244 709 human complementary DNA was mapped onto the hg19 reference genome and 43 829 gene loci, including nonprotein-coding ones, were identified. Of these loci, 35 631 were identified as potential protein-coding genes, and 22 898 of these were identical to known genes. In our analysis, 19 309 annotated genes were specific to H-InvDB and not found in RefSeq and Ensembl. In fact, 233 genes of the 19 309 turned out to have protein functions in this version of H-InvDB; they were annotated as unknown protein functions in the previous version. Furthermore, 11 genes were identified as known Mendelian disorder genes. It is advantageous that many biologically functional genes are hidden in the H-InvDB unique genes. As large-scale proteomic projects have been conducted to elucidate the functions of all human proteins, we have enhanced the proteomic information with an advanced protein view and new subdatabase of protein complexes (Protein Complex Database with quality index). We propose that H-InvDB is an important resource for finding novel candidate targets for medical care and drug development.

VarySysDB: a human genetic polymorphism database based on all H-InvDB transcripts

Creation of a vast variety of proteins is accomplished by genetic variation and a variety of alternative splicing transcripts. Currently, however, the abundant available data on genetic variation and the transcriptome are stored independently and in a dispersed fashion. In order to provide a research resource regarding the effects of human genetic polymorphism on various transcripts, we developed VarySysDB, a genetic polymorphism database based on 187 156 extensively annotated matured mRNA transcripts from 36 073 loci provided by H-InvDB. VarySysDB offers information encompassing published human genetic polymorphisms for each of these transcripts separately. This allows comparisons of effects derived from a polymorphism on different transcripts. The published information we analyzed includes single nucleotide polymorphisms and deletion–insertion polymorphisms from dbSNP, copy number variations from Database of Genomic Variants, short tandem repeats and single amino acid repeats from H-InvDB and linkage disequilibrium regions from D-HaploDB. The information can be searched and retrieved by features, functions and effects of polymorphisms, as well as by keywords. VarySysDB combines two kinds of viewers, GBrowse and Sequence View, to facilitate understanding of the positional relationship among polymorphisms, genome, transcripts, loci and functional domains. We expect that VarySysDB will yield useful information on polymorphisms affecting gene expression and phenotypes. VarySysDB is available at http://h-invitational.jp/varygene/.

A prioritization analysis of disease association by data-mining of functional annotation of human genes

Complex diseases result from contributions of multiple genes that act in concert through pathways. Here we present a method to prioritize novel candidates of disease-susceptibility genes depending on the biological similarities to the known disease-related genes. The extent of disease-susceptibility of a gene is prioritized by analyzing seven features of human genes captured in H-InvDB. Taking rheumatoid arthritis (RA) and prostate cancer (PC) as two examples, we evaluated the efficiency of our method. Highly scored genes obtained included TNFSF12 and OSM as candidate disease genes for RA and PC, respectively. Subsequent characterization of these genes based upon an extensive literature survey reinforced the validity of these highly scored genes as possible disease-susceptibility genes. Our approach, Prioritization ANalysis of Disease Association (PANDA), is an efficient and cost-effective method to narrow down a large set of genes into smaller subsets that are most likely to be involved in the disease pathogenesis.

Full-length transcriptome-based H-InvDB throws a new light on chromosome-centric proteomics.

H-Invitational Database (H-InvDB; http://hinv.jp/ ) is an integrated database of all human genes and transcripts that started in an international collaborative research project for establishing a functional annotation database of human full-length cDNAs. Because H-InvDB contains an abundance of information for human transcripts, including not only well-characterized protein-coding transcripts but also those without experimental evidence at the protein level, this will be a useful information resource for identifying novel and uncharacterized human proteins (so-called missing proteins). By extending predicted protein data in H-InvDB, we developed the H-Inv Extended Protein Database (H-EPD; http://hinv.jp/hinv/h-epd/ ). From now on, we plan to carry out a database-driven proteome research that makes full use of H-EPD to promote discoveries in the current and future C-HPP. Furthermore, we will push forward with the integration of genome, transcriptome, and proteome databases using a unique tool for connecting distributed databases and would like to develop a knowledge discovery system by incorporating data mining tools.