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/.

Although stakeholder involvement in policymaking is attracting attention in the fields of medicine and healthcare, a practical methodology has not yet been established. Rare-disease policy, specifically research priority setting for the allocation of limited research resources, is an area where evidence generation through stakeholder involvement is expected to be effective. We generated evidence for rare-disease policymaking through stakeholder involvement and explored effective collaboration among stakeholders.

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 2010 was the third in a series of meetings hosted by the Database Center for Life Sciences (DBCLS) in Tokyo, Japan. The overall goal of the BioHackathon series is to improve the quality and accessibility of life science research data on the Web by bringing together representatives from public databases, analytical tool providers, and cyber-infrastructure researchers to jointly tackle important challenges in the area of in silico biological research.

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.

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/.

The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level. Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following: integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms, non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information build 34 assembly) may contain misassembled or missing regions. We found that 6.5% of the human gene candidates (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for non-protein-coding RNA genes. In addition, among 72,027 uniquely mapped SNPs and insertions/deletions localized within human genes, 13,215 nonsynonymous SNPs, 315 nonsense SNPs, and 452 indels occurred in coding regions. Together with 25 polymorphic microsatellite repeats present in coding regions, they may alter protein structure, causing phenotypic effects or resulting in disease. The H-InvDB platform represents a substantial contribution to resources needed for the exploration of human biology and pathology.

Transcriptome Auto-annotation Conducting Tool (TACT) is a newly developed web-based automated tool for conducting functional annotation of transcripts by the integration of sequence similarity searches and functional motif predictions. We developed the TACT system by integrating two kinds of similarity searches, FASTY and BLASTX, against protein sequence databases, UniProtKB (Swiss-Prot/TrEMBL) and RefSeq, and a unified motif prediction program, InterProScan, into the ORF-prediction pipeline originally designed for the 'H-Invitational' human transcriptome annotation project. This system successively applies these constituent programs to an mRNA sequence in order to predict the most plausible ORF and the function of the protein encoded. In this study, we applied the TACT system to 19 574 non-redundant human transcripts registered in H-InvDB and evaluated its predictive power by the degree of agreement with human-curated functional annotation in H-InvDB. As a result, the TACT system could assign functional description to 12 559 transcripts (64.2%), the remainder being hypothetical proteins. Furthermore, the overall agreement of functional annotation with H-InvDB, including those transcripts annotated as hypothetical proteins, was 83.9% (16 432/19 574). These results show that the TACT system is useful for functional annotation and that the prediction of ORFs and protein functions is highly accurate and close to the results of human curation. TACT is freely available at http://www.jbirc.aist.go.jp/tact/.

The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009.

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 'd(N)/d(S) 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/.

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.

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.

Here we report the new features and improvements in our latest release of the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/), a comprehensive annotation resource for human genes and transcripts. H-InvDB, originally developed as an integrated database of the human transcriptome based on extensive annotation of large sets of full-length cDNA (FLcDNA) clones, now provides annotation for 120 558 human mRNAs extracted from the International Nucleotide Sequence Databases (INSD), in addition to 54 978 human FLcDNAs, in the latest release H-InvDB_4.6. We mapped those human transcripts onto the human genome sequences (NCBI build 36.1) and determined 34 699 human gene clusters, which could define 34 057 (98.1%) protein-coding and 642 (1.9%) non-protein-coding loci; 858 (2.5%) transcribed loci overlapped with predicted pseudogenes. For all these transcripts and genes, we provide comprehensive annotation including gene structures, gene functions, alternative splicing variants, functional non-protein-coding RNAs, functional domains, predicted sub cellular localizations, metabolic pathways, predictions of protein 3D structure, mapping of SNPs and microsatellite repeat motifs, co-localization with orphan diseases, gene expression profiles, orthologous genes, protein-protein interactions (PPI) and annotation for gene families. The current H-InvDB annotation resources consist of two main views: Transcript view and Locus view and eight sub-databases: the DiseaseInfo Viewer, H-ANGEL, the Clustering Viewer, G-integra, the TOPO Viewer, Evola, the PPI view and the Gene family/group.