BodyParts3D is a dictionary-type database for anatomy in which anatomical concepts are represented by 3D structure data that specify corresponding segments of a 3D whole-body model for an adult human male. It encompasses morphological and geometrical knowledge in anatomy and complements ontological representation. Moreover, BodyParts3D introduces a universal coordinate system in human anatomy, which may facilitate management of samples and data in biomedical research and clinical practice. As of today, 382 anatomical concepts, sufficient for mapping materials in most molecular medicine experiments, have been specified. Expansion of the dictionary by adding further segments and details to the whole-body model will continue in collaboration with clinical researchers until sufficient resolution and accuracy for most clinical application are achieved. BodyParts3D is accessible at: http://lifesciencedb.jp/ag/bp3d/.

The contiguous 874.423 base pair sequence corresponding to the 50.0-68.8 min region on the genetic map of the Escherichia coli K-12 (W3110) was constructed by the determination of DNA sequences in the 50.0-57.9 min region (360 kb) and two large (100 kb in all) and five short gaps in the 57.9-68.8 min region whose sequences had been registered in the DNA databases. We analyzed its sequence features and found that this region contained at least 894 potential open reading frames (ORFs), of which 346 (38.7%) were previously reported, 158 (17.7%) were homologous to other known genes, 232 (26.0%) were identical or similar to hypothetical genes registered in databases, and the remaining 158 (17.7%) showed no significant similarity to any other genes. A homology search of the ORFs also identified several new gene clusters. Those include two clusters of fimbrial genes, a gene cluster of three genes encoding homologues of the human long chain fatty acid degradation enzyme complex in the mitochondrial membrane, a cluster of at least nine genes involved in the utilization of ethanolamine, a cluster of the secondary set of 11 hyc genes participating in the formate hydrogenlyase reaction and a cluster of five genes coding for the homologues of degradation enzymes for aromatic hydrocarbons in Pseudomonas putida. We also noted a variety of novel genes, including two ORFs, which were homologous to the putative genes encoding xanthine dehydrogenase in the fly and a protein responsible for axonal guidance and outgrowth of the rat, mouse and nematode. An isoleucine tRNA gene, designated ileY, was also newly identified at 60.0 min.

TogoVar (https://togovar.org) is a database that integrates allele frequencies derived from Japanese populations and provides annotations for variant interpretation. First, a scheme to reanalyze individual-level genome sequence data deposited in the Japanese Genotype-phenotype Archive (JGA), a controlled-access database, was established to make allele frequencies publicly available. As more Japanese individual-level genome sequence data are deposited in JGA, the sample size employed in TogoVar is expected to increase, contributing to genetic study as reference data for Japanese populations. Second, public datasets of Japanese and non-Japanese populations were integrated into TogoVar to easily compare allele frequencies in Japanese and other populations. Each variant detected in Japanese populations was assigned a TogoVar ID as a permanent identifier. Third, these variants were annotated with molecular consequence, pathogenicity, and literature information for interpreting and prioritizing variants. Here, we introduce the newly developed TogoVar database that compares allele frequencies among Japanese and non-Japanese populations and describes the integrated annotations.

Accurate genotype imputation requires large-scale reference panel datasets. When conducting genotype imputation on the Japanese population, researchers can use such datasets under collaborative studies or controlled access conditions in public databases. We developed the NBDC-DDBJ imputation server, which securely provides users with a web user interface to execute genotype imputation on the server. Our benchmarking analysis showed that the accuracy of genotype imputation was improved by leveraging controlled access datasets to increase the number of haplotypes available for analysis compared to using publicly available reference panels such as the 1000 Genomes Project. The NBDC-DDBJ imputation server facilitates the use of controlled access datasets for accurate genotype imputation.