Akihiro Nakaya

The KEGG databases at GenomeNet

The Kyoto Encyclopedia of Genes and Genomes (KEGG) is the primary database resource of the Japanese GenomeNet service (http://www.genome.ad.jp/) for understanding higher order functional meanings and utilities of the cell or the organism from its genome information. KEGG consists of the PATHWAY database for the computerized knowledge on molecular interaction networks such as pathways and complexes, the GENES database for the information about genes and proteins generated by genome sequencing projects, and the LIGAND database for the information about chemical compounds and chemical reactions that are relevant to cellular processes. In addition to these three main databases, limited amounts of experimental data for microarray gene expression profiles and yeast two-hybrid systems are stored in the EXPRESSION and BRITE databases, respectively. Furthermore, a new database, named SSDB, is available for exploring the universe of all protein coding genes in the complete genomes and for identifying functional links and ortholog groups. The data objects in the KEGG databases are all represented as graphs and various computational methods are developed to detect graph features that can be related to biological functions. For example, the correlated clusters are graph similarities which can be used to predict a set of genes coding for a pathway or a complex, as summarized in the ortholog group tables, and the cliques in the SSDB graph are used to annotate genes. The KEGG databases are updated daily and made freely available (http://www.genome.ad.jp/kegg/).

Fabp7 maps to a quantitative trait locus for a schizophrenia endophenotype.

Deficits in prepulse inhibition (PPI) are a biological marker for schizophrenia. To unravel the mechanisms that control PPI, we performed quantitative trait loci (QTL) analysis on 1,010 F2 mice derived by crossing C57BL/6 (B6) animals that show high PPI with C3H/He (C3) animals that show low PPI. We detected six major loci for PPI, six for the acoustic startle response, and four for latency to response peak, some of which were sex-dependent. A promising candidate on the Chromosome 10-QTL was Fabp7 (fatty acid binding protein 7, brain), a gene with functional links to the N-methyl-D-aspartic acid (NMDA) receptor and expression in astrocytes. Fabp7-deficient mice showed decreased PPI and a shortened startle response latency, typical of the QTLs proposed effects. A quantitative complementation test supported Fabp7 as a potential PPI-QTL gene, particularly in male mice. Disruption of Fabp7 attenuated neurogenesis in vivo. Human FABP7 showed altered expression in schizophrenic brains and genetic association with schizophrenia, which were both evident in males when samples were divided by sex. These results suggest that FABP7 plays a novel and crucial role, linking the NMDA, neurodevelopmental, and glial theories of schizophrenia pathology and the PPI endophenotype, with larger or overt effects in males. We also discuss the results from the perspective of fetal programming.

In silico polymorphism analysis for the development of simple sequence repeat and transposon markers and construction of linkage map in cultivated peanut

BackgroundPeanut (Arachis hypogaea) is an autogamous allotetraploid legume (2n = 4x = 40) that is widely cultivated as a food and oil crop. More than 6,000 DNA markers have been developed in Arachis spp., but high-density linkage maps useful for genetics, genomics, and breeding have not been constructed due to extremely low genetic diversity. Polymorphic marker loci are useful for the construction of such high-density linkage maps. The present study used in silico analysis to develop simple sequence repeat-based and transposon-based markers.ResultsThe use of in silico analysis increased the efficiency of polymorphic marker development by more than 3-fold. In total, 926 (34.2%) of 2,702 markers showed polymorphisms between parental lines of the mapping population. Linkage analysis of the 926 markers along with 253 polymorphic markers selected from 4,449 published markers generated 21 linkage groups covering 2,166.4 cM with 1,114 loci. Based on the map thus produced, 23 quantitative trait loci (QTLs) for 15 agronomical traits were detected. Another linkage map with 326 loci was also constructed and revealed a relationship between the genotypes of the FAD2 genes and the ratio of oleic/linoleic acid in peanut seed.ConclusionsIn silico analysis of polymorphisms increased the efficiency of polymorphic marker development, and contributed to the construction of high-density linkage maps in cultivated peanut. The resultant maps were applicable to QTL analysis. Marker subsets and linkage maps developed in this study should be useful for genetics, genomics, and breeding in Arachis. The data are available at the Kazusa DNA Marker Database (http://marker.kazusa.or.jp).

KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters

The identification of orthologous genes in an increasing number of fully sequenced genomes is a challenging issue in recent genome science. Here we present KEGG OC (http://www.genome.jp/tools/oc/), a novel database of ortholog clusters (OCs). The current version of KEGG OC contains 1 176 030 OCs, obtained by clustering 8 357 175 genes in 2112 complete genomes (153 eukaryotes, 1830 bacteria and 129 archaea). The OCs were constructed by applying the quasi-clique-based clustering method to all possible protein coding genes in all complete genomes, based on their amino acid sequence similarities. It is computationally efficient to calculate OCs, which enables to regularly update the contents. KEGG OC has the following two features: (i) It consists of all complete genomes of a wide variety of organisms from three domains of life, and the number of organisms is the largest among the existing databases; and (ii) It is compatible with the KEGG database by sharing the same sets of genes and identifiers, which leads to seamless integration of OCs with useful components in KEGG such as biological pathways, pathway modules, functional hierarchy, diseases and drugs. The KEGG OC resources are accessible via OC Viewer that provides an interactive visualization of OCs at different taxonomic levels.

Nanoparticulation of BCG-CWS for application to bladder cancer therapy

The Mycobacterium bovis Bacille Calmette-Guerin cell wall skeleton (BCG-CWS) could be used to replace live BCG as a bladder cancer drug. However, because BCG-CWS is poorly soluble, has a strong-negative charge, very high molecular weight and heterogeneity in size of tens of μm, it cannot be used in such an application. We report herein on the development of a novel packaging method that permits BCG-CWS to be encapsulated into 166nm-sized lipid particles. The BCG-CWS encapsulated nano particle (CWS-NP) has a high uniformity and can be easily dispersed. Thus, it has the potential for use as a packaging method that would advance the scope of applications of BCG-CWS as a bladder cancer drug. In a functional evaluation, CWS-NP was efficiently taken up by mouse bladder tumor (MBT-2) cells in vitro and inhibited tumor growth in mice bearing MBT-2 tumors. Moreover, intravesically administered CWS-NP showed significant antitumor effects in a rat model with naturally developed bladder cancer. An enhancement in Th1 differentiation by CWS-NP was also confirmed in human T cells. In conclusion, CWS-NP represents a promising delivery system for BCG-CWS for clinical development as a potent bladder cancer drug.

Genotype Matrix Mapping: Searching for Quantitative Trait Loci Interactions in Genetic Variation in Complex Traits

Abstract In order to reveal quantitative trait loci (QTL) interactions and the relationship between various interactions in complex traits, we have developed a new QTL mapping approach, named genotype matrix mapping (GMM), which searches for QTL interactions in genetic variation. The central approach in GMM is the following. (1) Each tested marker is given a virtual matrix, named a genotype matrix (GM), containing intersecting lines and rows equal to the total allele number for that marker in the population analyzed. (2) QTL interactions are then estimated and compared through virtual networks among the GMs. To evaluate the contribution of marker combinations to a quantitative phenotype, the GMM method divides the samples into two non-overlapping subclasses, S0 and S1; the former contains the samples that have a specific genotype pattern to be evaluated, and the latter contains samples that do not. Based on this division, the F-measure is calculated as an index of significance. With the GMM method, we extracted significant marker combinations consisting of one to three interacting markers. The results indicated there were multiple QTL interactions affecting the phenotype (flowering date). GMM will be a valuable approach to identify QTL interactions in genetic variation of a complex trait within a variety of organisms.

Parallel Branch-and-Bound Graph Search for Correlated Association Rules

There have been proposed efficient ways of enumerating all the association rules that are interesting with respect to support, confidence, or other measures. In contrast, we examine the optimization problem of computing the optimal association rule that maximizes the significance of the correlation between the assumption and the conclusion of the rule. We propose a parallel branch-and-bound graph search algorithm tailored to this problem. The key features of the design are (1) novel branch-and-bound heuristics, and (2) a rule of rewriting conjunctions that avoids maintaining the list of visited nodes. Experiments on two different types of large-scale shared-memory multi-processors confirm that the speed-up of the computation time scales almost linearly with the number of processors, and the size of search space could be dramatically reduced by the branch-and-bound heuristics.

Plant Genome DataBase Japan (PGDBj): A Portal Website for the Integration of Plant Genome-Related Databases

The Plant Genome DataBase Japan (PGDBj, http://pgdbj.jp/?ln=en) is a portal website that aims to integrate plant genome-related information from databases (DBs) and the literature. The PGDBj is comprised of three component DBs and a cross-search engine, which provides a seamless search over the contents of the DBs. The three DBs are as follows. (i) The Ortholog DB, providing gene cluster information based on the amino acid sequence similarity. Over 500,000 amino acid sequences of 20 Viridiplantae species were subjected to reciprocal BLAST searches and clustered. Sequences from plant genome DBs (e.g. TAIR10 and RAP-DB) were also included in the cluster with a direct link to the original DB. (ii) The Plant Resource DB, integrating the SABRE DB, which provides cDNA and genome sequence resources accumulated and maintained in the RIKEN BioResource Center and National BioResource Projects. (iii) The DNA Marker DB, providing manually or automatically curated information of DNA markers, quantitative trait loci and related linkage maps, from the literature and external DBs. As the PGDBj targets various plant species, including model plants, algae, and crops important as food, fodder and biofuel, researchers in the field of basic biology as well as a wide range of agronomic fields are encouraged to perform searches using DNA sequences, gene names, traits and phenotypes of interest. The PGDBj will return the search results from the component DBs and various types of linked external DBs.

RNA secondary structure prediction using highly parallel computers

An RNA secondary structure prediction method using a highly parallel computer is reported. We focus on finding thermodynamically stable structures of a single-stranded RNA molecule. Our approach is based on a parallel combinatorial method which calculates the free energy of a molecule as the sum of the free energies of all the physically possible hydrogen bonds. Our parallel algorithm finds many highly stable structures all at once, while most of the conventional prediction methods find only the most stable structure. The important idea in our algorithm is search tree pruning, with dynamic load balancing across the processor elements in a parallel computer. Software tools for visualization and classification of secondary structures are also presented using the sequence of cadang-cadang coconut viroid as an example. Our software system runs on CM-5.

Genes associated with the progression of neurofibrillary tangles in Alzheimer’s disease

The spreading of neurofibrillary tangles (NFTs), intraneuronal aggregates of highly phosphorylated microtubule-associated protein tau, across the human brain is correlated with the cognitive severity of Alzheimer’s disease (AD). To identify genes relevant to NFT expansion defined by the Braak stage, we conducted whole-genome exon array analysis with an exploratory sample set consisting of 213 human post-mortem brain tissue specimens from the entorinal, temporal and frontal cortices of 71 brain-donor subjects: Braak NFT stages 0 (N=13), I–II (N=20), III–IV (N=19) and V–VI (N=19). We identified eight genes, RELN, PTGS2, MYO5C, TRIL, DCHS2, GRB14, NPAS4 and PHYHD1, associated with the Braak stage. The expression levels of three genes, PHYHD1, MYO5C and GRB14, exhibited reproducible association on real-time quantitative PCR analysis. In another sample set, including control subjects (N=30), and in patients with late-onset AD (N=37), dementia with Lewy bodies (N=17) and Parkinson disease (N=36), the expression levels of two genes, PHYHD1 and MYO5C, were obviously associated with late-onset AD. Protein–protein interaction network analysis with a public database revealed that PHYHD1 interacts with MYO5C via POT1, and PHYHD1 directly interacts with amyloid beta-peptide 42. It is thus likely that functional failure of PHYHD1 and MYO5C could lead to AD development.