Takeru Nakazato

Gendoo: Functional profiling of gene and disease features using MeSH vocabulary

Genome-wide data enables us to clarify the underlying molecular mechanisms of complex phenotypes. The Online Mendelian Inheritance in Man (OMIM) is a widely employed knowledge base of human genes and genetic disorders for biological researchers. However, OMIM has not been fully exploited for omics analysis because its bibliographic data structure is not suitable for computer automation. Here, we characterized diseases and genes by generating feature profiles of associated drugs, biological phenomena and anatomy with the MeSH (Medical Subject Headings) vocabulary. We obtained 1 760 054 pairs of OMIM entries and MeSH terms by utilizing the full set of MEDLINE articles. We developed a web-based application called Gendoo (gene, disease features ontology-based overview system) to visualize these profiles. By comparing feature profiles of types 1 and 2 diabetes, we clearly illustrated their differences: type 1 diabetes is an autoimmune disease (P-value = 4.55 × 10−5) and type 2 diabetes is related to obesity (P-value = 1.18 × 10−15). Gendoo and the developed feature profiles should be useful for omics analysis from molecular and clinical viewpoints. Gendoo is available at http://gendoo.dbcls.jp/.

MeSH ORA framework: R/Bioconductor packages to support MeSH over-representation analysis

BackgroundIn genome-wide studies, over-representation analysis (ORA) against a set of genes is an essential step for biological interpretation. Many gene annotation resources and software platforms for ORA have been proposed. Recently, Medical Subject Headings (MeSH) terms, which are annotations of PubMed documents, have been used for ORA. MeSH enables the extraction of broader meaning from the gene lists and is expected to become an exhaustive annotation resource for ORA. However, the existing MeSH ORA software platforms are still not sufficient for several reasons.ResultsIn this work, we developed an original MeSH ORA framework composed of six types of R packages, including MeSH.db, MeSH.AOR.db, MeSH.PCR.db, the org.MeSH.XXX.db-type packages, MeSHDbi, and meshr.ConclusionsUsing our framework, users can easily conduct MeSH ORA. By utilizing the enriched MeSH terms, related PubMed documents can be retrieved and saved on local machines within this framework.

Experimental design-based functional mining and characterization of high-throughput sequencing data in the sequence read archive.

High-throughput sequencing technology, also called next-generation sequencing (NGS), has the potential to revolutionize the whole process of genome sequencing, transcriptomics, and epigenetics. Sequencing data is captured in a public primary data archive, the Sequence Read Archive (SRA). As of January 2013, data from more than 14,000 projects have been submitted to SRA, which is double that of the previous year. Researchers can download raw sequence data from SRA website to perform further analyses and to compare with their own data. However, it is extremely difficult to search entries and download raw sequences of interests with SRA because the data structure is complicated, and experimental conditions along with raw sequences are partly described in natural language. Additionally, some sequences are of inconsistent quality because anyone can submit sequencing data to SRA with no quality check. Therefore, as a criterion of data quality, we focused on SRA entries that were cited in journal articles. We extracted SRA IDs and PubMed IDs (PMIDs) from SRA and full-text versions of journal articles and retrieved 2748 SRA ID-PMID pairs. We constructed a publication list referring to SRA entries. Since, one of the main themes of -omics analyses is clarification of disease mechanisms, we also characterized SRA entries by disease keywords, according to the Medical Subject Headings (MeSH) extracted from articles assigned to each SRA entry. We obtained 989 SRA ID-MeSH disease term pairs, and constructed a disease list referring to SRA data. We previously developed feature profiles of diseases in a system called “Gendoo”. We generated hyperlinks between diseases extracted from SRA and the feature profiles of it. The developed project, publication and disease lists resulting from this study are available at our web service, called “DBCLS SRA” (http://sra.dbcls.jp/). This service will improve accessibility to high-quality data from SRA.

Superoxide dismutases, SOD1 and SOD2, play a distinct role in the fat body during pupation in silkworm Bombyx mori.

One way that aerobic biological systems counteract the generation of reactive oxygen species (ROS) is with superoxide dismutase proteins SOD1 and SOD2 that metabolize superoxide radicals to molecular oxygen and hydrogen peroxide or scavenge oxygen radicals produced by the extensive oxidation-reduction and electron-transport reactions that occur in mitochondria. We characterized SOD1 and SOD2 of Bombyx mori isolated from the fat body of larvae. Immunological analysis demonstrated the presence of BmSOD1 and BmSOD2 in the silk gland, midgut, fat body, Malpighian tubules, testis and ovary from larvae to adults. We found that BmSOD2 had a unique expression pattern in the fat body through the fifth instar larval developmental stage. The anti-oxidative functions of BmSOD1 and BmSOD2 were assessed by exposing larvae to insecticide rotenone or vasodilator isosorbide dinitrate, which is an ROS generator in BmN4 cells; however, exposure to these compounds had no effect on the expression levels of either BmSOD protein. Next, we investigated the physiological role of BmSOD1 and BmSOD2 under environmental oxidative stress, applied through whole-body UV irradiation and assayed using quantitative RT-PCR, immunoblotting and microarray analysis. The mRNA expression level of both BmSOD1 and BmSOD2 was markedly increased but protein expression level was increased only slightly. To examine the differences in mRNA and protein level due to UV irradiation intensity, we performed microarray analysis. Gene set enrichment analysis revealed that genes in the insulin signaling pathway and PPAR signaling pathway were significantly up-regulated after 6 and 12 hours of UV irradiation. Taken together, the activities of BmSOD1 and BmSOD2 may be related to the response to UV irradiation stress in B. mori. These results suggest that BmSOD1 and BmSOD2 modulate environmental oxidative stress in the cell and have a specific role in fat body of B. mori during pupation.

Identification of functional enolase genes of the silkworm Bombyx mori from public databases with a combination of dry and wet bench processes

BackgroundVarious insect species have been added to genomic databases over the years. Thus, researchers can easily obtain online genomic information on invertebrates and insects. However, many incorrectly annotated genes are included in these databases, which can prevent the correct interpretation of subsequent functional analyses. To address this problem, we used a combination of dry and wet bench processes to select functional genes from public databases.ResultsEnolase is an important glycolytic enzyme in all organisms. We used a combination of dry and wet bench processes to identify functional enolases in the silkworm Bombyx mori (BmEno). First, we detected five annotated enolases from public databases using a Hidden Markov Model (HMM) search, and then through cDNA cloning, Northern blotting, and RNA-seq analysis, we revealed three functional enolases in B. mori: BmEno1, BmEno2, and BmEnoC. BmEno1 contained a conserved key amino acid residue for metal binding and substrate binding in other species. However, BmEno2 and BmEnoC showed a change in this key amino acid. Phylogenetic analysis showed that BmEno2 and BmEnoC were distinct from BmEno1 and other enolases, and were distributed only in lepidopteran clusters. BmEno1 was expressed in all of the tissues used in our study. In contrast, BmEno2 was mainly expressed in the testis with some expression in the ovary and suboesophageal ganglion. BmEnoC was weakly expressed in the testis. Quantitative RT-PCR showed that the mRNA expression of BmEno2 and BmEnoC correlated with testis development; thus, BmEno2 and BmEnoC may be related to lepidopteran-specific spermiogenesis.ConclusionsWe identified and characterized three functional enolases from public databases with a combination of dry and wet bench processes in the silkworm B. mori. In addition, we determined that BmEno2 and BmEnoC had species-specific functions. Our strategy could be helpful for the detection of minor genes and functional genes in non-model organisms from public databases.

Functional Interpretation of Omics Data by Profiling Genes and Diseases Using MeSH–Controlled Vocabulary

One of the major aims of molecular biology and medical science is to understand disease mechanisms. A genetic disorder is a disease caused by abnormalities in genes and chromosomes, and researchers often report the identification of disease-relevant genes and correlations between phenotypes and genotypes (Butte & Kohane 2006; Lamb 2007; PerezIratxeta et al. 2002, 2005, 2007). Omics analysis using microarray, new generation sequencing (NGS) technology, and mass spectrometry is widely employed for determining genome sequences and profiling gene expression. Changes in gene expression on a genome-wide scale can be detected by omics analysis, which provides various types of huge datasets. These data are often archived in public databases; nucleotide sequences in the DDBJ/EMBL/GenBank International Nucleotide Sequence Database (INSD) (Cochrane et al. 2011), gene expression in Gene Expression Omnibus (GEO) (Barrett et al. 2011), and journal articles in MEDLINE. Currently, research cannot continue without the use of these databases. In Japan, the Database Center for Life Science (DBCLS) has developed infrastructure for researchers to access and easily reuse these data by providing index sites such as INSD and GEO yellow pages and by constructing a portal site for life science databases and tools. Researchers can easily analyze public data in conjunction with their own omics data. Here we present an analytical method to clarify the associations between genes and diseases. We characterized genes and diseases by assigning a MeSH-controlled vocabulary (Nakazato et al. 2008, 2009). Our objective was to help interpret omics data from molecular and clinical aspects by comparing these feature profiles.

Construction of a simple evaluation system for the intestinal absorption of an orally administered medicine using Bombyx mori larvae

Human intestinal absorption is estimated using a human colon carcinoma cell line (Caco-2) cells from human colorectal adenocarcinoma, intestinal perfusion, or a mammalian model. These current evaluation systems are limited in their ability to estimate human intestinal absorption. In addition, in vivo evaluation systems using laboratory animals such as mice and rats entail animal ethics problems, and it is difficult to screen compounds on a large scale at the drug discovery stage. Thus, we propose the use of Bombyx mori larvae for evaluation of intestinal absorption of compounds as an alternative system in this study. First, to compare the characteristics among Caco-2 cells, human intestine, and B. mori larval midgut, we analyzed their RNA-seq data, and we found 26 drug transporters common to humans and B. mori. Next, we quantitatively developed an oral administration technique in B. mori and established a method using silkworm B. mori larvae that can easily estimate the intestinal permeability of compounds. Consequently, we could determine the dose and technique for oral administration in B. mori larvae. We also developed a B. mori model to evaluate the intestinal permeability of orally administered. Our constructed evaluation system will be useful for evaluating intestinal permeability in medical drug development.

Calculating the quality of public high-throughput sequencing data to obtain a suitable subset for reanalysis from the Sequence Read Archive

Abstract It is important for public data repositories to promote the reuse of archived data. In the growing field of omics science, however, the increasing number of submissions of high-throughput sequencing (HTSeq) data to public repositories prevents users from choosing a suitable data set from among the large number of search results. Repository users need to be able to set a threshold to reduce the number of results to obtain a suitable subset of high-quality data for reanalysis. We calculated the quality of sequencing data archived in a public data repository, the Sequence Read Archive (SRA), by using the quality control software FastQC. We obtained quality values for 1 171 313 experiments, which can be used to evaluate the suitability of data for reuse. We also visualized the data distribution in SRA by integrating the quality information and metadata of experiments and samples. We provide quality information of all of the archived sequencing data, which enable users to obtain sufficient quality sequencing data for reanalyses. The calculated quality data are available to the public in various formats. Our data also provide an example of enhancing the reuse of public data by adding metadata to published research data by a third party.