READ: RIKEN Expression Array Database

MiR-508-3p promotes proliferation and inhibits apoptosis of middle ear cholesteatoma cells by targeting PTEN/PI3K/AKT pathway

Cholesteatoma of the middle ear is a common disease in otolaryngology, which can lead to serious intracranial and extracranial complications. Recent studies showed that the dysregulation of microRNA may be involved in the formation of middle ear cholesteatoma. This study aimed to explore the regulatory effect of micro ribonucleic acid 508-3p (miR-508-3p) on proliferation and apoptosis of middle ear cholesteatoma cells and excavate its underlying regulatory mechanism. We found miR-508-3p expression was upregulated in tissues and cells of cholesteatoma which was inversely related to the expression of hsa_circ_0000007. Overexpression of miR-508-3p could notably facilitate cholesteatoma cell proliferation. Luciferase reporter assay showed that miR-508-3p bound the 3'-untranslated region of its downstream mRNA PTEN. Gain and loss of functions of miR-508-3p were performed to identify their roles in the biological behaviors of cholesteatoma cells, including proliferation and apoptosis. Rescue assays confirmed that PTEN could reverse the effect of miR-508-3p overexpression on cell proliferation. In a word, this study validated that the development of cholesteatoma may regulated by hsa_circ_0000007/miR-508-3p/ PTEN/ PI3K/Akt axis.

Active Role of the Necrotic Zone in Desensitization of Hypoxic Macrophages and Regulation of CSC-Fate: A hypothesis

Fast-proliferating cancer cells in the hypoxic region face a shortage of oxygen and nutrients, undergo necrotic cell death, and release numerous signaling components. Hypoxia-induced chemo-attractants signal for macrophages/monocytes to clear debris and return the system to steady state. Accordingly, macrophages arrange into pre-necrotic positions, where they are continuously exposed to stress signals. It can thus be hypothesized that gradual alteration of gene expression in macrophages eventually turns off their phagocytic machinery. Uncleared cell corpses within the hypoxic region potentially provide a rich source of building blocks for anaerobic metabolism of cancer stem cells via macropinocytosis, and are conceivably implicated in tumor progression and invasion.

RefEx, a reference gene expression dataset as a web tool for the functional analysis of genes

Gene expression data are exponentially accumulating; thus, the functional annotation of such sequence data from metadata is urgently required. However, life scientists have difficulty utilizing the available data due to its sheer magnitude and complicated access. We have developed a web tool for browsing reference gene expression pattern of mammalian tissues and cell lines measured using different methods, which should facilitate the reuse of the precious data archived in several public databases. The web tool is called Reference Expression dataset (RefEx), and RefEx allows users to search by the gene name, various types of IDs, chromosomal regions in genetic maps, gene family based on InterPro, gene expression patterns, or biological categories based on Gene Ontology. RefEx also provides information about genes with tissue-specific expression, and the relative gene expression values are shown as choropleth maps on 3D human body images from BodyParts3D. Combined with the newly incorporated Functional Annotation of Mammals (FANTOM) dataset, RefEx provides insight regarding the functional interpretation of unfamiliar genes. RefEx is publicly available at http://refex.dbcls.jp/.

Update of the FANTOM web resource: high resolution transcriptome of diverse cell types in mammals

Upon the first publication of the fifth iteration of the Functional Annotation of Mammalian Genomes collaborative project, FANTOM5, we gathered a series of primary data and database systems into the FANTOM web resource (http://fantom.gsc.riken.jp) to facilitate researchers to explore transcriptional regulation and cellular states. In the course of the collaboration, primary data and analysis results have been expanded, and functionalities of the database systems enhanced. We believe that our data and web systems are invaluable resources, and we think the scientific community will benefit for this recent update to deepen their understanding of mammalian cellular organization. We introduce the contents of FANTOM5 here, report recent updates in the web resource and provide future perspectives.

CellFinder: a cell data repository

CellFinder (http://www.cellfinder.org) is a comprehensive one-stop resource for molecular data characterizing mammalian cells in different tissues and in different development stages. It is built from carefully selected data sets stemming from other curated databases and the biomedical literature. To date, CellFinder describes 3394 cell types and 50 951 cell lines. The database currently contains 3055 microscopic and anatomical images, 205 whole-genome expression profiles of 194 cell/tissue types from RNA-seq and microarrays and 553 905 protein expressions for 535 cells/tissues. Text mining of a corpus of >2000 publications followed by manual curation confirmed expression information on ∼900 proteins and genes. CellFinder’s data model is capable to seamlessly represent entities from single cells to the organ level, to incorporate mappings between homologous entities in different species and to describe processes of cell development and differentiation. Its ontological backbone currently consists of 204 741 ontology terms incorporated from 10 different ontologies unified under the novel CELDA ontology. CellFinder’s web portal allows searching, browsing and comparing the stored data, interactive construction of developmental trees and navigating the partonomic hierarchy of cells and tissues through a unique body browser designed for life scientists and clinicians.

Modulated contact frequencies at gene-rich loci support a statistical helix model for mammalian chromatin organization

Background

Despite its critical role for mammalian gene regulation, the basic structural landscape of chromatin in living cells remains largely unknown within chromosomal territories below the megabase scale.

Results

Here, using the 3C-qPCR method, we investigate contact frequencies at high resolution within interphase chromatin at several mouse loci. We find that, at several gene-rich loci, contact frequencies undergo a periodical modulation (every 90 to 100 kb) that affects chromatin dynamics over large genomic distances (a few hundred kilobases). Interestingly, this modulation appears to be conserved in human cells, and bioinformatic analyses of locus-specific, long-range cis-interactions suggest that it may underlie the dynamics of a significant number of gene-rich domains in mammals, thus contributing to genome evolution. Finally, using an original model derived from polymer physics, we show that this modulation can be understood as a fundamental helix shape that chromatin tends to adopt in gene-rich domains when no significant locus-specific interaction takes place.

Conclusions

Altogether, our work unveils a fundamental aspect of chromatin dynamics in mammals and contributes to a better understanding of genome organization within chromosomal territories.

The RIKEN integrated database of mammals

The RIKEN integrated database of mammals (http://scinets.org/db/mammal) is the official undertaking to integrate its mammalian databases produced from multiple large-scale programs that have been promoted by the institute. The database integrates not only RIKEN's original databases, such as FANTOM, the ENU mutagenesis program, the RIKEN Cerebellar Development Transcriptome Database and the Bioresource Database, but also imported data from public databases, such as Ensembl, MGI and biomedical ontologies. Our integrated database has been implemented on the infrastructure of publication medium for databases, termed SciNetS/SciNeS, or the Scientists' Networking System, where the data and metadata are structured as a semantic web and are downloadable in various standardized formats. The top-level ontology-based implementation of mammal-related data directly integrates the representative knowledge and individual data records in existing databases to ensure advanced cross-database searches and reduced unevenness of the data management operations. Through the development of this database, we propose a novel methodology for the development of standardized comprehensive management of heterogeneous data sets in multiple databases to improve the sustainability, accessibility, utility and publicity of the data of biomedical information.

Computational evidence for functionality of noncoding mouse transcripts

Large-scale studies of mammalian genome transcription reveal that a large proportion of the genome is transcribed. It remains an open question whether the identified transcripts are functional. Here, we searched for computational evidence to support the functionality of 34,030 noncoding RNA (ncRNA) transcripts reported by the Fantom3 project. We show that compared to control sets, the Fantom ncRNA transcripts set is more conserved with human and rat. We also demonstrate that homologs of the Fantom ncRNA sequences in human and rat have more matches to ESTs. The conserved subgroup of sequences exhibits elevated expression levels in brain tissues. Finally, on average, the Fantom ncRNA sequences have lower minimal free energy of folding than the control sets. Taken together, these observations suggest that, as a group, the Fantom ncRNA set has properties that are different from random sets. Therefore, many of these transcripts may indeed have biological function.

Calculation of absolute expression values for DNA microarray data

INTRODUCTIONIn terms of cost per measurement, the use of DNA microarrays for comprehensive and quantitative expression measurements is vastly superior to other methods such as Northern blotting or quantitative reverse transcriptase polymerase chain reaction (QRT-PCR). However, the output values of DNA microarrays are not always highly reliable or accurate compared with other techniques, and the output data sometimes consist of measurements of relative expression (treated sample vs. untreated) rather than absolute expression values as desired. In effect, some measurements from some laboratories do not represent absolute expression values (such as the number of transcripts) and as such are experimentally deficient. To address the problem that some microarray data sets fail to reflect the number of mRNA molecules sufficiently in a given sample (i.e., fail to provide absolute expression levels), additional methods are required. The procedure described here provides a new method for converting microarray data to absolute expression values with the use of external data such as expressed sequence tags (ESTs) and cap analysis of gene expression (CAGE) tags.

Calculation of Spot Reliability Evaluation Scores (SRED) for DNA Microarray Data

INTRODUCTIONIn terms of cost per measurement, the use of DNA microarrays for comprehensive and quantitative expression measurements is vastly superior to other methods such as Northern blotting or quantitative reverse transcriptase polymerase chain reaction (QRT-PCR). However, the output values of DNA microarrays are not always highly reliable or accurate compared with other techniques, and the output data sometimes consist of measurements of relative expression (treated sample vs. untreated) rather than absolute expression values as desired. In effect, some measurements from some laboratories do not represent absolute expression values (such as the number of transcripts) and as such are experimentally deficient. This protocol addresses one problem in some microarray data: the absence of accurate measurements. Spot reliability evaluation score for DNA microarrays (SRED) offers a reliability value for each spot in the microarray. SRED does not require an entire microarray to assess the reliability, but rather analyzes the reliability of individual spots of the microarray. The calculation of a reliability index can be used for different microarray systems, which facilitates the analysis of multiple microarray data sets from different experimental platforms.

Gene expression during liver regeneration after partial hepatectomy in mice lacking type 1 tumor necrosis factor receptor

BACKGROUND

To investigate the function of tumor necrosis factor-alpha (TNF-alpha) during hepatocyte proliferation, we studied liver regeneration following partial hepatectomy in mice lacking type 1 TNF receptor (TNFR-1).

MATERIALS AND METHODS

TNFR-1 knockout (KO) and wild-type mice were subjected to partial (two-thirds) hepatectomy. Liver regeneration was evaluated by assessing liver weights and Ki67 immunohistochemistry. Riken complementary DNA microarray analysis was performed for liver samples from mice undergoing partial hepatectomy to better compare different mouse partial hepatectomy models (TNFR-1 KO mice, KO group; and wild-type mice, W group).

RESULTS

Liver weight was regained after 14 days in the KO group, and after 7 days in the W group. Genes including lipopolysaccharide, toll-like receptor 4 precursor, mitogen-activated protein kinase kinase kinase 4, mitogen-activated protein kinase kinase kinase kinase 4, and mitogen-activated protein kinase 8-interacting protein were up-regulated in the KO group. As for the cell-cycle-regulated genes, the levels of cyclin D1, nuclear factor-kappa B light chain, and TNF receptor super family membrane 1a were down-regulated in the KO group. Microarray analysis showed decreased activities of the hexokinase- and phospho-fructokinase-related glycolytic pathways in the KO group.

CONCLUSIONS

These results contribute to the better understanding of the mechanisms of liver regeneration after partial hepatectomy in TNFR-1 KO mice.

Microarray analysis of the AHR system: Tissue-specific flexibility in signal and target genes

Data mining published microarray experiments require that expression profiles are directly comparable. We performed linear global normalization on the data of 1967 Affymetrix U74av2 microarrays, i.e. the transcriptomes of >100 murine tissues or cell types. The mathematical transformation effectively nullifies inter-experimental or inter-laboratory differences between microarrays. The correctness of expression values was validated by quantitative RT-PCR. Using the database we analyze components of the aryl hydrocarbon receptor (AHR) signaling pathway in various tissues. We identified lineage and differentiation specific variant expression of AHR, ARNT, and HIF1alpha in the T-cell lineage and high expression of CYP1A1 in immature B cells and dendritic cells. Performing co-expression analysis we found unorthodox expression of the AHR in the absence of ARNT, particularly in stem cell populations, and can reject the hypothesis that ARNT2 takes over and is highly expressed when ARNT expression is low or absent. Furthermore the AHR shows no co-expression with any other transcript present on the chip. Analysis of differential gene expression under 308 conditions revealed 53 conditions under which the AHR is regulated, numerous conditions under which an intrinsic AHR action is modified as well as conditions activating the AHR even in the absence of known AHR ligands. Thus meta-analysis of published expression profiles is a powerful tool to gain novel insights into known and unknown systems.

Identification and characterization of TSAP, a novel gene specifically expressed in testis during spermatogenesis

Through in silico screens, we have identified many previously uncharacterized genes that display similar expression patterns as the mouse Dazl gene, a germ line-specific marker. Here, we report the identification and characterization of one of these novel genes. TSAP gene encodes a protein with 350 amino acids and contains five ankyrin repeats and a PEST sequence motif. Furthermore, we have generated an anti-TSAP antibody and have used three different approaches (RT-PCR, in situ hybridization, and immunohistochemistry) to investigate the expression profiles of TSAP mRNAs and proteins. TSAP is specifically expressed in testis, but not in other tissues such as ovary. Within the testis, TSAP is detected 10 days after birth and is mainly expressed in spermatocytes (ST) and later stage of germ cells, but not in spermatogonia (SG) or sertoli cells. Therefore, TSAP protein likely plays a role in spermatogenesis.

Databases of free expression

The rapid development of microarray technologies has led to a similar progression in gene expression analysis methods, gene expression applications, and gene expression databases. Public gene expression databases enable any researcher to examine expression of their favorite genes across a wide variety of samples, download sample data for development of new analysis methods, or answer broad questions about gene expression regulation, among other applications. A wide variety of public gene expression databases exist, and they vary in their content, analysis capabilities, and ease of use. This review highlights the current features and describes examples of two broad categories of mammalian microarray databases: tissue gene expression databases and data warehouses.

The study of metabolic pathways in tumors based on the transcriptome

DNA microarray technology revolutionized gene-expression analysis in molecular biology to observe patterns of gene expression in genomic scale. We review the biological aspects of genome-wide gene-expression activity in tumors specially focusing on the analysis of enzyme coding genes. First, the methods for analyzing gene-expression data for the study of metabolome in silico are discussed showing SV40T antigen expressing liver tumor data as an example. Next, an application for tumor metabolome analysis utilizing a reference set of gene-expression profiles is shown.

The Riken mouse genome encyclopedia project

The Riken mouse genome encyclopedia a comprehensive full-length cDNA collection and sequence database. High-level functional annotation is based on sequence homology search, expression profiling, mapping and protein-protein interactions. More than 1000000 clones prepared from 163 tissues were end-sequenced and classified into 128000 clusters, and 60000 representative clones were fully sequenced representing 24000 clear protein-encoding genes. The application of the mouse genome database for positional cloning and gene network regulation analysis is reported.

Identification of "pathologs" (disease-related genes) from the RIKEN mouse cDNA dataset using human curation plus FACTS, a new biological information extraction system

Background

A major goal in the post-genomic era is to identify and characterise disease susceptibility genes and to apply this knowledge to disease prevention and treatment. Rodents and humans have remarkably similar genomes and share closely related biochemical, physiological and pathological pathways. In this work we utilised the latest information on the mouse transcriptome as revealed by the RIKEN FANTOM2 project to identify novel human disease-related candidate genes. We define a new term "patholog" to mean a homolog of a human disease-related gene encoding a product (transcript, anti-sense or protein) potentially relevant to disease. Rather than just focus on Mendelian inheritance, we applied the analysis to all potential pathologs regardless of their inheritance pattern.

Results

Bioinformatic analysis and human curation of 60,770 RIKEN full-length mouse cDNA clones produced 2,578 sequences that showed similarity (70–85% identity) to known human-disease genes. Using a newly developed biological information extraction and annotation tool (FACTS) in parallel with human expert analysis of 17,051 MEDLINE scientific abstracts we identified 182 novel potential pathologs. Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. These pathologs were related to neoplastic (53%), hereditary (24%), immunological (5%), cardio-vascular (4%), or other (14%), disorders.

Conclusions

Large scale genome projects continue to produce a vast amount of data with potential application to the study of human disease. For this potential to be realised we need intelligent strategies for data categorisation and the ability to link sequence data with relevant literature. This paper demonstrates the power of combining human expert annotation with FACTS, a newly developed bioinformatics tool, to identify novel pathologs from within large-scale mouse transcript datasets.

Molecular basis of constitutive production of basement membrane components. Gene expression profiles of Engelbreth-Holm-Swarm tumor and F9 embryonal carcinoma cells

Engelbreth-Holm-Swarm (EHS) tumors produce large amounts of basement membrane (BM) components that are widely used as cell culture substrates mimicking BM functions. To delineate the tissue/organ origin of the tumor and the mechanisms operating in the BM overproduction, a genome-wide expression profile of EHS tumor was analyzed using RIKEN cDNA microarrays containing approximately 40,000 mouse cDNA clones. Expression profiles of F9 embryonal carcinoma cells that produce laminin-1 and other BM components upon differentiation into parietal endoderm-like cells (designated F9-PE) were also analyzed. Hierarchical clustering analysis showed that the gene expression profiles of EHS and F9-PE were the most similar among 49 mouse tissues/organs in the RIKEN Expression Array Database, suggesting that EHS tumor is parietal endoderm-derived. Quantitative PCR analysis confirmed that not only BM components but also the machineries required for efficient production of BM components, such as enzymes involved in post-translational modification and molecular chaperones, were highly expressed in both EHS and F9-PE. Pairs of similar transcription factor isoforms, such as Gata4/Gata6, Sox7/Sox17, and Cited1/Cited2, were also highly expressed in both EHS tumor and F9-PE. Time course analysis of F9 differentiation showed that up-regulation of the transcription factors was associated with those of BM components, suggesting their involvement in parietal endoderm specification and overproduction of the BM components.

Development and evaluation of an automated annotation pipeline and cDNA annotation system

Manual curation has long been held to be the "gold standard" for functional annotation of DNA sequence. Our experience with the annotation of more than 20,000 full-length cDNA sequences revealed problems with this approach, including inaccurate and inconsistent assignment of gene names, as well as many good assignments that were difficult to reproduce using only computational methods. For the FANTOM2 annotation of more than 60,000 cDNA clones, we developed a number of methods and tools to circumvent some of these problems, including an automated annotation pipeline that provides high-quality preliminary annotation for each sequence by introducing an "uninformative filter" that eliminates uninformative annotations, controlled vocabularies to accurately reflect both the functional assignments and the evidence supporting them, and a highly refined, Web-based manual annotation tool that allows users to view a wide array of sequence analyses and to assign gene names and putative functions using a consistent nomenclature. The ultimate utility of our approach is reflected in the low rate of reassignment of automated assignments by manual curation. Based on these results, we propose a new standard for large-scale annotation, in which the initial automated annotations are manually investigated and then computational methods are iteratively modified and improved based on the results of manual curation.

Systematic expression profiling of the mouse transcriptome using RIKEN cDNA microarrays

The number of known mRNA transcripts in the mouse has been greatly expanded by the RIKEN Mouse Gene Encyclopedia project. Validation of their reproducible expression in a tissue is an important contribution to the study of functional genomics. In this report, we determine the expression profile of 57,931 clones on 20 mouse tissues using cDNA microarrays. Of these 57,931 clones, 22,928 clones correspond to the FANTOM2 clone set. The set represents 20,234 transcriptional units (TUs) out of 33,409 TUs in the FANTOM2 set. We identified 7206 separate clones that satisfied stringent criteria for tissue-specific expression. Gene Ontology terms were assigned for these 7206 clones, and the proportion of 'molecular function' ontology for each tissue-specific clone was examined. These data will provide insights into the function of each tissue. Tissue-specific gene expression profiles obtained using our cDNA microarrays were also compared with the data extracted from the GNF Expression Atlas based on Affymetrix microarrays. One major outcome of the RIKEN transcriptome analysis is the identification of numerous nonprotein-coding mRNAs. The expression profile was also used to obtain evidence of expression for putative noncoding RNAs. In addition, 1926 clones (70%) of 2768 clones that were categorized as "unknown EST," and 1969 (58%) clones of 3388 clones that were categorized as "unclassifiable" were also shown to be reproducibly expressed.

Comprehensive analysis of the mouse metabolome based on the transcriptome

The complete set of cDNAs encoding the enzymes of known metabolic pathways has not previously been available for any mammal. Here, transcripts encoding the metabolic pathways of the mouse (mouse metabolome) were reconstructed by making use of the KEGG metabolic pathway database and gene ontology (GO) assignment to the mouse representative transcript and protein set (RTPS), which contains all available mouse transcript sequences including the FANTOM set of RIKEN mouse cDNA clones. By assigning EC numbers extracted from the molecular function ontology in GO, the known mouse transcriptome was predicted to encode enzymes with 726 unique EC numbers. Of these, 648 EC numbers were newly assigned based on the FANTOM set. The mouse metabolome confirmed by cDNA analysis includes almost all of the enzymes of well known pathways such as the tricarboxylic acid cycle and urea cycle. On the other hand, analysis of enzymes required for the tryptophan metabolism pathway revealed a lack of connectivity, indicating that cDNAs/genes encoding several key enzymes remain to be identified. The information derived from coexpression from the cDNA microarray analysis of enzymes of known function may lead to identification of the missing components of the metabolome, and will add new insights into the connectivity of the mammalian metabolic pathways.

Systematic characterization of the zinc-finger-containing proteins in the mouse transcriptome

Zinc-finger-containing proteins can be classified into evolutionary and functionally divergent protein families that share one or more domains in which a zinc ion is tetrahedrally coordinated by cysteines and histidines. The zinc finger domain defines one of the largest protein superfamilies in mammalian genomes;46 different conserved zinc finger domains are listed in InterPro (http://www.ebi.ac.uk/InterPro). Zinc finger proteins can bind to DNA, RNA, other proteins, or lipids as a modular domain in combination with other conserved structures. Owing to this combinatorial diversity, different members of zinc finger superfamilies contribute to many distinct cellular processes, including transcriptional regulation, mRNA stability and processing, and protein turnover. Accordingly, mutations of zinc finger genes lead to aberrations in a broad spectrum of biological processes such as development, differentiation, apoptosis, and immunological responses. This study provides the first comprehensive classification of zinc finger proteins in a mammalian transcriptome. Specific detailed analysis of the SP/Krüppel-like factors and the E3 ubiquitin-ligase RING-H2 families illustrates the importance of such an analysis for a more comprehensive functional classification of large protein families. We describe the characterization of a new family of C2H2 zinc-finger-containing proteins and a new conserved domain characteristic of this family, the identification and characterization of Sp8, a new member of the Sp family of transcriptional regulators, and the identification of five new RING-H2 proteins.

The mouse secretome: functional classification of the proteins secreted into the extracellular environment

We have developed a computational strategy to identify the set of soluble proteins secreted into the extracellular environment of a cell. Within the protein sequences predominantly derived from the RIKEN representative transcript and protein set, we identified 2033 unique soluble proteins that are potentially secreted from the cell. These proteins contain a signal peptide required for entry into the secretory pathway and lack any transmembrane domains or intracellular localization signals. This class of proteins, which we have termed the mouse secretome, included >500 novel proteins and 92 proteins <100 amino acids in length. Functional analysis of the secretome included identification of human orthologs, functional units based on InterPro and SCOP Superfamily predictions, and expression of the proteins within the RIKEN READ microarray database. To highlight the utility of this information, we discuss the CUB domain-containing protein family.

Detection of genes with tissue-specific expression patterns using Akaike's information criterion procedure

We applied a method based on Akaike's information criterion (AIC) to detect genes whose expression profile is considerably different in some tissue(s) than in others. Such observations are detected as outliers, and the method we used was originally developed to detect outliers. The main advantage of the method is that objective decisions are possible because the procedure is independent of a significance level. We applied the method to 48 expression ratios corresponding to various tissues in each of 14,610 clones obtained from the RIKEN Expression Array Database (READ; http://read.gsc.riken.go.jp). As a result, for several tissues (e.g., muscle, heart, and tongue tissues that contain similar cell types) we objectively obtained specific clones without any "thresholding." Our study demonstrates the feasibility of the method for detecting tissue-specific gene expression patterns.

RIKEN mouse genome encyclopedia

We have been working to establish the comprehensive mouse full-length cDNA collection and sequence database to cover as many genes as we can, named Riken mouse genome encyclopedia. Recently we are constructing higher-level annotation (Functional ANnoTation Of Mouse cDNA; FANTOM) not only with homology search based annotation but also with expression data profile, mapping information and protein-protein database. More than 1,000,000 clones prepared from 163 tissues were end-sequenced to classify into 159,789 clusters and 60,770 representative clones were fully sequenced. As a conclusion, the 60,770 sequences contained 33,409 unique. The next generation of life science is clearly based on all of the genome information and resources. Based on our cDNA clones we developed the additional system to explore gene function. We developed cDNA microarray system to print all of these cDNA clones, protein-protein interaction screening system, protein-DNA interaction screening system and so on. The integrated database of all the information is very useful not only for analysis of gene transcriptional network and for the connection of gene to phenotype to facilitate positional candidate approach. In this talk, the prospect of the application of these genome resourced should be discussed. More information is available at the web page: http://genome.gsc.riken.go.jp/.

Bioinformatics for the genomic sciences and towards systems biology. Japanese activities in the post-genome era

The knowledge gleaned from genome sequencing and post-genome analyses is having a very significant impact on a whole range of life sciences and their applications. 'Genome-wide analysis' is a good keyword to represent this tendency. Thanks to innovations in high-throughput measurement technologies and information technologies, genome-wide analysis is becoming available in a broad range of research fields from DNA sequences, gene and protein expressions, protein structures and interactions, to pathways or networks analysis. In fact, the number of research targets has increased by more than two orders in recent years and we should change drastically the attitude to research activities. The scope and speed of research activities are expanding and the field of bioinformatics is playing an important role. In parallel with the data-driven research approach that focuses on speedy handling and analyzing of the huge amount of data, a new approach is gradually gaining power. This is a 'model-driven research' approach, that incorporates biological modeling in its research framework. Computational simulations of biological processes play a pivotal role. By modeling and simulating, this approach aims at predicting and even designing the dynamic behaviors of complex biological systems, which is expected to make rapid progress in life science researches and lead to meaningful applications to various fields such as health care, food supply and improvement of environment. Genomic sciences are now advancing as great frontiers of research and applications in the 21st century. This article starts with surveying the general progress of bioinformatics (Section 1), and describes Japanese activities in bioinformatics (Section 2). In Section 3, I will introduce recent developments in Systems Biology which I think will become more important in the future.

Functional transcriptomes: comparative analysis of biological pathways and processes in eukaryotes to infer genetic networks among transcripts

Microarray technology enables us to monitor large changes in transcripts at any given time. The compilation of these data makes possible the comparison of such gene expression data on a genome-wide scale. As comparisons of genome sequence data yield new biological insights, comparative analyses of transcriptome data also promise new discoveries regarding metabolic pathways and cellular processes. The coordinated expression of genes shows that these genes physically interact with each other or are part of the same cascade. We have produced one of the largest expression profiles of adult mice and developmental tissues. These data, as well as the data on yeast from previous reports, were used to see whether coordinated expression (with high correlation coefficient) is closely coupled to the actual cascade on the pathway map.