Viva la revolution! A report from the FANTOM meeting

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.

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.

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.

Isolation and structure of the mouse 14-3-3 eta chain gene and the distribution of 14-3-3 eta mRNA in the mouse brain

14-3-3 protein is a brain-specific protein discovered by Moore and Perez, but at present is thought to be a multifunctional protein. To clarify the brain-specific function of the protein, we intend constructing a 14-3-3 eta gene knock-out mouse. As the first step of this process, we isolated the mouse 14-3-3 eta chain gene and determined its structure. The mouse gene is about 10 kb long and composed of two exons separated by a long intron. The transcription start site was identified and the polyadenylation signals (AATAAA) were found in exon 2 of the mouse gene. In the 5'-upstream sequence, we found several cis elements including a CRE sequence, a TATA box-like sequence, and a C/EBP element. Furthermore, the distribution of 14-3-3 eta mRNA in the mouse brain was examined by in situ hybridization histochemistry. The highest signals were found in the Purkinje cells of the cerebellum, the pyramidal cells of the hippocampus and the olfactory bulb neurons of the adult mouse. Neuronal expression of 14-3-3 eta in these regions mRNA may generally increase during postnatal brain development. The distribution of protein kinase C gamma in the mouse brain was also examined by immunohistochemistry. From the distribution of 14-3-3 eta mRNA and protein kinase C gamma in the mouse brain, the involvement of these compounds in the induction and maintenance of LTP was discussed.

FANTOM DB: database of Functional Annotation of RIKEN Mouse cDNA Clones

FANTOM DB, the database of Functional Annotation of RIKEN Mouse cDNA Clones, is designed to store sequence information of RIKEN full-length enriched mouse cDNA clones, graphical views of sequence analysis results, curated functional annotation information and additional descriptions, including Gene Ontology terms. RIKEN's Mouse Gene Encyclopedia Project aims to collect full-length enriched cDNA clones from various mouse tissues, determine the full-length nucleotide sequences, infer their chromosomal locations by computer and characterize gene expression patterns. FANTOM DB has been developed to facilitate this work and to facilitate functional genomic studies such as positional candidate cloning, cDNA microarrays and protein interaction analyses. FANTOM DB contains 21 076 full-length cDNA sequences with rich functional annotations and is publicly available. FANTOM DB thus provides curated functional annotation to RIKEN full-length enriched mouse clones, and has links to other public resources. FANTOM DB can be accessed at http://fantom.gsc.riken.go.jp/db/.

READ: RIKEN Expression Array Database

READ, the RIKEN Expression Array Database, is a database of expression profile data from the RIKEN mouse cDNA microarray. It stores the microarray experimental data and information, and provides Web interfaces for researchers to use to retrieve, analyze and display their data. The goals for READ are to serve as a storage site for microarray data from ongoing research in the RIKEN mouse encyclopedia project and to provide useful links and tools to decipher biologically important information. The gene information is based mainly on the fully annotated FANTOM database. READ can be accessed at http://read.gsc.riken.go.jp/. READ also provides a search tool [READ integrates gene expression neighbor (RINGENE)] for genes with similarities in expression profiling.