Kazunori Waki

The genome sequence and structure of rice chromosome 1

The rice species Oryza sativa is considered to be a model plant because of its small genome size, extensive genetic map, relative ease of transformation and synteny with other cereal crops. Here we report the essentially complete sequence of chromosome 1, the longest chromosome in the rice genome. We summarize characteristics of the chromosome structure and the biological insight gained from the sequence. The analysis of 43.3 megabases (Mb) of non-overlapping sequence reveals 6,756 protein coding genes, of which 3,161 show homology to proteins of Arabidopsis thaliana, another model plant. About 30% (2,073) of the genes have been functionally categorized. Rice chromosome 1 is (G + C)-rich, especially in its coding regions, and is characterized by several gene families that are dispersed or arranged in tandem repeats. Comparison with a draft sequence indicates the importance of a high-quality finished sequence.

Cap analysis gene expression for high-throughput analysis of transcriptional starting point and identification of promoter usage

We introduce cap analysis gene expression (CAGE), which is based on preparation and sequencing of concatamers of DNA tags deriving from the initial 20 nucleotides from 5′ end mRNAs. CAGE allows high-throughout gene expression analysis and the profiling of transcriptional start points (TSP), including promoter usage analysis. By analyzing four libraries (brain, cortex, hippocampus, and cerebellum), we redefined more accurately the TSPs of 11-27% of the analyzed transcriptional units that were hit. The frequency of CAGE tags correlates well with results from other analyses, such as serial analysis of gene expression, and furthermore maps the TSPs more accurately, including in tissue-specific cases. The high-throughput nature of this technology paves the way for understanding gene networks via correlation of promoter usage and gene transcriptional factor expression.

The regulated retrotransposon transcriptome of mammalian cells

Although repetitive elements pervade mammalian genomes, their overall contribution to transcriptional activity is poorly defined. Here, as part of the FANTOM4 project, we report that 6–30% of cap-selected mouse and human RNA transcripts initiate within repetitive elements. Analysis of approximately 250,000 retrotransposon-derived transcription start sites shows that the associated transcripts are generally tissue specific, coincide with gene-dense regions and form pronounced clusters when aligned to full-length retrotransposon sequences. Retrotransposons located immediately 5′ of protein-coding loci frequently function as alternative promoters and/or express noncoding RNAs. More than a quarter of RefSeqs possess a retrotransposon in their 3′ UTR, with strong evidence for the reduced expression of these transcripts relative to retrotransposon-free transcripts. Finally, a genome-wide screen identifies 23,000 candidate regulatory regions derived from retrotransposons, in addition to more than 2,000 examples of bidirectional transcription. We conclude that retrotransposon transcription has a key influence upon the transcriptional output of the mammalian genome.

Cytoskeletal Rearrangements in Synovial Fibroblasts as a Novel Pathophysiological Determinant of Modeled Rheumatoid Arthritis

Rheumatoid arthritis is a chronic inflammatory disease with a high prevalence and substantial socioeconomic burden. Despite intense research efforts, its aetiology and pathogenesis remain poorly understood. To identify novel genes and/or cellular pathways involved in the pathogenesis of the disease, we utilized a well-recognized tumour necrosis factor-driven animal model of this disease and performed high-throughput expression profiling with subtractive cDNA libraries and oligonucleotide microarray hybridizations, coupled with independent statistical analysis. This twin approach was validated by a number of different methods in other animal models of arthritis as well as in human patient samples, thus creating a unique list of disease modifiers of potential therapeutic value. Importantly, and through the integration of genetic linkage analysis and Gene Ontology–assisted functional discovery, we identified the gelsolin-driven synovial fibroblast cytoskeletal rearrangements as a novel pathophysiological determinant of the disease.

Libraries enriched for alternatively spliced exons reveal splicing patterns in melanocytes and melanomas

It is becoming increasingly clear that alternative splicing enables the complex development and homeostasis of higher organisms. To gain a better understanding of how splicing contributes to regulatory pathways, we have developed an alternative splicing library approach for the identification of alternatively spliced exons and their flanking regions by alternative splicing sequence enriched tags sequencing. Here, we have applied our approach to mouse melan-c melanocyte and B16-F10Y melanoma cell lines, in which 5,401 genes were found to be alternatively spliced. These genes include those encoding important regulatory factors such as cyclin D2, Ilk, MAPK12, MAPK14, RAB4, melastatin 1 and previously unidentified splicing events for 436 genes. Real-time PCR further identified cell line–specific exons for Tmc6, Abi1, Sorbs1, Ndel1 and Snx16. Thus, the ASL approach proved effective in identifying splicing events, which suggest that alternative splicing is important in melanoma development.

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.

A Resource for Transcriptomic Analysis in the Mouse Brain

Background The transcriptome of the cerebral cortex is remarkably homogeneous, with variations being stronger between individuals than between areas. It is thought that due to the presence of many distinct cell types, differences within one cell population will be averaged with the noise from others. Studies of sorted cells expressing the same transgene have shown that cell populations can be distinguished according to their transcriptional profile. Methodology We have prepared a low-redundancy set of 16,209 full-length cDNA clones which represents the transcriptome of the mouse visual cortex in its coding and non-coding aspects. Using an independent tag-based approach, CAGE, we confirmed the cortical expression of 72% of the clones. Clones were amplified by PCR and spotted on glass slides, and we interrogated the microarrays with RNA from flow-sorted fluorescent cells from the cerebral cortex of parvalbumin-egfp transgenic mice. Conclusions We provide an annotated cDNA clone collection which is particularly suitable for transcriptomic analysis in the mouse brain. Spotting it on microarrays, we compared the transcriptome of EGFP positive and negative cells in a parvalbumin-egfp transgenic background and showed that more than 30% of clones are differentially expressed. Our clone collection will be a useful resource for the study of the transcriptome of single cell types in the cerebral cortex.