Yoichiro Nakatani

The medaka draft genome and insights into vertebrate genome evolution

Teleosts comprise more than half of all vertebrate species and have adapted to a variety of marine and freshwater habitats. Their genome evolution and diversification are important subjects for the understanding of vertebrate evolution. Although draft genome sequences of two pufferfishes have been published, analysis of more fish genomes is desirable. Here we report a high-quality draft genome sequence of a small egg-laying freshwater teleost, medaka (Oryzias latipes). Medaka is native to East Asia and an excellent model system for a wide range of biology, including ecotoxicology, carcinogenesis, sex determination and developmental genetics. In the assembled medaka genome (700 megabases), which is less than half of the zebrafish genome, we predicted 20,141 genes, including ∼2,900 new genes, using 5′-end serial analysis of gene expression tag information. We found single nucleotide polymorphisms (SNPs) at an average rate of 3.42% between the two inbred strains derived from two regional populations; this is the highest SNP rate seen in any vertebrate species. Analyses based on the dense SNP information show a strict genetic separation of 4 million years (Myr) between the two populations, and suggest that differential selective pressures acted on specific gene categories. Four-way comparisons with the human, pufferfish (Tetraodon), zebrafish and medaka genomes revealed that eight major interchromosomal rearrangements took place in a remarkably short period of ∼50 Myr after the whole-genome duplication event in the teleost ancestor and afterwards, intriguingly, the medaka genome preserved its ancestral karyotype for more than 300 Myr.

Chromatin-associated periodicity in genetic variation downstream of transcriptional start sites

Might DNA sequence variation reflect germline genetic activity and underlying chromatin structure? We investigated this question using medaka (Japanese killifish, Oryzias latipes), by comparing the genomic sequences of two strains (Hd-rR and HNI) and by mapping ∼37.3 million nucleosome cores from Hd-rR blastulae and 11,654 representative transcription start sites from six embryonic stages. We observed a distinctive ∼200–base pair (bp) periodic pattern of genetic variation downstream of transcription start sites; the rate of insertions and deletions longer than 1 bp peaked at positions of approximately +200, +400, and +600 bp, whereas the point mutation rate showed corresponding valleys. This ∼200-bp periodicity was correlated with the chromatin structure, with nucleosome occupancy minimized at positions 0, +200, +400, and +600 bp. These data exemplify the potential for genetic activity (transcription) and chromatin structure to contribute to molding the DNA sequence on an evolutionary time scale.

High-Resolution Analysis of the 5′-End Transcriptome Using a Next Generation DNA Sequencer

Massively parallel, tag-based sequencing systems, such as the SOLiD system, hold the promise of revolutionizing the study of whole genome gene expression due to the number of data points that can be generated in a simple and cost-effective manner. We describe the development of a 5′–end transcriptome workflow for the SOLiD system and demonstrate the advantages in sensitivity and dynamic range offered by this tag-based application over traditional approaches for the study of whole genome gene expression. 5′-end transcriptome analysis was used to study whole genome gene expression within a colon cancer cell line, HT-29, treated with the DNA methyltransferase inhibitor, 5-aza-2′-deoxycytidine (5Aza). More than 20 million 25-base 5′-end tags were obtained from untreated and 5Aza-treated cells and matched to sequences within the human genome. Seventy three percent of the mapped unique tags were associated with RefSeq cDNA sequences, corresponding to approximately 14,000 different protein-coding genes in this single cell type. The level of expression of these genes ranged from 0.02 to 4,704 transcripts per cell. The sensitivity of a single sequence run of the SOLiD platform was 100–1,000 fold greater than that observed from 5′end SAGE data generated from the analysis of 70,000 tags obtained by Sanger sequencing. The high-resolution 5′end gene expression profiling presented in this study will not only provide novel insight into the transcriptional machinery but should also serve as a basis for a better understanding of cell biology.

Genome-wide profiling of DNA methylation in human cancer cells

Global changes in DNA methylation correlate with altered gene expression and genomic instability in cancer. We have developed a methylation-specific digital sequencing (MSDS) method that can assess DNA methylation on a genomic scale. MSDS is a simple, low-cost method that combines the use of methylation-sensitive restriction enzymes with second generation sequencing technology. DNA methylation in two colon cancer cell lines, HT29 and HCT116, was measured using MSDS. When methylation levels were compared between the two cell lines, many differentially methylated regions (DMRs) were identified in CpG island shore regions (located within 2kb of a CpG island), gene body regions and intergenic regions. The number of DMRs in the vicinity of gene transcription start sites correlated with the level of expression of TACC1, CLDN1, and PLEKHC1 (FERMT2) genes, which have been linked to carcinogenesis. The MSDS method has the potential to provide novel insight into the functional complexity of the human genome.

UTGB/medaka: genomic resource database for medaka biology

Medaka (Oryzias latipes) is a small egg-laying freshwater teleost native to East Asia that has become an excellent model system for developmental genetics and evolutionary biology. The draft medaka genome sequence (700 Mb) was reported in June 2007, and its substantial genomic resources have been opened to the public through the University of Tokyo Genome Browser Medaka (UTGB/medaka) database. This database provides basic genomic information, such as predicted genes, expressed sequence tags (ESTs), guanine/cytosine (GC) content, repeats and comparative genomics, as well as unique data resources including (i) 2473 genetic markers and experimentally confirmed PCR primers that amplify these markers, (ii) 142 414 bacterial artificial chromosome (BAC) and 217 344 fosmid end sequences that amount to 15.0- and 11.1-fold clone coverage of the entire genome, respectively, and were used for draft genome assembly, (iii) 16 519 460 single nucleotide polymorphisms (SNPs), and 2 859 905 insertions/deletions detected between two medaka inbred strain genomes and (iv) 841 235 5′-end serial analyses of gene-expression (SAGE) tags that identified 344 266 transcription start sites on the genome. UTGB/medaka is available at: http://medaka.utgenome.org/

Coordinated Changes in DNA Methylation in Antigen-Specific Memory CD4 T Cells

Memory CD4+ T cells are central regulators of both humoral and cellular immune responses. T cell differentiation results in specific changes in chromatin structure and DNA methylation of cytokine genes. Although the methylation status of a limited number of gene loci in T cells has been examined, the genome-wide DNA methylation status of memory CD4+ T cells remains unexplored. To further elucidate the molecular signature of memory T cells, we conducted methylome and transcriptome analyses of memory CD4+ T cells generated using T cells from TCR-transgenic mice. The resulting genome-wide DNA methylation profile revealed 1144 differentially methylated regions (DMRs) across the murine genome during the process of T cell differentiation, 552 of which were associated with gene loci. Interestingly, the majority of these DMRs were located in introns. These DMRs included genes such as CXCR6, Tbox21, Chsy1, and Cish, which are associated with cytokine production, homing to bone marrow, and immune responses. Methylation changes in memory T cells exposed to specific Ag appeared to regulate enhancer activity rather than promoter activity of immunologically relevant genes. In addition, methylation profiles differed between memory T cell subsets, demonstrating a link between T cell methylation status and T cell differentiation. By comparing DMRs between naive and Ag-specific memory T cells, this study provides new insights into the functional status of memory T cells.

Diversity of Ca2+-Induced Morphology Revealed by Morphological Phenotyping of Ca2+-Sensitive Mutants of Saccharomyces cerevisiae

ABSTRACT Yeast cell morphology can be treated as a quantitative trait using the image processing software CalMorph. In the present study, we investigated Ca2+-induced morphological changes in Ca2+-sensitive (cls) mutants of Saccharomyces cerevisiae, based on the discovery that the characteristic Ca2+-induced morphological changes in the Ca2+-sensitive mutant zds1 reflect changes in the Ca2+ signaling-mediated cell cycle control pathway. By applying hierarchical cluster analysis to the quantitative morphological data of 58 cls mutants, 31 of these mutants were classified into seven classes based on morphological similarities. The patterns of morphological change induced by Ca2+ in one class differed from those of another class. Based on the results obtained using versatile methods for phenotypic analysis, we conclude that a high concentration of Ca2+ exerts a wide variety of effects on yeast and that there are multiple Ca2+-regulatory pathways that are distinct from the Zds1p-related pathway.

Data mining tools for the Saccharomyces cerevisiae morphological database

For comprehensive understanding of precise morphological changes resulting from loss-of-function mutagenesis, a large collection of 1 899 247 cell images was assembled from 91 271 micrographs of 4782 budding yeast disruptants of non-lethal genes. All the cell images were processed computationally to measure ∼500 morphological parameters in individual mutants. We have recently made this morphological quantitative data available to the public through the Saccharomyces cerevisiae Morphological Database (SCMD). Inspecting the significance of morphological discrepancies between the wild type and the mutants is expected to provide clues to uncover genes that are relevant to the biological processes producing a particular morphology. To facilitate such intensive data mining, a suite of new software tools for visualizing parameter value distributions was developed to present mutants with significant changes in easily understandable forms. In addition, for a given group of mutants associated with a particular function, the system automatically identifies a combination of multiple morphological parameters that discriminates a mutant group from others significantly, thereby characterizing the function effectively. These data mining functions are available through the World Wide Web at .