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Shuichi Tsutsumi

Publications and source records attributed to Shuichi Tsutsumi.

17 recordsLinked to original sources
PubMed2025

JG2: an updated version of the Japanese population-specific reference genome.

Here we present the construction of JG2, an updated population-specific reference genome for the Japanese population. Utilizing data from three individuals previously used in the construction of JG1, several methodologies were employed to enhance genomic coverage and assembly quality. Hi-C sequencing technology facilitated phase-aware assembly, generating two haploid assemblies per individual and enabling improved representation of genetic variation. A meta-assembly strategy and a majority decision approach further refined assembly quality by combining the best sequences from multiple assemblies and minimizing the inclusion of rare variants. The resulting JG2 genome comprises chromosome-level sequences, mitochondrial chromosomes and unplaced scaffolds, offering more comprehensive coverage of the Japanese genome. Comparative analyses with other reference genomes demonstrated the accuracy and representativeness of JG2, highlighting its utility for genetic research involving the Japanese population. Overall, by adopting the phased assembly technique, JG2 represents a substantial advancement over the collapsed assembly-based JG1, with improvements including a greater number of identified variants (3,115,695 variants, of which 298,644 had an allele frequency (AF) of 1.0 in the 3.5KJPNv2 AF panel) and a higher N50 value (152,668,378 bp). These enhancements provide researchers with a more precise and comprehensive resource for understanding the genetic landscape of the Japanese population. The sequences and annotations are available on the jMorp website ( https://jmorp.megabank.tohoku.ac.jp/ ).

Journal Article↗
PubMed2007

Glucokinase and IRS-2 are required for compensatory beta cell hyperplasia in response to high-fat diet-induced insulin resistance.

Glucokinase (Gck) functions as a glucose sensor for insulin secretion, and in mice fed standard chow, haploinsufficiency of beta cell-specific Gck (Gck(+/-)) causes impaired insulin secretion to glucose, although the animals have a normal beta cell mass. When fed a high-fat (HF) diet, wild-type mice showed marked beta cell hyperplasia, whereas Gck(+/-) mice demonstrated decreased beta cell replication and insufficient beta cell hyperplasia despite showing a similar degree of insulin resistance. DNA chip analysis revealed decreased insulin receptor substrate 2 (Irs2) expression in HF diet-fed Gck(+/-) mouse islets compared with wild-type islets. Western blot analyses confirmed upregulated Irs2 expression in the islets of HF diet-fed wild-type mice compared with those fed standard chow and reduced expression in HF diet-fed Gck(+/-) mice compared with those of HF diet-fed wild-type mice. HF diet-fed Irs2(+/-) mice failed to show a sufficient increase in beta cell mass, and overexpression of Irs2 in beta cells of HF diet-fed Gck(+/-) mice partially prevented diabetes by increasing beta cell mass. These results suggest that Gck and Irs2 are critical requirements for beta cell hyperplasia to occur in response to HF diet-induced insulin resistance.

Animals↗
PubMed2006

An integrated map of p53-binding sites and histone modification in the human ENCODE regions.

TP53 (tumor protein p53; p53) regulates its target genes under various cellular stresses. By combining chromatin immunoprecipitation with oligonucleotide microarrays, we have mapped binding sites of p53 (p53-BS) in the genome of HCT116 human colon carcinoma cells, along with those of acetylated H3, acetylated H4, and methylated H3-K4. We analyzed a 30-Mb portion of the human genome selected as a representative model by the ENCODE Consortium. In the region, we found 37 p53-BS, of which the p53-binding motif was present in 32 (86%). Acetylated histone H3 and H4 were detected at 14 (38%) and 33 (89%) of the p53-BS, respectively. A significant portion (58%) of H4 acetylation in the p53-BS was not accompanied by H3 acetylation. Acetyl H3 were preferentially located at the 5' and 3' ends of genes, whereas acetyl H4 were distributed widely across the genome. These results provide novel insights into how p53 binding coordinates with histone modification in human.

Acetylation↗
PubMed2006

High-resolution mapping of DNA methylation in human genome using oligonucleotide tiling array.

DNA methylation is an epigenetic mark crucial in regulation of gene expression. Aberrant DNA methylation causes silencing of tumor suppressor genes and promotes chromosomal instability in human cancers. Most of previous studies for DNA methylation have focused on limited genomic regions, such as selected genes or promoter CpG islands (CGIs) containing recognition sites of methylation-sensitive restriction enzymes. Here, we describe a method for high-resolution analysis of DNA methylation using oligonucleotide tiling arrays. The input material is methylated DNA immunoprecipitated with anti-methylcytosine antibodies. We examined the ENCODE region ( approximately 1% of human genome) in three human colorectal cancer cell lines and identified over 700 candidate methylated sites (CMS), where 24 of 25 CMS selected randomly were subsequently verified by bisulfite sequencing. CMS were enriched in the 5' regulatory regions and the 3' regions of genes. We also compared DNA methylation patterns with histone H3 and H4 acetylation patterns in the HOXA cluster region. Our analysis revealed no acetylated histones in the hypermethylated region, demonstrating reciprocal relationship between DNA methylation and histone H3 and H4 acetylation. Our method recognizes DNA methylation with little bias by genomic location and, therefore, is useful for comprehensive high-resolution analysis of DNA methylation providing new findings in the epigenomics.

Acetylation↗
PubMed2005

Analysis of mechanism for human gammadelta T cell recognition of nonpeptide antigens.

Whereas human gammadelta T cells respond to nonpeptide antigens like pyrophosphomonoesters and alkyl amines in the primary reactions, only pyrophosphomonoesters provoke proliferative responses in the secondary responses. To elucidate the differences in stimulatory activity between the two groups of nonpeptide antigens, we systematically analyzed time courses of gene expressions by microarray analyses. While 253 genes were induced by stimulation with 2-methyl-3-butenyl-1-pyrophosphate (2M3B1PP), only 35 genes were detected after stimulation with isobutyl amine. Then, gammadelta T cells expressed various cytokines like XCL1-2, CCL3-4, TNF-alpha, and IFN-gamma in response to 2M3B1PP in a time-dependent manner, while transient expressions were observed in IBA during the time period. The differences in such responsiveness are likely to originate from the activation state of NFAT, which is involved in the expression of transcription factors, EGR1-3 and NR4A1-2, and might play a crucial role in effector functions of gammadelta T cells.

Antigens↗
PubMed2005

A meta-clustering analysis indicates distinct pattern alteration between two series of gene expression profiles for induced ischemic tolerance in rats.

We have developed a visualization methodology, called a "cluster overlap distribution map" (CODM), for comparing the clustering results of time series gene expression profiles generated under two different conditions. Although various clustering algorithms for gene expression data have been proposed, there are few effective methods to compare clustering results for different conditions. With CODM, the utilization of three-dimensional space and color allows intuitive visualization of changes in cluster set composition, changes in the expression patterns of genes between the two conditions, and relationship with other known gene information, such as transcription factors. We applied CODM to time series gene expression profiles obtained from rat four-vessel occlusion models combined with systemic hypotension and time-matched sham control animals (with sham operation), identifying distinct pattern alteration between the two. Comparisons of dynamic changes of time series gene expression levels under different conditions are important in various fields of gene expression profiling analysis, including toxicogenomics and pharmacogenomics. CODM will be valuable for various types of analyses within these fields, because it integrates and simultaneously visualizes various types of information across clustering results.

Algorithms↗
PubMed2005

Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues.

A critical and difficult part of studying cancer with DNA microarrays is data interpretation. Besides the need for data analysis algorithms, integration of additional information about genes might be useful. We performed genome-wide expression profiling of 36 types of normal human tissues and identified 2503 tissue-specific genes. We then systematically studied the expression of these genes in cancers by reanalyzing a large collection of published DNA microarray datasets. We observed that the expression level of liver-specific genes in hepatocellular carcinoma (HCC) correlates with the clinically defined degree of tumor differentiation. Through unsupervised clustering of tissue-specific genes differentially expressed in tumors, we extracted expression patterns that are characteristic of individual cell types, uncovering differences in cell lineage among tumor subtypes. We were able to detect the expression signature of hepatocytes in HCC, neuron cells in medulloblastoma, glia cells in glioma, basal and luminal epithelial cells in breast tumors, and various cell types in lung cancer samples. We also demonstrated that tissue-specific expression signatures are useful in locating the origin of metastatic tumors. Our study shows that integration of each gene's breadth of expression (BOE) in normal tissues is important for biological interpretation of the expression profiles of cancers in terms of tumor differentiation, cell lineage, and metastasis.

Algorithms↗
PubMed2004

Distinct chromosomal bias of gene expression signatures in the progression of hepatocellular carcinoma.

To identify the chromosomal aberrations associated with the progression of liver cancer, we applied expression imbalance map analysis to gene expression data from 31 hepatocellular carcinomas and 19 noncancerous tissues. Expression imbalance map analysis, which detects mRNA expression imbalance correlated with chromosomal regions, showed that expression gains of 1q21-23 (74%), 8q13-21 (48%), 12q23-24 (41%), 17q12-21(48%), 17q25 (25%), and 20q11 (22%) and losses of 4q13 (48%), 8p12-21 (32%), 13q14 (32%), and 17p13 (29%) were significantly associated with hepatocellular carcinoma. Most regions with altered expression identified by expression imbalance map were also identified in previous reports using comparative genomic hybridization. We demonstrated chromosomal copy number gain in 1q21-23 and loss in 17p13 by genomic quantitative PCR, suggesting that gene expression profiles reflect chromosomal alterations. Furthermore, expression imbalance map analysis revealed that more poorly differentiated hepatocellular carcinoma contain more chromosomal alterations, which are accumulated in a stepwise manner in the course of hepatocellular carcinoma progression: expression imbalance of 1q, 8p, 8q, and 17p occur as early events in hepatocarcinogenesis, and 12q, 17q25 and 20q occur as later events. In particular, expression gain of 17q12-21 and loss of 4q were seen to accumulate constantly through the dedifferentiation process. Our data suggest that gene expression profiles are subject to chromosomal bias and that expression imbalance map can correlate gene expression to gene loci with high resolution and sensitivity.

Aged↗
PubMed2004

Gene expression profiling and identification of novel prognostic marker genes in neuroblastoma.

To investigate the various genetic characteristics of and differences between early- and advanced-stage neuroblastoma (NB) and to identify candidate genes involved in NB progression, we performed DNA microarray analysis on 20 primary tumors. Two-way clustering analysis based on the expression pattern of approximately 500 of 1,700 genes revealed genetic subgroups in these NB tumors. Although 9 of the 13 early-stage tumors (69%) and 4 of the 6 advanced-stage tumors (67%) were classified as being in the same cluster, the remaining tumors showed different expression profiles. This indicates that both the early- and advanced-stage tumors were heterogeneous. Based on the microarray data, we identified the BIRC, CDKN2D, and SMARCD3 genes as those that are predominantly expressed in either the early or the advanced stage of NB. These genes have been reported to be associated with apoptosis, cell cycles, and the transcriptional activator, respectively. To better assess the prognostic value of the expression of these genes in NB, real-time polymerase chain reaction was carried out on 50 primary tumors. The expression of both the BIRC3 and CDKN2D genes was significantly higher in the early-stage group than in the advanced-stage group (P = 0.002 and 0.003, respectively), whereas the expression of the SMARCD3 gene was significantly reduced in the early-stage group (P = 0.02). Therefore, the BIRC, CDKN2D, and SMARCD3 genes are possible candidates for being novel prognostic markers for NB.

Biomarkers, Tumor↗
PubMed2003

Two distinct gene expression signatures in pediatric acute lymphoblastic leukemia with MLL rearrangements.

Acute lymphoblastic leukemia (ALL) with 11q23 translocations is usually associated with MLL gene rearrangement, but little is known about its leukemogenesis. We analyzed the gene expression profiles of pediatric ALL samples according to their translocations. Using oligonucleotide microarray analysis, we identified distinct expression profiles for 23 ALL samples with 11q23 translocations, including t(4;11) (n = 15), t(11;19) (n = 6), and t(5;11) (n = 2), compared with 9 ALL samples with other translocations, including t(12;21) (n = 6) and t(1;19) (n = 3). Gene expression scores of FLT3, MeisI, and CD44 for samples with MLL rearrangements were particularly high compared with those for other ALL samples. Statistical analysis of the gene expression profiles for the 21 ALL samples with MLL rearrangements at diagnosis revealed two subgroups that exclusively correlated with prognosis but not with any other clinico-pathological factor. The transcription factors CBF2 and CDP were highly expressed in the poor and good prognosis subgroups, respectively. In addition, their downstream target genes were differentially expressed. These findings provide new insights into the biological mechanisms of leukemogenesis and prognosis for pediatric ALL with MLL rearrangements.

Child↗
PubMed2003

Expression imbalance map: a new visualization method for detection of mRNA expression imbalance regions.

We describe the development of a new visualization method, called the expression imbalance map (EIM), for detecting mRNA expression imbalance regions, reflecting genomic losses and gains at a much higher resolution than conventional technologies such as comparative genomic hybridization (CGH). Simple spatial mapping of the microarray expression profiles on chromosomal location provides little information about genomic structure, because mRNA expression levels do not completely reflect genomic copy number and some microarray probes would be of low quality. The EIM, which does not employ arbitrary selection of thresholds in conjunction with hypergeometric distribution-based algorithm, has a high tolerance of these complex factors. The EIM could detect regionally underexpressed or overexpressed genes (called, here, an expression imbalance region) in lung cancer specimens from their gene expression data of oligonucleotide microarray. Many known as well as potential loci with frequent genomic losses or gains were detected as expression imbalance regions by the EIM. Therefore, the EIM should provide the user with further insight into genomic structure through mRNA expression.

Allelic Imbalance↗
PubMed2003

Reducing false positives in molecular pattern recognition.

In the search for new cancer subtypes by gene expression profiling, it is essential to avoid misclassifying samples of unknown subtypes as known ones. In this paper, we evaluated the false positive error rates of several classification algorithms through a 'null test' by presenting classifiers a large collection of independent samples that do not belong to any of the tumor types in the training dataset. The benchmark dataset is available at www2.genome.rcast.u-tokyo.ac.jp/pm/. We found that k-nearest neighbor (KNN) and support vector machine (SVM) have very high false positive error rates when fewer genes (<100) are used in prediction. The error rate can be partially reduced by including more genes. On the other hand, prototype matching (PM) method has a much lower false positive error rate. Such robustness can be achieved without loss of sensitivity by introducing suitable measures of prediction confidence. We also proposed a cluster-and-select technique to select genes for classification. The nonparametric Kruskal-Wallis H test is employed to select genes differentially expressed in multiple tumor types. To reduce the redundancy, we then divided these genes into clusters with similar expression patterns and selected a given number of genes from each cluster. The reliability of the new algorithm is tested on three public datasets.

Computational Biology↗
PubMed2002

Distinction in gene expression profiles of oligodendrogliomas with and without allelic loss of 1p.

Oligodendrogliomas frequently, but not always show sensitivity to chemotherapy and recent studies demonstrated that allelic loss of chromosome 1p is highly associated with this chemosensitivity. To gain insight into the molecular mechanism of such difference, we examined comprehensive gene expression profiles of 11 oligodendroglial tumors, six with and five without 1pLOH (loss of heterozygosity), and two normal brain tissues using the oligonucleotide microarray (GeneChip). Statistically significant numbers of genes were expressed differentially between the two genetic subsets. Clustering analysis separated the tumor subsets well. The tumors with 1pLOH had similar expression profiles to the normal brain for those differentially expressed genes. Many genes showing higher expression in tumors with 1pLOH were presumed to have functions in nervous tissues. Notably, the majority of the 123 genes showing significant expression reduction in tumors with 1pLOH were either on chromosome 1 (50%) or on 19 (10%), and the average expression reduction ratio was about 50% (0.54+/-0.13) possibly reflecting the chromosomal deletion. Thus, the biological difference between the genetic subsets of oligodendroglioma was indeed reflected to gene expression profile, which provided baseline information for further studies to elucidate the mechanism of chemosensitivity in gliomas.

Adult↗
PubMed2002

Global gene expression analysis of gastric cancer by oligonucleotide microarrays.

To gain molecular understanding of carcinogenesis, progression, and diversity of gastric cancer, 22 primary human advanced gastric cancer tissues and 8 noncancerous gastric tissues were analyzed by high-density oligonucleotide microarray in this study. Based on expression analysis of approximately 6800 genes, a two-way clustering algorithm successfully distinguished cancer tissues from noncancerous tissues. Subsequently, genes that were differentially expressed in cancer and noncancerous tissues were identified; 162 and 129 genes were highly expressed (P < 0.05) >2.5-fold in cancer tissues and noncancerous tissues, respectively. In cancer tissues, genes related to cell cycle, growth factor, cell motility, cell adhesion, and matrix remodeling were highly expressed. In noncancerous tissues, genes related to gastrointestinal-specific function and immune response were highly expressed. Furthermore, we identified several genes associated with lymph node metastasis including Oct-2 or histological types including Liver-Intestine Cadherin. These results provide not only a new molecular basis for understanding biological properties of gastric cancer, but also useful resources for future development of therapeutic targets and diagnostic markers for gastric cancer.

Cluster Analysis↗
PubMed2002

Identification of genes associated with dedifferentiation of hepatocellular carcinoma with expression profiling analysis.

To identify the genes associated with dedifferentiation of hepatocellular carcinoma (HCC), gene expression profiles of HCCs of well-and moderately differentiated grades were compared by means of oligonucleotide arrays. One tumor showed a nodule-in-nodule appearance (NIN), which is occasionally observed in the course of progression of HCC from well to less differentiated grade, when an inner, moderately differentiated tumor (MD) develops sequentially from the outer, well-differentiated tumor (WD). Seventy-six genes were identified to be up-regulated more than 3-fold and 33 genes were down-regulated in the inner nodule in NIN. By statistical analysis of the profiles from 10 individual additional liver tumors, 5 WDs and 5 MDs, we were able to identify 12 genes, LAMA3, PPIB, ADAR, PSMD4, NDUFS8, D9SVA, CCT3, GBAP, ARD1, RDBP, CSRP2, and TLE1, with significantly elevated expression, and 4 genes, CP, IL7R, CD48, and PLGL, with decreased expression in MD. These selected genes were further validated using another 12 tumors, 5 WDs and 7 MDs, with semi-quantitative RT-PCR. We also applied neighborhood analysis to list the genes with high predictability values as most closely correlated with WD-MD distinction. Seven genes, ADAR, PSMD4, D9SVA, CCT3, GBAP, RDBP, and CSRP2, whose expression was elevated and one gene, IL7R, whose expression was decreased, were included among the top 50 predictor genes. These genes are likely to be associated with dedifferentiation of HCC and their identification may help to elucidate the mechanism of liver cancer progression.

Carcinoma, Hepatocellular↗
PubMed2002

Fish oil feeding alters liver gene expressions to defend against PPARalpha activation and ROS production.

Fish oil rich in n-3 polyunsaturated fatty acids has been shown to reduce the risk of cardiovascular diseases partly by reduction of blood triglyceride concentration. This favorable effect mainly results from the combined effects of inhibition of lipogenesis by decrease of SREBP-1 and stimulation of fatty acid oxidation by activation of peroxisome proliferator-activated receptor-alpha (PPARalpha) in liver. However, because fish oil is easily peroxidized to form hydroperoxides and increases oxidative stress, some defense mechanism(s) against oxidative stress might occur. To understand these complex effects of fish oil diet, the gene expression profile of mice liver was analyzed using high-density oligonucleotide arrays. High-fat diet (60% of total energy intake) as either safflower oil or fish oil (tuna) was given to mice. After 6 mo of feeding, expression levels of a total of 6,521 genes were analyzed. In fish oil diet compared with safflower oil diet, immune reaction-related genes, antioxidant genes (several glutathione transferases, uncoupling protein 2, and Mn-superoxide dismutase), and lipid catabolism-related genes upregulated, whereas cholesterol and fatty acid synthesis-related genes and 17-alpha hydroxylase/C17-20 lyase and sulfotransferases related to production of endogenous PPARalpha ligands and reactive oxygen species (ROS) downregulated markedly. Because upregulation of these antioxidant genes and downregulation of sulfotransferases were also observed in mice administered fenofibrate, altered gene expression related to antioxidant system observed in fish oil feeding was mediated directly and indirectly by PPARalpha activation. However, downregulation of 17-alpha hydroxylase/C17-20 lyase was not due to PPARalpha activation. These data indicate that fish oil feeding downregulated the endogenous PPARalpha-activation system and increased antioxidant gene expressions to protect against ROS excess.

Animals↗