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Nucleic Acids Res. 2018 Jan 4;46(D1):D229-D238. doi: 10.1093/nar/gkx1001.

DBTSS/DBKERO for integrated analysis of transcriptional regulation.

Author information

1
Division of Translational Genomics, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Chiba, Japan.
2
Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Chiba, Japan.
3
Computational Regulatory Genomics Research Group, Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan.
4
Division of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan.
5
Department of Pathology, Keio University School of Medicine, Tokyo, Japan.
6
Institute of Molecular and Cellular Biosciences, the University of Tokyo, Tokyo, Japan.
7
Division of Epigenomics and Development, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan.
8
Department of Human Genetics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan.
9
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, the University of Tokyo, Chiba, Japan.
10
Human Genome Center, the Institute of Medical Science, the University of Tokyo, Tokyo, Japan.

Abstract

DBTSS (Database of Transcriptional Start Sites)/DBKERO (Database of Kashiwa Encyclopedia for human genome mutations in Regulatory regions and their Omics contexts) is the database originally initiated with the information of transcriptional start sites and their upstream transcriptional regulatory regions. In recent years, we updated the database to assist users to elucidate biological relevance of the human genome variations or somatic mutations in cancers which may affect the transcriptional regulation. In this update, we facilitate interpretations of disease associated genomic variation, using the Japanese population as a model case. We enriched the genomic variation dataset consisting of the 13,368 individuals collected for various genome-wide association studies and the reference epigenome information in the surrounding regions using a total of 455 epigenome datasets (four tissue types from 67 healthy individuals) collected for the International Human Epigenome Consortium (IHEC). The data directly obtained from the clinical samples was associated with that obtained from various model systems, such as the drug perturbation datasets using cultured cancer cells. Furthermore, we incorporated the results obtained using the newly developed analytical methods, Nanopore/10x Genomics long-read sequencing of the human genome and single cell analyses. The database is made publicly accessible at the URL (http://dbtss.hgc.jp/).

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