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      GTRD: an integrated view of transcription regulation

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          Abstract

          The Gene Transcription Regulation Database (GTRD; http://gtrd.biouml.org/) contains uniformly annotated and processed NGS data related to gene transcription regulation: ChIP-seq, ChIP-exo, DNase-seq, MNase-seq, ATAC-seq and RNA-seq. With the latest release, the database has reached a new level of data integration. All cell types (cell lines and tissues) presented in the GTRD were arranged into a dictionary and linked with different ontologies (BRENDA, Cell Ontology, Uberon, Cellosaurus and Experimental Factor Ontology) and with related experiments in specialized databases on transcription regulation (FANTOM5, ENCODE and GTEx). The updated version of the GTRD provides an integrated view of transcription regulation through a dedicated web interface with advanced browsing and search capabilities, an integrated genome browser, and table reports by cell types, transcription factors, and genes of interest.

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          The Molecular Signatures Database (MSigDB) hallmark gene set collection.

          Arthur Liberzon, Chet Birger, Helga Thorvaldsdóttir … (2015)
          The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.
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            NCBI GEO: archive for functional genomics data sets—update

            Tanya Barrett, Stephen Wilhite, Pierre Ledoux … (2012)
            The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.
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              The Genotype-Tissue Expression (GTEx) project.

              John M. Lonsdale, Jeffrey Thomas, Mike Salvatore … (2014)
              Genome-wide association studies have identified thousands of loci for common diseases, but, for the majority of these, the mechanisms underlying disease susceptibility remain unknown. Most associated variants are not correlated with protein-coding changes, suggesting that polymorphisms in regulatory regions probably contribute to many disease phenotypes. Here we describe the Genotype-Tissue Expression (GTEx) project, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.
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                Author and article information

                Contributors
                Semyon Kolmykov
                Ivan Yevshin
                Mikhail Kulyashov
                Ruslan Sharipov:
                ORCID: http://orcid.org/0000-0003-2182-5493
                Yury Kondrakhin
                Vsevolod J Makeev
                Ivan V Kulakovskiy
                Alexander Kel
                Fedor Kolpakov
                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date Collection: 08 January 2021
                Publication date (Electronic): 24 November 2020
                Publication date PMC-release: 24 November 2020
                Volume: 49
                Issue: D1
                Pages: D104-D111
                Affiliations
                BIOSOFT.RU, LLC , Novosibirsk 630090, Russian Federation
                Federal Research Center for Information and Computational Technologies , Novosibirsk 630090, Russian Federation
                Federal Research Center Institute of Cytology and Genetics SB RAS , Novosibirsk 630090, Russian Federation
                BIOSOFT.RU, LLC , Novosibirsk 630090, Russian Federation
                Federal Research Center for Information and Computational Technologies , Novosibirsk 630090, Russian Federation
                BIOSOFT.RU, LLC , Novosibirsk 630090, Russian Federation
                Federal Research Center for Information and Computational Technologies , Novosibirsk 630090, Russian Federation
                Novosibirsk State University , Novosibirsk 630090, Russian Federation
                BIOSOFT.RU, LLC , Novosibirsk 630090, Russian Federation
                Federal Research Center for Information and Computational Technologies , Novosibirsk 630090, Russian Federation
                Novosibirsk State University , Novosibirsk 630090, Russian Federation
                BIOSOFT.RU, LLC , Novosibirsk 630090, Russian Federation
                Federal Research Center for Information and Computational Technologies , Novosibirsk 630090, Russian Federation
                Vavilov Institute of General Genetics RAS , Moscow 119991, Russian Federation
                Moscow Institute of Physics and Technology (State University) , Dolgoprudny 141700, Russian Federation
                NRC «Kurchatov Institute» - GOSNIIGENETIKA, Kurchatov Genomic Center , Moscow 123182, Russian Federation
                Engelhardt Institute of Molecular Biology, Russian Academy of Sciences , Moscow 119991, Russian Federation
                Vavilov Institute of General Genetics RAS , Moscow 119991, Russian Federation
                Engelhardt Institute of Molecular Biology, Russian Academy of Sciences , Moscow 119991, Russian Federation
                Institute of Protein Research, Russian Academy of Sciences , Pushchino 142290, Russian Federation
                BIOSOFT.RU, LLC , Novosibirsk 630090, Russian Federation
                geneXplain GmbH , 38302 Wolfenbüttel, Germany
                Institute of Chemical Biology and Fundamental Medicine SB RAS , Novosibirsk 630090, Russian Federation
                BIOSOFT.RU, LLC , Novosibirsk 630090, Russian Federation
                Federal Research Center for Information and Computational Technologies , Novosibirsk 630090, Russian Federation
                Author notes
                To whom correspondence should be addressed. Tel: +7 383 363 68 29; Email: fedor@ 123456biouml.org
                Author information
                http://orcid.org/0000-0003-2182-5493
                Article
                Publisher ID: gkaa1057
                DOI: 10.1093/nar/gkaa1057
                PMC ID: 7778956
                PubMed ID: 33231677
                SO-VID: 4102ad26-59d0-494c-bda0-a25aa56e30ff
                Copyright © © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date accepted : 03 November 2020
                Date revision received : 18 October 2020
                Date received : 15 September 2020
                Page count
                Pages: 8
                Funding
                Funded by: Russian Science Foundation, DOI 10.13039/501100006769;
                Award ID: 19-14-00295
                Award ID: 20-74-10075
                Funded by: Ministry of Science and Higher Education of the Russian Federation, DOI 10.13039/501100012190;
                Award ID: 075-15-2019-1658
                Categories
                Subject: AcademicSubjects/SCI00010
                Subject: Database Issue

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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