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      SEdb 2.0: a comprehensive super-enhancer database of human and mouse

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Super-enhancers (SEs) are cell-specific DNA cis-regulatory elements that can supervise the transcriptional regulation processes of downstream genes. SEdb 2.0 ( http://www.licpathway.net/sedb) aims to provide a comprehensive SE resource and annotate their potential roles in gene transcriptions. Compared with SEdb 1.0, we have made the following improvements: (i) Newly added the mouse SEs and expanded the scale of human SEs. SEdb 2.0 contained 1 167 518 SEs from 1739 human H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq) samples and 550 226 SEs from 931 mouse H3K27ac ChIP-seq samples, which was five times that of SEdb 1.0. (ii) Newly added transcription factor binding sites (TFBSs) in SEs identified by TF motifs and TF ChIP-seq data. (iii) Added comprehensive (epi)genetic annotations of SEs, including chromatin accessibility regions, methylation sites, chromatin interaction regions and topologically associating domains (TADs). (iv) Newly embedded and updated search and analysis tools, including ‘Search SE by TF-based’, ‘Differential-Overlapping-SE analysis’ and ‘SE-based TF–Gene analysis’. (v) Newly provided quality control (QC) metrics for ChIP-seq processing. In summary, SEdb 2.0 is a comprehensive update of SEdb 1.0, which curates more SEs and annotation information than SEdb 1.0. SEdb 2.0 provides a friendly platform for researchers to more comprehensively clarify the important role of SEs in the biological process.

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          Most cited references78

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          Fast gapped-read alignment with Bowtie 2.

          Ben Langmead, Steven L Salzberg (2023)
          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Guangchuang Yu, Li-Gen Wang, Yanyan Han … (2012)
            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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              BEDTools: a flexible suite of utilities for comparing genomic features

              Aaron Quinlan, Ira Hall (2010)
              Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
              Article 0 comments Cited 6925 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Yuezhu Wang
                Chao Song
                Jun Zhao
                Yuexin Zhang
                Xilong Zhao
                Chenchen Feng
                Guorui Zhang
                Jiang Zhu
                Fan Wang
                Fengcui Qian
                Liwei Zhou
                Jian Zhang
                Xuefeng Bai
                Bo Ai
                Xinyu Liu
                Qiuyu Wang
                Chunquan Li:
                ORCID: https://orcid.org/0000-0002-4700-5496
                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: 06 January 2023
                Publication date (Electronic): 01 November 2022
                Publication date PMC-release: 01 November 2022
                Volume: 51
                Issue: D1
                Pages: D280-D290
                Affiliations
                The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                School of Computer, University of South China , Hengyang, Hunan 421001, China
                The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                School of Computer, University of South China , Hengyang, Hunan 421001, China
                The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                School of Computer, University of South China , Hengyang, Hunan 421001, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                School of Computer, University of South China , Hengyang, Hunan 421001, China
                The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                School of Computer, University of South China , Hengyang, Hunan 421001, China
                The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                Hunan Provincial Base for Scientific and Technological Innovation Cooperation, University of South China , Hengyang, Hunan 421001, China
                The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
                Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
                The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                School of Medical Informatics, Daqing Campus, Harbin Medical University , Daqing 163319, China
                School of Computer, University of South China , Hengyang, Hunan 421001, China
                The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                Hunan Provincial Base for Scientific and Technological Innovation Cooperation, University of South China , Hengyang, Hunan 421001, China
                The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
                Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China , Hengyang, Hunan 421001, China
                Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
                Author notes
                To whom correspondence should be addressed. Tel: +86 13272311691; Fax: +86 0734 8279018; Email: lcqbio@ 123456163.com

                The authors wish it to be known that, in their opinion, the first four authors should be regarded as Joint First Authors.

                Author information
                https://orcid.org/0000-0002-4700-5496
                Article
                Publisher ID: gkac968
                DOI: 10.1093/nar/gkac968
                PMC ID: 9825585
                PubMed ID: 36318264
                SO-VID: 97cbe051-822d-4ecf-8595-6078542ee998
                Copyright © © The Author(s) 2022. 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 ( https://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 : 13 October 2022
                Date revision received : 09 October 2022
                Date received : 14 September 2022
                Page count
                Pages: 11
                Funding
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 62171166
                Award ID: 62001145
                Award ID: 62272212
                Funded by: Natural Science Foundation for Distinguished Young Scholars of Heilongjiang Province of China;
                Award ID: JQ2020C004
                Funded by: Research Foundation of the First Affiliated Hospital of University of South China for Advanced Talents;
                Award ID: 20210002-1005 USCAT-2021-01
                Funded by: Wu Liande Youth Science Research Fund of Harbin Medical University (Daqing);
                Award ID: JFWLD202001
                Funded by: China Postdoctoral Science Foundation, DOI 10.13039/501100002858;
                Award ID: 2019M661311
                Funded by: Hunan Provincial Base for Scientific and Technological Innovation Cooperation;
                Award ID: 2019CB1009
                Categories
                Subject: AcademicSubjects/SCI00010
                Subject: Database Issue

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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