ScEnhancer: a Single-cell Enhancer Resource with Annotation Across Hundreds of Tissue/cell Types in Three Species

Overview

Journal Nucleic Acids Res

Publisher Oxford University Press

Specialty Biochemistry

Date 2021 Nov 11

PMID 34761274

Citations 10

Authors

Tianshun Gao

Zilong Zheng

Yihang Pan

Chengming Zhu

Fuxin Wei

Jinqiu Yuan

Rui Sun

Shuo Fang

Nan Wang

Yang Zhou

Jiang Qian

Affiliations

Soon will be listed here.

Abstract

Previous studies on enhancers and their target genes were largely based on bulk samples that represent 'average' regulatory activities from a large population of millions of cells, masking the heterogeneity and important effects from the sub-populations. In recent years, single-cell sequencing technology has enabled the profiling of open chromatin accessibility at the single-cell level (scATAC-seq), which can be used to annotate the enhancers and promoters in specific cell types. A comprehensive resource is highly desirable for exploring how the enhancers regulate the target genes at the single-cell level. Hence, we designed a single-cell database scEnhancer (http://enhanceratlas.net/scenhancer/), covering 14 527 776 enhancers and 63 658 600 enhancer-gene interactions from 1 196 906 single cells across 775 tissue/cell types in three species. An unsupervised learning method was employed to sort and combine tens or hundreds of single cells in each tissue/cell type to obtain the consensus enhancers. In addition, we utilized a cis-regulatory network algorithm to identify the enhancer-gene connections. Finally, we provided a user-friendly platform with seven useful modules to search, visualize, and browse the enhancers/genes. This database will facilitate the research community towards a functional analysis of enhancers at the single-cell level.

Citing Articles

scBlood: A comprehensive single-cell accessible chromatin database of blood cells.

Zhao Y, Yu Z, Cui T, Li L, Li Y, Qian F Comput Struct Biotechnol J. 2024; 23:2746-2753.

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Integration of chromosome locations and functional aspects of enhancers and topologically associating domains in knowledge graphs enables versatile queries about gene regulation.

Mulero-Hernandez J, Mironov V, Minarro-Gimenez J, Kuiper M, Fernandez-Breis J Nucleic Acids Res. 2024; 52(15):e69.

PMID: 38967009 PMC: 11347148. DOI: 10.1093/nar/gkae566.

HyGAnno: hybrid graph neural network-based cell type annotation for single-cell ATAC sequencing data.

Zhang W, Cui Y, Liu B, Loza M, Park S, Nakai K Brief Bioinform. 2024; 25(3).

PMID: 38581422 PMC: 10998639. DOI: 10.1093/bib/bbae152.

scATAC-Ref: a reference of scATAC-seq with known cell labels in multiple species.

Qian F, Zhou L, Zhu Y, Li Y, Yu Z, Feng C Nucleic Acids Res. 2023; 52(D1):D285-D292.

PMID: 37897340 PMC: 10767920. DOI: 10.1093/nar/gkad924.

MethMarkerDB: a comprehensive cancer DNA methylation biomarker database.

Zhu Z, Zhou Q, Sun Y, Lai F, Wang Z, Hao Z Nucleic Acids Res. 2023; 52(D1):D1380-D1392.

PMID: 37889076 PMC: 10767949. DOI: 10.1093/nar/gkad923.

References

Parisi F, Strino F, Nadler B, Kluger Y . Ranking and combining multiple predictors without labeled data. Proc Natl Acad Sci U S A. 2014; 111(4):1253-8. PMC: 3910607. DOI: 10.1073/pnas.1219097111. View

Buenrostro J, Wu B, Litzenburger U, Ruff D, Gonzales M, Snyder M . Single-cell chromatin accessibility reveals principles of regulatory variation. Nature. 2015; 523(7561):486-90. PMC: 4685948. DOI: 10.1038/nature14590. View

Przytycki P, Pollard K . CellWalker integrates single-cell and bulk data to resolve regulatory elements across cell types in complex tissues. Genome Biol. 2021; 22(1):61. PMC: 7883575. DOI: 10.1186/s13059-021-02279-1. View

. UniProt: the universal protein knowledgebase. Nucleic Acids Res. 2016; 45(D1):D158-D169. PMC: 5210571. DOI: 10.1093/nar/gkw1099. View

Zeng W, Chen S, Cui X, Chen X, Gao Z, Jiang R . SilencerDB: a comprehensive database of silencers. Nucleic Acids Res. 2020; 49(D1):D221-D228. PMC: 7778955. DOI: 10.1093/nar/gkaa839. View

Hinrichs A, Karolchik D, Baertsch R, Barber G, Bejerano G, Clawson H . The UCSC Genome Browser Database: update 2006. Nucleic Acids Res. 2005; 34(Database issue):D590-8. PMC: 1347506. DOI: 10.1093/nar/gkj144. View

Flicek P, Amode M, Barrell D, Beal K, Brent S, Carvalho-Silva D . Ensembl 2012. Nucleic Acids Res. 2011; 40(Database issue):D84-90. PMC: 3245178. DOI: 10.1093/nar/gkr991. View

Yan F, Powell D, Curtis D, Wong N . From reads to insight: a hitchhiker's guide to ATAC-seq data analysis. Genome Biol. 2020; 21(1):22. PMC: 6996192. DOI: 10.1186/s13059-020-1929-3. View

McWilliam H, Li W, Uludag M, Squizzato S, Park Y, Buso N . Analysis Tool Web Services from the EMBL-EBI. Nucleic Acids Res. 2013; 41(Web Server issue):W597-600. PMC: 3692137. DOI: 10.1093/nar/gkt376. View

10.

Ranzoni A, Tangherloni A, Berest I, Riva S, Myers B, Strzelecka P . Integrative Single-Cell RNA-Seq and ATAC-Seq Analysis of Human Developmental Hematopoiesis. Cell Stem Cell. 2020; 28(3):472-487.e7. PMC: 7939551. DOI: 10.1016/j.stem.2020.11.015. View

11.

Pliner H, Packer J, McFaline-Figueroa J, Cusanovich D, Daza R, Aghamirzaie D . Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data. Mol Cell. 2018; 71(5):858-871.e8. PMC: 6582963. DOI: 10.1016/j.molcel.2018.06.044. View

12.

Fishilevich S, Nudel R, Rappaport N, Hadar R, Plaschkes I, Iny Stein T . GeneHancer: genome-wide integration of enhancers and target genes in GeneCards. Database (Oxford). 2017; 2017. PMC: 5467550. DOI: 10.1093/database/bax028. View

13.

Wang A, Chiou J, Poirion O, Buchanan J, Valdez M, Verheyden J . Single-cell multiomic profiling of human lungs reveals cell-type-specific and age-dynamic control of SARS-CoV2 host genes. Elife. 2020; 9. PMC: 7688309. DOI: 10.7554/eLife.62522. View

14.

Rickels R, Shilatifard A . Enhancer Logic and Mechanics in Development and Disease. Trends Cell Biol. 2018; 28(8):608-630. DOI: 10.1016/j.tcb.2018.04.003. View

15.

Granja J, Corces M, Pierce S, Bagdatli S, Choudhry H, Chang H . ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. Nat Genet. 2021; 53(3):403-411. PMC: 8012210. DOI: 10.1038/s41588-021-00790-6. View

16.

Ashoor H, Kleftogiannis D, Radovanovic A, Bajic V . DENdb: database of integrated human enhancers. Database (Oxford). 2015; 2015. PMC: 4560934. DOI: 10.1093/database/bav085. View

17.

Chen C, Zhou D, Gu Y, Wang C, Zhang M, Lin X . SEA version 3.0: a comprehensive extension and update of the Super-Enhancer archive. Nucleic Acids Res. 2019; 48(D1):D198-D203. PMC: 7145603. DOI: 10.1093/nar/gkz1028. View

18.

Wimmers F, Donato M, Kuo A, Ashuach T, Gupta S, Li C . The single-cell epigenomic and transcriptional landscape of immunity to influenza vaccination. Cell. 2021; 184(15):3915-3935.e21. PMC: 8316438. DOI: 10.1016/j.cell.2021.05.039. View

19.

Kumar R, Lathwal A, Kumar V, Patiyal S, Raghav P, Raghava G . CancerEnD: A database of cancer associated enhancers. Genomics. 2020; 112(5):3696-3702. DOI: 10.1016/j.ygeno.2020.04.028. View

20.

Haft D, DiCuccio M, Badretdin A, Brover V, Chetvernin V, ONeill K . RefSeq: an update on prokaryotic genome annotation and curation. Nucleic Acids Res. 2017; 46(D1):D851-D860. PMC: 5753331. DOI: 10.1093/nar/gkx1068. View