Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data

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

We developed Lisa ( http://lisa.cistrome.org/) to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on the input gene sets, Lisa first uses histone mark ChIP-seq and chromatin accessibility profiles to construct a chromatin model related to the regulation of these genes. Using TR ChIP-seq peaks or imputed TR binding sites, Lisa probes the chromatin models using in silico deletion to find the most relevant TRs. Applied to gene sets derived from targeted TF perturbation experiments, Lisa boosted the performance of imputed TR cistromes and outperformed alternative methods in identifying the perturbed TRs.

Related collections

Most cited references 29

Record: found
Abstract: found
Article: not found

A unique chromatin signature uncovers early developmental enhancers in humans.

Alvaro Rada-Iglesias, Ruchi Bajpai, Tomek Swigut … (2011)

Cell-fate transitions involve the integration of genomic information encoded by regulatory elements, such as enhancers, with the cellular environment. However, identification of genomic sequences that control human embryonic development represents a formidable challenge. Here we show that in human embryonic stem cells (hESCs), unique chromatin signatures identify two distinct classes of genomic elements, both of which are marked by the presence of chromatin regulators p300 and BRG1, monomethylation of histone H3 at lysine 4 (H3K4me1), and low nucleosomal density. In addition, elements of the first class are distinguished by the acetylation of histone H3 at lysine 27 (H3K27ac), overlap with previously characterized hESC enhancers, and are located proximally to genes expressed in hESCs and the epiblast. In contrast, elements of the second class, which we term 'poised enhancers', are distinguished by the absence of H3K27ac, enrichment of histone H3 lysine 27 trimethylation (H3K27me3), and are linked to genes inactive in hESCs and instead are involved in orchestrating early steps in embryogenesis, such as gastrulation, mesoderm formation and neurulation. Consistent with the poised identity, during differentiation of hESCs to neuroepithelium, a neuroectoderm-specific subset of poised enhancers acquires a chromatin signature associated with active enhancers. When assayed in zebrafish embryos, poised enhancers are able to direct cell-type and stage-specific expression characteristic of their proximal developmental gene, even in the absence of sequence conservation in the fish genome. Our data demonstrate that early developmental enhancers are epigenetically pre-marked in hESCs and indicate an unappreciated role of H3K27me3 at distal regulatory elements. Moreover, the wealth of new regulatory sequences identified here provides an invaluable resource for studies and isolation of transient, rare cell populations representing early stages of human embryogenesis.

0 comments Cited 911 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

BigWig and BigBed: enabling browsing of large distributed datasets

W. J. Kent, A. S. Zweig, Lisa Barber … (2010)

Summary: BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Availability and implementation: Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu Contact: ann@soe.ucsc.edu Supplementary information: Supplementary byte-level details of the BigWig and BigBed file formats are available at Bioinformatics online. For an in-depth description of UCSC data file formats and custom tracks, see http://genome.ucsc.edu/FAQ/FAQformat.html and http://genome.ucsc.edu/goldenPath/help/hgTracksHelp.html

0 comments Cited 614 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

The Myc/Max/Mad network and the transcriptional control of cell behavior.

C Grandori, S M Cowley, L P James … (2000)

The Myc/Max/Mad network comprises a group of transcription factors whose distinct interactions result in gene-specific transcriptional activation or repression. A great deal of research indicates that the functions of the network play roles in cell proliferation, differentiation, and death. In this review we focus on the Myc and Mad protein families and attempt to relate their biological functions to their transcriptional activities and gene targets. Both Myc and Mad, as well as the more recently described Mnt and Mga proteins, form heterodimers with Max, permitting binding to specific DNA sequences. These DNA-bound heterodimers recruit coactivator or corepressor complexes that generate alterations in chromatin structure, which in turn modulate transcription. Initial identification of target genes suggests that the network regulates genes involved in the cell cycle, growth, life span, and morphology. Because Myc and Mad proteins are expressed in response to diverse signaling pathways, the network can be viewed as a functional module which acts to convert environmental signals into specific gene-regulatory programs.

0 comments Cited 293 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Jing Zhang: zhangjing@tongji.edu.cn

Clifford A. Meyer:

ORCID: http://orcid.org/0000-0002-8321-2839

cliff_meyer@ds.dfci.harvard.edu

X. Shirley Liu: xsliu@ds.dfci.harvard.edu

Journal

Journal ID (nlm-ta): Genome Biol

Journal ID (iso-abbrev): Genome Biol

Title: Genome Biology

Publisher: BioMed Central (London )

ISSN (Print): 1474-7596

ISSN (Electronic): 1474-760X

Publication date (Electronic): 7 February 2020

Publication date PMC-release: 7 February 2020

Publication date Collection: 2020

Volume: 21

Electronic Location Identifier: 32

Affiliations

[1 ]GRID grid.24516.34, ISNI 0000000123704535, Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Science and Technology, , Tongji University, ; Shanghai, 200433 China

[2 ]GRID grid.411333.7, ISNI 0000 0004 0407 2968, Center of Molecular Medicine, , Children’s Hospital of Fudan University, ; Shanghai, 201102 China

[3 ]GRID grid.24516.34, ISNI 0000000123704535, Stem Cell Translational Research Center, Tongji Hospital, School of Life Science and Technology, , Tongji University, ; Shanghai, 200065 China

[4 ]GRID grid.65499.37, ISNI 0000 0001 2106 9910, Center for Functional Cancer Epigenetics, , Dana-Farber Cancer Institute, ; Boston, MA 02215 USA

[5 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Medical Oncology, Dana-Farber Cancer Institute, , Harvard Medical School, ; Boston, MA 02215 USA

[6 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Data Sciences, , Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, ; Boston, MA 02215 USA

Author information

Clifford A. Meyer http://orcid.org/0000-0002-8321-2839

Article

Publisher ID: 1934

DOI: 10.1186/s13059-020-1934-6

PMC ID: 7007693

PubMed ID: 32033573

SO-VID: 0ecc2b92-617b-48e6-8cd4-53e926f28214

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 5 June 2019

Date accepted : 13 January 2020

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000054, National Cancer Institute;

Award ID: U24 CA237617

Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;

Award ID: U24 HG009446

Award Recipient : X. Shirley Liu

Funded by: Science and Technology Commission of Shanghai Municipality (CN)

Award ID: 18YF1402500

Award Recipient : Qian Qin

Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;

Award ID: 31801110

Award Recipient : Shenglin Mei

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: transcription factors,gene regulation,chromatin accessibility,dnase-seq,h3k27ac chip-seq,differential gene expression,gene set analysis

Data availability:

ScienceOpen disciplines: Genetics

Keywords: transcription factors, gene regulation, chromatin accessibility, dnase-seq, h3k27ac chip-seq, differential gene expression, gene set analysis

Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data

Read this article at

Abstract

Related collections

Genome Engineering using CRISPR

Most cited references 29

A unique chromatin signature uncovers early developmental enhancers in humans.

BigWig and BigBed: enabling browsing of large distributed datasets

The Myc/Max/Mad network and the transcriptional control of cell behavior.

Author and article information

Contributors

Journal

Affiliations

Author information

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 273

Cited by 127

Most referenced authors 1,814