Evidence map›Paper›PMID 25984238›Full record

ArticleEpigenetics & chromatin2015

Occupancy by key transcription factors is a more accurate predictor of enhancer activity than histone modifications or chromatin accessibility.

Nergiz Dogan, Weisheng Wu, Christapher S Morrissey, Kuan-Bei Chen, Aaron Stonestrom, Maria Long, Cheryl A Keller, Yong Cheng, Deepti Jain, Axel Visel and 4 more

Open access · goldAbstract read
In one paragraph

Article in Epigenetics & chromatin, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed
7.4field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

75 citing papers in PubMed, 121 citations in OpenAlex.

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  11. LDB1 establishes multi-enhancer networks to regulate gene expression.bioRxiv : the preprint server for biology · 2024
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15 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 7 institutions in 1 country.

Nergiz DoganCenter for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, 304 Wartik Laboratory, University Park, PA 16802 USA.
Weisheng WuCenter for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, 304 Wartik Laboratory, University Park, PA 16802 USA ; Bioinformatics Core, Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218 USA.
Christapher S MorrisseyCenter for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, 304 Wartik Laboratory, University Park, PA 16802 USA.
Kuan-Bei ChenCenter for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, 304 Wartik Laboratory, University Park, PA 16802 USA.
Aaron StonestromDivision of Hematology, The Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA 19104 USA ; Perelman School of Medicine at the University of Pennsylvania, 415 Curie Boulevard, Philadelphia, PA 19104 USA.
Maria LongCenter for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, 304 Wartik Laboratory, University Park, PA 16802 USA.
Cheryl A KellerCenter for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, 304 Wartik Laboratory, University Park, PA 16802 USA.
Yong ChengDepartment of Genetics, Mail Stop-5120, Stanford University, Stanford, CA 94305 USA.
Deepti JainCenter for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, 304 Wartik Laboratory, University Park, PA 16802 USA.
Axel ViselGenomics Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Mailstop 84-171, Berkeley, CA 94720 USA ; DOE Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA 94598 USA.
Len A PennacchioGenomics Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Mailstop 84-171, Berkeley, CA 94720 USA ; DOE Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA 94598 USA.
Mitchell J WeissDepartment of Hematology, St Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105 USA.
Gerd A BlobelDivision of Hematology, The Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA 19104 USA ; Perelman School of Medicine at the University of Pennsylvania, 415 Curie Boulevard, Philadelphia, PA 19104 USA.
Ross C HardisonCenter for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, 304 Wartik Laboratory, University Park, PA 16802 USA.
Pennsylvania State University · USChildren's Hospital of Philadelphia · USJoint Genome Institute · USLawrence Berkeley National Laboratory · USStanford University · USSt. Jude Children's Research Hospital · USUniversity of Pennsylvania · US

Funding

Generation of an In Vivo Human Genome Transcriptional Enhancer DatasetR01HG003988 · NHGRI · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI Len Alexander Pennacchio · 2006 to 2026
$24.1M
Toward a comprehensive functional annotation of the human genomeU54HG006998 · NHGRI · HUDSON-ALPHA INSTITUTE FOR BIOTECHNOLOGY · PI MYERS, RICHARD M · 2012 to 2016
$17.5M
Transcriptional Networks Controlling Erythroid DifferentiationR01DK054937 · NIDDK · CHILDREN'S HOSP OF PHILADELPHIA · PI Gerd A Blobel · 1999 to 2026
$12.8M
Embryonic Stem Cell-Derived Platelets as Cellular TherapeuticsU01HL099656 · NHLBI · CHILDREN'S HOSP OF PHILADELPHIA · PI PONCZ, MORTIMER · 2009 to 2015
$8.6M
Research BaseP30DK090969 · NIDDK · CHILDREN'S HOSP OF PHILADELPHIA · PI CARROLL, MARTIN · 2010 to 2015
$5.7M
Global Predictions and Tests of Erythroid RegulationR01DK065806 · NIDDK · PENNSYLVANIA STATE UNIVERSITY-UNIV PARK · PI BLOBEL, GERD A, CHIAROMONTE, FRANCESCA · 2004 to 2013
$5.3M
Roles of CBP &PCAF During Hematopoietic DifferentiationR01DK058044 · NIDDK · CHILDREN'S HOSP OF PHILADELPHIA · PI BLOBEL, GERD A · 2002 to 2023
$4.5M
Epigenetic Control of Hematopoietic Gene ExpressionR37DK058044 · NIDDK · CHILDREN'S HOSP OF PHILADELPHIA · PI BLOBEL, GERD A · 2010 to 2019
$3.7M
Enhance human ENCODE by function comparisons to mouseRC2HG005573 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI HARDISON, ROSS C · 2009 to 2011
$2.2M
Global Predictions and Tests of Hematopoietic RegulationR56DK065806 · NIDDK · PENNSYLVANIA STATE UNIVERSITY, THE · PI BLOBEL, GERD A, BODINE, DAVID M. · 2014 to 2014
$224k
NHGRI NIH HHS R01 HG003988NHGRI NIH HHS RC2 HG005573NHGRI NIH HHS U54 HG006998NHLBI NIH HHS U01 HL099656NIDDK NIH HHS P30 DK090969NIDDK NIH HHS R01 DK054937NIDDK NIH HHS R01 DK058044NIDDK NIH HHS R01 DK065806NIDDK NIH HHS R37 DK058044NIDDK NIH HHS R56 DK065806
6 · The paper itself

Abstract

backgroundRegulated gene expression controls organismal development, and variation in regulatory patterns has been implicated in complex traits. Thus accurate prediction of enhancers is important for further understanding of these processes. Genome-wide measurement of epigenetic features, such as histone modifications and occupancy by transcription factors, is improving enhancer predictions, but the contribution of these features to prediction accuracy is not known. Given the importance of the hematopoietic transcription factor TAL1 for erythroid gene activation, we predicted candidate enhancers based on genomic occupancy by TAL1 and measured their activity. Contributions of multiple features to enhancer prediction were evaluated based on the results of these and other studies.

resultsTAL1-bound DNA segments were active enhancers at a high rate both in transient transfections of cultured cells (39 of 79, or 56%) and transgenic mice (43 of 66, or 65%). The level of binding signal for TAL1 or GATA1 did not help distinguish TAL1-bound DNA segments as active versus inactive enhancers, nor did the density of regulation-related histone modifications. A meta-analysis of results from this and other studies (273 tested predicted enhancers) showed that the presence of TAL1, GATA1, EP300, SMAD1, H3K4 methylation, H3K27ac, and CAGE tags at DNase hypersensitive sites gave the most accurate predictors of enhancer activity, with a success rate over 80% and a median threefold increase in activity. Chromatin accessibility assays and the histone modifications H3K4me1 and H3K27ac were sensitive for finding enhancers, but they have high false positive rates unless transcription factor occupancy is also included.

conclusionsOccupancy by key transcription factors such as TAL1, GATA1, SMAD1, and EP300, along with evidence of transcription, improves the accuracy of enhancer predictions based on epigenetic features.

Indexed as

Enhancer assayFunctional genomicsGATA1Gene regulationHistone modificationsTAL1

Identifiers

PMID25984238
PMCPMC4432502
OpenAlexW1988760117

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.