Evidence map›Paper›PMID 26490019›Full record

ArticleNature communications2015

ChEC-seq kinetics discriminates transcription factor binding sites by DNA sequence and shape in vivo.

Gabriel E Zentner, Sivakanthan Kasinathan, Beibei Xin, Remo Rohs, Steven Henikoff

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Nature communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 126 papers.

0numbers the graph read from it
0cells of the map it votes in
126citing papers in PubMed
8.7field-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

126 citing papers in PubMed, 220 citations in OpenAlex.

  1. Review
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  9. Article
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  11. CUT&Tag for Chromatin Profiling in Cancer Tissue.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  12. Article
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  15. Article
  16. aBIOTECH · 2025
    Review
  17. Article
  18. Article
  19. Article
  20. Article

66 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Gabriel E ZentnerBasic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA.
Sivakanthan KasinathanBasic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA.
Beibei XinMolecular and Computational Biology Program, Departments of Biological Sciences, Chemistry, Physics, and Computer Science, University of Southern California, Los Angeles, California 90089, USA.
Remo RohsMolecular and Computational Biology Program, Departments of Biological Sciences, Chemistry, Physics, and Computer Science, University of Southern California, Los Angeles, California 90089, USA.
Steven HenikoffBasic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA.
Fred Hutch Cancer Center · USUniversity of Southern California · US

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Marian Esvelt · 1985 to 2026
$296.4M
University of Washington Medical Scientist Training Program: MD/PhDT32GM007266 · NIGMS · UNIVERSITY OF WASHINGTON · PI HORWITZ, MARSHALL S. · 1985 to 2023
$30.4M
Chromosome Metabolism and Cancer Training GrantT32CA009657 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI EISENMAN, ROBERT NEIL · 1991 to 2020
$7.6M
Epigenomic profiling of histone turnover kinetics in mammalian cellsR01ES020116 · NIEHS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI HENIKOFF, STEVEN · 2010 to 2014
$2.4M
Genome analysis based on the integration of DNA sequence and shapeR01GM106056 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ROHS, REMO · 2014 to 2017
$1.3M
FHCRC High-Performance Computing ClusterS10OD020069 · OD · FRED HUTCHINSON CANCER RESEARCH CENTER · PI KOOPERBERG, CHARLES L · 2015 to 2015
$600k
High-resolution analysis of chromatin regulation by the Max networkF30CA186458 · NCI · UNIVERSITY OF WASHINGTON · PI KASINATHAN, SIVAKANTHAN · 2014 to 2017
$171k
Howard Hughes Medical InstituteNCI NIH HHS F30 CA186458NCI NIH HHS F30CA186458NCI NIH HHS P30 CA015704NCI NIH HHS T32 CA009657NCI NIH HHS T32CA009657NIEHS NIH HHS R01 ES020116NIEHS NIH HHS R01ES020116NIGMS NIH HHS R01 GM106056NIGMS NIH HHS R01GM106056NIGMS NIH HHS T32 GM007266NIH HHS S10 OD020069
6 · The paper itself

Abstract

Chromatin endogenous cleavage (ChEC) uses fusion of a protein of interest to micrococcal nuclease (MNase) to target calcium-dependent cleavage to specific genomic loci in vivo. Here we report the combination of ChEC with high-throughput sequencing (ChEC-seq) to map budding yeast transcription factor (TF) binding. Temporal analysis of ChEC-seq data reveals two classes of sites for TFs, one displaying rapid cleavage at sites with robust consensus motifs and the second showing slow cleavage at largely unique sites with low-scoring motifs. Sites with high-scoring motifs also display asymmetric cleavage, indicating that ChEC-seq provides information on the directionality of TF-DNA interactions. Strikingly, similar DNA shape patterns are observed regardless of motif strength, indicating that the kinetics of ChEC-seq discriminates DNA recognition through sequence and/or shape. We propose that time-resolved ChEC-seq detects both high-affinity interactions of TFs with consensus motifs and sites preferentially sampled by TFs during diffusion and sliding.

Indexed as

Binding SitesChromatinDNADNA-Binding ProteinsHigh-Throughput Nucleotide SequencingMicrococcal NucleaseMolecular ConformationNucleotide MotifsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsShelterin ComplexTelomere-Binding ProteinsTranscription FactorsABF1 protein, S cerevisiaeChromatinDNADNA-Binding ProteinsMicrococcal NucleaseRAP1 protein, S cerevisiaeREB1 protein, S cerevisiaeSaccharomyces cerevisiae ProteinsShelterin ComplexTelomere-Binding ProteinsTranscription Factors

Identifiers

PMID26490019
PMCPMC4618392
OpenAlexW2172368992

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.