Evidence map›Paper›PMID 24428924›Full record

ArticleBMC genomics2014

T-KDE: a method for genome-wide identification of constitutive protein binding sites from multiple ChIP-seq data sets.

Yuanyuan Li, David M Umbach, Leping Li

Abstract read
In one paragraph

Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Yuanyuan Li
David M Umbach
Leping LiBiostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, Morrisville, NC 27709, USA. li3@niehs.nih.gov.

Funding

BioinformaticsZIAES101765 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI LI, LEPING · 2009 to 2025
$21.0M
Intramural NIH HHSNIEHS NIH HHS ES101765
6 · The paper itself

Abstract

backgroundA protein may bind to its target DNA sites constitutively, i.e., regardless of cell type. Intuitively, constitutive binding sites should be biologically functional. A prerequisite for understanding their functional relevance is knowing all their locations for a protein of interest. Genome-wide discovery of constitutive binding sites requires robust and efficient computational methods to integrate results from numerous binding experiments. Such methods are lacking, however.

resultsTo locate constitutive binding sites for a protein using ChIP-seq data for that protein from multiple cell lines, we developed a method, T-KDE, which combines a binary range tree with a kernel density estimator. Using 132 CTCF (CCCTC-binding factor) ChIP-seq datasets, we showed that the number of constitutive sites identified by T-KDE is robust to the choice of tuning parameter and that T-KDE identifies binding site locations more accurately than a binning approach. Furthermore, T-KDE can identify constitutive sites that are missed by a motif-based approach either because a bound site failed to reach the motif significance cutoff or because the peak sequence scanned was too short. By studying sites declared constitutive by T-KDE but not by the motif-based approach, we discovered two new CTCF motif variants. Using ENCODE data on 22 transcription factors (TF) in 132 cell lines, we identified constitutive binding sites for each TF and provide evidence that, for some TFs, they may be biologically meaningful.

conclusionsT-KDE is an efficient and effective method to predict constitutive protein binding sites using ChIP-seq peaks from multiple cell lines. Besides constitutive binding sites for a given protein, T-KDE can identify genomic "hot spots" where several different proteins bind and, conversely, cell-type-specific sites bound by a given protein.

Indexed as

GenomeAlgorithmsBase SequenceBinding SitesCCCTC-Binding FactorCell Line, TumorChromatin ImmunoprecipitationDNAGenomicsHumansProtein BindingRepressor ProteinsSequence Analysis, DNASoftwareCCCTC-Binding FactorCTCF protein, humanDNARepressor Proteins

Identifiers

PMID24428924
PMCPMC3903014

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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.