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A widespread distribution of genomic CeMyoD binding sites revealed and cross validated by ChIP-Chip and ChIP-Seq techniques.

ABSTRACT: Identifying transcription factor binding sites genome-wide using chromatin immunoprecipitation (ChIP)-based technology is becoming an increasingly important tool in addressing developmental questions. However, technical problems associated with factor abundance and suitable ChIP reagents are common obstacles to these studies in many biological systems. We have used two completely different, widely applicable methods to determine by ChIP the genome-wide binding sites of the master myogenic regulatory transcription factor HLH-1 (CeMyoD) in C. elegans embryos. The two approaches, ChIP-seq and ChIP-chip, yield strongly overlapping results revealing that HLH-1 preferentially binds to promoter regions of genes enriched for E-box sequences (CANNTG), known binding sites for this well-studied class of transcription factors. HLH-1 binding sites were enriched upstream of genes known to be expressed in muscle, consistent with its role as a direct transcriptional regulator. HLH-1 binding was also detected at numerous sites unassociated with muscle gene expression, as has been previously described for its mouse homolog MyoD. These binding sites may reflect several additional functions for HLH-1, including its interactions with one or more co-factors to activate (or repress) gene expression or a role in chromatin organization distinct from direct transcriptional regulation of target genes. Our results also provide a comparison of ChIP methodologies that can overcome limitations commonly encountered in these types of studies while highlighting the complications of assigning in vivo functions to identified target sites.

SUBMITTER: Lei H

PROVIDER: S-EPMC3012110 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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A widespread distribution of genomic CeMyoD binding sites revealed and cross validated by ChIP-Chip and ChIP-Seq techniques.

Lei Haiyan H Fukushige Tetsunari T Niu Wei W Sarov Mihail M Reinke Valerie V Krause Michael M

PloS one 20101229 12

Identifying transcription factor binding sites genome-wide using chromatin immunoprecipitation (ChIP)-based technology is becoming an increasingly important tool in addressing developmental questions. However, technical problems associated with factor abundance and suitable ChIP reagents are common obstacles to these studies in many biological systems. We have used two completely different, widely applicable methods to determine by ChIP the genome-wide binding sites of the master myogenic regula ...[more]

PMID: 21209968

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Project description:BackgroundStrand cross-correlation profiles are used for both peak calling pre-analysis and quality control (QC) in chromatin immunoprecipitation followed by sequencing (ChIP-seq) analysis. Despite its potential for robust and accurate assessments of signal-to-noise ratio (S/N) because of its peak calling independence, it remains unclear what aspects of quality such strand cross-correlation profiles actually measure.ResultsWe introduced a simple model to simulate the mapped read-density of ChIP-seq and then derived the theoretical maximum and minimum of cross-correlation coefficients between strands. The results suggest that the maximum coefficient of typical ChIP-seq samples is directly proportional to the number of total mapped reads and the square of the ratio of signal reads, and inversely proportional to the number of peaks and the length of read-enriched regions. Simulation analysis supported our results and evaluation using 790 ChIP-seq data obtained from the public database demonstrated high consistency between calculated cross-correlation coefficients and estimated coefficients based on the theoretical relations and peak calling results. In addition, we found that the mappability-bias-correction improved sensitivity, enabling differentiation of maximum coefficients from the noise level. Based on these insights, we proposed virtual S/N (VSN), a novel peak call-free metric for S/N assessment. We also developed PyMaSC, a tool to calculate strand cross-correlation and VSN efficiently. VSN achieved most consistent S/N estimation for various ChIP targets and sequencing read depths. Furthermore, we demonstrated that a combination of VSN and pre-existing peak calling results enable the estimation of the numbers of detectable peaks for posterior experiments and assess peak calling results.ConclusionsWe present the first theoretical insights into the strand cross-correlation, and the results reveal the potential and the limitations of strand cross-correlation analysis. Our quality assessment framework using VSN provides peak call-independent QC and will help in the evaluation of peak call analysis in ChIP-seq experiments.

Dataset Information

A widespread distribution of genomic CeMyoD binding sites revealed and cross validated by ChIP-Chip and ChIP-Seq techniques.

Publications

A widespread distribution of genomic CeMyoD binding sites revealed and cross validated by ChIP-Chip and ChIP-Seq techniques.

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