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A comparative analysis of genome-wide chromatin immunoprecipitation data for mammalian transcription factors.

ABSTRACT: Genome-wide location analysis (ChIP-chip, ChIP-PET) is a powerful technique to study mammalian transcriptional regulation. In order to obtain a basic understanding of the location data generated for mammalian transcription factors and potential issues in their analysis, we conducted a comparative study of eight independent ChIP experiments involving six different transcription factors in human and mouse. Our cross-study comparisons, to the best of our knowledge the first to analyze multiple datasets, revealed the importance of carefully chosen genomic controls in the de novo identification of key transcription factor binding motifs, raised issues about the interpretation of ubiquitously occurring sequence motifs, and demonstrated the clustering tendency of protein-binding regions for certain transcription factors.

SUBMITTER: Ji H

PROVIDER: S-EPMC1669715 | biostudies-literature | 2006

REPOSITORIES: biostudies-literature

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A comparative analysis of genome-wide chromatin immunoprecipitation data for mammalian transcription factors.

Ji Hongkai H Vokes Steven A SA Wong Wing H WH

Nucleic acids research 20061107 21

Genome-wide location analysis (ChIP-chip, ChIP-PET) is a powerful technique to study mammalian transcriptional regulation. In order to obtain a basic understanding of the location data generated for mammalian transcription factors and potential issues in their analysis, we conducted a comparative study of eight independent ChIP experiments involving six different transcription factors in human and mouse. Our cross-study comparisons, to the best of our knowledge the first to analyze multiple data ...[more]

PMID: 17090591

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Project description:BackgroundBivalent chromatin is an exemplar of epigenetic plasticity. This co-occurrence of active-associated H3K4me3 and inactive-associated H3K27me3 histone modifications on opposite tails of the same nucleosome occurs predominantly at promoters that are poised for future transcriptional upregulation or terminal silencing. We know little of the dynamics, resolution, and regulation of this chromatin state outside of embryonic stem cells where it was first described. This is partly due to the technical challenges distinguishing bone-fide bivalent chromatin, where both marks are on the same nucleosome, from allelic or sample heterogeneity where there is a mix of H3K4me3-only and H3K27me3-only mononucleosomes.ResultsHere, we present a robust and sensitive method to accurately map bivalent chromatin genome-wide, along with controls, from as little as 2 million cells. We optimized and refined the sequential ChIP protocol which uses two sequential overnight immunoprecipitation reactions to robustly purify nucleosomes that are truly bivalent and contain both H3K4me3 and H3K27me3 modifications. Our method generates high quality genome-wide maps with strong peak enrichment and low background, which can be analyzed using standard bioinformatic packages. Using this method, we detect 8,789 bivalent regions in mouse embryonic stem cells corresponding to 3,918 predominantly CpG rich and developmentally regulated gene promoters. Furthermore, profiling Dppa2/4 knockout mouse embryonic stem cells, which lose both H3K4me3 and H3K27me3 at approximately 10% of bivalent promoters, demonstrated the ability of our method to capture bivalent chromatin dynamics.ConclusionsOur optimized sequential reChIP method enables high-resolution genome-wide assessment of bivalent chromatin together with all required controls in as little as 2 million cells. We share a detailed protocol and guidelines that will enable bivalent chromatin landscapes to be generated in a range of cellular contexts, greatly enhancing our understanding of bivalent chromatin and epigenetic plasticity beyond embryonic stem cells.

Dataset Information

A comparative analysis of genome-wide chromatin immunoprecipitation data for mammalian transcription factors.

Publications

A comparative analysis of genome-wide chromatin immunoprecipitation data for mammalian transcription factors.

Similar Datasets

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