Dataset Information


DNase I hypersensitivity and algorithmic prediction of TF binding in early pancreatic mES directed differentiation

ABSTRACT: This dataset uses DNase-seq to profile the genome-wide DNase I hypersensitivity of mES and mES-derived cells along an early pancreatic lineage and provides the locations of putative Transcription Factor (TF) binding sites using the PIQ algorithm. DNase-seq takes advantage of the preferential cutting of DNase I in open chromatin and steric blockage of of DNase I by tightly bound TFs that protect associated genomic DNA sequences. After deep sequencing of DNase I–digested genomic DNA from intact nuclei, genome-wide data on chromatin accessibility as well as TF-specific DNase I protection profiles that reveal the genomic binding locations of a majority of TFs are obtained. Such TF signature ‘DNase profiles’ reflect the effect of the TF on DNA shape and local chromatin architecture, extending hundreds of base pairs from a TF binding site, and these profiles are centered on ‘DNase footprints’ at the binding motif itself, which reflects the biophysics of protein-DNA binding. An algorithm, PIQ, is then applied that models the specific profile of each factor, and in combination with sequence information predicts the likely binding locations of over 700 TFs genome wide. This dataset includes DNase-seq hypersensitivity data from 6 mES-derived cell types: mESC, Mesendoderm, Mesoderm, Endoderm, Intestinal Endoderm, and Prepancreatic Endoderm. For each cell type, TF binding site predictions are made based on the identification TF-specific DNase-seq profiles over any of 1331 possible binding motifs. After significance thesholding, genome-wide binding site predictions for <700 TFs are included.

ORGANISM(S): Mus musculus  

SUBMITTER: Tatsunori Hashimoto   David K Gifford  Sophia Lewis  Amira A Barkal  John P van Hoff  Vivek Karun  Charles W O'Donnell  Tommi Jaakkola  David K. Gifford  Richard I Sherwood 

PROVIDER: E-GEOD-53776 | ArrayExpress | 2014-01-19



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Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape.

Sherwood Richard I RI   Hashimoto Tatsunori T   O'Donnell Charles W CW   Lewis Sophia S   Barkal Amira A AA   van Hoff John Peter JP   Karun Vivek V   Jaakkola Tommi T   Gifford David K DK  

Nature biotechnology 20140119 2

We describe protein interaction quantitation (PIQ), a computational method for modeling the magnitude and shape of genome-wide DNase I hypersensitivity profiles to identify transcription factor (TF) binding sites. Through the use of machine-learning techniques, PIQ identified binding sites for >700 TFs from one DNase I hypersensitivity analysis followed by sequencing (DNase-seq) experiment with accuracy comparable to that of chromatin immunoprecipitation followed by sequencing (ChIP-seq). We app  ...[more]

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