Unknown,Transcriptomics,Genomics,Proteomics

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Induced Cdx2 binding in embryonic stem cells and endodermal cells


ABSTRACT: Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPSM-bM-^@M-^Ys multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with pre-existing genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. In this study, we characterize the binding of Cdx2 in embryonic stem cells, endodermal cells, and progenitor motor neurons using V5- or FLAG-tagged doxycycline inducible Cdx2 ESC lines (iCdx2). Endoderm and progenitor motor neurons are generated from the ES cells using directed differentiation approaches. The cells are then exposed to Dox to express the tagged Cdx2 construct. The genome-wide binding of the induced full-length Cdx2 transcription factor is profiled using ChIP-seq with an anti-V5 or anti-FLAG antibody. We also examine the binding behavior of a truncated version of the Cdx2 protein, where a protein interaction domain contained in the first 59 amino acids has been deleted. An appropriate pseudo-IP control experiment for these ChIP-seq experiments has been previously submitted under accession number GSM766062.

ORGANISM(S): Mus musculus

SUBMITTER: Shaun Mahony 

PROVIDER: E-GEOD-39435 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

An integrated model of multiple-condition ChIP-Seq data reveals predeterminants of Cdx2 binding.

Mahony Shaun S   Edwards Matthew D MD   Mazzoni Esteban O EO   Sherwood Richard I RI   Kakumanu Akshay A   Morrison Carolyn A CA   Wichterle Hynek H   Gifford David K DK  

PLoS computational biology 20140327 3


Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneo  ...[more]

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