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Distinct properties of cell-type-specific and shared transcription factor binding sites.

ABSTRACT: Most human transcription factors bind a small subset of potential genomic sites and often use different subsets in different cell types. To identify mechanisms that govern cell-type-specific transcription factor binding, we used an integrative approach to study estrogen receptor ? (ER). We found that ER exhibits two distinct modes of binding. Shared sites, bound in multiple cell types, are characterized by high-affinity estrogen response elements (EREs), inaccessible chromatin, and a lack of DNA methylation, while cell-specific sites are characterized by a lack of EREs, co-occurrence with other transcription factors, and cell-type-specific chromatin accessibility and DNA methylation. These observations enabled accurate quantitative models of ER binding that suggest tethering of ER to one-third of cell-specific sites. The distinct properties of cell-specific binding were also observed with glucocorticoid receptor and for ER in primary mouse tissues, representing an elegant genomic encoding scheme for generating cell-type-specific gene regulation.

SUBMITTER: Gertz J

PROVIDER: S-EPMC3811135 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Distinct properties of cell-type-specific and shared transcription factor binding sites.

Gertz Jason J Savic Daniel D Varley Katherine E KE Partridge E Christopher EC Safi Alexias A Jain Preti P Cooper Gregory M GM Reddy Timothy E TE Crawford Gregory E GE Myers Richard M RM

Molecular cell 20130926 1

Most human transcription factors bind a small subset of potential genomic sites and often use different subsets in different cell types. To identify mechanisms that govern cell-type-specific transcription factor binding, we used an integrative approach to study estrogen receptor α (ER). We found that ER exhibits two distinct modes of binding. Shared sites, bound in multiple cell types, are characterized by high-affinity estrogen response elements (EREs), inaccessible chromatin, and a lack of DNA ...[more]

PMID: 24076218

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Project description:MotivationCell-type-specific gene expression is maintained in large part by transcription factors (TFs) selectively binding to distinct sets of sites in different cell types. Recent research works have provided evidence that such cell-type-specific binding is determined by TF's intrinsic sequence preferences, cooperative interactions with co-factors, cell-type-specific chromatin landscapes and 3D chromatin interactions. However, computational prediction and characterization of cell-type-specific and shared binding sites is rarely studied.ResultsIn this article, we propose two computational approaches for predicting and characterizing cell-type-specific and shared binding sites by integrating multiple types of features, in which one is based on XGBoost and another is based on convolutional neural network (CNN). To validate the performance of our proposed approaches, ChIP-seq datasets of 10 binding factors were collected from the GM12878 (lymphoblastoid) and K562 (erythroleukemic) human hematopoietic cell lines, each of which was further categorized into cell-type-specific (GM12878- and K562-specific) and shared binding sites. Then, multiple types of features for these binding sites were integrated to train the XGBoost- and CNN-based models. Experimental results show that our proposed approaches significantly outperform other competing methods on three classification tasks. Moreover, we identified independent feature contributions for cell-type-specific and shared sites through SHAP values and explored the ability of the CNN-based model to predict cell-type-specific and shared binding sites by excluding or including DNase signals. Furthermore, we investigated the generalization ability of our proposed approaches to different binding factors in the same cellular environment.Availability and implementationThe source code is available at: https://github.com/turningpoint1988/CSSBS.Supplementary informationSupplementary data are available at Bioinformatics online.

Dataset Information

Distinct properties of cell-type-specific and shared transcription factor binding sites.

Publications

Distinct properties of cell-type-specific and shared transcription factor binding sites.

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