Abstract

BackgroundRegulated gene expression controls organismal development, and variation in regulatory patterns has been implicated in complex traits. Thus accurate prediction of enhancers is important for further understanding of these processes. Genome-wide measurement of epigenetic features, such as histone modifications and occupancy by transcription factors, is improving enhancer predictions, but the contribution of these features to prediction accuracy is not known. Given the importance of the hematopoietic transcription factor TAL1 for erythroid gene activation, we predicted candidate enhancers based on genomic occupancy by TAL1 and measured their activity. Contributions of multiple features to enhancer prediction were evaluated based on the results of these and other studies.ResultsTAL1-bound DNA segments were active enhancers at a high rate both in transient transfections of cultured cells (39 of 79, or 56%) and transgenic mice (43 of 66, or 65%). The level of binding signal for TAL1 or GATA1 did not help distinguish TAL1-bound DNA segments as active versus inactive enhancers, nor did the density of regulation-related histone modifications. A meta-analysis of results from this and other studies (273 tested predicted enhancers) showed that the presence of TAL1, GATA1, EP300, SMAD1, H3K4 methylation, H3K27ac, and CAGE tags at DNase hypersensitive sites gave the most accurate predictors of enhancer activity, with a success rate over 80% and a median threefold increase in activity. Chromatin accessibility assays and the histone modifications H3K4me1 and H3K27ac were sensitive for finding enhancers, but they have high false positive rates unless transcription factor occupancy is also included.ConclusionsOccupancy by key transcription factors such as TAL1, GATA1, SMAD1, and EP300, along with evidence of transcription, improves the accuracy of enhancer predictions based on epigenetic features.Electronic supplementary materialThe online version of this article (doi:10.1186/s13072-015-0009-5) contains supplementary material, which is available to authorized users.

Highlights

  • Regulated gene expression controls organismal development, and variation in regulatory patterns has been implicated in complex traits

  • Occupancy by T-cell acute lymphocytic leukemia protein 1 (TAL1) is a strong predictor of enhancer activity We began with the set of 4,915 DNA segments determined by ChIP-seq to be bound by TAL1 (TAL1 occupied DNA segments or TAL1 OSs) (Table 1; Additional file 1: Table S1) in G1E-ER4 cells treated with betaestradiol, which are a model for erythroblasts differentiating in response to restoration of GATA-binding factor 1 (GATA1) [39,40]

  • The vast majority of TAL1 OSs were in regions of accessible chromatin (DNase I hypersensitive sites, DHSs; [36,44]) containing histone modifications (HMs) associated with gene regulatory regions (H3K27ac [45], histone H3 lysine mono-methylation (H3K4me1) [36], and/or histone H3 lysine tri-methylation (H3K4me3) [36]; Figure 1B)

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Summary

Introduction

Regulated gene expression controls organismal development, and variation in regulatory patterns has been implicated in complex traits. Accurate identification of cis-regulatory modules (CRMs), such as enhancers, is essential for understanding mechanisms of gene regulation, modeling regulation during differentiation, and interpreting the effects of genetic variants associated with complex traits. Challenges to meeting this goal are formidable [1]. The complex of bound proteins tends to interact with co-activators such as EP300 [16], and the TF-bound enhancer is flanked by nucleosomes with characteristic histone modifications, such as H3K4 monomethylation (H3K4me1) and H3K27 acetylation (H3K27ac) [17,18,19]. Another approach used a discriminatory machine-learning approach to integrate multiple datasets and data types to predict and validate developmental enhancers [29]

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