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Background Recent studies have suggested that combinations of multiple epigenetic modifications are essential for controlling gene expression. Despite numerous computational approaches have been developed to decipher the combinatorial epigenetic patterns or “epigenetic code”, none of them has explicitly addressed the relationship between a specific transcription factor (TF) and the patterns. Methods Here, we developed a novel computational method, T-cep, for annotating chromatin states associated with a specific TF. T-cep is composed of three key consecutive modules: (i) Data preprocessing, (ii) HMM training, and (iii) Potential TF-states calling. Results We evaluated T-cep on a TCF7L2-omics data. Unexpectedly, our method has uncovered a novel set of TCF7L2-regulated intragenic enhancers missed by other software tools, where the associated genes exert the highest gene expression. We further used siRNA knockdown, Co-transfection, RT-qPCR and Luciferase Reporter Assay not only to validate the accuracy and efficiency of prediction by T-cep, but also to confirm the functionality of TCF7L2-regulated enhancers in both MCF7 and PANC1 cells respectively. Conclusions Our study for the first time at a genome-wide scale reveals the enhanced transcriptional activity of cell-type-specific TCF7L2 intragenic enhancers in regulating gene expression. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3764-9) contains supplementary material, which is available to authorized users.

Background Epigenetic modifications are essential for controlling gene expression. Recent studies have shown that not only single epigenetic modifications but also combinations of multiple epigenetic modifications play vital roles in gene regulation. A striking example is the long hypomethylated regions enriched with modified H3K27me3 (called, "K27HMD" regions), which are exposed to suppress the expression of key developmental genes relevant to cellular development and differentiation during embryonic stages in vertebrates. It is thus a biologically important issue to develop an effective optimization algorithm for detecting long DNA regions (e.g., >4 kbp in size) that harbor a specific combination of epigenetic modifications (e.g., K27HMD regions). However, to date, optimization algorithms for these purposes have received little attention, and available methods are still heuristic and ad hoc. Results In this paper, we propose a linear time algorithm for calculating a set of non-overlapping regions that maximizes the sum of similarities between the vector of focal epigenetic states and the vectors of raw epigenetic states at DNA positions in the set of regions. The average elapsed time to process the epigenetic data of any of human chromosomes was less than 2 seconds on an Intel Xeon CPU. To demonstrate the effectiveness of the algorithm, we estimated large K27HMD regions in the medaka and human genomes using our method, ChromHMM, and a heuristic method. Conclusions We confirmed that the advantages of our method over those of the two other methods. Our method is flexible enough to handle other types of epigenetic combinations. The program that implements the method is called "CSMinfinder" and is made available at: http://mlab.cb.k.u-tokyo.ac.jp/~ichikawa/Segmentation/

Background Combinations of histone variants and modifications, conceptually representing a histone code, have been proposed to play a significant role in gene regulation and developmental processes in complex organisms. While various mechanisms have been implicated in establishing and maintaining epigenetic patterns at specific locations in the genome, they are generally believed to be independent of primary DNA sequence on a more global scale. Results To address this systematically in the case of the human genome, we have analyzed primary DNA sequences underlying patterns of 19 different methylated histones in human primary T-cells and patterns of three methylated histones across additional human cell lines. We report strong sequence biases associated with most of these histone marks genome-wide in each cell type. Furthermore, the sequence characteristics for such association are distinct for different groups of histone marks. Conclusions These findings provide evidence of an influence of genomic sequence on patterns of histone modification associated with gene expression and chromatin programming, and they suggest that the mechanisms responsible for global histone modifications may interpret genomic sequence in various ways.

Background An underlying tenet of the epigenetic code hypothesis is the existence of protein domains that can recognize various chromatin structures. To date, two major candidates have emerged: (i) the bromodomain, which can recognize certain acetylation marks and (ii) the chromodomain, which can recognize certain methylation marks. Results The Epc-N (E nhancer of P olyc omb-N-terminus) domain is formally defined herein. This domain is conserved across eukaryotes and is predicted to form a right-handed orthogonal four-helix bundle with extended strands at both termini. The types of amino acid residues that define the Epc-N domain suggest a role in mediating protein-protein interactions, possibly specifically in the context of chromatin binding, and the types of proteins in which it is found (known components of histone acetyltransferase complexes) strongly suggest a role in epigenetic structure formation and/or recognition. There appear to be two major Epc-N protein families that can be divided into four unique protein subfamilies. Two of these subfamilies (I and II) may be related to one another in that subfamily I can be viewed as a plant-specific expansion of subfamily II. The other two subfamilies (III and IV) appear to be related to one another by duplication events in a primordial fungal-metazoan-mycetozoan ancestor. Subfamilies III and IV are further defined by the presence of an evolutionarily conserved five-center-zinc-binding motif in the loop connecting the second and third helices of the four-helix bundle. This m otif appears to consist of a P HD followed by a mononuclear Z n knuckle, followed by a P HD-like derivative, and will thus be referred to as the PZPM. All non-Epc-N proteins studied thus far that contain the PZPM have been implicated in histone methylation and/or gene silencing. In addition, an unusual phyletic distribution of Epc-N-containing proteins is observed. Conclusion The data suggest that the Epc-N domain is a protein-protein interaction module found in chromatin associated proteins. It is possible that the Epc-N domain serves as a direct link between histone acetylation and methylation statuses. The unusual phyletic distribution of Epc-N-containing proteins may provide a conduit for future insight into how different organisms form, perceive and respond to epigenetic information.

Background Combinatorial histone modification is an important epigenetic mechanism for regulating chromatin state and gene expression. Given the rapid accumulation of genome-wide histone modification maps, there is a pressing need for computational methods capable of joint analysis of multiple maps to reveal combinatorial modification patterns. Results We present the Semi-Supervised Coherent and Shifted Bicluster Identification algorithm (SS-CoSBI). It uses prior knowledge of combinatorial histone modifications to guide the biclustering process. Specifically, co-occurrence frequencies of histone modifications characterized by mass spectrometry are used as probabilistic priors to adjust the similarity measure in the biclustering process. Using a high-quality set of transcriptional enhancers and associated histone marks, we demonstrate that SS-CoSBI outperforms its predecessor by finding histone modification and genomic locus biclusters with higher enrichment of enhancers. We apply SS-CoSBI to identify multiple cell-type-specific combinatorial histone modification states associated with human enhancers. We show enhancer histone modification states are correlated with the expression of nearby genes. Further, we find that enhancers with the histone mark H3K4me1 have higher levels of DNA methylation and decreased expression of nearby genes, suggesting a functional interplay between H3K4me1 and DNA methylation that can modulate enhancer activities. Conclusions The analysis presented here provides a systematic characterization of combinatorial histone codes of enhancers across three human cell types using a novel semi-supervised biclustering algorithm. As epigenomic maps accumulate, SS-CoSBI will become increasingly useful for understanding combinatorial chromatin modifications by taking advantage of existing knowledge. Availability and implementation SS-CoSBI is implemented in C. The source code is freely available at http://www.healthcare.uiowa.edu/labs/tan/SS-CoSBI.gz.