ChIP-seq and beyond: new and improved methodologies to detect and characterize protein-DNA interactions. Nat Rev Genet. 2012;13:840-852. [PMID: 23090257 DOI: 10.1038/nrg3306]

Modeling protein-DNA binding via high-throughput in vitro technologies

Protein-DNA binding plays a central role in gene regulation and by that in all processes in the living cell. Novel experimental and computational approaches facilitate better understanding of protein-DNA binding preferences via high-throughput measurement of protein binding to a large number of DNA sequences and inference of binding models from them. Here we review the state of the art in measuring protein-DNA binding in vitro, emphasizing the advantages and limitations of different technologies. In addition, we describe models for representing protein-DNA binding preferences and key computational approaches to learn those from high-throughput data. Using large experimental data sets, we test the performance of different models based on different measuring techniques. We conclude with pertinent open problems.

Genomic mapping of chromatin proteins by using Daminv modification of an FLP-dependent DamID approach

To identify interactions of chromatin proteins with the genome of the cell type of interest that is a part of heterologous tissues and organs of Drosophila, an FLP-dependent DamID approach was recently developed [4], which does not require sorting of cells or nuclei. Here, a modification of this approach, Dam^inv, is described. The modified approach was validated by generating the binding pattern of the LAM protein, a component of the inner membrane of the nuclear envelope, with the genome of glial cells of the Drosophila larval central brains.

The promise of epigenetic therapy: reprogramming the cancer epigenome

Epigenetics refers to heritable molecular determinants of phenotype independent of DNA sequence. Epigenetic features include DNA methylation, histone modifications, non-coding RNAs, and chromatin structure. The epigenetic status of cells plays a crucial role in determining their differentiation state and proper function within multicellular organisms. Disruption of these processes is now understood to be a major contributor to cancer development and progression, and recent efforts have attempted to pharmacologically reverse such altered epigenetics. In this mini-review we introduce the concept of epigenetic drivers of cancer and discuss how aberrant DNA methylation, histone modifications, and chromatin states are being targeted using drugs either in preclinical, or clinical development, and how they fit in the context of existing therapies.

Transcription factor-DNA binding: beyond binding site motifs

Sequence-specific transcription factors (TFs) regulate gene expression by binding to cis-regulatory elements in promoter and enhancer DNA. While studies of TF-DNA binding have focused on TFs' intrinsic preferences for primary nucleotide sequence motifs, recent studies have elucidated additional layers of complexity that modulate TF-DNA binding. In this review, we discuss technological developments for identifying TF binding preferences and highlight recent discoveries that elaborate how TF interactions, local DNA structure, and genomic features influence TF-DNA binding. We highlight novel approaches for characterizing functional binding site motifs that promise to inform our understanding of how TF binding controls gene expression and ultimately contributes to phenotype.

Spatial transcriptomics: paving the way for tissue-level systems biology

The tissues in our bodies are complex systems composed of diverse cell types that often interact in highly structured repeating anatomical units. External gradients of morphogens, directional blood flow, as well as the secretion and absorption of materials by cells generate distinct microenvironments at different tissue coordinates. Such spatial heterogeneity enables optimized function through division of labor among cells. Unraveling the design principles that govern this spatial division of labor requires techniques to quantify the entire transcriptomes of cells while accounting for their spatial coordinates. In this review we describe how recent advances in spatial transcriptomics open the way for tissue-level systems biology.

Interplay between genetic and epigenetic mechanisms in rheumatoid arthritis

Genetic and environmental factors contribute to the risk for rheumatoid arthritis (RA), with epigenetics serving as a possible interface through which risk factors contribute to RA. High-throughput technologies for interrogating genome and epigenome, and the availability of genetic and epigenetic datasets across a diversity of cell types, enable the identification of candidate causal genetic variants for RA to study their function in core RA processes. To date, RA risk variants were studied in the immune cells but not joint resident cells, for example, synovial fibroblasts. Synovial fibroblasts from different joints are distinct, anatomically specialized cells, defined by joint-specific transcriptomes, epigenomes and phenotypes. Cell type-specific analysis of epigenetic changes, together with genetic fine mapping and interrogation of chromatin 3D interactions may identify new disease relevant pathways, potential therapeutic targets and biomarkers for RA progression or therapy response.

Genome-wide analysis of chromatin structures in Trypanosoma brucei using high-resolution MNase-ChIP-seq

Specific DNA-protein interactions are the basis for many important cellular mechanisms like the regulation of gene expression or replication. Knowledge about the precise genomic locations of DNA-protein interactions is important because it provides insight into the regulation of these processes. Recently, we have adapted an approach that combines micrococcal nuclease (MNase) digestion of chromatin with chromatin immunoprecipitation in Trypanosoma brucei. Here, we describe in detail how this method can be used to map the genome-wide distribution of nucleosomes or other DNA-binding proteins at high resolution in T. brucei.

Global histone modification fingerprinting in human cells using epigenetic reverse phase protein array

The balance between acetylation and deacetylation of histone proteins plays a critical role in the regulation of genomic functions. Aberrations in global levels of histone modifications are linked to carcinogenesis and are currently the focus of intense scrutiny and translational research investments to develop new therapies, which can modify complex disease pathophysiology through epigenetic control. However, despite significant progress in our understanding of the molecular mechanisms of epigenetic machinery in various genomic contexts and cell types, the links between epigenetic modifications and cellular phenotypes are far from being clear. For example, enzymes controlling histone modifications utilize key cellular metabolites associated with intra- and extracellular feedback loops, adding a further layer of complexity to this process. Meanwhile, it has become increasingly evident that new assay technologies which provide robust and precise measurement of global histone modifications are required, for at least two pressing reasons: firstly, many approved drugs are known to influence histone modifications and new cancer therapies are increasingly being developed towards targeting histone deacetylases (HDACs) and other epigenetic readers and writers. Therefore, robust assays for fingerprinting the global effects of such drugs on preclinical cell, organoid and in vivo models is required; and secondly, robust histone-fingerprinting assays applicable to patient samples may afford the development of next-generation diagnostic and prognostic tools. In our study, we have used a panel of monoclonal antibodies to determine the relative changes in the global abundance of post-translational modifications on histones purified from cancer cell lines treated with HDAC inhibitors using a novel technique, called epigenetic reverse phase protein array. We observed a robust increase in acetylation levels within 2–24 h after inhibition of HDACs in different cancer cell lines. Moreover, when these cells were treated with N-acetylated amino acids in addition to HDACs, we detected a further increase in histone acetylation, demonstrating that these molecules could be utilized as donors of the acetyl moiety for protein acetylation. Consequently, this study not only offers a novel assay for diagnostics and drug screening but also warrants further research of the novel class of inexpensive, non-toxic natural compounds that could potentiate the effects of HDAC inhibitors and is therefore of interest for cancer therapeutics.

iHMS: a database integrating human histone modification data across developmental stages and tissues

Background

Differences in chromatin states are critical to the multiplicity of cell states. Recently genome-wide histone modification maps of diverse human developmental stages and tissues have been charted.

Description

To facilitate the investigation of epigenetic dynamics and regulatory mechanisms in cellular differentiation processes, we developed iHMS, an integrated human histone modification database that incorporates massive histone modification maps spanning different developmental stages, lineages and tissues (http://www.tongjidmb.com/human/index.html). It also includes genome-wide expression data of different conditions, reference gene annotations, GC content and CpG island information. By providing an intuitive and user-friendly query interface, iHMS enables comprehensive query and comparative analysis based on gene names, genomic region locations, histone modification marks and cell types. Moreover, it offers an efficient browser that allows users to visualize and compare multiple genome-wide histone modification maps and related expression profiles across different developmental stages and tissues.

Conclusion

iHMS is of great helpfulness to understand how global histone modification state transitions impact cellular phenotypes across different developmental stages and tissues in the human genome. This extensive catalog of histone modification states thus presents an important resource for epigenetic and developmental studies.

Practical Guidelines for High-Resolution Epigenomic Profiling of Nucleosomal Histones in Postmortem Human Brain Tissue

BACKGROUND

The nervous system may include more than 100 residue-specific posttranslational modifications of histones forming the nucleosome core that are often regulated in cell-type-specific manner. On a genome-wide scale, some of the histone posttranslational modification landscapes show significant overlap with the genetic risk architecture for several psychiatric disorders, fueling PsychENCODE and other large-scale efforts to comprehensively map neuronal and nonneuronal epigenomes in hundreds of specimens. However, practical guidelines for efficient generation of histone chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) datasets from postmortem brains are needed.

METHODS

Protocols and quality controls are given for the following: 1) extraction, purification, and NeuN neuronal marker immunotagging of nuclei from adult human cerebral cortex; 2) fluorescence-activated nuclei sorting; 3) preparation of chromatin by micrococcal nuclease digest; 4) ChIP for open chromatin-associated histone methylation and acetylation; and 5) generation and sequencing of ChIP-seq libraries.

RESULTS

We present a ChIP-seq pipeline for epigenome mapping in the neuronal and nonneuronal nuclei from the postmortem brain. This includes a stepwise system of quality controls and user-friendly data presentation platforms.

CONCLUSIONS

Our practical guidelines will be useful for projects aimed at histone posttranslational modification mapping in chromatin extracted from hundreds of postmortem brain samples in cell-type-specific manner.

Few regulatory metabolites coordinate expression of central metabolic genes in Escherichia coli

Transcription networks consist of hundreds of transcription factors with thousands of often overlapping target genes. While we can reliably measure gene expression changes, we still understand relatively little why expression changes the way it does. How does a coordinated response emerge in such complex networks and how many input signals are necessary to achieve it? Here, we unravel the regulatory program of gene expression in Escherichia coli central carbon metabolism with more than 30 known transcription factors. Using a library of fluorescent transcriptional reporters, we comprehensively quantify the activity of central metabolic promoters in 26 environmental conditions. The expression patterns were dominated by growth rate‐dependent global regulation for most central metabolic promoters in concert with highly condition‐specific activation for only few promoters. Using an approximate mathematical description of promoter activity, we dissect the contribution of global and specific transcriptional regulation. About 70% of the total variance in promoter activity across conditions was explained by global transcriptional regulation. Correlating the remaining specific transcriptional regulation of each promoter with the cell's metabolome response across the same conditions identified potential regulatory metabolites. Remarkably, cyclic AMP, fructose‐1,6‐bisphosphate, and fructose‐1‐phosphate alone explained most of the specific transcriptional regulation through their interaction with the two major transcription factors Crp and Cra. Thus, a surprisingly simple regulatory program that relies on global transcriptional regulation and input from few intracellular metabolites appears to be sufficient to coordinate E. coli central metabolism and explain about 90% of the experimentally observed transcription changes in 100 genes.

COPAR: A ChIP-Seq Optimal Peak Analyzer

Sequencing data quality and peak alignment efficiency of ChIP-sequencing profiles are directly related to the reliability and reproducibility of NGS experiments. Till now, there is no tool specifically designed for optimal peak alignment estimation and quality-related genomic feature extraction for ChIP-sequencing profiles. We developed open-sourced COPAR, a user-friendly package, to statistically investigate, quantify, and visualize the optimal peak alignment and inherent genomic features using ChIP-seq data from NGS experiments. It provides a versatile perspective for biologists to perform quality-check for high-throughput experiments and optimize their experiment design. The package COPAR can process mapped ChIP-seq read file in BED format and output statistically sound results for multiple high-throughput experiments. Together with three public ChIP-seq data sets verified with the developed package, we have deposited COPAR on GitHub under a GNU GPL license.

Genome-Wide Cell Type-Specific Mapping of In Vivo Chromatin Protein Binding Using an FLP-Inducible DamID System in Drosophila

A thorough study of the genome-wide binding patterns of chromatin proteins is essential for understanding the regulatory mechanisms of genomic processes in eukaryotic nuclei, including DNA replication, transcription, and repair. The DNA adenine methyltransferase identification (DamID) method is a powerful tool to identify genomic binding sites of chromatin proteins. This method does not require fixation of cells and the use of specific antibodies, and has been used to generate genome-wide binding maps of more than a hundred different proteins in Drosophila tissue culture cells. Recent versions of inducible DamID allow performing cell type-specific profiling of chromatin proteins even in small samples of Drosophila tissues that contain heterogeneous cell types. Importantly, with these methods sorting of cells of interest or their nuclei is not necessary as genomic DNA isolated from the whole tissue can be used as an input. Here, I describe in detail an FLP-inducible DamID method, namely generation of suitable transgenic flies, activation of the Dam transgenes by the FLP recombinase, isolation of DNA from small amounts of dissected tissues, and subsequent identification of the DNA binding sites of the chromatin proteins.

Dynamic epigenetic mode analysis using spatial temporal clustering

Background

Differentiation of human embryonic stem cells requires precise control of gene expression that depends on specific spatial and temporal epigenetic regulation. Recently available temporal epigenomic data derived from cellular differentiation processes provides an unprecedented opportunity for characterizing fundamental properties of epigenomic dynamics and revealing regulatory roles of epigenetic modifications.

Results

This paper presents a spatial temporal clustering approach, named STCluster, which exploits the temporal variation information of epigenomes to characterize dynamic epigenetic mode during cellular differentiation. This approach identifies significant spatial temporal patterns of epigenetic modifications along human embryonic stem cell differentiation and cluster regulatory sequences by their spatial temporal epigenetic patterns.

Conclusions

The results show that this approach is effective in capturing epigenetic modification patterns associated with specific cell types. In addition, STCluster allows straightforward identification of coherent epigenetic modes in multiple cell types, indicating the ability in the establishment of the most conserved epigenetic signatures during cellular differentiation process.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1331-z) contains supplementary material, which is available to authorized users.

DGW: an exploratory data analysis tool for clustering and visualisation of epigenomic marks

Background

Functional genomic and epigenomic research relies fundamentally on sequencing based methods like ChIP-seq for the detection of DNA-protein interactions. These techniques return large, high dimensional data sets with visually complex structures, such as multi-modal peaks extended over large genomic regions. Current tools for visualisation and data exploration represent and leverage these complex features only to a limited extent.

Results

We present DGW, an open source software package for simultaneous alignment and clustering of multiple epigenomic marks. DGW uses Dynamic Time Warping to adaptively rescale and align genomic distances which allows to group regions of interest with similar shapes, thereby capturing the structure of epigenomic marks. We demonstrate the effectiveness of the approach in a simulation study and on a real epigenomic data set from the ENCODE project.

Conclusions

Our results show that DGW automatically recognises and aligns important genomic features such as transcription start sites and splicing sites from histone marks. DGW is available as an open source Python package.

An Alternative Approach to ChIP-Seq Normalization Enables Detection of Genome-Wide Changes in Histone H3 Lysine 27 Trimethylation upon EZH2 Inhibition

Chromatin immunoprecipitation and DNA sequencing (ChIP-seq) has been instrumental in inferring the roles of histone post-translational modifications in the regulation of transcription, chromatin compaction and other cellular processes that require modulation of chromatin structure. However, analysis of ChIP-seq data is challenging when the manipulation of a chromatin-modifying enzyme significantly affects global levels of histone post-translational modifications. For example, small molecule inhibition of the methyltransferase EZH2 reduces global levels of histone H3 lysine 27 trimethylation (H3K27me3). However, standard ChIP-seq normalization and analysis methods fail to detect a decrease upon EZH2 inhibitor treatment. We overcome this challenge by employing an alternative normalization approach that is based on the addition of Drosophila melanogaster chromatin and a D. melanogaster-specific antibody into standard ChIP reactions. Specifically, the use of an antibody that exclusively recognizes the D. melanogaster histone variant H2Av enables precipitation of D. melanogaster chromatin as a minor fraction of the total ChIP DNA. The D. melanogaster ChIP-seq tags are used to normalize the human ChIP-seq data from DMSO and EZH2 inhibitor-treated samples. Employing this strategy, a substantial reduction in H3K27me3 signal is now observed in ChIP-seq data from EZH2 inhibitor treated samples.

Genome-wide epigenomic profiling for biomarker discovery

A myriad of diseases is caused or characterized by alteration of epigenetic patterns, including changes in DNA methylation, post-translational histone modifications, or chromatin structure. These changes of the epigenome represent a highly interesting layer of information for disease stratification and for personalized medicine. Traditionally, epigenomic profiling required large amounts of cells, which are rarely available with clinical samples. Also, the cellular heterogeneity complicates analysis when profiling clinical samples for unbiased genome-wide biomarker discovery. Recent years saw great progress in miniaturization of genome-wide epigenomic profiling, enabling large-scale epigenetic biomarker screens for disease diagnosis, prognosis, and stratification on patient-derived samples. All main genome-wide profiling technologies have now been scaled down and/or are compatible with single-cell readout, including: (i) Bisulfite sequencing to determine DNA methylation at base-pair resolution, (ii) ChIP-Seq to identify protein binding sites on the genome, (iii) DNaseI-Seq/ATAC-Seq to profile open chromatin, and (iv) 4C-Seq and HiC-Seq to determine the spatial organization of chromosomes. In this review we provide an overview of current genome-wide epigenomic profiling technologies and main technological advances that allowed miniaturization of these assays down to single-cell level. For each of these technologies we evaluate their application for future biomarker discovery. We will focus on (i) compatibility of these technologies with methods used for clinical sample preservation, including methods used by biobanks that store large numbers of patient samples, and (ii) automation of these technologies for robust sample preparation and increased throughput.

The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data

BACKGROUND

ChIP-seq and related high-throughput chromatin profilig assays generate ever increasing volumes of highly valuable biological data. To make sense out of it, biologists need versatile, efficient and user-friendly tools for access, visualization and itegrative analysis of such data.

RESULTS

Here we present the ChIP-Seq command line tools and web server, implementing basic algorithms for ChIP-seq data analysis starting with a read alignment file. The tools are optimized for memory-efficiency and speed thus allowing for processing of large data volumes on inexpensive hardware. The web interface provides access to a large database of public data. The ChIP-Seq tools have a modular and interoperable design in that the output from one application can serve as input to another one. Complex and innovative tasks can thus be achieved by running several tools in a cascade.

CONCLUSIONS

The various ChIP-Seq command line tools and web services either complement or compare favorably to related bioinformatics resources in terms of computational efficiency, ease of access to public data and interoperability with other web-based tools. The ChIP-Seq server is accessible at http://ccg.vital-it.ch/chipseq/ .

Collaborative Completion of Transcription Factor Binding Profiles via Local Sensitive Unified Embedding

Although the newly available ChIP-seq data provides immense opportunities for comparative study of regulatory activities across different biological conditions, due to cost, time or sample material availability, it is not always possible for researchers to obtain binding profiles for every protein in every sample of interest, which considerably limits the power of integrative studies. Recently, by leveraging related information from measured data, Ernst et al. proposed ChromImpute for predicting additional ChIP-seq and other types of datasets, it is demonstrated that the imputed signal tracks accurately approximate the experimentally measured signals, and thereby could potentially enhance the power of integrative analysis. Despite the success of ChromImpute, in this paper, we reexamine its learning process, and show that its performance may degrade substantially and sometimes may even fail to output a prediction when the available data is scarce. This limitation could hurt its applicability to important predictive tasks, such as the imputation of TF binding data. To alleviate this problem, we propose a novel method called Local Sensitive Unified Embedding (LSUE) for imputing new ChIP-seq datasets. In LSUE, the ChIP-seq data compendium are fused together by mapping proteins, samples, and genomic positions simultaneously into the Euclidean space, thereby making their underling associations directly evaluable using simple calculations. In contrast to ChromImpute which mainly makes use of the local correlations between available datasets, LSUE can better estimate the overall data structure by formulating the representation learning of all involved entities as a single unified optimization problem. Meanwhile, a novel form of local sensitive low rank regularization is also proposed to further improve the performance of LSUE. Experimental evaluations on the ENCODE TF ChIP-seq data illustrate the performance of the proposed model. The code of LSUE is available at https://github.com/ekffar/LSUE.

Differential peak calling of ChIP-seq signals with replicates with THOR

The study of changes in protein-DNA interactions measured by ChIP-seq on dynamic systems, such as cell differentiation, response to treatments or the comparison of healthy and diseased individuals, is still an open challenge. There are few computational methods comparing changes in ChIP-seq signals with replicates. Moreover, none of these previous approaches addresses ChIP-seq specific experimental artefacts arising from studies with biological replicates. We propose THOR, a Hidden Markov Model based approach, to detect differential peaks between pairs of biological conditions with replicates. THOR provides all pre- and post-processing steps required in ChIP-seq analyses. Moreover, we propose a novel normalization approach based on housekeeping genes to deal with cases where replicates have distinct signal-to-noise ratios. To evaluate differential peak calling methods, we delineate a methodology using both biological and simulated data. This includes an evaluation procedure that associates differential peaks with changes in gene expression as well as histone modifications close to these peaks. We evaluate THOR and seven competing methods on data sets with distinct characteristics from in vitro studies with technical replicates to clinical studies of cancer patients. Our evaluation analysis comprises of 13 comparisons between pairs of biological conditions. We show that THOR performs best in all scenarios.

Q-nexus: a comprehensive and efficient analysis pipeline designed for ChIP-nexus

Background

ChIP-nexus, an extension of the ChIP-exo protocol, can be used to map the borders of protein-bound DNA sequences at nucleotide resolution, requires less input DNA and enables selective PCR duplicate removal using random barcodes. However, the use of random barcodes requires additional preprocessing of the mapping data, which complicates the computational analysis. To date, only a very limited number of software packages are available for the analysis of ChIP-exo data, which have not yet been systematically tested and compared on ChIP-nexus data.

Results

Here, we present a comprehensive software package for ChIP-nexus data that exploits the random barcodes for selective removal of PCR duplicates and for quality control. Furthermore, we developed bespoke methods to estimate the width of the protected region resulting from protein-DNA binding and to infer binding positions from ChIP-nexus data. Finally, we applied our peak calling method as well as the two other methods MACE and MACS2 to the available ChIP-nexus data.

Conclusions

The Q-nexus software is efficient and easy to use. Novel statistics about duplication rates in consideration of random barcodes are calculated. Our method for the estimation of the width of the protected region yields unbiased signatures that are highly reproducible for biological replicates and at the same time very specific for the respective factors analyzed. As judged by the irreproducible discovery rate (IDR), our peak calling algorithm shows a substantially better reproducibility. An implementation of Q-nexus is available at http://charite.github.io/Q/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3164-6) contains supplementary material, which is available to authorized users.

Analysis of Heterochromatin in Schizosaccharomyces pombe

This introduction briefly describes the biology of heterochromatin in the fission yeast Schizosaccharomyces pombe We highlight some of the salient features of fission yeast that render it an excellent unicellular eukaryote for studying heterochromatin. We then discuss key aspects of heterochromatin that are of interest to those in the field, and last we introduce experimental approaches often used to investigate heterochromatin.

Understanding the genetic liability to schizophrenia through the neuroepigenome

The Psychiatric Genomics Consortium-Schizophrenia Workgroup (PGC-SCZ) recently identified 108 loci associated with increased risk for schizophrenia (SCZ). The vast majority of these variants reside within non-coding sequences of the genome and are predicted to exert their effects by affecting the mechanism of action of cis regulatory elements (CREs), such as promoters and enhancers. Although a number of large-scale collaborative efforts (e.g. ENCODE) have achieved a comprehensive mapping of CREs in human cell lines or tissue homogenates, it is becoming increasingly evident that many risk-associated variants are enriched for expression Quantitative Trait Loci (eQTLs) and CREs in specific tissues or cells. As such, data derived from previous research endeavors may not capture fully cell-type and/or region specific changes associated with brain diseases. Coupling recent technological advances in genomics with cell-type specific methodologies, we are presented with an unprecedented opportunity to better understand the genetics of normal brain development and function and, in turn, the molecular basis of neuropsychiatric disorders. In this review, we will outline ongoing efforts towards this goal and will discuss approaches with the potential to shed light on the mechanism(s) of action of cell-type specific cis regulatory elements and their putative roles in disease, with particular emphasis on understanding the manner in which the epigenome and CREs influence the etiology of SCZ.

Cistrome Data Browser: a data portal for ChIP-Seq and chromatin accessibility data in human and mouse

Chromatin immunoprecipitation, DNase I hypersensitivity and transposase-accessibility assays combined with high-throughput sequencing enable the genome-wide study of chromatin dynamics, transcription factor binding and gene regulation. Although rapidly accumulating publicly available ChIP-seq, DNase-seq and ATAC-seq data are a valuable resource for the systematic investigation of gene regulation processes, a lack of standardized curation, quality control and analysis procedures have hindered extensive reuse of these data. To overcome this challenge, we built the Cistrome database, a collection of ChIP-seq and chromatin accessibility data (DNase-seq and ATAC-seq) published before January 1, 2016, including 13 366 human and 9953 mouse samples. All the data have been carefully curated and processed with a streamlined analysis pipeline and evaluated with comprehensive quality control metrics. We have also created a user-friendly web server for data query, exploration and visualization. The resulting Cistrome DB (Cistrome Data Browser), available online at http://cistrome.org/db, is expected to become a valuable resource for transcriptional and epigenetic regulation studies.

A comparative study of ChIP-seq sequencing library preparation methods

Background

ChIP-seq is the primary technique used to investigate genome-wide protein-DNA interactions. As part of this procedure, immunoprecipitated DNA must undergo “library preparation” to enable subsequent high-throughput sequencing. To facilitate the analysis of biopsy samples and rare cell populations, there has been a recent proliferation of methods allowing sequencing library preparation from low-input DNA amounts. However, little information exists on the relative merits, performance, comparability and biases inherent to these procedures. Notably, recently developed single-cell ChIP procedures employing microfluidics must also employ library preparation reagents to allow downstream sequencing.

Results

In this study, seven methods designed for low-input DNA/ChIP-seq sample preparation (Accel-NGS® 2S, Bowman-method, HTML-PCR, SeqPlex™, DNA SMART™, TELP and ThruPLEX®) were performed on five replicates of 1 ng and 0.1 ng input H3K4me3 ChIP material, and compared to a “gold standard” reference PCR-free dataset. The performance of each method was examined for the prevalence of unmappable reads, amplification-derived duplicate reads, reproducibility, and for the sensitivity and specificity of peak calling.

Conclusions

We identified consistent high performance in a subset of the tested reagents, which should aid researchers in choosing the most appropriate reagents for their studies. Furthermore, we expect this work to drive future advances by identifying and encouraging use of the most promising methods and reagents. The results may also aid judgements on how comparable are existing datasets that have been prepared with different sample library preparation reagents.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3135-y) contains supplementary material, which is available to authorized users.

Fluorogenic sensor platform for the histone code using receptors from dynamic combinatorial libraries

A sensor array has been developed that can differentiate multiple post-translational modifications in the same peptide and their relative positions in the sequence, including multiple methylations, providing a promising new tool for deciphering the histone code.

Post-translational modifications (PTMs) on histone tails act in diverse combinations in the ‘histone code’ to control gene expression, with dysregulation observed in a variety of diseases. However, detection and sensing methods are limited, expensive, and/or low-throughput, including MS and antibody based detection. We found that by combining four synthetic receptors developed by dynamic combinatorial chemistry (DCC) in an indicator displacement system, we are able to create a pattern-based sensor platform that can discriminate single PTMs such as methylation and acetylation on a representative histone peptide with 100% accuracy as well as peptides bearing both dimethyl and trimethyl lysine in the presence of arginine methylation, which has not previously been demonstrated, and can even correctly distinguish the position of lysine methylation individually or in the presence of other PTMs. To extend this approach, a full panel of thirteen analytes containing different combinations of PTMs were classified with 96 ± 1% overall accuracy in a 50% left-out analysis, demonstrating the robustness and versatility of the sensor array. Finally, the sensor platform was also used to demonstrate proof of concept for enzymatic assays by analysing the mock reaction of a threonine kinase, successfully identifying analytes representative of substrate conversion both with and without neighboring PTMs. This work provides a rapid platform for the analysis of peptides bearing complex modifications and highlights the utility of receptors discovered though DCC that display variations in binding affinity and selectivity.

ChIP-Seq: Library Preparation and Sequencing

Chromatin immunoprecipitation with massively parallel DNA sequencing (ChIP-Seq) has been used extensively to determine the genome-wide location of DNA-binding factors, such as transcription factors, posttranscriptionally modified histones, and members of the transcription complex, to assess regulatory input, epigenetic modifications, and transcriptional activity, respectively. Here we describe methods to isolate chromatin from tissues, immunoprecipitate DNA bound to a protein of interest, and perform next-generation sequencing to identify a genome-wide DNA-binding pattern.

Preparation of Low-Input and Ligation-Free ChIP-seq Libraries Using Template-Switching Technology

Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) has become the gold standard for mapping of transcription factors and histone modifications throughout the genome. However, for ChIP experiments involving few cells or targeting low-abundance transcription factors, the small amount of DNA recovered makes ligation of adapters very challenging. In this unit, we describe a ChIP-seq workflow that can be applied to small cell numbers, including a robust single-tube and ligation-free method for preparation of sequencing libraries from sub-nanogram amounts of ChIP DNA. An example ChIP protocol is first presented, resulting in selective enrichment of DNA-binding proteins and cross-linked DNA fragments immobilized on beads via an antibody bridge. This is followed by a protocol for fast and easy cross-linking reversal and DNA recovery. Finally, we describe a fast, ligation-free library preparation protocol, featuring DNA SMART technology, resulting in samples ready for Illumina sequencing. © 2016 by John Wiley & Sons, Inc.

iDamIDseq and iDEAR: an improved method and computational pipeline to profile chromatin-binding proteins

DNA adenine methyltransferase identification (DamID) has emerged as an alternative method to profile protein-DNA interactions; however, critical issues limit its widespread applicability. Here, we present iDamIDseq, a protocol that improves specificity and sensitivity by inverting the steps DpnI-DpnII and adding steps that involve a phosphatase and exonuclease. To determine genome-wide protein-DNA interactions efficiently, we present the analysis tool iDEAR (iDamIDseq Enrichment Analysis with R). The combination of DamID and iDEAR permits the establishment of consistent profiles for transcription factors, even in transient assays, as we exemplify using the small teleost medaka (Oryzias latipes). We report that the bacterial Dam-coding sequence induces aberrant splicing when it is used with different promoters to drive tissue-specific expression. Here, we present an optimization of the sequence to avoid this problem. This and our other improvements will allow researchers to use DamID effectively in any organism, in a general or targeted manner.

Summary: Critical improvements to the DamID protocol improve specificity and sensitivity in determining genome-wide protein-DNA interactions in transient or stable transgenic animal lines.

Histone acetylation dependent energy landscapes in tri-nucleosome revealed by residue-resolved molecular simulations

Histone tail acetylation is a key epigenetic marker that tends to open chromatin folding and activate transcription. Despite intensive studies, precise roles of individual lysine acetylation in chromatin folding have only been poorly understood. Here, we revealed structural dynamics of tri-nucleosomes with several histone tail acetylation states and analyzed histone tail interactions with DNA by performing molecular simulations at an unprecedentedly high resolution. We found versatile acetylation-dependent landscapes of tri-nucleosome. The H4 and H2A tail acetylation reduced the contact between the first and third nucleosomes mediated by the histone tails. The H3 tail acetylation reduced its interaction with neighboring linker DNAs resulting in increase of the distance between consecutive nucleosomes. Notably, two copies of the same histone in a single nucleosome have markedly asymmetric interactions with DNAs, suggesting specific pattern of nucleosome docking albeit high inherent flexibility. Estimated transcription factor accessibility was significantly high for the H4 tail acetylated structures.

Pathogen Infection and MORC Proteins Affect Chromatin Accessibility of Transposable Elements and Expression of Their Proximal Genes in Arabidopsis

To assess the role of MORC1 in epigenetics in relation to plant immunity, genome-wide chromatin accessibility was compared between mock- or Pseudomonas syringae pv. tomato-inoculated wild type (WT) Arabidopsis, the morc1/2 double mutant, or both. Most changes in chromatin accessibility, scored by DNase I hypersensitive sites (DHSs), were located in the promoters of genes and transposable elements (TEs). Comparisons between morc1/2 and WT receiving the same treatment revealed differential DHSs (dDHSs) predominantly associated with heterochromatic TEs. By contrast, comparisons between mock- and P. syringae pv. tomato-inoculated plants from the same genotype showed dDHSs associated with biotic and abiotic stress-related genes; a smaller but significant population was in TEs. Moreover, many defense genes, including PR-1, PR-2, and PR-5, were proximal to P. syringae pv. tomato-induced, TE-associated dDHSs. A random subset of these defense genes showed moderately delayed or reduced expression or both in P. syringae pv. tomato-infected morc1/2 as compared with WT. MORC1 was physically bound to chromatin in a P. syringae pv. tomato infection-responsive manner at sites dispersed throughout the genome. Notably, silencing of TE-associated dDHSs proximal to these infection-induced, MORC1-interacting sites led to significant suppression of P. syringae pv. tomato-induced transcription of adjacent defense genes, including PR-1. These results provide evidence that MORC1 is associated with TEs and suggest that a subset of these TEs may help regulate their proximal defense genes.

The role of enhancers in cancer

Enhancer elements function as the logic gates of the genetic regulatory circuitry. One of their most important functions is the integration of extracellular signals with intracellular cell fate information to generate cell type-specific transcriptional responses. Mutations occurring in cancer often misregulate enhancers that normally control the signal-dependent expression of growth-related genes. This misregulation can result from trans-acting mechanisms, such as activation of the transcription factors or epigenetic regulators that control enhancer activity, or can be caused in cis by direct mutations that alter the activity of the enhancer or its target gene specificity. These processes can generate tumour type-specific super-enhancers and establish a 'locked' gene regulatory state that drives the uncontrolled proliferation of cancer cells. Here, we review the role of enhancers in cancer, and their potential as therapeutic targets.

Genome-wide analysis reveals positional-nucleosome-oriented binding pattern of pioneer factor FOXA1

The compaction of nucleosomal structures creates a barrier for DNA-binding transcription factors (TFs) to access their cognate cis-regulatory elements. Pioneer factors (PFs) such as FOXA1 are able to directly access these cis-targets within compact chromatin. However, how these PFs interplay with nucleosomes remains to be elucidated, and is critical for us to understand the underlying mechanism of gene regulation. Here, we have conducted a computational analysis on a strand-specific paired-end ChIP-exo (termed as ChIP-ePENS) data of FOXA1 in LNCaP cells by our novel algorithm ePEST. We find that FOXA1 chromatin binding occurs via four distinct border modes (or footprint boundary patterns), with a preferential footprint boundary patterns relative to FOXA1 motif orientation. In addition, from this analysis three fundamental nucleotide positions (oG, oS and oH) emerged as major determinants for blocking exo-digestion and forming these four distinct border modes. By integrating histone MNase-seq data, we found an astonishingly consistent, ‘well-positioned’ configuration occurs between FOXA1 motifs and dyads of nucleosomes genome-wide. We further performed ChIP-seq of eight chromatin remodelers and found an increased occupancy of these remodelers on FOXA1 motifs for all four border modes (or footprint boundary patterns), indicating the full occupancy of FOXA1 complex on the three blocking sites (oG, oS and oH) likely produces an active regulatory status with well-positioned phasing for protein binding events. Together, our results suggest a positional-nucleosome-oriented accessing model for PFs seeking target motifs, in which FOXA1 can examine each underlying DNA nucleotide and is able to sense all potential motifs regardless of whether they face inward or outward from histone octamers along the DNA helix axis.

From Genetics to Epigenetics: New Perspectives in Tourette Syndrome Research

Gilles de la Tourette Syndrome (TS) is a neurodevelopmental disorder marked by the appearance of multiple involuntary motor and vocal tics. TS presents high comorbidity rates with other disorders such as attention deficit hyperactivity disorder (ADHD) and obsessive compulsive disorder (OCD). TS is highly heritable and has a complex polygenic background. However, environmental factors also play a role in the manifestation of symptoms. Different epigenetic mechanisms may represent the link between these two causalities. Epigenetic regulation has been shown to have an impact in the development of many neuropsychiatric disorders, however very little is known about its effects on Tourette Syndrome. This review provides a summary of the recent findings in genetic background of TS, followed by an overview on different epigenetic mechanisms, such as DNA methylation, histone modifications, and non-coding RNAs in the regulation of gene expression. Epigenetic studies in other neurological and psychiatric disorders are discussed along with the TS-related epigenetic findings available in the literature to date. Moreover, we are proposing that some general epigenetic mechanisms seen in other neuropsychiatric disorders may also play a role in the pathogenesis of TS.

Proteomics to study DNA-bound and chromatin-associated gene regulatory complexes

High-resolution mass spectrometry (MS)-based proteomics is a powerful method for the identification of soluble protein complexes and large-scale affinity purification screens can decode entire protein interaction networks. In contrast, protein complexes residing on chromatin have been much more challenging, because they are difficult to purify and often of very low abundance. However, this is changing due to recent methodological and technological advances in proteomics. Proteins interacting with chromatin marks can directly be identified by pulldowns with synthesized histone tails containing posttranslational modifications (PTMs). Similarly, pulldowns with DNA baits harbouring single nucleotide polymorphisms or DNA modifications reveal the impact of those DNA alterations on the recruitment of transcription factors. Accurate quantitation – either isotope-based or label free – unambiguously pinpoints proteins that are significantly enriched over control pulldowns. In addition, protocols that combine classical chromatin immunoprecipitation (ChIP) methods with mass spectrometry (ChIP-MS) target gene regulatory complexes in their in-vivo context. Similar to classical ChIP, cells are crosslinked with formaldehyde and chromatin sheared by sonication or nuclease digested. ChIP-MS baits can be proteins in tagged or endogenous form, histone PTMs, or lncRNAs. Locus-specific ChIP-MS methods would allow direct purification of a single genomic locus and the proteins associated with it. There, loci can be targeted either by artificial DNA-binding sites and corresponding binding proteins or via proteins with sequence specificity such as TAL or nuclease deficient Cas9 in combination with a specific guide RNA. We predict that advances in MS technology will soon make such approaches generally applicable tools in epigenetics.

Artificial zinc finger DNA binding domains: versatile tools for genome engineering and modulation of gene expression

Genome editing and alteration of gene expression by synthetic DNA binding activities gained a lot of momentum over the last decade. This is due to the development of new DNA binding molecules with enhanced binding specificity. The most commonly used DNA binding modules are zinc fingers (ZFs), TALE-domains, and the RNA component of the CRISPR/Cas9 system. These binding modules are fused or linked to either nucleases that cut the DNA and induce DNA repair processes, or to protein domains that activate or repress transcription of genes close to the targeted site in the genome. This review focuses on the structure, design, and applications of ZF DNA binding domains (ZFDBDs). ZFDBDs are relatively small and have been shown to penetrate the cell membrane without additional tags suggesting that they could be delivered to cells without a DNA or RNA intermediate. Advanced algorithms that are based on extensive knowledge of the mode of ZF/DNA interactions are used to design the amino acid composition of ZFDBDs so that they bind to unique sites in the genome. Off-target binding has been a concern for all synthetic DNA binding molecules. Thus, increasing the specificity and affinity of ZFDBDs will have a significant impact on their use in analytical or therapeutic settings.

Next generation sequencing technology and genomewide data analysis: Perspectives for retinal research

The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well.

Cofactor squelching: Artifact or fact?

Cofactor squelching is the term used to describe competition between transcription factors (TFs) for a limited amount of cofactors in a cell with the functional consequence that TFs in a given cell interfere with the activity of each other. Since cofactor squelching was proposed based primarily on reporter assays some 30 years ago, it has remained controversial, and the idea that it could be a physiologically relevant mechanism for transcriptional repression has not received much support. However, recent genome-wide studies have demonstrated that signal-dependent TFs are very often absent from the enhancers that are acutely repressed by those signals, which is consistent with an indirect mechanism of repression such as squelching. Here we review these recent studies in the light of the classical studies of cofactor squelching, and we discuss how TF cooperativity in so-called hotspots and super-enhancers may sensitize these to cofactor squelching.

Chromatin Immunoprecipitation Assay: Examining the Interaction of NFkB with the VEGF Promoter

The chromatin immunoprecipitation (ChIP) assay is a versatile technique used to evaluate the association of proteins with specific DNA regions both in vivo and in vitro. This assay can be used to identify proteins associated with a specific region of the genome, or the opposite, to identify the many regions of the genome associated with a particular protein. The ChIP assay can also be used to analyze binding of transcription factors, transcription cofactors, DNA replication factors, and DNA repair proteins. Here we describe a useful ChIP-qPCR protocol to examine the interaction of NFkB with the VEGF promoter in adult rat primary cardiomyocytes that have been mechanically stretched after attaching to the extracellular matrix protein laminin.

ElemeNT: a computational tool for detecting core promoter elements

Core promoter elements play a pivotal role in the transcriptional output, yet they are often detected manually within sequences of interest. Here, we present 2 contributions to the detection and curation of core promoter elements within given sequences. First, the Elements Navigation Tool (ElemeNT) is a user-friendly web-based, interactive tool for prediction and display of putative core promoter elements and their biologically-relevant combinations. Second, the CORE database summarizes ElemeNT-predicted core promoter elements near CAGE and RNA-seq-defined Drosophila melanogaster transcription start sites (TSSs). ElemeNT's predictions are based on biologically-functional core promoter elements, and can be used to infer core promoter compositions. ElemeNT does not assume prior knowledge of the actual TSS position, and can therefore assist in annotation of any given sequence. These resources, freely accessible at http://lifefaculty.biu.ac.il/gershon-tamar/index.php/resources, facilitate the identification of core promoter elements as active contributors to gene expression.

Insights into the Ecology and Evolution of Polyploid Plants through Network Analysis

Polyploidy is a widespread phenomenon throughout eukaryotes, with important ecological and evolutionary consequences. Although genes operate as components of complex pathways and networks, polyploid changes in genes and gene expression have typically been evaluated as either individual genes or as a part of broad-scale analyses. Network analysis has been fruitful in associating genomic and other 'omic'-based changes with phenotype for many systems. In polyploid species, network analysis has the potential not only to facilitate a better understanding of the complex 'omic' underpinnings of phenotypic and ecological traits common to polyploidy, but also to provide novel insight into the interaction among duplicated genes and genomes. This adds perspective to the global patterns of expression (and other 'omic') change that accompany polyploidy and to the patterns of recruitment and/or loss of genes following polyploidization. While network analysis in polyploid species faces challenges common to other analyses of duplicated genomes, present technologies combined with thoughtful experimental design provide a powerful system to explore polyploid evolution. Here, we demonstrate the utility and potential of network analysis to questions pertaining to polyploidy with an example involving evolution of the transgressively superior cotton fibres found in polyploid Gossypium hirsutum. By combining network analysis with prior knowledge, we provide further insights into the role of profilins in fibre domestication and exemplify the potential for network analysis in polyploid species.

Detecting and correcting the binding-affinity bias in ChIP-seq data using inter-species information

BACKGROUND

Transcriptional gene regulation is a fundamental process in nature, and the experimental and computational investigation of DNA binding motifs and their binding sites is a prerequisite for elucidating this process. ChIP-seq has become the major technology to uncover genomic regions containing those binding sites, but motifs predicted by traditional computational approaches using these data are distorted by a ubiquitous binding-affinity bias. Here, we present an approach for detecting and correcting this bias using inter-species information.

RESULTS

We find that the binding-affinity bias caused by the ChIP-seq experiment in the reference species is stronger than the indirect binding-affinity bias in orthologous regions from phylogenetically related species. We use this difference to develop a phylogenetic footprinting model that is capable of detecting and correcting the binding-affinity bias. We find that this model improves motif prediction and that the corrected motifs are typically softer than those predicted by traditional approaches.

CONCLUSIONS

These findings indicate that motifs published in databases and in the literature are artificially sharpened compared to the native motifs. These findings also indicate that our current understanding of transcriptional gene regulation might be blurred, but that it is possible to advance this understanding by taking into account inter-species information available today and even more in the future.

Evolution of Gene Regulation in Humans

As a species, we possess unique biological features that distinguish us from other primates. Here, we review recent efforts to identify changes in gene regulation that drove the evolution of novel human phenotypes. We discuss genotype-directed comparisons of human and nonhuman primate genomes to identify human-specific genetic changes that may encode new regulatory functions. We also review phenotype-directed approaches, which use comparisons of gene expression or regulatory function in homologous human and nonhuman primate cells and tissues to identify changes in expression levels or regulatory activity that may be due to genetic changes in humans. Together, these studies are beginning to reveal the landscape of regulatory innovation in human evolution and point to specific regulatory changes for further study. Finally, we highlight two novel strategies to model human-specific regulatory functions in vivo: primate induced pluripotent stem cells and the generation of humanized mice by genome editing.

Network-Based Interpretation of Diverse High-Throughput Datasets through the Omics Integrator Software Package

High-throughput, ‘omic’ methods provide sensitive measures of biological responses to perturbations. However, inherent biases in high-throughput assays make it difficult to interpret experiments in which more than one type of data is collected. In this work, we introduce Omics Integrator, a software package that takes a variety of ‘omic’ data as input and identifies putative underlying molecular pathways. The approach applies advanced network optimization algorithms to a network of thousands of molecular interactions to find high-confidence, interpretable subnetworks that best explain the data. These subnetworks connect changes observed in gene expression, protein abundance or other global assays to proteins that may not have been measured in the screens due to inherent bias or noise in measurement. This approach reveals unannotated molecular pathways that would not be detectable by searching pathway databases. Omics Integrator also provides an elegant framework to incorporate not only positive data, but also negative evidence. Incorporating negative evidence allows Omics Integrator to avoid unexpressed genes and avoid being biased toward highly-studied hub proteins, except when they are strongly implicated by the data. The software is comprised of two individual tools, Garnet and Forest, that can be run together or independently to allow a user to perform advanced integration of multiple types of high-throughput data as well as create condition-specific subnetworks of protein interactions that best connect the observed changes in various datasets. It is available at http://fraenkel.mit.edu/omicsintegrator and on GitHub at https://github.com/fraenkel-lab/OmicsIntegrator.

Strategies for targeting primate neural circuits with viral vectors

Understanding how the brain works requires understanding how different types of neurons contribute to circuit function and organism behavior. Progress on this front has been accelerated by optogenetics and chemogenetics, which provide an unprecedented level of control over distinct neuronal types in small animals. In primates, however, targeting specific types of neurons with these tools remains challenging. In this review, we discuss existing and emerging strategies for directing genetic manipulations to targeted neurons in the adult primate central nervous system. We review the literature on viral vectors for gene delivery to neurons, focusing on adeno-associated viral vectors and lentiviral vectors, their tropism for different cell types, and prospects for new variants with improved efficacy and selectivity. We discuss two projection targeting approaches for probing neural circuits: anterograde projection targeting and retrograde transport of viral vectors. We conclude with an analysis of cell type-specific promoters and other nucleotide sequences that can be used in viral vectors to target neuronal types at the transcriptional level.

DNA Methylation Analysis of ChIP Products at Single Nucleotide Resolution by Pyrosequencing®

Interaction and co-occurrence of protein and DNA-based epigenetic modifications have become a topic of interest for many fundamental and biomedical questions. We describe within this chapter a protocol that combines two techniques in order to determine the methylation status of the DNA specifically associated with a protein of interest. First, DNA that directly interacts with the selected protein (such as a specific histone modification, a transcription factor, or any other DNA-associated protein) is purified by standard chromatin immunoprecipitation (ChIP). Second, the level of DNA methylation of this immunoprecipitated DNA is measured by bisulfite conversion and Pyrosequencing, a quantitative sequencing-by-synthesis method. This procedure allows determining the methylation status of genomic DNA associated to a specific protein at single nucleotide resolution.