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]

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.

Epigenetic Profiling of H3K4Me3 Reveals Herbal Medicine Jinfukang-Induced Epigenetic Alteration Is Involved in Anti-Lung Cancer Activity

Traditional Chinese medicine Jinfukang (JFK) has been clinically used for treating lung cancer. To examine whether epigenetic modifications are involved in its anticancer activity, we performed a global profiling analysis of H3K4Me3, an epigenomic marker associated with active gene expression, in JFK-treated lung cancer cells. We identified 11,670 genes with significantly altered status of H3K4Me3 modification following JFK treatment (P < 0.05). Gene Ontology analysis indicates that these genes are involved in tumor-related pathways, including pathway in cancer, basal cell carcinoma, apoptosis, induction of programmed cell death, regulation of transcription (DNA-templated), intracellular signal transduction, and regulation of peptidase activity. In particular, we found that the levels of H3K4Me3 at the promoters of SUSD2, CCND2, BCL2A1, and TMEM158 are significantly altered in A549, NCI-H1975, NCI-H1650, and NCI-H2228 cells, when treated with JFK. Collectively, these findings provide the first evidence that the anticancer activity of JFK involves modulation of histone modification at many cancer-related gene loci.

Next-generation sequencing (NGS) in the microbiological world: How to make the most of your money

The Sanger sequencing method produces relatively long DNA sequences of unmatched quality and has been considered for long time as the gold standard for sequencing DNA. Many improvements of the Sanger method that culminated with fluorescent dyes coupled with automated capillary electrophoresis enabled the sequencing of the first genomes. Nevertheless, using this technology to sequence whole genomes was costly, laborious and time consuming even for genomes that are relatively small in size. A major technological advance was the introduction of next-generation sequencing (NGS) pioneered by 454 Life Sciences in the early part of the 21th century. NGS allowed scientists to sequence thousands to millions of DNA molecules in a single machine run. Since then, new NGS technologies have emerged and existing NGS platforms have been improved, enabling the production of genome sequences at an unprecedented rate as well as broadening the spectrum of NGS applications. The current affordability of generating genomic information, especially with microbial samples, has resulted in a false sense of simplicity that belies the fact that many researchers still consider these technologies a black box. In this review, our objective is to identify and discuss four steps that we consider crucial to the success of any NGS-related project. These steps are: (1) the definition of the research objectives beyond sequencing and appropriate experimental planning, (2) library preparation, (3) sequencing and (4) data analysis. The goal of this review is to give an overview of the process, from sample to analysis, and discuss how to optimize your resources to achieve the most from your NGS-based research. Regardless of the evolution and improvement of the sequencing technologies, these four steps will remain relevant.

Molecular Mechanisms of Floral Boundary Formation in Arabidopsis

Boundary formation is a crucial developmental process in plant organogenesis. Boundaries separate cells with distinct identities and act as organizing centers to control the development of adjacent organs. In flower development, initiation of floral primordia requires the formation of the meristem-to-organ (M-O) boundaries and floral organ development depends on the establishment of organ-to-organ (O-O) boundaries. Studies in this field have revealed a suite of genes and regulatory pathways controlling floral boundary formation. Many of these genes are transcription factors that interact with phytohormone pathways. This review will focus on the functions and interactions of the genes that play important roles in the floral boundaries and discuss the molecular mechanisms that integrate these regulatory pathways to control the floral boundary formation.

MOCCS: Clarifying DNA-binding motif ambiguity using ChIP-Seq data

BACKGROUND

As a key mechanism of gene regulation, transcription factors (TFs) bind to DNA by recognizing specific short sequence patterns that are called DNA-binding motifs. A single TF can accept ambiguity within its DNA-binding motifs, which comprise both canonical (typical) and non-canonical motifs. Clarification of such DNA-binding motif ambiguity is crucial for revealing gene regulatory networks and evaluating mutations in cis-regulatory elements. Although chromatin immunoprecipitation sequencing (ChIP-seq) now provides abundant data on the genomic sequences to which a given TF binds, existing motif discovery methods are unable to directly answer whether a given TF can bind to a specific DNA-binding motif.

RESULTS

Here, we report a method for clarifying the DNA-binding motif ambiguity, MOCCS. Given ChIP-Seq data of any TF, MOCCS comprehensively analyzes and describes every k-mer to which that TF binds. Analysis of simulated datasets revealed that MOCCS is applicable to various ChIP-Seq datasets, requiring only a few minutes per dataset. Application to the ENCODE ChIP-Seq datasets proved that MOCCS directly evaluates whether a given TF binds to each DNA-binding motif, even if known position weight matrix models do not provide sufficient information on DNA-binding motif ambiguity. Furthermore, users are not required to provide numerous parameters or background genomic sequence models that are typically unavailable. MOCCS is implemented in Perl and R and is freely available via https://github.com/yuifu/moccs.

CONCLUSIONS

By complementing existing motif-discovery software, MOCCS will contribute to the basic understanding of how the genome controls diverse cellular processes via DNA-protein interactions.

Investigation of Viral and Host Chromatin by ChIP-PCR or ChIP-Seq Analysis

Complex regulation of viral transcription patterns and DNA replication levels is a feature of many DNA viruses. This is especially true for those viruses which establish latent or persistent infections (e.g., herpesviruses, papillomaviruses, polyomaviruses, or adenovirus), as long-term persistence often requires adaptation of gene expression programs and/or replication levels to the cellular milieu. A key factor in the control of such processes is the establishment of a specific chromatin state on promoters or replication origins, which in turn will determine whether or not the underlying DNA is accessible for other factors that mediate downstream processes. Chromatin immunoprecipitation (ChIP) is a powerful technique to investigate viral chromatin, in particular to study binding patterns of modified histones, transcription factors or other DNA-/chromatin-binding proteins that regulate the viral lifecycle. Here, we provide protocols that are suitable for performing ChIP-PCR and ChIP-Seq studies on chromatin of large and small viral genomes.

Characterization of chromatin accessibility with a transposome hypersensitive sites sequencing (THS-seq) assay

Chromatin accessibility captures in vivo protein-chromosome binding status, and is considered an informative proxy for protein-DNA interactions. DNase I and Tn5 transposase assays require thousands to millions of fresh cells for comprehensive chromatin mapping. Applying Tn5 tagmentation to hundreds of cells results in sparse chromatin maps. We present a transposome hypersensitive sites sequencing assay for highly sensitive characterization of chromatin accessibility. Linear amplification of accessible DNA ends with in vitro transcription, coupled with an engineered Tn5 super-mutant, demonstrates improved sensitivity on limited input materials, and accessibility of small regions near distal enhancers, compared with ATAC-seq.

Genome-Wide Epigenetic Studies in Human Disease: A Primer on -Omic Technologies

Epigenetic information encoded in covalent modifications of DNA and histone proteins regulates fundamental biological processes through the action of chromatin regulators, transcription factors, and noncoding RNA species. Epigenetic plasticity enables an organism to respond to developmental and environmental signals without genetic changes. However, aberrant epigenetic control plays a key role in pathogenesis of disease. Normal epigenetic states could be disrupted by detrimental mutations and expression alteration of chromatin regulators or by environmental factors. In this primer, we briefly review the epigenetic basis of human disease and discuss how recent discoveries in this field could be translated into clinical diagnosis, prevention, and treatment. We introduce platforms for mapping genome-wide chromatin accessibility, nucleosome occupancy, DNA-binding proteins, and DNA methylation, primarily focusing on the integration of DNA methylation and chromatin immunoprecipitation-sequencing technologies into disease association studies. We highlight practical considerations in applying high-throughput epigenetic assays and formulating analytical strategies. Finally, we summarize current challenges in sample acquisition, experimental procedures, data analysis, and interpretation and make recommendations on further refinement in these areas. Incorporating epigenomic testing into the clinical research arsenal will greatly facilitate our understanding of the epigenetic basis of disease and help identify novel therapeutic targets.

Predicting transcription factor site occupancy using DNA sequence intrinsic and cell-type specific chromatin features

Background

Understanding the mechanisms by which transcription factors (TF) are recruited to their physiological target sites is crucial for understanding gene regulation. DNA sequence intrinsic features such as predicted binding affinity are often not very effective in predicting in vivo site occupancy and in any case could not explain cell-type specific binding events. Recent reports show that chromatin accessibility, nucleosome occupancy and specific histone post-translational modifications greatly influence TF site occupancy in vivo. In this work, we use machine-learning methods to build predictive models and assess the relative importance of different sequence-intrinsic and chromatin features in the TF-to-target-site recruitment process.

Methods

Our study primarily relies on recent data published by the ENCODE consortium. Five dissimilar TFs assayed in multiple cell-types were selected as examples: CTCF, JunD, REST, GABP and USF2. We used two types of candidate target sites: (a) predicted sites obtained by scanning the whole genome with a position weight matrix, and (b) cell-type specific peak lists provided by ENCODE. Quantitative in vivo occupancy levels in different cell-types were based on ChIP-seq data for the corresponding TFs. In parallel, we computed a number of associated sequence-intrinsic and experimental features (histone modification, DNase I hypersensitivity, etc.) for each site. Machine learning algorithms were then used in a binary classification and regression framework to predict site occupancy and binding strength, for the purpose of assessing the relative importance of different contextual features.

Results

We observed striking differences in the feature importance rankings between the five factors tested. PWM-scores were amongst the most important features only for CTCF and REST but of little value for JunD and USF2. Chromatin accessibility and active histone marks are potent predictors for all factors except REST. Structural DNA parameters, repressive and gene body associated histone marks are generally of little or no predictive value.

Conclusions

We define a general and extensible computational framework for analyzing the importance of various DNA-intrinsic and chromatin-associated features in determining cell-type specific TF binding to target sites. The application of our methodology to ENCODE data has led to new insights on transcription regulatory processes and may serve as example for future studies encompassing even larger datasets.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0846-z) contains supplementary material, which is available to authorized users.

Methods to Study Long Noncoding RNA Biology in Cancer

Thousands of long noncoding RNAs (lncRNAs) have been discovered in recent years. The functions of lncRNAs range broadly from regulating chromatin structure and gene expression in the nucleus to controlling messenger RNA (mRNA) processing, mRNA posttranscriptional regulation, cellular signaling, and protein activity in the cytoplasm. Experimental and computational techniques have been developed to characterize lncRNAs in high-throughput scale, to study the lncRNA function in vitro and in vivo, to map lncRNA binding sites on the genome, and to capture lncRNA-protein interactions with the identification of lncRNA-binding partners, binding sites, and interaction determinants. In this chapter, we will discuss these technologies and their applications in decoding the functions of lncRNAs. Understanding these techniques including their advantages and disadvantages and developing them in the future will be essential to elaborate the roles of lncRNAs in cancer and other diseases.

Probing DNA interactions with proteins using a single-molecule toolbox: inside the cell, in a test tube and in a computer

DNA-interacting proteins have roles in multiple processes, many operating as molecular machines which undergo dynamic meta-stable transitions to bring about their biological function. To fully understand this molecular heterogeneity, DNA and the proteins that bind to it must ideally be interrogated at a single molecule level in their native in vivo environments, in a time-resolved manner, fast enough to sample the molecular transitions across the free-energy landscape. Progress has been made over the past decade in utilizing cutting-edge tools of the physical sciences to address challenging biological questions concerning the function and modes of action of several different proteins which bind to DNA. These physiologically relevant assays are technically challenging but can be complemented by powerful and often more tractable in vitro experiments which confer advantages of the chemical environment with enhanced detection signal-to-noise of molecular signatures and transition events. In the present paper, we discuss a range of techniques we have developed to monitor DNA-protein interactions in vivo, in vitro and in silico. These include bespoke single-molecule fluorescence microscopy techniques to elucidate the architecture and dynamics of the bacterial replisome and the structural maintenance of bacterial chromosomes, as well as new computational tools to extract single-molecule molecular signatures from live cells to monitor stoichiometry, spatial localization and mobility in living cells. We also discuss recent developments from our laboratory made in vitro, complementing these in vivo studies, which combine optical and magnetic tweezers to manipulate and image single molecules of DNA, with and without bound protein, in a new super-resolution fluorescence microscope.

motifDiverge: a model for assessing the statistical significance of gene regulatory motif divergence between two DNA sequences

Next-generation sequencing technology enables the identification of thousands of gene regulatory sequences in many cell types and organisms. We consider the problem of testing if two such sequences differ in their number of binding site motifs for a given transcription factor (TF) protein. Binding site motifs impart regulatory function by providing TFs the opportunity to bind to genomic elements and thereby affect the expression of nearby genes. Evolutionary changes to such functional DNA are hypothesized to be major contributors to phenotypic diversity within and between species; but despite the importance of TF motifs for gene expression, no method exists to test for motif loss or gain. Assuming that motif counts are Binomially distributed, and allowing for dependencies between motif instances in evolutionarily related sequences, we derive the probability mass function of the difference in motif counts between two nucleotide sequences. We provide a method to numerically estimate this distribution from genomic data and show through simulations that our estimator is accurate. Finally, we introduce the R package motifDiverge that implements our methodology and illustrate its application to gene regulatory enhancers identified by a mouse developmental time course experiment. While this study was motivated by analysis of regulatory motifs, our results can be applied to any problem involving two correlated Bernoulli trials.

Standardizing chromatin research: a simple and universal method for ChIP-seq

Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) is a key technique in chromatin research. Although heavily applied, existing ChIP-seq protocols are often highly fine-tuned workflows, optimized for specific experimental requirements. Especially the initial steps of ChIP-seq, particularly chromatin shearing, are deemed to be exceedingly cell-type-specific, thus impeding any protocol standardization efforts. Here we demonstrate that harmonization of ChIP-seq workflows across cell types and conditions is possible when obtaining chromatin from properly isolated nuclei. We established an ultrasound-based nuclei extraction method (NEXSON: Nuclei EXtraction by SONication) that is highly effective across various organisms, cell types and cell numbers. The described method has the potential to replace complex cell-type-specific, but largely ineffective, nuclei isolation protocols. By including NEXSON in ChIP-seq workflows, we completely eliminate the need for extensive optimization and sample-dependent adjustments. Apart from this significant simplification, our approach also provides the basis for a fully standardized ChIP-seq and yields highly reproducible transcription factor and histone modifications maps for a wide range of different cell types. Even small cell numbers (∼10 000 cells per ChIP) can be easily processed without application of modified chromatin or library preparation protocols.

cChIP-seq: a robust small-scale method for investigation of histone modifications

BACKGROUND

ChIP-seq is highly utilized for mapping histone modifications that are informative about gene regulation and genome annotations. For example, applying ChIP-seq to histone modifications such as H3K4me1 has facilitated generating epigenomic maps of putative enhancers. This powerful technology, however, is limited in its application by the large number of cells required. ChIP-seq involves extensive manipulation of sample material and multiple reactions with limited quality control at each step, therefore, scaling down the number of cells required has proven challenging. Recently, several methods have been proposed to overcome this limit but most of these methods require extensive optimization to tailor the protocol to the specific antibody used or number of cells being profiled.

RESULTS

Here we describe a robust, yet facile method, which we named carrier ChIP-seq (cChIP-seq), for use on limited cell amounts. cChIP-seq employs a DNA-free histone carrier in order to maintain the working ChIP reaction scale, removing the need to tailor reactions to specific amounts of cells or histone modifications to be assayed. We have applied our method to three different histone modifications, H3K4me3, H3K4me1 and H3K27me3 in the K562 cell line, and H3K4me1 in H1 hESCs. We successfully obtained epigenomic maps for these histone modifications starting with as few as 10,000 cells. We compared cChIP-seq data to data generated as part of the ENCODE project. ENCODE data are the reference standard in the field and have been generated starting from tens of million of cells. Our results show that cChIP-seq successfully recapitulates bulk data. Furthermore, we showed that the differences observed between small-scale ChIP-seq data and ENCODE data are largely to be due to lab-to-lab variability rather than operating on a reduced scale.

CONCLUSIONS

Data generated using cChIP-seq are equivalent to reference epigenomic maps from three orders of magnitude more cells. Our method offers a robust and straightforward approach to scale down ChIP-seq to as low as 10,000 cells. The underlying principle of our strategy makes it suitable for being applied to a vast range of chromatin modifications without requiring expensive optimization. Furthermore, our strategy of a DNA-free carrier can be adapted to most ChIP-seq protocols.

Cystoisospora suis - A Model of Mammalian Cystoisosporosis

Cystoisospora suis is a coccidian species that typically affects suckling piglets. Infections occur by oral uptake of oocysts and are characterized by non-hemorrhagic transient diarrhea, resulting in poor weight gain. Apparently, primary immune responses to C. suis cannot readily be mounted by neonates, which contributes to the establishment and rapid development of the parasite, while in older pigs age-resistance prevents disease development. However, the presence of extraintestinal stages, although not unequivocally demonstrated, is suspected to enable parasite persistence together with the induction and maintenance of immune response in older pigs, which in turn may facilitate the transfer of C. suis-specific factors from sow to offspring. It is assumed that neonates are particularly prone to clinical disease because infections with C. suis interfere with the establishment of the gut microbiome. Clostridia have been especially inferred to profit from the altered intestinal environment during parasite infection. New tools, particularly in the area of genomics, might illustrate the interactions between C. suis and its host and pave the way for the development of new control methods not only for porcine cystoisosporosis but also for other mammalian Cystoisospora infections. The first reference genome for C. suis is under way and will be a fertile ground to discover new drugs and vaccines. At the same time, the establishment and refinement of an in vivo model and an in vitro culture system, supporting the complete life cycle of C. suis, will underpin the functional characterization of the parasite and shed light on its biology and control.

Uncovering drug-responsive regulatory elements

Nucleotide changes in gene regulatory elements can have a major effect on interindividual differences in drug response. For example, by reviewing all published pharmacogenomic genome-wide association studies, we show here that 96.4% of the associated single nucleotide polymorphisms reside in noncoding regions. We discuss how sequencing technologies are improving our ability to identify drug response-associated regulatory elements genome-wide and to annotate nucleotide variants within them. We highlight specific examples of how nucleotide changes in these elements can affect drug response and illustrate the techniques used to find them and functionally characterize them. Finally, we also discuss challenges in the field of drug-responsive regulatory elements that need to be considered in order to translate these findings into the clinic.

Intersection of genetics and epigenetics in monozygotic twin genomes

As a final function of various epigenetic mechanisms, chromatin regulation is a transcription control process that especially demonstrates active interaction with genetic elements. Thus, chromatin structure has become a principal focus in recent genomics researches that strive to characterize regulatory functions of DNA variants related to diseases or other traits. Although researchers have been focusing on DNA methylation when studying monozygotic (MZ) twins, a great model in epigenetics research, interactions between genetics and epigenetics in chromatin level are expected to be an imperative research trend in the future. In this review, we discuss how the genome, epigenome, and transcriptome of MZ twins can be studied in an integrative manner from this perspective.

MUSIC: identification of enriched regions in ChIP-Seq experiments using a mappability-corrected multiscale signal processing framework

We present MUSIC, a signal processing approach for identification of enriched regions in ChIP-Seq data, available at music.gersteinlab.org. MUSIC first filters the ChIP-Seq read-depth signal for systematic noise from non-uniform mappability, which fragments enriched regions. Then it performs a multiscale decomposition, using median filtering, identifying enriched regions at multiple length scales. This is useful given the wide range of scales probed in ChIP-Seq assays. MUSIC performs favorably in terms of accuracy and reproducibility compared with other methods. In particular, analysis of RNA polymerase II data reveals a clear distinction between the stalled and elongating forms of the polymerase.

Evolution of regulatory networks in Candida glabrata: learning to live with the human host

The opportunistic human fungal pathogen Candida glabrata is second only to C. albicans as the cause of Candida infections and yet is more closely related to Saccharomyces cerevisiae. Recent advances in functional genomics technologies and computational approaches to decipher regulatory networks, and the comparison of these networks among these and other Ascomycete species, have revealed both unique and shared strategies in adaptation to a human commensal/opportunistic pathogen lifestyle and antifungal drug resistance in C. glabrata. Recently, several C. glabrata sister species in the Nakeseomyces clade representing both human associated (commensal) and environmental isolates have had their genomes sequenced and analyzed. This has paved the way for comparative functional genomics studies to characterize the regulatory networks in these species to identify informative patterns of conservation and divergence linked to phenotypic evolution in the Nakaseomyces lineage.

Introduction to the analysis of next generation sequencing data and its application to venous thromboembolism

Despite knowledge of various inherited risk factors associated with venous thromboembolism (VTE), no definite cause can be found in about 50% of patients. The application of data-driven searches such as GWAS has not been able to identify genetic variants with implications for clinical care, and unexplained heritability remains. In the past years, the development of several so-called next generation sequencing (NGS) platforms is offering the possibility of generating fast, inexpensive and accurate genomic information. However, so far their application to VTE has been very limited. Here we review basic concepts of NGS data analysis and explore the application of NGS technology to VTE. We provide both computational and biological viewpoints to discuss potentials and challenges of NGS-based studies.

A Glimpse to Background and Characteristics of Major Molecular Biological Networks

Recently, biology has become a data intensive science because of huge data sets produced by high throughput molecular biological experiments in diverse areas including the fields of genomics, transcriptomics, proteomics, and metabolomics. These huge datasets have paved the way for system-level analysis of the processes and subprocesses of the cell. For system-level understanding, initially the elements of a system are connected based on their mutual relations and a network is formed. Among omics researchers, construction and analysis of biological networks have become highly popular. In this review, we briefly discuss both the biological background and topological properties of major types of omics networks to facilitate a comprehensive understanding and to conceptualize the foundation of network biology.

Detrimental effects of duplicate reads and low complexity regions on RNA- and ChIP-seq data

Background

Adapter trimming and removal of duplicate reads are common practices in next-generation sequencing pipelines. Sequencing reads ambiguously mapped to repetitive and low complexity regions can also be problematic for accurate assessment of the biological signal, yet their impact on sequencing data has not received much attention. We investigate how trimming the adapters, removing duplicates, and filtering out reads overlapping low complexity regions influence the significance of biological signal in RNA- and ChIP-seq experiments.

Methods

We assessed the effect of data processing steps on the alignment statistics and the functional enrichment analysis results of RNA- and ChIP-seq data. We compared differentially processed RNA-seq data with matching microarray data on the same patient samples to determine whether changes in pre-processing improved correlation between the two. We have developed a simple tool to remove low complexity regions, RepeatSoaker, available at https://github.com/mdozmorov/RepeatSoaker, and tested its effect on the alignment statistics and the results of the enrichment analyses.

Results

Both adapter trimming and duplicate removal moderately improved the strength of biological signals in RNA-seq and ChIP-seq data. Aggressive filtering of reads overlapping with low complexity regions, as defined by RepeatMasker, further improved the strength of biological signals, and the correlation between RNA-seq and microarray gene expression data.

Conclusions

Adapter trimming and duplicates removal, coupled with filtering out reads overlapping low complexity regions, is shown to increase the quality and reliability of detecting biological signals in RNA-seq and ChIP-seq data.

De novo ChIP-seq analysis

Methods for the analysis of chromatin immunoprecipitation sequencing (ChIP-seq) data start by aligning the short reads to a reference genome. While often successful, they are not appropriate for cases where a reference genome is not available. Here we develop methods for de novo analysis of ChIP-seq data. Our methods combine de novo assembly with statistical tests enabling motif discovery without the use of a reference genome. We validate the performance of our method using human and mouse data. Analysis of fly data indicates that our method outperforms alignment based methods that utilize closely related species.

Genomic approaches to studying human-specific developmental traits

Changes in developmental regulatory programs drive both disease and phenotypic differences among species. Linking human-specific traits to alterations in development is challenging, because we have lacked the tools to assay and manipulate regulatory networks in human and primate embryonic cells. This field was transformed by the sequencing of hundreds of genomes – human and non-human – that can be compared to discover the regulatory machinery of genes involved in human development. This approach has identified thousands of human-specific genome alterations in developmental genes and their regulatory regions. With recent advances in stem cell techniques, genome engineering, and genomics, we can now test these sequences for effects on developmental gene regulation and downstream phenotypes in human cells and tissues.

CETCh-seq: CRISPR epitope tagging ChIP-seq of DNA-binding proteins

Chromatin immunoprecipitation followed by next-generation DNA sequencing (ChIP-seq) is a widely used technique for identifying transcription factor (TF) binding events throughout an entire genome. However, ChIP-seq is limited by the availability of suitable ChIP-seq grade antibodies, and the vast majority of commercially available antibodies fail to generate usable data sets. To ameliorate these technical obstacles, we present a robust methodological approach for performing ChIP-seq through epitope tagging of endogenous TFs. We used clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-based genome editing technology to develop CRISPR epitope tagging ChIP-seq (CETCh-seq) of DNA-binding proteins. We assessed the feasibility of CETCh-seq by tagging several DNA-binding proteins spanning a wide range of endogenous expression levels in the hepatocellular carcinoma cell line HepG2. Our data exhibit strong correlations between both replicate types as well as with standard ChIP-seq approaches that use TF antibodies. Notably, we also observed minimal changes to the cellular transcriptome and to the expression of the tagged TF. To examine the robustness of our technique, we further performed CETCh-seq in the breast adenocarcinoma cell line MCF7 as well as mouse embryonic stem cells and observed similarly high correlations. Collectively, these data highlight the applicability of CETCh-seq to accurately define the genome-wide binding profiles of DNA-binding proteins, allowing for a straightforward methodology to potentially assay the complete repertoire of TFs, including the large fraction for which ChIP-quality antibodies are not available.

Xenopus tropicalis Genome Re-Scaffolding and Re-Annotation Reach the Resolution Required for In Vivo ChIA-PET Analysis

Genome-wide functional analyses require high-resolution genome assembly and annotation. We applied ChIA-PET to analyze gene regulatory networks, including 3D chromosome interactions, underlying thyroid hormone (TH) signaling in the frog Xenopus tropicalis. As the available versions of Xenopus tropicalis assembly and annotation lacked the resolution required for ChIA-PET we improve the genome assembly version 4.1 and annotations using data derived from the paired end tag (PET) sequencing technologies and approaches (e.g., DNA-PET [gPET], RNA-PET etc.). The large insert (~10Kb, ~17Kb) paired end DNA-PET with high throughput NGS sequencing not only significantly improved genome assembly quality, but also strongly reduced genome “fragmentation”, reducing total scaffold numbers by ~60%. Next, RNA-PET technology, designed and developed for the detection of full-length transcripts and fusion mRNA in whole transcriptome studies (ENCODE consortia), was applied to capture the 5' and 3' ends of transcripts. These amendments in assembly and annotation were essential prerequisites for the ChIA-PET analysis of TH transcription regulation. Their application revealed complex regulatory configurations of target genes and the structures of the regulatory networks underlying physiological responses. Our work allowed us to improve the quality of Xenopus tropicalis genomic resources, reaching the standard required for ChIA-PET analysis of transcriptional networks. We consider that the workflow proposed offers useful conceptual and methodological guidance and can readily be applied to other non-conventional models that have low-resolution genome data.

Recent advances in the use of mass spectrometry to examine structure/function relationships in photosystem II

Tandem mass spectrometry often coupled with chemical modification techniques, is developing into increasingly important tool in structural biology. These methods can provide important supplementary information concerning the structural organization and subunit make-up of membrane protein complexes, identification of conformational changes occurring during enzymatic reactions, identification of the location of posttranslational modifications, and elucidation of the structure of assembly and repair complexes. In this review, we will present a brief introduction to Photosystem II, tandem mass spectrometry and protein modification techniques that have been used to examine the photosystem. We will then discuss a number of recent case studies that have used these techniques to address open questions concerning PS II. These include the nature of subunit-subunit interactions within the phycobilisome, the interaction of phycobilisomes with Photosystem I and the Orange Carotenoid Protein, the location of CyanoQ, PsbQ and PsbP within Photosystem II, and the identification of phosphorylation and oxidative modification sites within the photosystem. Finally, we will discuss some of the future prospects for the use of these methods in examining other open questions in PS II structural biochemistry.

ChIPmentation: fast, robust, low-input ChIP-seq for histones and transcription factors

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to map histone marks and transcription factor binding throughout the genome. Here we present ChIPmentation, a method that combines chromatin immunoprecipitation with sequencing library preparation by Tn5 transposase (“tagmentation”). ChIPmentation introduces sequencing-compatible adapters in a single-step reaction directly on bead-bound chromatin, which reduces time, cost, and input requirements, thus providing a convenient and broadly useful alternative to existing ChIP-seq protocols.

SpDamID: Marking DNA Bound by Protein Complexes Identifies Notch-Dimer Responsive Enhancers

We developed Split DamID (SpDamID), a protein complementation version of DamID, to mark genomic DNA bound in vivo by interacting or juxtapositioned transcription factors. Inactive halves of DAM (DNA adenine methyltransferase) were fused to protein pairs to be queried. Either direct interaction between proteins or proximity enabled DAM reconstitution and methylation of adenine in GATC. Inducible SpDamID was used to analyze Notch-mediated transcriptional activation. We demonstrate that Notch complexes label RBP sites broadly across the genome and show that a subset of these complexes that recruit MAML and p300 undergo changes in chromatin accessibility in response to Notch signaling. SpDamID differentiates between monomeric and dimeric binding, thereby allowing for identification of half-site motifs used by Notch dimers. Motif enrichment of Notch enhancers coupled with SpDamID reveals co-targeting of regulatory sequences by Notch and Runx1. SpDamID represents a sensitive and powerful tool that enables dynamic analysis of combinatorial protein-DNA transactions at a genome-wide level.

Chromosomal polymorphism in mammals: an evolutionary perspective

Although chromosome rearrangements (CRs) are central to studies of genome evolution, our understanding of the evolutionary consequences of the early stages of karyotypic differentiation (i.e. polymorphism), especially the non-meiotic impacts, is surprisingly limited. We review the available data on chromosomal polymorphisms in mammals so as to identify taxa that hold promise for developing a more comprehensive understanding of chromosomal change. In doing so, we address several key questions: (i) to what extent are mammalian karyotypes polymorphic, and what types of rearrangements are principally involved? (ii) Are some mammalian lineages more prone to chromosomal polymorphism than others? More specifically, do (karyotypically) polymorphic mammalian species belong to lineages that are also characterized by past, extensive karyotype repatterning? (iii) How long can chromosomal polymorphisms persist in mammals? We discuss the evolutionary implications of these questions and propose several research avenues that may shed light on the role of chromosome change in the diversification of mammalian populations and species.

Quantitative assessment of RNA-protein interactions with high-throughput sequencing-RNA affinity profiling

Because RNA-protein interactions have a central role in a wide array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay that couples sequencing on an Illumina GAIIx genome analyzer with the quantitative assessment of protein-RNA interactions. This assay is able to analyze interactions between one or possibly several proteins with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of the EGFP and negative elongation factor subunit E (NELF-E) proteins with their corresponding canonical and mutant RNA aptamers. Here we provide a detailed protocol for HiTS-RAP that can be completed in about a month (8 d hands-on time). This includes the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, HiTS and protein binding with a GAIIx instrument, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, quantitative analysis of RNA on a massively parallel array (RNA-MaP) and RNA Bind-n-Seq (RBNS), for quantitative analysis of RNA-protein interactions.

Count ratio model reveals bias affecting NGS fold changes

Various biases affect high-throughput sequencing read counts. Contrary to the general assumption, we show that bias does not always cancel out when fold changes are computed and that bias affects more than 20% of genes that are called differentially regulated in RNA-seq experiments with drastic effects on subsequent biological interpretation. Here, we propose a novel approach to estimate fold changes. Our method is based on a probabilistic model that directly incorporates count ratios instead of read counts. It provides a theoretical foundation for pseudo-counts and can be used to estimate fold change credible intervals as well as normalization factors that outperform currently used normalization methods. We show that fold change estimates are significantly improved by our method by comparing RNA-seq derived fold changes to qPCR data from the MAQC/SEQC project as a reference and analyzing random barcoded sequencing data. Our software implementation is freely available from the project website http://www.bio.ifi.lmu.de/software/lfc.

DNA-Protein Cross-Links: Formation, Structural Identities, and Biological Outcomes

Noncovalent DNA-protein interactions are at the heart of normal cell function. In eukaryotic cells, genomic DNA is wrapped around histone octamers to allow for chromosomal packaging in the nucleus. Binding of regulatory protein factors to DNA directs replication, controls transcription, and mediates cellular responses to DNA damage. Because of their fundamental significance in all cellular processes involving DNA, dynamic DNA-protein interactions are required for cell survival, and their disruption is likely to have serious biological consequences. DNA-protein cross-links (DPCs) form when cellular proteins become covalently trapped on DNA strands upon exposure to various endogenous, environmental and chemotherapeutic agents. DPCs progressively accumulate in the brain and heart tissues as a result of endogenous exposure to reactive oxygen species and lipid peroxidation products, as well as normal cellular metabolism. A range of structurally diverse DPCs are found following treatment with chemotherapeutic drugs, transition metal ions, and metabolically activated carcinogens. Because of their considerable size and their helix-distorting nature, DPCs interfere with the progression of replication and transcription machineries and hence hamper the faithful expression of genetic information, potentially contributing to mutagenesis and carcinogenesis. Mass spectrometry-based studies have identified hundreds of proteins that can become cross-linked to nuclear DNA in the presence of reactive oxygen species, carcinogen metabolites, and antitumor drugs. While many of these proteins including histones, transcription factors, and repair proteins are known DNA binding partners, other gene products with no documented affinity for DNA also participate in DPC formation. Furthermore, multiple sites within DNA can be targeted for cross-linking including the N7 of guanine, the C-5 methyl group of thymine, and the exocyclic amino groups of guanine, cytosine, and adenine. This structural complexity complicates structural and biological studies of DPC lesions. Two general strategies have been developed for creating DNA strands containing structurally defined, site-specific DPCs. Enzymatic methodologies that trap DNA modifying proteins on their DNA substrate are site specific and efficient, but do not allow for systematic studies of DPC lesion structure on their biological outcomes. Synthetic methodologies for DPC formation are based on solid phase synthesis of oligonucleotide strands containing protein-reactive unnatural DNA bases. The latter approach allows for a wider range of protein substrates to be conjugated to DNA and affords a greater flexibility for the attachment sites within DNA. In this Account, we outline the chemistry of DPC formation in cells, describe our recent efforts to identify the cross-linked proteins by mass spectrometry, and discuss various methodologies for preparing DNA strands containing structurally defined, site specific DPC lesions. Polymerase bypass experiments conducted with model DPCs indicate that the biological outcomes of these bulky lesions are strongly dependent on the peptide/protein size and the exact cross-linking site within DNA. Future studies are needed to elucidate the mechanisms of DPC repair and their biological outcomes in living cells.

Multiplexing of ChIP-Seq Samples in an Optimized Experimental Condition Has Minimal Impact on Peak Detection

Multiplexing samples in sequencing experiments is a common approach to maximize information yield while minimizing cost. In most cases the number of samples that are multiplexed is determined by financial consideration or experimental convenience, with limited understanding on the effects on the experimental results. Here we set to examine the impact of multiplexing ChIP-seq experiments on the ability to identify a specific epigenetic modification. We performed peak detection analyses to determine the effects of multiplexing. These include false discovery rates, size, position and statistical significance of peak detection, and changes in gene annotation. We found that, for histone marker H3K4me3, one can multiplex up to 8 samples (7 IP + 1 input) at ~21 million single-end reads each and still detect over 90% of all peaks found when using a full lane for sample (~181 million reads). Furthermore, there are no variations introduced by indexing or lane batch effects and importantly there is no significant reduction in the number of genes with neighboring H3K4me3 peaks. We conclude that, for a well characterized antibody and, therefore, model IP condition, multiplexing 8 samples per lane is sufficient to capture most of the biological signal.