ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia

DNA methylation regulates associative reward learning

Reward-related memories are essential for adaptive behavior and evolutionary fitness, but they are also a core component of maladaptive brain diseases such as addiction. Reward learning requires dopamine neurons located in the ventral tegmental area (VTA), which encode relationships between predictive cues and future rewards. Recent evidence suggests that epigenetic mechanisms, including DNA methylation, are essential regulators of neuronal plasticity and experience-driven behavioral change. However, the role of epigenetic mechanisms in reward learning is poorly understood. Here we show that the formation of reward-related associative memories in rats upregulates key plasticity genes in the VTA, which are correlated with memory strength and associated with gene-specific changes in DNA methylation. Moreover, DNA methylation in the VTA is required for the formation of stimulus-reward associations. These results provide the first evidence that that activity-dependent methylation and demethylation of DNA is an essential substrate for the behavioral and neuronal plasticity driven by reward-related experiences.

Mapping human epigenomes

As the second dimension to the genome, the epigenome contains key information specific to every type of cells. Thousands of human epigenome maps have been produced in recent years thanks to rapid development of high throughput epigenome mapping technologies. In this review, we discuss the current epigenome mapping toolkit and utilities of epigenome maps. We focus particularly on mapping of DNA methylation, chromatin modification state, and chromatin structures, and emphasize the use of epigenome maps to delineate human gene regulatory sequences and developmental programs. We also provide a perspective on the progress of the epigenomics field and challenges ahead.

A quality control system for profiles obtained by ChIP sequencing

The absence of a quality control (QC) system is a major weakness for the comparative analysis of genome-wide profiles generated by next-generation sequencing (NGS). This concerns particularly genome binding/occupancy profiling assays like chromatin immunoprecipitation (ChIP-seq) but also related enrichment-based studies like methylated DNA immunoprecipitation/methylated DNA binding domain sequencing, global run on sequencing or RNA-seq. Importantly, QC assessment may significantly improve multidimensional comparisons that have great promise for extracting information from combinatorial analyses of the global profiles established for chromatin modifications, the bindings of epigenetic and chromatin-modifying enzymes/machineries, RNA polymerases and transcription factors and total, nascent or ribosome-bound RNAs. Here we present an approach that associates global and local QC indicators to ChIP-seq data sets as well as to a variety of enrichment-based studies by NGS. This QC system was used to certify >5600 publicly available data sets, hosted in a database for data mining and comparative QC analyses.

Role of long non-coding RNAs in normal and malignant hematopoiesis

Long non-coding RNAs (lncRNAs) are defined as a class of nonprotein-coding transcripts greater than 200 nucleotides in length, which have diverse functions in development and diseases including hematopoiesis. Recent advances have revealed that lncRNAs regulate hematopoietic development at almost every stage, including differentiation of the myelocyte, lymphocyte, and erythrocyte. Abnormal regulation of the lncRNAs may block aspects of blood development, which can lead to different types of hematopoietic disorders. These findings highlight the role of lncRNAs as potential therapeutic tools in malignant hematopoiesis. In this review, we summarize recent progress in the study of functional lncRNAs associated with blood development, as well as dysregulated lncRNAs involved in diverse blood diseases by interacting with crucial susceptibility genes in different pathways. In addition, we discuss genome-wide studies on lncRNAs, which are helpful for genome screening and in-depth functional study of lncRNAs associated with blood development and disease.

Quantifying transcription factor kinetics: at work or at play?

Transcription factors (TFs) interact dynamically in vivo with chromatin binding sites. Here we summarize and compare the four different techniques that are currently used to measure these kinetics in live cells, namely fluorescence recovery after photobleaching (FRAP), fluorescence correlation spectroscopy (FCS), single molecule tracking (SMT) and competition ChIP (CC). We highlight the principles underlying each of these approaches as well as their advantages and disadvantages. A comparison of data from each of these techniques raises an important question: do measured transcription kinetics reflect biologically functional interactions at specific sites (i.e. working TFs) or do they reflect non-specific interactions (i.e. playing TFs)? To help resolve this dilemma we discuss five key unresolved biological questions related to the functionality of transient and prolonged binding events at both specific promoter response elements as well as non-specific sites. In support of functionality, we review data suggesting that TF residence times are tightly regulated, and that this regulation modulates transcriptional output at single genes. We argue that in addition to this site-specific regulatory role, TF residence times also determine the fraction of promoter targets occupied within a cell thereby impacting the functional status of cellular gene networks. Thus, TF residence times are key parameters that could influence transcription in multiple ways.

Distinct global shifts in genomic binding profiles of limb malformation-associated HOXD13 mutations

Gene regulation by transcription factors (TFs) determines developmental programs and cell identity. Consequently, mutations in TFs can lead to dramatic phenotypes in humans by disrupting gene regulation. To date, the molecular mechanisms that actually cause these phenotypes have been difficult to address experimentally. ChIP-seq, which couples chromatin immunoprecipitation with high-throughput sequencing, allows TF function to be investigated on a genome-wide scale, enabling new approaches for the investigation of gene regulation. Here, we present the application of ChIP-seq to explore the effect of missense mutations in TFs on their genome-wide binding profile. Using a retroviral expression system in chicken mesenchymal stem cells, we elucidated the mechanism underlying a novel missense mutation in HOXD13 (Q317K) associated with a complex hand and foot malformation phenotype. The mutated glutamine (Q) is conserved in most homeodomains, a notable exception being bicoid-type homeodomains that have lysine (K) at this position. Our results show that the mutation results in a shift in the binding profile of the mutant toward a bicoid/PITX1 motif. Gene expression analysis and functional assays using in vivo overexpression studies confirm that the mutation results in a partial conversion of HOXD13 into a TF with bicoid/PITX1 properties. A similar shift was not observed with another mutation, Q317R, which is associated with brachysyndactyly, suggesting that the bicoid/PITX1-shift observed for Q317K might be related to the severe clinical phenotype. The methodology described can be used to investigate a wide spectrum of TFs and mutations that have not previously been amenable to ChIP-seq experiments.

Genome-wide analysis reveals coating of the mitochondrial genome by TFAM

Mitochondria contain a 16.6 kb circular genome encoding 13 proteins as well as mitochondrial tRNAs and rRNAs. Copies of the genome are organized into nucleoids containing both DNA and proteins, including the machinery required for mtDNA replication and transcription. The transcription factor TFAM is critical for initiation of transcription and replication of the genome, and is also thought to perform a packaging function. Although specific binding sites required for initiation of transcription have been identified in the D-loop, little is known about the characteristics of TFAM binding in its nonspecific packaging state. In addition, it is unclear whether TFAM also plays a role in the regulation of nuclear gene expression. Here we investigate these questions by using ChIP-seq to directly localize TFAM binding to DNA in human cells. Our results demonstrate that TFAM uniformly coats the whole mitochondrial genome, with no evidence of robust TFAM binding to the nuclear genome. Our study represents the first high-resolution assessment of TFAM binding on a genome-wide scale in human cells.

Inferring nucleosome positions with their histone mark annotation from ChIP data

Motivation: The nucleosome is the basic repeating unit of chromatin. It contains two copies each of the four core histones H2A, H2B, H3 and H4 and about 147 bp of DNA. The residues of the histone proteins are subject to numerous post-translational modifications, such as methylation or acetylation. Chromatin immunoprecipitiation followed by sequencing (ChIP-seq) is a technique that provides genome-wide occupancy data of these modified histone proteins, and it requires appropriate computational methods.

Results: We present NucHunter, an algorithm that uses the data from ChIP-seq experiments directed against many histone modifications to infer positioned nucleosomes. NucHunter annotates each of these nucleosomes with the intensities of the histone modifications. We demonstrate that these annotations can be used to infer nucleosomal states with distinct correlations to underlying genomic features and chromatin-related processes, such as transcriptional start sites, enhancers, elongation by RNA polymerase II and chromatin-mediated repression. Thus, NucHunter is a versatile tool that can be used to predict positioned nucleosomes from a panel of histone modification ChIP-seq experiments and infer distinct histone modification patterns associated to different chromatin states.

Availability: The software is available at http://epigen.molgen.mpg.de/nuchunter/.

Contact:chung@molgen.mpg.de

Supplementary information:Supplementary data are available at Bioinformatics online.

Genome-wide analysis of transcriptional regulators in human HSPCs reveals a densely interconnected network of coding and noncoding genes

Genome-wide combinatorial binding patterns for key transcription factors (TFs) have not been reported for primary human hematopoietic stem and progenitor cells (HSPCs), and have constrained analysis of the global architecture of molecular circuits controlling these cells. Here we provide high-resolution genome-wide binding maps for a heptad of key TFs (FLI1, ERG, GATA2, RUNX1, SCL, LYL1, and LMO2) in human CD34(+) HSPCs, together with quantitative RNA and microRNA expression profiles. We catalog binding of TFs at coding genes and microRNA promoters, and report that combinatorial binding of all 7 TFs is favored and associated with differential expression of genes and microRNA in HSPCs. We also uncover a previously unrecognized association between FLI1 and RUNX1 pairing in HSPCs, we establish a correlation between the density of histone modifications that mark active enhancers and the number of overlapping TFs at a peak, we demonstrate bivalent histone marks at promoters of heptad target genes in CD34(+) cells that are poised for later expression, and we identify complex relationships between specific microRNAs and coding genes regulated by the heptad. Taken together, these data reveal the power of integrating multifactor sequencing of chromatin immunoprecipitates with coding and noncoding gene expression to identify regulatory circuits controlling cell identity.

Next-generation sequencing: a powerful tool for the discovery of molecular markers in breast ductal carcinoma in situ

Mammographic screening leads to frequent biopsies and concomitant overdiagnosis of breast cancer, particularly ductal carcinoma in situ (DCIS). Some DCIS lesions rapidly progress to invasive carcinoma, whereas others remain indolent. Because we cannot yet predict which lesions will not progress, all DCIS is regarded as malignant, and many women are overtreated. Thus, there is a pressing need for a panel of molecular markers in addition to the current clinical and pathological factors to provide prognostic information. Genomic technologies such as microarrays have made major contributions to defining subtypes of breast cancer. Next-generation sequencing (NGS) modalities offer unprecedented depth of expression analysis through revealing transcriptional boundaries, mutations, rare transcripts and alternative splice variants. NGS approaches are just beginning to be applied to DCIS. Here, the authors review the applications and challenges of NGS in discovering novel potential therapeutic targets and candidate biomarkers in the premalignant progression of breast cancer.

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites

During cell division, transcription factors (TFs) are removed from chromatin twice, during DNA synthesis and during condensation of chromosomes. How TFs can efficiently find their sites following these stages has been unclear. Here, we have analyzed the binding pattern of expressed TFs in human colorectal cancer cells. We find that binding of TFs is highly clustered and that the clusters are enriched in binding motifs for several major TF classes. Strikingly, almost all clusters are formed around cohesin, and loss of cohesin decreases both DNA accessibility and binding of TFs to clusters. We show that cohesin remains bound in S phase, holding the nascent sister chromatids together at the TF cluster sites. Furthermore, cohesin remains bound to the cluster sites when TFs are evicted in early M phase. These results suggest that cohesin-binding functions as a cellular memory that promotes re-establishment of TF clusters after DNA replication and chromatin condensation.

Genome-wide survey by ChIP-seq reveals YY1 regulation of lincRNAs in skeletal myogenesis

Skeletal muscle differentiation is orchestrated by a network of transcription factors, epigenetic regulators, and non-coding RNAs. The transcription factor Yin Yang 1 (YY1) silences multiple target genes in myoblasts (MBs) by recruiting Ezh2 (Enhancer of Zeste Homologue2). To elucidate genome-wide YY1 binding in MBs, we performed chromatin immunoprecipitation (ChIP)-seq and found 1820 specific binding sites in MBs with a large portion residing in intergenic regions. Detailed analysis demonstrated that YY1 acts as an activator for many loci in addition to its known repressor function. No significant co-occupancy was found between YY1 and Ezh2, suggesting an additional Ezh2-independent function for YY1 in MBs. Further analysis of intergenic binding sites showed that YY1 potentially regulates dozens of large intergenic non-coding RNAs (lincRNAs), whose function in myogenesis is underexplored. We characterized a novel muscle-associated lincRNA (Yam-1) that is positively regulated by YY1. Yam-1 is downregulated upon differentiation and acts as an inhibitor of myogenesis. We demonstrated that Yam-1 functions through in cis regulation of miR-715, which in turn targets Wnt7b. Our findings not only provide the first genome-wide picture of YY1 association in muscle cells, but also uncover the functional role of lincRNA Yam-1.

Oncogenic ETS fusions deregulate E2F3 target genes in Ewing sarcoma and prostate cancer

Deregulated E2F transcription factor activity occurs in the vast majority of human tumors and has been solidly implicated in disturbances of cell cycle control, proliferation, and apoptosis. Aberrant E2F regulatory activity is often caused by impairment of control through pRB function, but little is known about the interplay of other oncoproteins with E2F. Here we show that ETS transcription factor fusions resulting from disease driving rearrangements in Ewing sarcoma (ES) and prostate cancer (PC) are one such class of oncoproteins. We performed an integrative study of genome-wide DNA-binding and transcription data in EWSR1/FLI1 expressing ES and TMPRSS2/ERG containing PC cells. Supported by promoter activity and mutation analyses, we demonstrate that a large fraction of E2F3 target genes are synergistically coregulated by these aberrant ETS proteins. We propose that the oncogenic effect of ETS fusion oncoproteins is in part mediated by the disruptive effect of the E2F–ETS interaction on cell cycle control. Additionally, a detailed analysis of the regulatory targets of the characteristic EWSR1/FLI1 fusion in ES identifies two functionally distinct gene sets. While synergistic regulation in concert with E2F in the promoter of target genes has a generally activating effect, EWSR1/FLI1 binding independent of E2F3 is predominantly associated with repressed differentiation genes. Thus, EWSR1/FLI1 appears to promote oncogenesis by simultaneously promoting cell proliferation and perturbing differentiation.

Arpeggio: harmonic compression of ChIP-seq data reveals protein-chromatin interaction signatures

Researchers generating new genome-wide data in an exploratory sequencing study can gain biological insights by comparing their data with well-annotated data sets possessing similar genomic patterns. Data compression techniques are needed for efficient comparisons of a new genomic experiment with large repositories of publicly available profiles. Furthermore, data representations that allow comparisons of genomic signals from different platforms and across species enhance our ability to leverage these large repositories. Here, we present a signal processing approach that characterizes protein–chromatin interaction patterns at length scales of several kilobases. This allows us to efficiently compare numerous chromatin-immunoprecipitation sequencing (ChIP-seq) data sets consisting of many types of DNA-binding proteins collected from a variety of cells, conditions and organisms. Importantly, these interaction patterns broadly reflect the biological properties of the binding events. To generate these profiles, termed Arpeggio profiles, we applied harmonic deconvolution techniques to the autocorrelation profiles of the ChIP-seq signals. We used 806 publicly available ChIP-seq experiments and showed that Arpeggio profiles with similar spectral densities shared biological properties. Arpeggio profiles of ChIP-seq data sets revealed characteristics that are not easily detected by standard peak finders. They also allowed us to relate sequencing data sets from different genomes, experimental platforms and protocols. Arpeggio is freely available at http://sourceforge.net/p/arpeggio/wiki/Home/.

Chromatin tandem affinity purification sequencing

Chromatin immunoprecipitation coupled with ultra-high-throughput sequencing (ChIP-seq) is a widely used method for mapping the interactions of proteins with DNA. However, the requirements for ChIP-grade antibodies impede wider application of this method, and variations in results can be high owing to differences in affinity and cross-reactivity of antibodies. Therefore, we developed chromatin tandem affinity purification (ChTAP) as an effective alternative to ChIP. Through the use of affinity tags and reagents that are identical for all proteins investigated, ChTAP enables one to directly compare the binding between different transcription factors and to directly assess the background in control experiments. Thus, ChTAP-seq can be used to rapidly map the genome-wide binding of multiple DNA-binding proteins in a wide range of cell types. ChTAP can be completed in 3-4 d, starting from cross-linking of chromatin to purification of ChIP DNA.

Genomic targets, and histone acetylation and gene expression profiling of neural HDAC inhibition

Histone deacetylase inhibitors (HDACis) have been shown to potentiate hippocampal-dependent memory and synaptic plasticity and to ameliorate cognitive deficits and degeneration in animal models for different neuropsychiatric conditions. However, the impact of these drugs on hippocampal histone acetylation and gene expression profiles at the genomic level, and the molecular mechanisms that underlie their specificity and beneficial effects in neural tissue, remains obscure. Here, we mapped four relevant histone marks (H3K4me3, AcH3K9,14, AcH4K12 and pan-AcH2B) in hippocampal chromatin and investigated at the whole-genome level the impact of HDAC inhibition on acetylation profiles and basal and activity-driven gene expression. HDAC inhibition caused a dramatic histone hyperacetylation that was largely restricted to active loci pre-marked with H3K4me3 and AcH3K9,14. In addition, the comparison of Chromatin immunoprecipitation sequencing and gene expression profiles indicated that Trichostatin A-induced histone hyperacetylation, like histone hypoacetylation induced by histone acetyltransferase deficiency, had a modest impact on hippocampal gene expression and did not affect the transient transcriptional response to novelty exposure. However, HDAC inhibition caused the rapid induction of a homeostatic gene program related to chromatin deacetylation. These results illuminate both the relationship between hippocampal gene expression and histone acetylation and the mechanism of action of these important neuropsychiatric drugs.

Human Transcriptome and Chromatin Modifications: An ENCODE Perspective

A decade-long project, led by several international research groups, called the Encyclopedia of DNA Elements (ENCODE), recently released an unprecedented amount of data. The ambitious project covers transcriptome, cistrome, epigenome, and interactome data from more than 1,600 sets of experiments in human. To make use of this valuable resource, it is important to understand the information it represents and the techniques that were used to generate these data. In this review, we introduce the data that ENCODE generated, summarize the observations from the data analysis, and revisit a computational approach that ENCODE used to predict gene expression, with a focus on the human transcriptome and its association with chromatin modifications.

Molecular network of ChIP-Seq-based NF-κB p65 target genes involves diverse immune functions relevant to the immunopathogenesis of multiple sclerosis

BACKGROUND

The transcription factor nuclear factor-kappa B (NF-κB) acts as a central regulator of immune response, stress response, cell proliferation, and apoptosis. Aberrant regulation of NF-κB function triggers development of cancers, metabolic diseases, and autoimmune diseases. We attempted to characterize a global picture of the NF-κB target gene network relevant to the immunopathogenesis of multiple sclerosis (MS).

METHODS

We identified the comprehensive set of 918 NF-κB p65 binding sites on protein-coding genes from chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) dataset of TNFα-stimulated human B lymphoblastoid cells. The molecular network was studied by a battery of pathway analysis tools of bioinformatics.

RESULTS

The GenomeJack genome viewer showed that NF-κB p65 binding sites were accumulated in promoter (35.5%) and intronic (54.9%) regions with an existence of the NF-κB consensus sequence motif. A set of 52 genes (5.7%) corresponded to known NF-κB targets by database search. KEGG, PANTHER, and Ingenuity Pathways Analysis (IPA) revealed that the NF-κB p65 target gene network is linked to regulation of immune functions and oncogenesis, including B cell receptor signaling, T cell activation pathway, Toll-like receptor signaling, and apoptosis signaling, and molecular mechanisms of cancers. KeyMolnet indicated an involvement of the complex crosstalk among core transcription factors in the NF-κB p65 target gene network. Furthermore, the set of NF-κB p65 target genes included 10 genes among 98 MS risk alleles and 49 molecules among 709 MS brain lesion-specific proteins.

CONCLUSIONS

These results suggest that aberrant regulation of NF-κB-mediated gene expression, by inducing dysfunction of diverse immune functions, is closely associated with development and progression of MS.

ZBTB33 binds unmethylated regions of the genome associated with actively expressed genes

BACKGROUND

DNA methylation and repressive histone modifications cooperate to silence promoters. One mechanism by which regions of methylated DNA could acquire repressive histone modifications is via methyl DNA-binding transcription factors. The zinc finger protein ZBTB33 (also known as Kaiso) has been shown in vitro to bind preferentially to methylated DNA and to interact with the SMRT/NCoR histone deacetylase complexes. We have performed bioinformatic analyses of Kaiso ChIP-seq and DNA methylation datasets to test a model whereby binding of Kaiso to methylated CpGs leads to loss of acetylated histones at target promoters.

RESULTS

Our results suggest that, contrary to expectations, Kaiso does not bind to methylated DNA in vivo but instead binds to highly active promoters that are marked with high levels of acetylated histones. In addition, our studies suggest that DNA methylation and nucleosome occupancy patterns restrict access of Kaiso to potential binding sites and influence cell type-specific binding.

CONCLUSIONS

We propose a new model for the genome-wide binding and function of Kaiso whereby Kaiso binds to unmethylated regulatory regions and contributes to the active state of target promoters.

Evidence for multiple roles for grainyhead-like 2 in the establishment and maintenance of human mucociliary airway epithelium.[corrected]

Most of the airways of the human lung are lined by an epithelium made up of ciliated and secretory luminal cells and undifferentiated basal progenitor cells. The integrity of this epithelium and its ability to act as a selective barrier are critical for normal lung function. In other epithelia, there is evidence that transcription factors of the evolutionarily conserved grainyheadlike (GRHL) family play key roles in coordinating multiple cellular processes required for epithelial morphogenesis, differentiation, remodeling, and repair. However, only a few target genes have been identified, and little is known about GRHL function in the adult lung. Here we focus on the role of GRHL2 in primary human bronchial epithelial cells, both as undifferentiated progenitors and as they differentiate in air-liquid interface culture into an organized mucociliary epithelium with transepithelial resistance. Using a dominant-negative protein or shRNA to inhibit GRHL2, we follow changes in epithelial phenotype and gene transcription using RNA sequencing or microarray analysis. We identify several hundreds of genes that are directly or indirectly regulated by GRHL2 in both undifferentiated cells and air-liquid interface cultures. Using ChIP sequencing to map sites of GRHL2 binding in the basal cells, we identify 7,687 potential primary targets and confirm that GRHL2 binding is strongly enriched near GRHL2-regulated genes. Taken together, the results support the hypothesis that GRHL2 plays a key role in regulating many physiological functions of human airway epithelium, including those involving cell morphogenesis, adhesion, and motility.

DROMPA: easy-to-handle peak calling and visualization software for the computational analysis and validation of ChIP-seq data

Chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) can identify genomic regions that bind proteins involved in various chromosomal functions. Although the development of next-generation sequencers offers the technology needed to identify these protein-binding sites, the analysis can be computationally challenging because sequencing data sometimes consist of >100 million reads/sample. Herein, we describe a cost-effective and time-efficient protocol that is generally applicable to ChIP-seq analysis; this protocol uses a novel peak-calling program termed DROMPA to identify peaks and an additional program, parse2wig, to preprocess read-map files. This two-step procedure drastically reduces computational time and memory requirements compared with other programs. DROMPA enables the identification of protein localization sites in repetitive sequences and efficiently identifies both broad and sharp protein localization peaks. Specifically, DROMPA outputs a protein-binding profile map in pdf or png format, which can be easily manipulated by users who have a limited background in bioinformatics.

Mapping functional transcription factor networks from gene expression data

A critical step in understanding how a genome functions is determining which transcription factors (TFs) regulate each gene. Accordingly, extensive effort has been devoted to mapping TF networks. In Saccharomyces cerevisiae, protein–DNA interactions have been identified for most TFs by ChIP-chip, and expression profiling has been done on strains deleted for most TFs. These studies revealed that there is little overlap between the genes whose promoters are bound by a TF and those whose expression changes when the TF is deleted, leaving us without a definitive TF network for any eukaryote and without an efficient method for mapping functional TF networks. This paper describes NetProphet, a novel algorithm that improves the efficiency of network mapping from gene expression data. NetProphet exploits a fundamental observation about the nature of TF networks: The response to disrupting or overexpressing a TF is strongest on its direct targets and dissipates rapidly as it propagates through the network. Using S. cerevisiae data, we show that NetProphet can predict thousands of direct, functional regulatory interactions, using only gene expression data. The targets that NetProphet predicts for a TF are at least as likely to have sites matching the TF's binding specificity as the targets implicated by ChIP. Unlike most ChIP targets, the NetProphet targets also show evidence of functional regulation. This suggests a surprising conclusion: The best way to begin mapping direct, functional TF-promoter interactions may not be by measuring binding. We also show that NetProphet yields new insights into the functions of several yeast TFs, including a well-studied TF, Cbf1, and a completely unstudied TF, Eds1.

Interplay between chromatin state, regulator binding, and regulatory motifs in six human cell types

The regions bound by sequence-specific transcription factors can be highly variable across different cell types despite the static nature of the underlying genome sequence. This has been partly attributed to changes in chromatin accessibility, but a systematic picture has been hindered by the lack of large-scale data sets. Here, we use 456 binding experiments for 119 regulators and 84 chromatin maps generated by the ENCODE in six human cell types, and relate those to a global map of regulatory motif instances for these factors. We find specific and robust chromatin state preferences for each regulator beyond the previously reported open-chromatin association, suggesting a much richer chromatin landscape beyond simple accessibility. The preferentially bound chromatin states of regulators were enriched for sequence motifs of regulators relative to all states, suggesting that these preferences are at least partly encoded by the genomic sequence. Relative to all regions bound by a regulator, however, regulatory motifs were surprisingly depleted in the regulator's preferentially bound states, suggesting additional non-sequence-specific binding beyond the level predicted by the regulatory motifs. Such permissive binding was largely restricted to open-chromatin regions showing histone modification marks characteristic of active enhancer and promoter regions, whereas open-chromatin regions lacking such marks did not show permissive binding. Lastly, the vast majority of cobinding of regulator pairs is predicted by the chromatin state preferences of individual regulators. Overall, our results suggest a joint role of sequence motifs and specific chromatin states beyond mere accessibility in mediating regulator binding dynamics across different cell types.

Non-canonical protein-DNA interactions identified by ChIP are not artifacts

Background

ChIP-chip and ChIP-seq are widely used methods to map protein-DNA interactions on a genomic scale in vivo. Waldminghaus and Skarstad recently reported, in this journal, a modified method for ChIP-chip. Based on a comparison of our previously-published ChIP-chip data for Escherichia coli σ³² with their own data, Waldminghaus and Skarstad concluded that many of the σ³² targets identified in our earlier work are false positives. In particular, we identified many non-canonical σ³² targets that are located inside genes or are associated with genes that show no detectable regulation by σ³². Waldminghaus and Skarstad propose that such non-canonical sites are artifacts, identified due to flaws in the standard ChIP methodology. Waldminghaus and Skarstad suggest specific changes to the standard ChIP procedure that reportedly eliminate the claimed artifacts.

Results

We reanalyzed our published ChIP-chip datasets for σ³² and the datasets generated by Waldminghaus and Skarstad to assess data quality and reproducibility. We also performed targeted ChIP/qPCR for σ³² and an unrelated transcription factor, AraC, using the standard ChIP method and the modified ChIP method proposed by Waldminghaus and Skarstad. Furthermore, we determined the association of core RNA polymerase with disputed σ³² promoters, with and without overexpression of σ³². We show that (i) our published σ³² ChIP-chip datasets have a consistently higher dynamic range than those of Waldminghaus and Skarstad, (ii) our published σ³² ChIP-chip datasets are highly reproducible, whereas those of Waldminghaus and Skarstad are not, (iii) non-canonical σ³² target regions are enriched in a σ³² ChIP in a heat shock-dependent manner, regardless of the ChIP method used, (iv) association of core RNA polymerase with some disputed σ³² target genes is induced by overexpression of σ³², (v) σ³² targets disputed by Waldminghaus and Skarstad are predominantly those that are most weakly bound, and (vi) the modifications to the ChIP method proposed by Waldminghaus and Skarstad reduce enrichment of all protein-bound genomic regions.

Conclusions

The modifications to the ChIP-chip method suggested by Waldminghaus and Skarstad reduce rather than increase the quality of ChIP data. Hence, the non-canonical σ³² targets identified in our previous study are likely to be genuine. We propose that the failure of Waldminghaus and Skarstad to identify many of these σ³² targets is due predominantly to the lower data quality in their study. We conclude that surprising ChIP-chip results are not artifacts to be ignored, but rather indications that our understanding of DNA-binding proteins is incomplete.

The challenges of delivering bioinformatics training in the analysis of high-throughput data

High-throughput technologies are widely used in the field of functional genomics and used in an increasing number of applications. For many ‘wet lab’ scientists, the analysis of the large amount of data generated by such technologies is a major bottleneck that can only be overcome through very specialized training in advanced data analysis methodologies and the use of dedicated bioinformatics software tools. In this article, we wish to discuss the challenges related to delivering training in the analysis of high-throughput sequencing data and how we addressed these challenges in the hands-on training courses that we have developed at the European Bioinformatics Institute.

High-throughput chromatin immunoprecipitation for genome-wide mapping of in vivo protein-DNA interactions and epigenomic states

Dynamic protein binding to DNA elements regulates genome function and cell fate. Although methods for mapping in vivo protein-DNA interactions are becoming crucial for every aspect of genomic research, they are laborious and costly, thereby limiting progress. Here we present a protocol for mapping in vivo protein-DNA interactions using a high-throughput chromatin immunoprecipitation (HT-ChIP) approach. By using paramagnetic beads, we streamline the entire ChIP and indexed library construction process: sample transfer and loss is minimized and the need for manually labor-intensive procedures such as washes, gel extraction and DNA precipitation is eliminated. All of this allows for fully automated, cost effective and highly sensitive 96-well ChIP sequencing (ChIP-seq). Sample preparation takes 3 d from cultured cells to pooled libraries. Compared with previous methods, HT-ChIP is more suitable for large-scale in vivo studies, specifically those measuring the dynamics of a large number of different chromatin modifications/transcription factors or multiple perturbations.

Nuclear Factor I genomic binding associates with chromatin boundaries

Background

The Nuclear Factor I (NFI) family of DNA binding proteins (also called CCAAT box transcription factors or CTF) is involved in both DNA replication and gene expression regulation. Using chromatin immuno-precipitation and high throughput sequencing (ChIP-Seq), we performed a genome-wide mapping of NFI DNA binding sites in primary mouse embryonic fibroblasts.

Results

We found that in vivo and in vitro NFI DNA binding specificities are indistinguishable, as in vivo ChIP-Seq NFI binding sites matched predictions based on previously established position weight matrix models of its in vitro binding specificity. Combining ChIP-Seq with mRNA profiling data, we found that NFI preferentially associates with highly expressed genes that it up-regulates, while binding sites were under-represented at expressed but unregulated genes. Genomic binding also correlated with markers of transcribed genes such as histone modifications H3K4me3 and H3K36me3, even outside of annotated transcribed loci, implying NFI in the control of the deposition of these modifications. Positional correlation between + and - strand ChIP-Seq tags revealed that, in contrast to other transcription factors, NFI associates with a nucleosomal length of cleavage-resistant DNA, suggesting an interaction with positioned nucleosomes. In addition, NFI binding prominently occurred at boundaries displaying discontinuities in histone modifications specific of expressed and silent chromatin, such as loci submitted to parental allele-specific imprinted expression.

Conclusions

Our data thus suggest that NFI nucleosomal interaction may contribute to the partitioning of distinct chromatin domains and to epigenetic gene expression regulation.

NFI ChIP-Seq and input control DNA data were deposited at Gene Expression Omnibus (GEO) repository under accession number GSE15844. Gene expression microarray data for mouse embryonic fibroblasts are on GEO accession number GSE15871.

Molecular network of chromatin immunoprecipitation followed by deep sequencing-based vitamin D receptor target genes

BACKGROUND

Vitamin D is a liposoluble vitamin essential for calcium metabolism. The ligand-bound vitamin D receptor (VDR), heterodimerized with retinoid X receptor, interacts with vitamin D response elements (VDREs) to regulate gene expression. Vitamin D deficiency due to insufficient sunlight exposure confers an increased risk for multiple sclerosis (MS).

OBJECTIVE

To study a protective role of vitamin D in multiple sclerosis (MS), it is important to characterize the global molecular network of VDR target genes (VDRTGs) in immune cells.

METHODS

We identified genome-wide VDRTGs collectively from two distinct chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) datasets of VDR-binding sites derived from calcitriol-treated human cells of B cell and monocyte origins. We mapped short reads of next generation sequencing (NGS) data on hg19 with Bowtie, detected the peaks with Model-based Analysis of ChIP-Seq (MACS), and identified genomic locations by GenomeJack, a novel genome viewer for NGS platforms.

RESULTS

We found 2997 stringent peaks distributed on protein-coding genes, chiefly located in the promoter and the intron on VDRE DR3 sequences. However, the corresponding transcriptome data verified calcitriol-induced upregulation of only a small set of VDRTGs. The molecular network of 1541 calcitriol-responsive VDRTGs showed a significant relationship with leukocyte transendothelial migration, Fcγ receptor-mediated phagocytosis, and transcriptional regulation by VDR, suggesting a pivotal role of genome-wide VDRTGs in immune regulation.

CONCLUSION

These results suggest the working hypothesis that persistent deficiency of vitamin D might perturb the complex network of VDRTGs in immune cells, being responsible for induction of an autoimmune response causative for MS.

Toward mapping the biology of the genome

This issue of Genome Research presents new results, methods, and tools from The ENCODE Project (ENCyclopedia of DNA Elements), which collectively represents an important step in moving beyond a parts list of the genome and promises to shape the future of genomic research. This collection sheds light on basic biological questions and frames the current debate over the optimization of tools and methodological challenges necessary to compare and interpret large complex data sets focused on how the genome is organized and regulated. In a number of instances, the authors have highlighted the strengths and limitations of current computational and technical approaches, providing the community with useful standards, which should stimulate development of new tools. In many ways, these papers will ripple through the scientific community, as those in pursuit of understanding the “regulatory genome” will heavily traverse the maps and tools. Similarly, the work should have a substantive impact on how genetic variation contributes to specific diseases and traits by providing a compendium of functional elements for follow-up study. The success of these papers should not only be measured by the scope of the scientific insights and tools but also by their ability to attract new talent to mine existing and future data.

What does our genome encode?

In its first production phase, The ENCODE Project Consortium (ENCODE) has generated thousands of genome-scale data sets, resulting in a genomic “parts list” that encompasses transcripts, sites of transcription factor binding, and other functional features that now number in the millions of distinct elements. These data are reshaping many long-held beliefs concerning the information content of the human and other complex genomes, including the very definition of the gene. Here I discuss and place in context many of the leading findings of ENCODE, as well as trends that are shaping the generation and interpretation of ENCODE data. Finally, I consider prospects for the future, including maximizing the accuracy, completeness, and utility of ENCODE data for the community.

Sex-biased networks and nodes of sexually antagonistic conflict in Drosophila

Sexual antagonism, or conflict, can occur when males and females harbor opposing reproductive strategies. The large fraction of sex-biased genes in genomes present considerable opportunities for conflict to occur, suggesting that sexual antagonism may potentially be a general phenomenon at the molecular level. Here, we employ a novel strategy to identify potential nodes of sexual conflict in Drosophila melanogaster by coupling male, female, and sex-unbiased networks derived from genome-wide expression data with available genetic and protein interaction data. We find that sex-biased networks comprise a large fraction (~1/3) of the total interaction network with the male network possessing nearly twice the number of nodes (genes) relative to the female network. However, there are far less edges or interaction partners among male relative to female subnetworks as seen in their power law distributions. We further identified 598 sex-unbiased genes that can act as indirect nodes of interlocus sexual conflict as well as 271 direct nodal pairs of potential conflict between male- and female-biased genes. The pervasiveness of such potentially conflicting nodes may explain the rapid evolution of sex-biased as well as non-sex-biased genes via this molecular mechanism of sexual selection even among taxa such as Drosophila that are nominally sexually dimorphic.

MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing data

Motivation: Reliable estimation of the mean fragment length for next-generation short-read sequencing data is an important step in next-generation sequencing analysis pipelines, most notably because of its impact on the accuracy of the enriched regions identified by peak-calling algorithms. Although many peak-calling algorithms include a fragment-length estimation subroutine, the problem has not been adequately solved, as demonstrated by the variability of the estimates returned by different algorithms.

Results: In this article, we investigate the use of strand cross-correlation to estimate mean fragment length of single-end data and show that traditional estimation approaches have mixed reliability. We observe that the mappability of different parts of the genome can introduce an artificial bias into cross-correlation computations, resulting in incorrect fragment-length estimates. We propose a new approach, called mappability-sensitive cross-correlation (MaSC), which removes this bias and allows for accurate and reliable fragment-length estimation. We analyze the computational complexity of this approach, and evaluate its performance on a test suite of NGS datasets, demonstrating its superiority to traditional cross-correlation analysis.

Availability: An open-source Perl implementation of our approach is available at http://www.perkinslab.ca/Software.html.

Contact:tperkins@ohri.ca

Supplementary information:Supplementary data are available at Bioinformatics online.

ENCODE data in the UCSC Genome Browser: year 5 update

The Encyclopedia of DNA Elements (ENCODE), http://encodeproject.org, has completed its fifth year of scientific collaboration to create a comprehensive catalog of functional elements in the human genome, and its third year of investigations in the mouse genome. Since the last report in this journal, the ENCODE human data repertoire has grown by 898 new experiments (totaling 2886), accompanied by a major integrative analysis. In the mouse genome, results from 404 new experiments became available this year, increasing the total to 583, collected during the course of the project. The University of California, Santa Cruz, makes this data available on the public Genome Browser http://genome.ucsc.edu for visual browsing and data mining. Download of raw and processed data files are all supported. The ENCODE portal provides specialized tools and information about the ENCODE data sets.

The relationship between long-range chromatin occupancy and polymerization of the Drosophila ETS family transcriptional repressor Yan

ETS family transcription factors are evolutionarily conserved downstream effectors of Ras/MAPK signaling with critical roles in development and cancer. In Drosophila, the ETS repressor Yan regulates cell proliferation and differentiation in a variety of tissues; however, the mechanisms of Yan-mediated repression are not well understood and only a few direct target genes have been identified. Yan, like its human ortholog TEL1, self-associates through an N-terminal sterile α-motif (SAM), leading to speculation that Yan/TEL1 polymers may spread along chromatin to form large repressive domains. To test this hypothesis, we created a monomeric form of Yan by recombineering a point mutation that blocks SAM-mediated self-association into the yan genomic locus and compared its genome-wide chromatin occupancy profile to that of endogenous wild-type Yan. Consistent with the spreading model predictions, wild-type Yan-bound regions span multiple kilobases. Extended occupancy patterns appear most prominent at genes encoding crucial developmental regulators and signaling molecules and are highly conserved between Drosophila melanogaster and D. virilis, suggesting functional relevance. Surprisingly, although occupancy is reduced, the Yan monomer still makes extensive multikilobase contacts with chromatin, with an overall pattern similar to that of wild-type Yan. Despite its near-normal chromatin recruitment, the repressive function of the Yan monomer is significantly impaired, as evidenced by elevated target gene expression and failure to rescue a yan null mutation. Together our data argue that SAM-mediated polymerization contributes to the functional output of the active Yan repressive complexes that assemble across extended stretches of chromatin, but does not directly mediate recruitment to DNA or chromatin spreading.

STAR: ultrafast universal RNA-seq aligner

MOTIVATION

Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases.

RESULTS

To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy.

AVAILABILITY AND IMPLEMENTATION

STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

ChIP-seq and beyond: new and improved methodologies to detect and characterize protein-DNA interactions

Chromatin immunoprecipitation experiments followed by sequencing (ChIP-seq) detect protein-DNA binding events and chemical modifications of histone proteins. Challenges in the standard ChIP-seq protocol have motivated recent enhancements in this approach, such as reducing the number of cells that are required and increasing the resolution. Complementary experimental approaches - for example, DNaseI hypersensitive site mapping and analysis of chromatin interactions that are mediated by particular proteins - provide additional information about DNA-binding proteins and their function. These data are now being used to identify variability in the functions of DNA-binding proteins across genomes and individuals. In this Review, I describe the latest advances in methods to detect and functionally characterize DNA-bound proteins.

An integrated encyclopedia of DNA elements in the human genome

The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.