Sole-Search: an integrated analysis program for peak detection and functional annotation using ChIP-seq data

Graph-Based Integration of Histone Modification Profiles

In this work, we introduce a similarity-network-based approach to explore the role of interacting single-cell histone modification signals in haematopoiesis—the process of differentiation of blood cells. Histones are proteins that provide structural support to chromosomes. They are subject to chemical modifications—acetylation or methylation—that affect the degree of accessibility of genes and, in turn, the formation of different phenotypes. The concentration of histone modifications can be modelled as a continuous signal, which can be used to build single-cell profiles. In the present work, the profiles of cell types involved in haematopoiesis are built based on all the major histone modifications (i.e., H3K27ac, H3K27me3, H3K36me3, H3K4me1, H3K4me3, H3K9me3) by counting the number of peaks in the modification signals; then, the profiles are used to compute modification-specific similarity networks among the considered phenotypes. As histone modifications come as interacting signals, we applied a similarity network fusion technique to integrate these networks in a unique graph, with the aim of studying the simultaneous effect of all the modifications for the determination of different phenotypes. The networks permit defining of a graph-cut-based separation score for evaluating the homogeneity of subgroups of cell types corresponding to the myeloid and lymphoid phenotypes in the classical representation of the haematopoietic tree. Resulting scores show that separation into myeloid and lymphoid phenotypes reflects the actual process of haematopoiesis.

HERON: A Novel Tool Enables Identification of Long, Weakly Enriched Genomic Domains in ChIP-seq Data

The explosive development of next-generation sequencing-based technologies has allowed us to take an unprecedented look at many molecular signatures of the non-coding genome. In particular, the ChIP-seq (Chromatin ImmunoPrecipitation followed by sequencing) technique is now very commonly used to assess the proteins associated with different non-coding DNA regions genome-wide. While the analysis of such data related to transcription factor binding is relatively straightforward, many modified histone variants, such as H3K27me3, are very important for the process of gene regulation but are very difficult to interpret. We propose a novel method, called HERON (HiddEn MaRkov mOdel based peak calliNg), for genome-wide data analysis that is able to detect DNA regions enriched for a certain feature, even in difficult settings of weakly enriched long DNA domains. We demonstrate the performance of our method both on simulated and experimental data.

AnnoMiner is a new web-tool to integrate epigenetics, transcription factor occupancy and transcriptomics data to predict transcriptional regulators

Gene expression regulation requires precise transcriptional programs, led by transcription factors in combination with epigenetic events. Recent advances in epigenomic and transcriptomic techniques provided insight into different gene regulation mechanisms. However, to date it remains challenging to understand how combinations of transcription factors together with epigenetic events control cell-type specific gene expression. We have developed the AnnoMiner web-server, an innovative and flexible tool to annotate and integrate epigenetic, and transcription factor occupancy data. First, AnnoMiner annotates user-provided peaks with gene features. Second, AnnoMiner can integrate genome binding data from two different transcriptional regulators together with gene features. Third, AnnoMiner offers to explore the transcriptional deregulation of genes nearby, or within a specified genomic region surrounding a user-provided peak. AnnoMiner’s fourth function performs transcription factor or histone modification enrichment analysis for user-provided gene lists by utilizing hundreds of public, high-quality datasets from ENCODE for the model organisms human, mouse, Drosophila and C. elegans. Thus, AnnoMiner can predict transcriptional regulators for a studied process without the strict need for chromatin data from the same process. We compared AnnoMiner to existing tools and experimentally validated several transcriptional regulators predicted by AnnoMiner to indeed contribute to muscle morphogenesis in Drosophila. AnnoMiner is freely available at http://chimborazo.ibdm.univ-mrs.fr/AnnoMiner/.

Facilitating Analysis of Publicly Available ChIP-Seq Data for Integrative Studies

ChIP-Seq, a technique that allows for quantification of DNA sequences bound by transcription factors or histones, has been widely used to characterize genome-wide DNA-protein binding at baseline and induced by specific exposures. Integrating results of multiple ChIP-Seq datasets is a convenient approach to identify robust DNA- protein binding sites and determine their cell-type specificity. We developed brocade, a computational pipeline for reproducible analysis of publicly available ChIP-Seq data that creates R markdown reports containing information on datasets downloaded, quality control metrics, and differential binding results. Glucocorticoids are commonly used anti-inflammatory drugs with tissue-specific effects that are not fully understood. We demonstrate the utility of brocade via the analysis of five ChIP-Seq datasets involving glucocorticoid receptor (GR), a transcription factor that mediates glucocorticoid response, to identify cell type-specific and shared GR binding sites across the five cell types. Our results show that brocade facilitates analysis of individual ChIP-Seq datasets and comparative studies involving multiple datasets.

Three-dimensional analysis reveals altered chromatin interaction by enhancer inhibitors harbors TCF7L2-regulated cancer gene signature

Distal regulatory elements influence the activity of gene promoters through chromatin looping. Chromosome conformation capture (3C) methods permit identification of chromatin contacts across different regions of the genome. However, due to limitations in the resolution of these methods, the detection of functional chromatin interactions remains a challenge. In the current study, we employ an integrated approach to define and characterize the functional chromatin contacts of human pancreatic cancer cells. We applied tethered chromatin capture to define classes of chromatin domains on a genome-wide scale. We identified three types of structural domains (topologically associated, boundary, and gap) and investigated the functional relationships of these domains with respect to chromatin state and gene expression. We uncovered six distinct sub-domains associated with epigenetic states. Interestingly, specific epigenetically active domains are sensitive to treatment with histone acetyltransferase (HAT) inhibitors and decrease in H3K27 acetylation levels. To examine whether the subdomains that change upon drug treatment are functionally linked to transcription factor regulation, we compared TCF7L2 chromatin binding and gene regulation to HAT inhibition. We identified a subset of coding RNA genes that together can stratify pancreatic cancer patients into distinct survival groups. Overall, this study describes a process to evaluate the functional features of chromosome architecture and reveals the impact of epigenetic inhibitors on chromosome architecture and identifies genes that may provide insight into disease outcome.

GLANET: genomic loci annotation and enrichment tool

Motivation

Genomic studies identify genomic loci representing genetic variations, transcription factor (TF) occupancy, or histone modification through next generation sequencing (NGS) technologies. Interpreting these loci requires evaluating them with known genomic and epigenomic annotations.

Results

We present GLANET as a comprehensive annotation and enrichment analysis tool which implements a sampling-based enrichment test that accounts for GC content and/or mappability biases, jointly or separately. GLANET annotates and performs enrichment analysis on these loci with a rich library. We introduce and perform novel data-driven computational experiments for assessing the power and Type-I error of its enrichment procedure which show that GLANET has attained high statistical power and well-controlled Type-I error rate. As a key feature, users can easily extend its library with new gene sets and genomic intervals. Other key features include assessment of impact of single nucleotide variants (SNPs) on TF binding sites and regulation based pathway enrichment analysis.

Availability and implementation

GLANET can be run using its GUI or on command line. GLANET's source code is available at https://github.com/burcakotlu/GLANET . Tutorials are provided at https://glanet.readthedocs.org .

Contact

burcak@ceng.metu.edu.tr or oznur.tastan@cs.bilkent.edu.tr.

Supplementary information

Supplementary data are available at Bioinformatics online.

Identification of Plagl1/Zac1 binding sites and target genes establishes its role in the regulation of extracellular matrix genes and the imprinted gene network

PLAGL1/ZAC1 undergoes parental genomic imprinting, is paternally expressed, and is a member of the imprinted gene network (IGN). It encodes a zinc finger transcription factor with anti-proliferative activity and is a candidate tumor suppressor gene on 6q24 whose expression is frequently lost in various neoplasms. Conversely, gain of PLAGL1 function is responsible for transient neonatal diabetes mellitus, a rare genetic disease that results from defective pancreas development. In the present work, we showed that Plagl1 up-regulation was not associated with DNA damage-induced cell cycle arrest. It was rather associated with physiological cell cycle exit that occurred with contact inhibition, growth factor withdrawal, or cell differentiation. To gain insights into Plagl1 mechanism of action, we identified Plagl1 target genes by combining chromatin immunoprecipitation and genome-wide transcriptomics in transfected cell lines. Plagl1-elicited gene regulation correlated with multiple binding to the proximal promoter region through a GC-rich motif. Plagl1 target genes included numerous genes involved in signaling, cell adhesion, and extracellular matrix composition, including collagens. Plagl1 targets also included 22% of the 409 genes that make up the IGN. Altogether, this work identified Plagl1 as a transcription factor that coordinated the regulation of a subset of IGN genes and controlled extracellular matrix composition.

DNA methylation-based chromatin compartments and ChIP-seq profiles reveal transcriptional drivers of prostate carcinogenesis

BACKGROUND

Profiles of DNA methylation of many tissues relevant in human disease have been obtained from microarrays and are publicly available. These can be used to generate maps of chromatin compartmentalization, demarcating open and closed chromatin across the genome. Additionally, large sets of genome-wide transcription factor binding profiles have been made available thanks to ChIP-seq technology.

METHODS

We have identified genomic regions with altered chromatin compartmentalization in prostate adenocarcinoma tissue relative to normal prostate tissue, using DNA methylation microarray data from The Cancer Genome Atlas. DNA binding profiles from the Encyclopedia of DNA Elements (ENCODE) ChIP-seq studies have been systematically screened to find transcription factors with inferred DNA binding sites located in discordantly open/closed chromatin in malignant tissue (compared with non-cancer control tissue). We have combined this with tests for corresponding up-/downregulation of the transcription factors' putative target genes to obtain an integrated measure of cancer-specific regulatory activity to identify likely transcriptional drivers of prostate cancer.

RESULTS

Generally, we find that the degree to which transcription factors preferentially bind regions of chromatin that become more accessible during prostate carcinogenesis is significantly associated to the level of systematic upregulation of their targets, at the level of gene expression. Our approach has yielded 11 transcription factors that show strong cancer-specific transcriptional activation of targets, including the novel candidates KAT2A and TRIM28, alongside established drivers of prostate cancer MYC, ETS1, GABP and YY1.

CONCLUSIONS

This approach to integrated epigenetic and transcriptional profiling using publicly available data represents a cheap and powerful technique for identifying potential drivers of human disease. In our application to prostate adenocarcinoma data, the fact that well-known drivers are amongst the top candidates suggests that the discovery of novel candidate drivers may unlock pathways to future medicines. Data download instructions and code to reproduce this work are available at GitHub under 'edcurry/PRAD-compartments'.

Features that define the best ChIP-seq peak calling algorithms

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is an important tool for studying gene regulatory proteins, such as transcription factors and histones. Peak calling is one of the first steps in the analysis of these data. Peak calling consists of two sub-problems: identifying candidate peaks and testing candidate peaks for statistical significance. We surveyed 30 methods and identified 12 features of the two sub-problems that distinguish methods from each other. We picked six methods GEM, MACS2, MUSIC, BCP, Threshold-based method (TM) and ZINBA] that span this feature space and used a combination of 300 simulated ChIP-seq data sets, 3 real data sets and mathematical analyses to identify features of methods that allow some to perform better than the others. We prove that methods that explicitly combine the signals from ChIP and input samples are less powerful than methods that do not. Methods that use windows of different sizes are more powerful than the ones that do not. For statistical testing of candidate peaks, methods that use a Poisson test to rank their candidate peaks are more powerful than those that use a Binomial test. BCP and MACS2 have the best operating characteristics on simulated transcription factor binding data. GEM has the highest fraction of the top 500 peaks containing the binding motif of the immunoprecipitated factor, with 50% of its peaks within 10 base pairs of a motif. BCP and MUSIC perform best on histone data. These findings provide guidance and rationale for selecting the best peak caller for a given application.

Characterizing Genetic Susceptibility to Breast Cancer in Women of African Ancestry

Background: Genome-wide association studies have identified approximately 100 common genetic variants associated with breast cancer risk, the majority of which were discovered in women of European ancestry. Because of different patterns of linkage disequilibrium, many of these genetic markers may not represent signals in populations of African ancestry.Methods: We tested 74 breast cancer risk variants and conducted fine-mapping of these susceptibility regions in 6,522 breast cancer cases and 7,643 controls of African ancestry from three genetic consortia (AABC, AMBER, and ROOT).Results: Fifty-four of the 74 variants (73%) were found to have ORs that were directionally consistent with those previously reported, of which 12 were nominally statistically significant (P < 0.05). Through fine-mapping, in six regions (3p24, 12p11, 14q13, 16q12/FTO, 16q23, 19p13), we observed seven markers that better represent the underlying risk variant for overall breast cancer or breast cancer subtypes, whereas in another two regions (11q13, 16q12/TOX3), we identified suggestive evidence of signals that are independent of the reported index variant. Overlapping chromatin features and regulatory elements suggest that many of the risk alleles lie in regions with biological functionality.Conclusions: Through fine-mapping of known susceptibility regions, we have revealed alleles that better characterize breast cancer risk in women of African ancestry.Impact: The risk alleles identified represent genetic markers for modeling and stratifying breast cancer risk in women of African ancestry. Cancer Epidemiol Biomarkers Prev; 26(7); 1016-26. ©2017 AACR.

ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline

BACKGROUND

Transcription factor binding, histone modification, and chromatin accessibility studies are important approaches to understanding the biology of gene regulation. ChIP-seq and DNase-seq have become the standard techniques for studying protein-DNA interactions and chromatin accessibility respectively, and comprehensive quality control (QC) and analysis tools are critical to extracting the most value from these assay types. Although many analysis and QC tools have been reported, few combine ChIP-seq and DNase-seq data analysis and quality control in a unified framework with a comprehensive and unbiased reference of data quality metrics.

RESULTS

ChiLin is a computational pipeline that automates the quality control and data analyses of ChIP-seq and DNase-seq data. It is developed using a flexible and modular software framework that can be easily extended and modified. ChiLin is ideal for batch processing of many datasets and is well suited for large collaborative projects involving ChIP-seq and DNase-seq from different designs. ChiLin generates comprehensive quality control reports that include comparisons with historical data derived from over 23,677 public ChIP-seq and DNase-seq samples (11,265 datasets) from eight literature-based classified categories. To the best of our knowledge, this atlas represents the most comprehensive ChIP-seq and DNase-seq related quality metric resource currently available. These historical metrics provide useful heuristic quality references for experiment across all commonly used assay types. Using representative datasets, we demonstrate the versatility of the pipeline by applying it to different assay types of ChIP-seq data. The pipeline software is available open source at https://github.com/cfce/chilin .

CONCLUSION

ChiLin is a scalable and powerful tool to process large batches of ChIP-seq and DNase-seq datasets. The analysis output and quality metrics have been structured into user-friendly directories and reports. We have successfully compiled 23,677 profiles into a comprehensive quality atlas with fine classification for users.

Wnt-signalling pathways and microRNAs network in carcinogenesis: experimental and bioinformatics approaches

Over the past few years, microRNAs (miRNAs) have not only emerged as integral regulators of gene expression at the post-transcriptional level but also respond to signalling molecules to affect cell function(s). miRNAs crosstalk with a variety of the key cellular signalling networks such as Wnt, transforming growth factor-β and Notch, control stem cell activity in maintaining tissue homeostasis, while if dysregulated contributes to the initiation and progression of cancer. Herein, we overview the molecular mechanism(s) underlying the crosstalk between Wnt-signalling components (canonical and non-canonical) and miRNAs, as well as changes in the miRNA/Wnt-signalling components observed in the different forms of cancer. Furthermore, the fundamental understanding of miRNA-mediated regulation of Wnt-signalling pathway and vice versa has been significantly improved by high-throughput genomics and bioinformatics technologies. Whilst, these approaches have identified a number of specific miRNA(s) that function as oncogenes or tumour suppressors, additional analyses will be necessary to fully unravel the links among conserved cellular signalling pathways and miRNAs and their potential associated components in cancer, thereby creating therapeutic avenues against tumours. Hence, we also discuss the current challenges associated with Wnt-signalling/miRNAs complex and the analysis using the biomedical experimental and bioinformatics approaches.

An Integrated Analysis of MicroRNA and mRNA Expression Profiles to Identify RNA Expression Signatures in Lambskin Hair Follicles in Hu Sheep

Wave patterns in lambskin hair follicles are an important factor determining the quality of sheep’s wool. Hair follicles in lambskin from Hu sheep, a breed unique to China, have 3 types of waves, designated as large, medium, and small. The quality of wool from small wave follicles is excellent, while the quality of large waves is considered poor. Because no molecular and biological studies on hair follicles of these sheep have been conducted to date, the molecular mechanisms underlying the formation of different wave patterns is currently unknown. The aim of this article was to screen the candidate microRNAs (miRNA) and genes for the development of hair follicles in Hu sheep. Two-day-old Hu lambs were selected from full-sib individuals that showed large, medium, and small waves. Integrated analysis of microRNA and mRNA expression profiles employed high-throughout sequencing technology. Approximately 13, 24, and 18 differentially expressed miRNAs were found between small and large waves, small and medium waves, and medium and large waves, respectively. A total of 54, 190, and 81 differentially expressed genes were found between small and large waves, small and medium waves, and medium and large waves, respectively, by RNA sequencing (RNA-seq) analysis. Differentially expressed genes were classified using gene ontology and pathway analyses. They were found to be mainly involved in cell differentiation, proliferation, apoptosis, growth, immune response, and ion transport, and were associated with MAPK and the Notch signaling pathway. Reverse transcription-polymerase chain reaction (RT-PCR) analyses of differentially-expressed miRNA and genes were consistent with sequencing results. Integrated analysis of miRNA and mRNA expression indicated that, compared to small waves, large waves included 4 downregulated miRNAs that had regulatory effects on 8 upregulated genes and 3 upregulated miRNAs, which in turn influenced 13 downregulated genes. Compared to small waves, medium waves included 13 downregulated miRNAs that had regulatory effects on 64 upregulated genes and 4 upregulated miRNAs, which in turn had regulatory effects on 22 downregulated genes. Compared to medium waves, large waves consisted of 13 upregulated miRNAs that had regulatory effects on 48 downregulated genes. These differentially expressed miRNAs and genes may play a significant role in forming different patterns, and provide evidence for the molecular mechanisms underlying the formation of hair follicles of varying patterns.

Reusable, extensible, and modifiable R scripts and Kepler workflows for comprehensive single set ChIP-seq analysis

Background

There has been an enormous expansion of use of chromatin immunoprecipitation followed by sequencing (ChIP-seq) technologies. Analysis of large-scale ChIP-seq datasets involves a complex series of steps and production of several specialized graphical outputs. A number of systems have emphasized custom development of ChIP-seq pipelines. These systems are primarily based on custom programming of a single, complex pipeline or supply libraries of modules and do not produce the full range of outputs commonly produced for ChIP-seq datasets. It is desirable to have more comprehensive pipelines, in particular ones addressing common metadata tasks, such as pathway analysis, and pipelines producing standard complex graphical outputs. It is advantageous if these are highly modular systems, available as both turnkey pipelines and individual modules, that are easily comprehensible, modifiable and extensible to allow rapid alteration in response to new analysis developments in this growing area. Furthermore, it is advantageous if these pipelines allow data provenance tracking.

Results

We present a set of 20 ChIP-seq analysis software modules implemented in the Kepler workflow system; most (18/20) were also implemented as standalone, fully functional R scripts. The set consists of four full turnkey pipelines and 16 component modules. The turnkey pipelines in Kepler allow data provenance tracking. Implementation emphasized use of common R packages and widely-used external tools (e.g., MACS for peak finding), along with custom programming. This software presents comprehensive solutions and easily repurposed code blocks for ChIP-seq analysis and pipeline creation. Tasks include mapping raw reads, peakfinding via MACS, summary statistics, peak location statistics, summary plots centered on the transcription start site (TSS), gene ontology, pathway analysis, and de novo motif finding, among others.

Conclusions

These pipelines range from those performing a single task to those performing full analyses of ChIP-seq data. The pipelines are supplied as both Kepler workflows, which allow data provenance tracking, and, in the majority of cases, as standalone R scripts. These pipelines are designed for ease of modification and repurposing.

Misregulation of Alternative Splicing in a Mouse Model of Rett Syndrome

Mutations in the human MECP2 gene cause Rett syndrome (RTT), a severe neurodevelopmental disorder that predominantly affects girls. Despite decades of work, the molecular function of MeCP2 is not fully understood. Here we report a systematic identification of MeCP2-interacting proteins in the mouse brain. In addition to transcription regulators, we found that MeCP2 physically interacts with several modulators of RNA splicing, including LEDGF and DHX9. These interactions are disrupted by RTT causing mutations, suggesting that they may play a role in RTT pathogenesis. Consistent with the idea, deep RNA sequencing revealed misregulation of hundreds of splicing events in the cortex of Mecp2 knockout mice. To reveal the functional consequence of altered RNA splicing due to the loss of MeCP2, we focused on the regulation of the splicing of the flip/flop exon of Gria2 and other AMPAR genes. We found a significant splicing shift in the flip/flop exon toward the flop inclusion, leading to a faster decay in the AMPAR gated current and altered synaptic transmission. In summary, our study identified direct physical interaction between MeCP2 and splicing factors, a novel MeCP2 target gene, and established functional connection between a specific RNA splicing change and synaptic phenotypes in RTT mice. These results not only help our understanding of the molecular function of MeCP2, but also reveal potential drug targets for future therapies.

Rett syndrome (RTT) is a debilitating neurodevelopmental disorder with no cure or effective treatment. To fully understand the disease mechanism and develop therapies, it is necessary to study all aspects of the molecular function of methyl-CpG binding protein 2 (MeCP2), mutations in which have been identified as the genetic cause of RTT. Over the years, MeCP2 has been shown to maintain DNA methylation, regulate transcription and chromatin structure, control microRNA processing, and modulate RNA splicing. Among these known functions, the role of MeCP2 in modulating RNA splicing is less well understood. We took several unbiased approaches to investigate the how MeCP2 may regulate splicing, what splicing changes are caused by the loss of MeCP2, and what functional consequences are caused by altered splicing. We discovered that MeCP2 interacts with splicing factors to regulated the splicing of glutamate receptor genes, which mediate the vast majority of excitatory synaptic transmission in the brain; and linked the altered splicing of glutamate receptor genes to specific synaptic changes in a RTT mouse model. Our findings not only advance the understanding of RTT disease mechanism, but also reveal a potential drug target for future development of therapies.

Effects on the transcriptome upon deletion of a distal element cannot be predicted by the size of the H3K27Ac peak in human cells

Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with increased risk for colorectal cancer (CRC). A molecular understanding of the functional consequences of this genetic variation is complicated because most GWAS SNPs are located in non-coding regions. We used epigenomic information to identify H3K27Ac peaks in HCT116 colon cancer cells that harbor SNPs associated with an increased risk for CRC. Employing CRISPR/Cas9 nucleases, we deleted a CRC risk-associated H3K27Ac peak from HCT116 cells and observed large-scale changes in gene expression, resulting in decreased expression of many nearby genes. As a comparison, we showed that deletion of a robust H3K27Ac peak not associated with CRC had minimal effects on the transcriptome. Interestingly, although there is no H3K27Ac peak in HEK293 cells in the E7 region, deletion of this region in HEK293 cells decreased expression of several of the same genes that were downregulated in HCT116 cells, including the MYC oncogene. Accordingly, deletion of E7 causes changes in cell culture assays in HCT116 and HEK293 cells. In summary, we show that effects on the transcriptome upon deletion of a distal regulatory element cannot be predicted by the size or presence of an H3K27Ac peak.

Global analysis of transcription factor-binding sites in yeast using ChIP-Seq

Transcription factors influence gene expression through their ability to bind DNA at specific regulatory elements. Specific DNA-protein interactions can be isolated through the chromatin immunoprecipitation (ChIP) procedure, in which DNA fragments bound by the protein of interest are recovered. ChIP is followed by high-throughput DNA sequencing (Seq) to determine the genomic provenance of ChIP DNA fragments and their relative abundance in the sample. This chapter describes a ChIP-Seq strategy adapted for budding yeast to enable the genome-wide characterization of binding sites of transcription factors (TFs) and other DNA-binding proteins in an efficient and cost-effective way.Yeast strains with epitope-tagged TFs are most commonly used for ChIP-Seq, along with their matching untagged control strains. The initial step of ChIP involves the cross-linking of DNA and proteins. Next, yeast cells are lysed and sonicated to shear chromatin into smaller fragments. An antibody against an epitope-tagged TF is used to pull down chromatin complexes containing DNA and the TF of interest. DNA is then purified and proteins degraded. Specific barcoded adapters for multiplex DNA sequencing are ligated to ChIP DNA. Short DNA sequence reads (28-36 base pairs) are parsed according to the barcode and aligned against the yeast reference genome, thus generating a nucleotide-resolution map of transcription factor-binding sites and their occupancy.

FEATnotator: A tool for integrated annotation of sequence features and variation, facilitating interpretation in genomics experiments

As approaches are sought for more efficient and democratized uses of non-model and expanded model genomics references, ease of integration of genomic feature datasets is especially desirable in multidisciplinary research communities. Valuable conclusions are often missed or slowed when researchers refer experimental results to a single reference sequence that lacks integrated pan-genomic and multi-experiment data in accessible formats. Association of genomic positional information, such as results from an expansive variety of next-generation sequencing experiments, with annotated reference features such as genes or predicted protein binding sites, provides the context essential for conclusions and ongoing research. When the experimental system includes polymorphic genomic inputs, rapid calculation of gene structural and protein translational effects of sequence variation from the reference can be invaluable. Here we present FEATnotator, a lightweight, fast and easy to use open source software program that integrates and reports overlap and proximity in genomic information from any user-defined datasets including those from next generation sequencing applications. We illustrate use of the tool by summarizing whole genome sequence variation of a widely used natural isolate of Arabidopsis thaliana in the context of gene models of the reference accession. Previous discovery of a protein coding deletion influencing root development is replicated rapidly. Appropriate even in investigations of a single gene or genic regions such as QTL, comprehensive reports provided by FEATnotator better prepare researchers for interpretation of their experimental results. The tool is available for download at http://featnotator.sourceforge.net.

Global transcriptome and chromatin occupancy analysis reveal the short isoform of GATA1 is deficient for erythroid specification and gene expression

GATA1 is a master transcriptional regulator of the differentiation of several related myeloid blood cell types, including erythrocytes and megakaryocytes. Germ-line mutations that cause loss of full length GATA1, but allow for expression of the short isoform (GATA1s), are associated with defective erythropoiesis in a subset of patients with Diamond Blackfan Anemia. Despite extensive studies of GATA1s in megakaryopoiesis, the mechanism by which GATA1s fails to support normal erythropoiesis is not understood. In this study, we used global gene expression and chromatin occupancy analysis to compare the transcriptional activity of GATA1s to GATA1. We discovered that compared to GATA1, GATA1s is less able to activate the erythroid gene expression program and terminal differentiation in cells with dual erythroid-megakaryocytic differentiation potential. Moreover, we found that GATA1s bound to many of its erythroid-specific target genes less efficiently than full length GATA1. These results suggest that the impaired ability of GATA1s to promote erythropoiesis in DBA may be caused by failure to occupy erythroid-specific gene regulatory elements.

A novel role for the Pol I transcription factor UBTF in maintaining genome stability through the regulation of highly transcribed Pol II genes

Mechanisms to coordinate programs of highly transcribed genes required for cellular homeostasis and growth are unclear. Upstream binding transcription factor (UBTF, also called UBF) is thought to function exclusively in RNA polymerase I (Pol I)-specific transcription of the ribosomal genes. Here, we report that the two isoforms of UBTF (UBTF1/2) are also enriched at highly expressed Pol II-transcribed genes throughout the mouse genome. Further analysis of UBTF1/2 DNA binding in immortalized human epithelial cells and their isogenically matched transformed counterparts reveals an additional repertoire of UBTF1/2-bound genes involved in the regulation of cell cycle checkpoints and DNA damage response. As proof of a functional role for UBTF1/2 in regulating Pol II transcription, we demonstrate that UBTF1/2 is required for recruiting Pol II to the highly transcribed histone gene clusters and for their optimal expression. Intriguingly, lack of UBTF1/2 does not affect chromatin marks or nucleosome density at histone genes. Instead, it results in increased accessibility of the histone promoters and transcribed regions to micrococcal nuclease, implicating UBTF1/2 in mediating DNA accessibility. Unexpectedly, UBTF2, which does not function in Pol I transcription, is sufficient to regulate histone gene expression in the absence of UBTF1. Moreover, depletion of UBTF1/2 and subsequent reduction in histone gene expression is associated with DNA damage and genomic instability independent of Pol I transcription. Thus, we have uncovered a novel role for UBTF1 and UBTF2 in maintaining genome stability through coordinating the expression of highly transcribed Pol I (UBTF1 activity) and Pol II genes (UBTF2 activity).

In silico pooling of ChIP-seq control experiments

As next generation sequencing technologies are becoming more economical, large-scale ChIP-seq studies are enabling the investigation of the roles of transcription factor binding and epigenome on phenotypic variation. Studying such variation requires individual level ChIP-seq experiments. Standard designs for ChIP-seq experiments employ a paired control per ChIP-seq sample. Genomic coverage for control experiments is often sacrificed to increase the resources for ChIP samples. However, the quality of ChIP-enriched regions identifiable from a ChIP-seq experiment depends on the quality and the coverage of the control experiments. Insufficient coverage leads to loss of power in detecting enrichment. We investigate the effect of in silico pooling of control samples within multiple biological replicates, multiple treatment conditions, and multiple cell lines and tissues across multiple datasets with varying levels of genomic coverage. Our computational studies suggest guidelines for performing in silico pooling of control experiments. Using vast amounts of ENCODE data, we show that pairwise correlations between control samples originating from multiple biological replicates, treatments, and cell lines/tissues can be grouped into two classes representing whether or not in silico pooling leads to power gain in detecting enrichment between the ChIP and the control samples. Our findings have important implications for multiplexing samples.

Functional annotation of colon cancer risk SNPs

Colorectal cancer (CRC) is a leading cause of cancer-related deaths in the United States. Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with increased risk for CRC. A molecular understanding of the functional consequences of this genetic variation has been complicated because each GWAS SNP is a surrogate for hundreds of other SNPs, most of which are located in non-coding regions. Here we use genomic and epigenomic information to test the hypothesis that the GWAS SNPs and/or correlated SNPs are in elements that regulate gene expression, and identify 23 promoters and 28 enhancers. Using gene expression data from normal and tumour cells, we identify 66 putative target genes of the risk-associated enhancers (10 of which were also identified by promoter SNPs). Employing CRISPR nucleases, we delete one risk-associated enhancer and identify genes showing altered expression. We suggest that similar studies be performed to characterize all CRC risk-associated enhancers.

Previous studies identified genetic variants associated with colorectal cancer (CRC), but the functional consequences of these genetic risk factors remain poorly understood. Here, the authors report that CRC risk variants reside in promoters and enhancers and could increase colon cancer risk through gene expression regulation.

Global loss of DNA methylation uncovers intronic enhancers in genes showing expression changes

BACKGROUND

Gene expression is epigenetically regulated by a combination of histone modifications and methylation of CpG dinucleotides in promoters. In normal cells, CpG-rich promoters are typically unmethylated, marked with histone modifications such as H3K4me3, and are highly active. During neoplastic transformation, CpG dinucleotides of CG-rich promoters become aberrantly methylated, corresponding with the removal of active histone modifications and transcriptional silencing. Outside of promoter regions, distal enhancers play a major role in the cell type-specific regulation of gene expression. Enhancers, which function by bringing activating complexes to promoters through chromosomal looping, are also modulated by a combination of DNA methylation and histone modifications.

RESULTS

Here we use HCT116 colorectal cancer cells with and without mutations in DNA methyltransferases, the latter of which results in a 95% reduction in global DNA methylation levels. These cells are used to study the relationship between DNA methylation, histone modifications, and gene expression. We find that the loss of DNA methylation is not sufficient to reactivate most of the silenced promoters. In contrast, the removal of DNA methylation results in the activation of a large number of enhancer regions as determined by the acquisition of active histone marks.

CONCLUSIONS

Although the transcriptome is largely unaffected by the loss of DNA methylation, we identify two distinct mechanisms resulting in the upregulation of distinct sets of genes. One is a direct result of DNA methylation loss at a set of promoter regions and the other is due to the presence of new intragenic enhancers.

Bipartite recognition of DNA by TCF/Pangolin is remarkably flexible and contributes to transcriptional responsiveness and tissue specificity of wingless signaling

The T-cell factor (TCF) family of transcription factors are major mediators of Wnt/β-catenin signaling in metazoans. All TCFs contain a High Mobility Group (HMG) domain that possesses specific DNA binding activity. In addition, many TCFs contain a second DNA binding domain, the C-clamp, which binds to DNA motifs referred to as Helper sites. While HMG and Helper sites are both important for the activation of several Wnt dependent cis-regulatory modules (W-CRMs), the rules of what constitutes a functional HMG-Helper site pair are unknown. In this report, we employed a combination of in vitro binding, reporter gene analysis and bioinformatics to address this question, using the Drosophila family member TCF/Pangolin (TCF/Pan) as a model. We found that while there were constraints for the orientation and spacing of HMG-Helper pairs, the presence of a Helper site near a HMG site in any orientation increased binding and transcriptional response, with some orientations displaying tissue-specific patterns. We found that altering an HMG-Helper site pair from a sub-optimal to optimal orientation/spacing dramatically increased the responsiveness of a W-CRM in several fly tissues. In addition, we used the knowledge gained to bioinformatically identify two novel W-CRMs, one that was activated by Wnt/β-catenin signaling in the prothoracic gland, a tissue not previously connected to this pathway. In sum, this work extends the importance of Helper sites in fly W-CRMs and suggests that the type of HMG-Helper pair is a major factor in setting the threshold for Wnt activation and tissue-responsiveness.

Regulation of gene expression is controlled in large part by proteins known as transcription factors, which bind to specific DNA sequences in the genome. The DNA binding domains of transcription factors recognize short stretches (5–11 base pairs) of DNA with considerable sequence degeneracy. This means that a single DNA binding domain, on its own, cannot find its targets in the vast excess of genomic sequence. We are studying this question using TCF/Pangolin, a Drosophila transcription factor that mediates Wnt/β-catenin signaling, an important developmental cell-cell communication pathway. TCF/Pangolin contains two DNA binding domains that bind to a pair of DNA motifs known as HMG and Helper sites. We used a combination of biochemistry, genetics and bioinformatics to elucidate the spacing and orientation constraints of HMG-Helper site pairs. We found that HMG-Helper site spacing/orientation influenced the sensitivity of a target to Wnt signaling, as well as its tissue-responsiveness. We used this information to improve our ability to search the Drosophila genome for Wnt targets, one of which was activated by the pathway in the fly ring gland, the major endocrine organ in insects. Our work is relevant to related mammalian TCF family members, which are implicated in development, stem cell biology and the progression of cancer.

Best practices for mapping replication origins in eukaryotic chromosomes

Understanding the regulatory principles ensuring complete DNA replication in each cell division is critical for deciphering the mechanisms that maintain genomic stability. Recent advances in genome sequencing technology facilitated complete mapping of DNA replication sites and helped move the field from observing replication patterns at a handful of single loci to analyzing replication patterns genome-wide. These advances address issues, such as the relationship between replication initiation events, transcription, and chromatin modifications, and identify potential replication origin consensus sequences. This unit summarizes the technological and fundamental aspects of replication profiling and briefly discusses novel insights emerging from mining large datasets, published in the last 3 years, and also describes DNA replication dynamics on a whole-genome scale.

Analysis of an artificial zinc finger epigenetic modulator: widespread binding but limited regulation

Artificial transcription factors (ATFs) and genomic nucleases based on a DNA binding platform consisting of multiple zinc finger domains are currently being developed for clinical applications. However, no genome-wide investigations into their binding specificity have been performed. We have created six-finger ATFs to target two different 18 nt regions of the human SOX2 promoter; each ATF is constructed such that it contains or lacks a super KRAB domain (SKD) that interacts with a complex containing repressive histone methyltransferases. ChIP-seq analysis of the effector-free ATFs in MCF7 breast cancer cells identified thousands of binding sites, mostly in promoter regions; the addition of an SKD domain increased the number of binding sites ∼5-fold, with a majority of the new sites located outside of promoters. De novo motif analyses suggest that the lack of binding specificity is due to subsets of the finger domains being used for genomic interactions. Although the ATFs display widespread binding, few genes showed expression differences; genes repressed by the ATF-SKD have stronger binding sites and are more enriched for a 12 nt motif. Interestingly, epigenetic analyses indicate that the transcriptional repression caused by the ATF-SKD is not due to changes in active histone modifications.

Global analysis of ZNF217 chromatin occupancy in the breast cancer cell genome reveals an association with ERalpha

BACKGROUND

The ZNF217 gene, encoding a C2H2 zinc finger protein, is located at 20q13 and found amplified and overexpressed in greater than 20% of breast tumors. Current studies indicate ZNF217 drives tumorigenesis, yet the regulatory mechanisms of ZNF217 are largely unknown. Because ZNF217 associates with chromatin modifying enzymes, we postulate that ZNF217 functions to regulate specific gene signaling networks. Here, we present a large-scale functional genomic analysis of ZNF217, which provides insights into the regulatory role of ZNF217 in MCF7 breast cancer cells.

RESULTS

ChIP-seq analysis reveals that the majority of ZNF217 binding sites are located at distal regulatory regions associated with the chromatin marks H3K27ac and H3K4me1. Analysis of ChIP-seq transcription factor binding sites shows clustering of ZNF217 with FOXA1, GATA3 and ERalpha binding sites, supported by the enrichment of corresponding motifs for the ERalpha-associated cis-regulatory sequences. ERalpha expression highly correlates with ZNF217 in lysates from breast tumors (n = 15), and ERalpha co-precipitates ZNF217 and its binding partner CtBP2 from nuclear extracts. Transcriptome profiling following ZNF217 depletion identifies differentially expressed genes co-bound by ZNF217 and ERalpha; gene ontology suggests a role for ZNF217-ERalpha in expression programs associated with ER+ breast cancer studies found in the Molecular Signature Database. Data-mining of expression data from breast cancer patients correlates ZNF217 with reduced overall survival.

CONCLUSIONS

Our genome-wide ZNF217 data suggests a functional role for ZNF217 at ERalpha target genes. Future studies will investigate whether ZNF217 expression contributes to aberrant ERalpha regulatory events in ER+ breast cancer and hormone resistance.

OccuPeak: ChIP-Seq peak calling based on internal background modelling

ChIP-seq has become a major tool for the genome-wide identification of transcription factor binding or histone modification sites. Most peak-calling algorithms require input control datasets to model the occurrence of background reads to account for local sequencing and GC bias. However, the GC-content of reads in Input-seq datasets deviates significantly from that in ChIP-seq datasets. Moreover, we observed that a commonly used peak calling program performed equally well when the use of a simulated uniform background set was compared to an Input-seq dataset. This contradicts the assumption that input control datasets are necessary to fatefully reflect the background read distribution. Because the GC-content of the abundant single reads in ChIP-seq datasets is similar to those of randomly sampled regions we designed a peak-calling algorithm with a background model based on overlapping single reads. The application, OccuPeak, uses the abundant low frequency tags present in each ChIP-seq dataset to model the background, thereby avoiding the need for additional datasets. Analysis of the performance of OccuPeak showed robust model parameters. Its measure of peak significance, the excess ratio, is only dependent on the tag density of a peak and the global noise levels. Compared to the commonly used peak-calling applications MACS and CisGenome, OccuPeak had the highest sensitivity in an enhancer identification benchmark test, and performed similar in an overlap tests of transcription factor occupation with DNase I hypersensitive sites and H3K27ac sites. Moreover, peaks called by OccuPeak were significantly enriched with cardiac disease-associated SNPs. OccuPeak runs as a standalone application and does not require extensive tweaking of parameters, making its use straightforward and user friendly. Availability: http://occupeak.hfrc.nl

PePr: a peak-calling prioritization pipeline to identify consistent or differential peaks from replicated ChIP-Seq data

MOTIVATION

ChIP-Seq is the standard method to identify genome-wide DNA-binding sites for transcription factors (TFs) and histone modifications. There is a growing need to analyze experiments with biological replicates, especially for epigenomic experiments where variation among biological samples can be substantial. However, tools that can perform group comparisons are currently lacking.

RESULTS

We present a peak-calling prioritization pipeline (PePr) for identifying consistent or differential binding sites in ChIP-Seq experiments with biological replicates. PePr models read counts across the genome among biological samples with a negative binomial distribution and uses a local variance estimation method, ranking consistent or differential binding sites more favorably than sites with greater variability. We compared PePr with commonly used and recently proposed approaches on eight TF datasets and show that PePr uniquely identifies consistent regions with enriched read counts, high motif occurrence rate and known characteristics of TF binding based on visual inspection. For histone modification data with broadly enriched regions, PePr identified differential regions that are consistent within groups and outperformed other methods in scaling False Discovery Rate (FDR) analysis.

AVAILABILITY AND IMPLEMENTATION

http://code.google.com/p/pepr-chip-seq/.

Modeling transcriptional networks regulating secondary growth and wood formation in forest trees

The complex interactions among the genes that underlie a biological process can be modeled and presented as a transcriptional network, in which genes (nodes) and their interactions (edges) are shown in a graphical form similar to a wiring diagram. A large number of genes have been identified that are expressed during the radial woody growth of tree stems (secondary growth), but a comprehensive understanding of how these genes interact to influence woody growth is currently lacking. Modeling transcriptional networks has recently been made tractable by next-generation sequencing-based technologies that can comprehensively catalog gene expression and transcription factor-binding genome-wide, but has not yet been extensively applied to undomesticated tree species or woody growth. Here we discuss basic features of transcriptional networks, approaches for modeling biological networks, and examples of biological network models developed for forest trees to date. We discuss how transcriptional network research is being developed in the model forest tree genus, Populus, and how this research area can be further developed and applied. Transcriptional network models for forest tree secondary growth and wood formation could ultimately provide new predictive models to accelerate hypothesis-driven research and develop new breeding applications.

The spatiotemporal program of DNA replication is associated with specific combinations of chromatin marks in human cells

The duplication of mammalian genomes is under the control of a spatiotemporal program that orchestrates the positioning and the timing of firing of replication origins. The molecular mechanisms coordinating the activation of about predicted origins remain poorly understood, partly due to the intrinsic rarity of replication bubbles, making it difficult to purify short nascent strands (SNS). The precise identification of origins based on the high-throughput sequencing of SNS constitutes a new methodological challenge. We propose a new statistical method with a controlled resolution, adapted to the detection of replication origins from SNS data. We detected an average of 80,000 replication origins in different cell lines. To evaluate the consistency between different protocols, we compared SNS detections with bubble trapping detections. This comparison demonstrated a good agreement between genome-wide methods, with 65% of SNS-detected origins validated by bubble trapping, and 44% of bubble trapping origins validated by SNS origins, when compared at the same resolution. We investigated the interplay between the spatial and the temporal programs of replication at fine scales. We show that most of the origins detected in regions replicated in early S phase are shared by all the cell lines investigated whereas cell-type-specific origins tend to be replicated in late S phase. We shed a new light on the key role of CpG islands, by showing that 80% of the origins associated with CGIs are constitutive. Our results further show that at least 76% of CGIs are origins of replication. The analysis of associations with chromatin marks at different timing of cell division revealed new potential epigenetic regulators driving the spatiotemporal activity of replication origins. We highlight the potential role of H4K20me1 and H3K27me3, the coupling of which is correlated with increased efficiency of replication origins, clearly identifying those marks as potential key regulators of replication origins.

Replication is the mechanism by which genomes are duplicated into two exact copies. Genomic stability is under the control of a spatiotemporal program that orchestrates both the positioning and the timing of firing of about 50,000 replication starting points, also called replication origins. Replication bubbles found at origins have been very difficult to map due to their short lifespan. Moreover, with the flood of data characterizing new sequencing technologies, the precise statistical analysis of replication data has become an additional challenge. We propose a new method to map replication origins on the human genome, and we assess the reliability of our finding using experimental validation and comparison with origins maps obtained by bubble trapping. This fine mapping then allowed us to identify potential regulators of the replication dynamics. Our study highlights the key role of CpG Islands and identifies new potential epigenetic regulators (methylation of lysine 4 on histone H4, and tri-methylation of lysine 27 on histone H3) whose coupling is correlated with an increase in the efficiency of replication origins, suggesting those marks as potential key regulators of replication. Overall, our study defines new potentially important pathways that might regulate the sequential firing of origins during genome duplication.

Widespread FRA1-dependent control of mesenchymal transdifferentiation programs in colorectal cancer cells

Tumor invasion and metastasis involves complex remodeling of gene expression programs governing epithelial homeostasis. Mutational activation of the RAS-ERK is a frequent occurrence in many cancers and has been shown to drive overexpression of the AP-1 family transcription factor FRA1, a potent regulator of migration and invasion in a variety of tumor cell types. However, the nature of FRA1 transcriptional targets and the molecular pathways through which they promote tumor progression remain poorly understood. We found that FRA1 was strongly expressed in tumor cells at the invasive front of human colorectal cancers (CRCs), and that its depletion suppressed mesenchymal-like features in CRC cells in vitro. Genome-wide analysis of FRA1 chromatin occupancy and transcriptional regulation identified epithelial-mesenchymal transition (EMT)-related genes as a major class of direct FRA1 targets in CRC cells. Expression of the pro-mesenchymal subset of these genes predicted adverse outcomes in CRC patients, and involved FRA-1-dependent regulation and cooperation with TGFβ signaling pathway. Our findings reveal an unexpectedly widespread and direct role for FRA1 in control of epithelial-mesenchymal plasticity in CRC cells, and suggest that FRA1 plays an important role in mediating cross talk between oncogenic RAS-ERK and TGFβ signaling networks during tumor progression.

A survey of motif finding Web tools for detecting binding site motifs in ChIP-Seq data

Abstract

ChIP-Seq (chromatin immunoprecipitation sequencing) has provided the advantage for finding motifs as ChIP-Seq experiments narrow down the motif finding to binding site locations. Recent motif finding tools facilitate the motif detection by providing user-friendly Web interface. In this work, we reviewed nine motif finding Web tools that are capable for detecting binding site motifs in ChIP-Seq data. We showed each motif finding Web tool has its own advantages for detecting motifs that other tools may not discover. We recommended the users to use multiple motif finding Web tools that implement different algorithms for obtaining significant motifs, overlapping resemble motifs, and non-overlapping motifs. Finally, we provided our suggestions for future development of motif finding Web tool that better assists researchers for finding motifs in ChIP-Seq data.

Reviewers

This article was reviewed by Prof. Sandor Pongor, Dr. Yuriy Gusev, and Dr. Shyam Prabhakar (nominated by Prof. Limsoon Wong).

Leveraging biological replicates to improve analysis in ChIP-seq experiments

ChIP-seq experiments identify genome-wide profiles of DNA-binding molecules including transcription factors, enzymes and epigenetic marks. Biological replicates are critical for reliable site discovery and are required for the deposition of data in the ENCODE and modENCODE projects. While early reports suggested two replicates were sufficient, the widespread application of the technique has led to emerging consensus that the technique is noisy and that increasing replication may be worthwhile. Additional biological replicates also allow for quantitative assessment of differences between conditions. To date it has remained controversial about how to confirm peak identification and to determine signal strength across biological replicates, particularly when the number of replicates is greater than two. Using objective metrics, we evaluate the consistency of biological replicates in ChIP-seq experiments with more than two replicates. We compare several approaches for binding site determination, including two popular but disparate peak callers, CisGenome and MACS2. Here we propose read coverage as a quantitative measurement of signal strength for estimating sample concordance. Determining binding based on genomic features, such as promoters, is also examined. We find that increasing the number of biological replicates increases the reliability of peak identification. Critically, binding sites with strong biological evidence may be missed if researchers rely on only two biological replicates. When more than two replicates are performed, a simple majority rule (>50% of samples identify a peak) identifies peaks more reliably in all biological replicates than the absolute concordance of peak identification between any two replicates, further demonstrating the utility of increasing replicate numbers in ChIP-seq experiments.

AnnotateGenomicRegions: a web application

BACKGROUND

Modern genomic technologies produce large amounts of data that can be mapped to specific regions in the genome. Among the first steps in interpreting the results is annotation of genomic regions with known features such as genes, promoters, CpG islands etc. Several tools have been published to perform this task. However, using these tools often requires a significant amount of bioinformatics skills and/or downloading and installing dedicated software.

RESULTS

Here we present AnnotateGenomicRegions, a web application that accepts genomic regions as input and outputs a selection of overlapping and/or neighboring genome annotations. Supported organisms include human (hg18, hg19), mouse (mm8, mm9, mm10), zebrafish (danRer7), and Saccharomyces cerevisiae (sacCer2, sacCer3). AnnotateGenomicRegions is accessible online on a public server or can be installed locally. Some frequently used annotations and genomes are embedded in the application while custom annotations may be added by the user.

CONCLUSIONS

The increasing spread of genomic technologies generates the need for a simple-to-use annotation tool for genomic regions that can be used by biologists and bioinformaticians alike. AnnotateGenomicRegions meets this demand. AnnotateGenomicRegions is an open-source web application that can be installed on any personal computer or institute server. AnnotateGenomicRegions is available at: http://cru.genomics.iit.it/AnnotateGenomicRegions.

Comprehensive functional annotation of 77 prostate cancer risk loci

Genome-wide association studies (GWAS) have revolutionized the field of cancer genetics, but the causal links between increased genetic risk and onset/progression of disease processes remain to be identified. Here we report the first step in such an endeavor for prostate cancer. We provide a comprehensive annotation of the 77 known risk loci, based upon highly correlated variants in biologically relevant chromatin annotations--we identified 727 such potentially functional SNPs. We also provide a detailed account of possible protein disruption, microRNA target sequence disruption and regulatory response element disruption of all correlated SNPs at r(2) ≥ 0.88%. 88% of the 727 SNPs fall within putative enhancers, and many alter critical residues in the response elements of transcription factors known to be involved in prostate biology. We define as risk enhancers those regions with enhancer chromatin biofeatures in prostate-derived cell lines with prostate-cancer correlated SNPs. To aid the identification of these enhancers, we performed genomewide ChIP-seq for H3K27-acetylation, a mark of actively engaged enhancers, as well as the transcription factor TCF7L2. We analyzed in depth three variants in risk enhancers, two of which show significantly altered androgen sensitivity in LNCaP cells. This includes rs4907792, that is in linkage disequilibrium (r(2) = 0.91) with an eQTL for NUDT11 (on the X chromosome) in prostate tissue, and rs10486567, the index SNP in intron 3 of the JAZF1 gene on chromosome 7. Rs4907792 is within a critical residue of a strong consensus androgen response element that is interrupted in the protective allele, resulting in a 56% decrease in its androgen sensitivity, whereas rs10486567 affects both NKX3-1 and FOXA-AR motifs where the risk allele results in a 39% increase in basal activity and a 28% fold-increase in androgen stimulated enhancer activity. Identification of such enhancer variants and their potential target genes represents a preliminary step in connecting risk to disease process.

The diversity of zinc-finger genes on human chromosome 19 provides an evolutionary mechanism for defense against inherited endogenous retroviruses

Endogenous retroviruses (ERVs) are remnants of ancient retroviral infections of the germ line that can remain capable of replication within the host genome. In the soma, DNA methylation and repressive chromatin keep the majority of this parasitic DNA transcriptionally silent. However, it is unclear how the host organism adapts to recognize and silence novel invading retroviruses that enter the germ line. Krueppel-Associated Box (KRAB)-associated protein 1 (KAP1) is a transcriptional regulatory factor that drives the epigenetic repression of many different loci in mammalian genomes. Here, we use published experimental data to provide evidence that human KAP1 is recruited to endogenous retroviral DNA by KRAB-containing zinc-finger transcription factors (TFs). Many of these zinc-finger genes exist in clusters associated with human chromosome 19. We demonstrate that these clusters are located at hotspots for copy number variation (CNV), generating a large and continuing diversity of zinc-finger TFs with new generations. These zinc-finger genes possess a wide variety of DNA binding affinities, but their role as transcriptional repressors is conserved. We also perform a computational study of the different ERVs that invaded the human genome during primate evolution. We find candidate zinc-finger repressors that arise in the genome for each ERV family that enters the genomes of primates. In particular, we show that those repressors that gained their binding affinity to retrovirus sequences at the same time as their targets invaded the human lineage are preferentially located on chromosome 19 (P-value: 3 × 10⁻³).

Integrative analysis of SF-1 transcription factor dosage impact on genome-wide binding and gene expression regulation

Steroidogenic Factor-1 (SF-1) is a nuclear receptor that has a pivotal role in the development of adrenal glands and gonads and in the control of steroid hormone production, being also implicated in the pathogenesis of adrenocortical tumors. We have analyzed the mechanisms how SF-1 controls gene expression in adrenocortical cells and showed that it regulates different categories of genes according to its dosage. Significant correlations exist between the localization of SF-1-binding sites in chromatin under different dosage conditions and dosage-dependent regulation of gene expression. Our study revealed unexpected functional interactions between SF-1 and Neuron-Restrictive Silencer Factor/RE1-Silencing Transcription Factor (NRSF/REST), which was first characterized as a repressor of neuronal gene expression in non-neuronal tissues, in the regulation of gene expression in steroidogenic cells. When overexpressed, SF-1 reshapes the repertoire of NRSF/REST-regulated genes, relieving repression of key steroidogenic genes. These data show that NRSF/REST has a novel function in regulating gene expression in steroidogenic cells and suggest that it may have a broad role in regulating tissue-specific gene expression programs.

Selective regulation of lymphopoiesis and leukemogenesis by individual zinc fingers of Ikaros

C2H2 zinc fingers are found in several transcriptional regulators in the immune system. However, these proteins usually contain more fingers than are needed for stable DNA binding, suggesting that different fingers regulate different genes and functions. Mice lacking finger 1 or finger 4 of Ikaros exhibited distinct subsets of the phenotypes of Ikaros-null mice. Most notably, the two fingers controlled different stages of lymphopoiesis and finger 4 was selectively required for tumor suppression. The distinct phenotypes suggest that only a small number of Ikaros target genes are critical for each of its biological functions. Subdivision of phenotypes and targets by mutagenesis of individual fingers will facilitate efforts to understand how members of this prevalent family regulate development, immunity and disease.

Genome-wide analysis of transcription factor-binding sites in skeletal muscle cells using ChIP-seq

Transcriptional regulation of gene expression constitutes a fundamental mechanism of many developmental processes. Therefore, identification and characterization of binding sites of transcription factors are important for uncovering the mechanisms of a particular developmental process. Here, we describe detailed procedures for genome-wide analysis of binding sites of a transcription factor involved in the fiber-type differentiation of skeletal muscle. By conducting ChIP-seq followed by a series of downstream analyses, in-depth information on binding sites of transcription factors can be obtained in a genome-wide manner.

Gene regulatory elements of the cardiac conduction system

The coordinated contraction of the heart relies on the generation and conduction of the electrical impulse. Aberrations of the function of the cardiac conduction system have been associated with various arrhythmogenic disorders and increased risk of sudden cardiac death. The genetics underlying conduction system function have been investigated using functional studies and genome-wide association studies. Both methods point towards the involvement of ion channel genes and the transcription factors that govern their activity. A large fraction of disease- and trait-associated sequence variants lie within non-coding sequences, enriched with epigenetic marks indicative of regulatory DNA. Although sequence conservation as a result of functional constraint has been a useful property to identify transcriptional enhancers, this identification process has been advanced through the development of techniques such as ChIP-seq and chromatin conformation capture technologies. The role of variation in gene regulatory elements in the cardiac conduction system has recently been demonstrated by studies on enhancers of SCN5A/SCN10A and TBX5. In both studies, a region harbouring a functionally implicated single-nucleotide polymorphism was shown to drive reproducible cardiac expression in a reporter gene assay. Furthermore, the risk variant of the allele abrogated enhancer function in both cases. Functional studies on regulatory DNA will likely receive a boost through recent developments in genome modification technologies.

The calcineurin-NFAT-angiopoietin-2 signaling axis in lung endothelium is critical for the establishment of lung metastases

The premetastatic niche is a predetermined site of metastases, awaiting the influx of tumor cells. However, the regulation of the angiogenic switch at these sites has not been examined. Here, we demonstrate that the calcineurin and nuclear factor of activated T cells (NFAT) pathway is activated specifically in lung endothelium prior to the detection of tumor cells that preferentially metastasize to the lung. Upregulation of the calcineurin pathway via deletion of its endogenous inhibitor Dscr1 leads to a significant increase in lung metastases due to increased expression of a newly identified NFAT target, Angiopoietin-2 (ANG2). Increased VEGF levels specifically in the lung, and not other organ microenvironments, trigger a threshold of calcineurin-NFAT signaling that transactivates Ang2 in lung endothelium. Further, we demonstrate that overexpression of DSCR1 or the ANG2 receptor, soluble TIE2, prevents the activation of lung endothelium, inhibiting lung metastases in our mouse models. Our studies provide insights into mechanisms underlying angiogenesis in the premetastatic niche and offer targets for lung metastases.

Integrative genomics of gene and metabolic regulation by estrogen receptors α and β, and their coregulators

The closely related transcription factors (TFs), estrogen receptors ERα and ERβ, regulate divergent gene expression programs and proliferative outcomes in breast cancer. Utilizing breast cancer cells with ERα, ERβ, or both receptors as a model system to define the basis for differing response specification by related TFs, we show that these TFs and their key coregulators, SRC3 and RIP140, generate overlapping as well as unique chromatin-binding and transcription-regulating modules. Cistrome and transcriptome analyses and the use of clustering algorithms delineated 11 clusters representing different chromatin-bound receptor and coregulator assemblies that could be functionally associated through enrichment analysis with distinct patterns of gene regulation and preferential coregulator usage, RIP140 with ERβ and SRC3 with ERα. The receptors modified each other's transcriptional effect, and ERβ countered the proliferative drive of ERα through several novel mechanisms associated with specific binding-site clusters. Our findings delineate distinct TF-coregulator assemblies that function as control nodes, specifying precise patterns of gene regulation, proliferation, and metabolism, as exemplified by two of the most important nuclear hormone receptors in human breast cancer.

Accounting for immunoprecipitation efficiencies in the statistical analysis of ChIP-seq data

Background

ImmunoPrecipitation (IP) efficiencies may vary largely between different antibodies and between repeated experiments with the same antibody. These differences have a large impact on the quality of ChIP-seq data: a more efficient experiment will necessarily lead to a higher signal to background ratio, and therefore to an apparent larger number of enriched regions, compared to a less efficient experiment. In this paper, we show how IP efficiencies can be explicitly accounted for in the joint statistical modelling of ChIP-seq data.

Results

We fit a latent mixture model to eight experiments on two proteins, from two laboratories where different antibodies are used for the two proteins. We use the model parameters to estimate the efficiencies of individual experiments, and find that these are clearly different for the different laboratories, and amongst technical replicates from the same lab. When we account for ChIP efficiency, we find more regions bound in the more efficient experiments than in the less efficient ones, at the same false discovery rate. A priori knowledge of the same number of binding sites across experiments can also be included in the model for a more robust detection of differentially bound regions among two different proteins.

Conclusions

We propose a statistical model for the detection of enriched and differentially bound regions from multiple ChIP-seq data sets. The framework that we present accounts explicitly for IP efficiencies in ChIP-seq data, and allows to model jointly, rather than individually, replicates and experiments from different proteins, leading to more robust biological conclusions.

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.

MeCP2 modulates gene expression pathways in astrocytes

Background

Mutations in MECP2 encoding methyl-CpG-binding protein 2 (MeCP2) cause the X-linked neurodevelopmental disorder Rett syndrome. Rett syndrome patients exhibit neurological symptoms that include irregular breathing, impaired mobility, stereotypic hand movements, and loss of speech. MeCP2 protein epigenetically modulates gene expression through genome-wide binding to methylated CpG dinucleotides. While neurons have the highest level of MeCP2 expression, astrocytes and other cell types also express detectable levels of MeCP2. Recent studies suggest that astrocytes likely control the progression of Rett syndrome. Thus, the object of these studies was to identify gene targets that are affected by loss of MeCP2 binding in astrocytes.

Methods

To identify gene targets of MeCP2 in astrocytes, combined approaches of expression microarray and chromatin immunoprecipitation of MeCP2 followed by sequencing (ChIP-seq) were compared between wild-type and MeCP2-deficient astrocytes. MeCP2 gene targets were compared with genes in the top 10% of MeCP2 binding levels in gene windows either within 2 kb upstream of the transcription start site, or the ‘gene body’ that extended from transcription start to end site, or 2 kb downstream of the transcription end site.

Results

A total of 118 gene transcripts surpassed the highly significant threshold (P < 0.005, fold change > 1.2) in expression microarray analysis from triplicate cultures. The top 10% of genes with the highest levels of MeCP2 binding were identified in two independent ChIP-seq experiments. Together this integrated, genome-wide screen for MeCP2 target genes provided an overlapping list of 19 high-confidence MeCP2-responsive gene transcripts in astrocytes. Validation of candidate target gene transcripts by RT-PCR revealed that expression of Apoc2, Cdon, Csrp and Nrep were consistently responsive to MeCP2 deficiency in astrocytes.

Conclusions

The first MeCP2 ChIP-seq and gene expression microarray analysis in astrocytes reveals a set of potential MeCP2 target genes that may contribute to normal astrocyte signaling, cell division and neuronal support functions, the loss of which may contribute to the Rett syndrome phenotype.

Combining multiple ChIP-seq peak detection systems using combinatorial fusion

Background

Due to the recent rapid development in ChIP-seq technologies, which uses high-throughput next-generation DNA sequencing to identify the targets of Chromatin Immunoprecipitation, there is an increasing amount of sequencing data being generated that provides us with greater opportunity to analyze genome-wide protein-DNA interactions. In particular, we are interested in evaluating and enhancing computational and statistical techniques for locating protein binding sites. Many peak detection systems have been developed; in this study, we utilize the following six: CisGenome, MACS, PeakSeq, QuEST, SISSRs, and TRLocator.

Results

We define two methods to merge and rescore the regions of two peak detection systems and analyze the performance based on average precision and coverage of transcription start sites. The results indicate that ChIP-seq peak detection can be improved by fusion using score or rank combination.

Conclusion

Our method of combination and fusion analysis would provide a means for generic assessment of available technologies and systems and assist researchers in choosing an appropriate system (or fusion method) for analyzing ChIP-seq data. This analysis offers an alternate approach for increasing true positive rates, while decreasing false positive rates and hence improving the ChIP-seq peak identification process.

TCF/LEFs and Wnt signaling in the nucleus

T-cell factor/lymphoid enhancer factor (TCF/LEF) transcription factors are the major end point mediators of Wnt/Wingless signaling throughout metazoans. TCF/LEFs are multifunctional proteins that use their sequence-specific DNA-binding and context-dependent interactions to specify which genes will be regulated by Wnts. Much of the work to define their actions has focused on their ability to repress target gene expression when Wnt signals are absent and to recruit β-catenin to target genes for activation when Wnts are present. Recent advances have highlighted how these on/off actions are regulated by Wnt signals and stabilized β-catenin. In contrast to invertebrates, which typically contain one TCF/LEF protein that can both activate and repress Wnt targets, gene duplication and isoform complexity of the family in vertebrates have led to specialization, in which individual TCF/LEF isoforms have distinct activities.