Epigenetic Analyses of Human Left Atrial Tissue Identifies Gene Networks Underlying Atrial Fibrillation.

BACKGROUND: Atrial fibrillation (AF) often arises from structural abnormalities in the left atria (LA). Annotation of the noncoding genome in human LA is limited, as are effects on gene expression and chromatin architecture. Many AF-associated genetic variants reside in noncoding regions; this knowledge gap impairs efforts to understand the molecular mechanisms of AF and cardiac conduction phenotypes. METHODS: We generated a model of the LA noncoding genome by profiling 7 histone post-translational modifications (active: H3K4me3, H3K4me2, H3K4me1, H3K27ac, H3K36me3; repressive: H3K27me3, H3K9me3), CTCF binding, and gene expression in samples from 5 individuals without structural heart disease or AF. We used MACS2 to identify peak regions (P<0.01), applied a Markov model to classify regulatory elements, and annotated this model with matched gene expression data. We intersected chromatin states with expression quantitative trait locus, DNA methylation, and HiC chromatin interaction data from LA and left ventricle. Finally, we integrated genome-wide association data for AF and electrocardiographic traits to link disease-related variants to genes. RESULTS: Our model identified 21 epigenetic states, encompassing regulatory motifs, such as promoters, enhancers, and repressed regions. Genes were regulated by proximal chromatin states; repressive states were associated with a significant reduction in gene expression (P<2×10-16). Chromatin states were differentially methylated, promoters were less methylated than repressed regions (P<2×10-16). We identified over 15 000 LA-specific enhancers, defined by homeobox family motifs, and annotated several cardiovascular disease susceptibility loci. Intersecting AF and PR genome-wide association studies loci with long-range chromatin conformation data identified a gene interaction network dominated by NKX2-5, TBX3, ZFHX3, and SYNPO2L. CONCLUSIONS: Profiling the noncoding genome provides new insights into the gene expression and chromatin regulation in human LA tissue. These findings enabled identification of a gene network underlying AF; our experimental and analytic approach can be extended to identify molecular mechanisms for other cardiac diseases and traits.

Epigenetic and Transcriptional Networks Underlying Atrial Fibrillation.

Genome-wide association studies have uncovered over a 100 genetic loci associated with atrial fibrillation (AF), the most common arrhythmia. Many of the top AF-associated loci harbor key cardiac transcription factors, including PITX2, TBX5, PRRX1, and ZFHX3. Moreover, the vast majority of the AF-associated variants lie within noncoding regions of the genome where causal variants affect gene expression by altering the activity of transcription factors and the epigenetic state of chromatin. In this review, we discuss a transcriptional regulatory network model for AF defined by effector genes in Genome-wide association studies loci. We describe the current state of the field regarding the identification and function of AF-relevant gene regulatory networks, including variant regulatory elements, dose-sensitive transcription factor functionality, target genes, and epigenetic states. We illustrate how altered transcriptional networks may impact cardiomyocyte function and ionic currents that impact AF risk. Last, we identify the need for improved tools to identify and functionally test transcriptional components to define the links between genetic variation, epigenetic gene regulation, and atrial function.

Hominin-specific regulatory elements selectively emerged in oligodendrocytes and are disrupted in autism patients.

Speciation is associated with substantial rewiring of the regulatory circuitry underlying the expression of genes. Determining which changes are relevant and underlie the emergence of the human brain or its unique susceptibility to neural disease has been challenging. Here we annotate changes to gene regulatory elements (GREs) at cell type resolution in the brains of multiple primate species spanning most of primate evolution. We identify a unique set of regulatory elements that emerged in hominins prior to the separation of humans and chimpanzees. We demonstrate that these hominin gains perferentially affect oligodendrocyte function postnatally and are preferentially affected in the brains of autism patients. This preference is also observed for human-specific GREs suggesting this system is under continued selective pressure. Our data provide a roadmap of regulatory rewiring across primate evolution providing insight into the genomic changes that underlie the emergence of the brain and its susceptibility to neural disease.

BAZ2A safeguards genome architecture of ground-state pluripotent stem cells.

Chromosomes have an intrinsic tendency to segregate into compartments, forming long-distance contacts between loci of similar chromatin states. How genome compartmentalization is regulated remains elusive. Here, comparison of mouse ground-state embryonic stem cells (ESCs) characterized by open and active chromatin, and advanced serum ESCs with a more closed and repressed genome, reveals distinct regulation of their genome organization due to differential dependency on BAZ2A/TIP5, a component of the chromatin remodeling complex NoRC. On ESC chromatin, BAZ2A interacts with SNF2H, DNA topoisomerase 2A (TOP2A) and cohesin. BAZ2A associates with chromatin sub-domains within the active A compartment, which intersect through long-range contacts. We found that ground-state chromatin selectively requires BAZ2A to limit the invasion of active domains into repressive compartments. BAZ2A depletion increases chromatin accessibility at B compartments. Furthermore, BAZ2A regulates H3K27me3 genome occupancy in a TOP2A-dependent manner. Finally, ground-state ESCs require BAZ2A for growth, differentiation, and correct expression of developmental genes. Our results uncover the propensity of open chromatin domains to invade repressive domains, which is counteracted by chromatin remodeling to establish genome partitioning and preserve cell identity.

4C-seq from beginning to end: A detailed protocol for sample preparation and data analysis.

Chromosome conformation capture (3C) methods measure DNA contact frequencies based on nuclear proximity ligation, to uncover in vivo genomic folding patterns. 4C-seq is a derivative 3C method, designed to search the genome for sequences contacting a selected genomic site of interest. 4C-seq employs inverse PCR and next generation sequencing to amplify, identify and quantify its proximity ligated DNA fragments. It generates high-resolution contact profiles for selected genomic sites based on limited amounts of sequencing reads. 4C-seq can be used to study multiple aspects of genome organization. It primarily serves to identify specific long-range DNA contacts between individual regulatory DNA modules, forming for example regulatory chromatin loops between enhancers and promoters, or architectural chromatin loops between cohesin- and CTCF- associated domain boundaries. Additionally, 4C-seq contact profiles can reveal the contours of contact domains and can identify the structural domains that co-occupy the same nuclear compartment. Here, we present an improved step-by-step protocol for sample preparation and the generation of 4C-seq sequencing libraries, including an optimized PCR and 4C template purification strategy. In addition, a data processing pipeline is provided which processes multiplexed 4C-seq reads directly from FASTQ files and generates files compatible with standard genome browsers for visualization and further statistical analysis of the data such as peak calling using peakC. The protocols and the pipeline presented should readily allow anyone to generate, visualize and interpret their own high resolution 4C contact datasets.

An enhancer cluster controls gene activity and topology of the SCN5A-SCN10A locus in vivo.

Mutations and variations in and around SCN5A, encoding the major cardiac sodium channel, influence impulse conduction and are associated with a broad spectrum of arrhythmia disorders. Here, we identify an evolutionary conserved regulatory cluster with super enhancer characteristics downstream of SCN5A, which drives localized cardiac expression and contains conduction velocity-associated variants. We use genome editing to create a series of deletions in the mouse genome and show that the enhancer cluster controls the conformation of a >0.5 Mb genomic region harboring multiple interacting gene promoters and enhancers. We find that this cluster and its individual components are selectively required for cardiac Scn5a expression, normal cardiac conduction and normal embryonic development. Our studies reveal physiological roles of an enhancer cluster in the SCN5A-SCN10A locus, show that it controls the chromatin architecture of the locus and Scn5a expression, and suggest that genetic variants affecting its activity may influence cardiac function.

Transcription-factor-dependent enhancer transcription defines a gene regulatory network for cardiac rhythm.

The noncoding genome is pervasively transcribed. Noncoding RNAs (ncRNAs) generated from enhancers have been proposed as a general facet of enhancer function and some have been shown to be required for enhancer activity. Here we examine the transcription-factor-(TF)-dependence of ncRNA expression to define enhancers and enhancer-associated ncRNAs that are involved in a TF-dependent regulatory network. TBX5, a cardiac TF, regulates a network of cardiac channel genes to maintain cardiac rhythm. We deep sequenced wildtype and Tbx5-mutant mouse atria, identifying ~2600 novel Tbx5-dependent ncRNAs. Tbx5-dependent ncRNAs were enriched for tissue-specific marks of active enhancers genome-wide. Tbx5-dependent ncRNAs emanated from regions that are enriched for TBX5-binding and that demonstrated Tbx5-dependent enhancer activity. Tbx5-dependent ncRNA transcription provided a quantitative metric of Tbx5-dependent enhancer activity, correlating with target gene expression. We identified RACER, a novel Tbx5-dependent long noncoding RNA (lncRNA) required for the expression of the calcium-handling gene Ryr2. We illustrate that TF-dependent enhancer transcription can illuminate components of TF-dependent gene regulatory networks.

A Genetic Variant Associated with Five Vascular Diseases Is a Distal Regulator of Endothelin-1 Gene Expression.

Genome-wide association studies (GWASs) implicate the PHACTR1 locus (6p24) in risk for five vascular diseases, including coronary artery disease, migraine headache, cervical artery dissection, fibromuscular dysplasia, and hypertension. Through genetic fine mapping, we prioritized rs9349379, a common SNP in the third intron of the PHACTR1 gene, as the putative causal variant. Epigenomic data from human tissue revealed an enhancer signature at rs9349379 exclusively in aorta, suggesting a regulatory function for this SNP in the vasculature. CRISPR-edited stem cell-derived endothelial cells demonstrate rs9349379 regulates expression of endothelin 1 (EDN1), a gene located 600 kb upstream of PHACTR1. The known physiologic effects of EDN1 on the vasculature may explain the pattern of risk for the five associated diseases. Overall, these data illustrate the integration of genetic, phenotypic, and epigenetic analysis to identify the biologic mechanism by which a common, non-coding variant can distally regulate a gene and contribute to the pathogenesis of multiple vascular diseases.

Mutual epithelium-macrophage dependency in liver carcinogenesis mediated by ST18.

The ST18 gene has been proposed to act either as a tumor suppressor or as an oncogene in different human cancers, but direct evidence for its role in tumorigenesis has been lacking thus far. Here, we demonstrate that ST18 is critical for tumor progression and maintenance in a mouse model of liver cancer, based on oncogenic transformation and adoptive transfer of primary precursor cells (hepatoblasts). ST18 messenger RNA (mRNA) and protein were detectable neither in normal liver nor in cultured hepatoblasts, but were readily expressed after subcutaneous engraftment and tumor growth. ST18 expression in liver cells was induced by inflammatory cues, including acute or chronic inflammation in vivo, as well as coculture with macrophages in vitro. Knocking down the ST18 mRNA in transplanted hepatoblasts delayed tumor progression. Induction of ST18 knockdown in pre-established tumors caused rapid tumor involution associated with pervasive morphological changes, proliferative arrest, and apoptosis in tumor cells, as well as depletion of tumor-associated macrophages, vascular ectasia, and hemorrhage. Reciprocally, systemic depletion of macrophages in recipient animals had very similar phenotypic consequences, impairing either tumor development or maintenance, and suppressing ST18 expression in hepatoblasts. Finally, RNA sequencing of ST18-depleted tumors before involution revealed down-regulation of inflammatory response genes, pointing to the suppression of nuclear factor kappa B-dependent transcription. CONCLUSION: ST18 expression in epithelial cells is induced by tumor-associated macrophages, contributing to the reciprocal feed-forward loop between both cell types in liver tumorigenesis. Our findings warrant the exploration of means to interfere with ST18-dependent epithelium-macrophage interactions in a therapeutic setting. (Hepatology 2017;65:1708-1719).

The mitochondrial translation machinery as a therapeutic target in Myc-driven lymphomas.

The oncogenic transcription factor Myc is required for the progression and maintenance of diverse tumors. This has led to the concept that Myc itself, Myc-activated gene products, or associated biological processes might constitute prime targets for cancer therapy. Here, we present an in vivo reverse-genetic screen targeting a set of 241 Myc-activated mRNAs in mouse B-cell lymphomas, unraveling a critical role for the mitochondrial ribosomal protein (MRP) Ptcd3 in tumor maintenance. Other MRP-coding genes were also up regulated in Myc-induced lymphoma, pointing to a coordinate activation of the mitochondrial translation machinery. Inhibition of mitochondrial translation with the antibiotic Tigecycline was synthetic-lethal with Myc activation, impaired respiratory activity and tumor cell survival in vitro, and significantly extended lifespan in lymphoma-bearing mice. We have thus identified a novel Myc-induced metabolic dependency that can be targeted by common antibiotics, opening new therapeutic perspectives in Myc-overexpressing tumors.

Identification of MYC-Dependent Transcriptional Programs in Oncogene-Addicted Liver Tumors.

Tumors driven by activation of the transcription factor MYC generally show oncogene addiction. However, the gene expression programs that depend upon sustained MYC activity remain unknown. In this study, we employed a mouse model of liver carcinoma driven by a reversible tet-MYC transgene, combined with chromatin immunoprecipitation and gene expression profiling to identify MYC-dependent regulatory events. As previously reported, MYC-expressing mice exhibited hepatoblastoma- and hepatocellular carcinoma-like tumors, which regressed when MYC expression was suppressed. We further show that cellular transformation, and thus initiation of liver tumorigenesis, were impaired in mice harboring a MYC mutant unable to associate with the corepressor protein MIZ1 (ZBTB17). Notably, switching off the oncogene in advanced carcinomas revealed that MYC was required for the continuous activation and repression of distinct sets of genes, constituting no more than half of all genes deregulated during tumor progression and an even smaller subset of all MYC-bound genes. Altogether, our data provide the first detailed analysis of a MYC-dependent transcriptional program in a fully developed carcinoma and offer a guide to identifying the critical effectors contributing to MYC-driven tumor maintenance. Cancer Res; 76(12); 3463-72. ©2016 AACR.

Integrated Systems for NGS Data Management and Analysis: Open Issues and Available Solutions.

Next-generation sequencing (NGS) technologies have deeply changed our understanding of cellular processes by delivering an astonishing amount of data at affordable prices; nowadays, many biology laboratories have already accumulated a large number of sequenced samples. However, managing and analyzing these data poses new challenges, which may easily be underestimated by research groups devoid of IT and quantitative skills. In this perspective, we identify five issues that should be carefully addressed by research groups approaching NGS technologies. In particular, the five key issues to be considered concern: (1) adopting a laboratory management system (LIMS) and safeguard the resulting raw data structure in downstream analyses; (2) monitoring the flow of the data and standardizing input and output directories and file names, even when multiple analysis protocols are used on the same data; (3) ensuring complete traceability of the analysis performed; (4) enabling non-experienced users to run analyses through a graphical user interface (GUI) acting as a front-end for the pipelines; (5) relying on standard metadata to annotate the datasets, and when possible using controlled vocabularies, ideally derived from biomedical ontologies. Finally, we discuss the currently available tools in the light of these issues, and we introduce HTS-flow, a new workflow management system conceived to address the concerns we raised. HTS-flow is able to retrieve information from a LIMS database, manages data analyses through a simple GUI, outputs data in standard locations and allows the complete traceability of datasets, accompanying metadata and analysis scripts.

methylPipe and compEpiTools: a suite of R packages for the integrative analysis of epigenomics data.

BACKGROUND: Numerous methods are available to profile several epigenetic marks, providing data with different genome coverage and resolution. Large epigenomic datasets are then generated, and often combined with other high-throughput data, including RNA-seq, ChIP-seq for transcription factors (TFs) binding and DNase-seq experiments. Despite the numerous computational tools covering specific steps in the analysis of large-scale epigenomics data, comprehensive software solutions for their integrative analysis are still missing. Multiple tools must be identified and combined to jointly analyze histone marks, TFs binding and other -omics data together with DNA methylation data, complicating the analysis of these data and their integration with publicly available datasets. RESULTS: To overcome the burden of integrating various data types with multiple tools, we developed two companion R/Bioconductor packages. The former, methylPipe, is tailored to the analysis of high- or low-resolution DNA methylomes in several species, accommodating (hydroxy-)methyl-cytosines in both CpG and non-CpG sequence context. The analysis of multiple whole-genome bisulfite sequencing experiments is supported, while maintaining the ability of integrating targeted genomic data. The latter, compEpiTools, seamlessly incorporates the results obtained with methylPipe and supports their integration with other epigenomics data. It provides a number of methods to score these data in regions of interest, leading to the identification of enhancers, lncRNAs, and RNAPII stalling/elongation dynamics. Moreover, it allows a fast and comprehensive annotation of the resulting genomic regions, and the association of the corresponding genes with non-redundant GeneOntology terms. Finally, the package includes a flexible method based on heatmaps for the integration of various data types, combining annotation tracks with continuous or categorical data tracks. CONCLUSIONS: methylPipe and compEpiTools provide a comprehensive Bioconductor-compliant solution for the integrative analysis of heterogeneous epigenomics data. These packages are instrumental in providing biologists with minimal R skills a complete toolkit facilitating the analysis of their own data, or in accelerating the analyses performed by more experienced bioinformaticians.

Selective transcriptional regulation by Myc in cellular growth control and lymphomagenesis.

The c-myc proto-oncogene product, Myc, is a transcription factor that binds thousands of genomic loci. Recent work suggested that rather than up- and downregulating selected groups of genes, Myc targets all active promoters and enhancers in the genome (a phenomenon termed 'invasion') and acts as a general amplifier of transcription. However, the available data did not readily discriminate between direct and indirect effects of Myc on RNA biogenesis. We addressed this issue with genome-wide chromatin immunoprecipitation and RNA expression profiles during B-cell lymphomagenesis in mice, in cultured B cells and fibroblasts. Consistent with long-standing observations, we detected general increases in total RNA or messenger RNA copies per cell (hereby termed 'amplification') when comparing actively proliferating cells with control quiescent cells: this was true whether cells were stimulated by mitogens (requiring endogenous Myc for a proliferative response) or by deregulated, oncogenic Myc activity. RNA amplification and promoter/enhancer invasion by Myc were separable phenomena that could occur without one another. Moreover, whether or not associated with RNA amplification, Myc drove the differential expression of distinct subsets of target genes. Hence, although having the potential to interact with all active or poised regulatory elements in the genome, Myc does not directly act as a global transcriptional amplifier. Instead, our results indicate that Myc activates and represses transcription of discrete gene sets, leading to changes in cellular state that can in turn feed back on global RNA production and turnover.

DBATE: database of alternative transcripts expression.

The use of high-throughput RNA sequencing technology (RNA-seq) allows whole transcriptome analysis, providing an unbiased and unabridged view of alternative transcript expression. Coupling splicing variant-specific expression with its functional inference is still an open and difficult issue for which we created the DataBase of Alternative Transcripts Expression (DBATE), a web-based repository storing expression values and functional annotation of alternative splicing variants. We processed 13 large RNA-seq panels from human healthy tissues and in disease conditions, reporting expression levels and functional annotations gathered and integrated from different sources for each splicing variant, using a variant-specific annotation transfer pipeline. The possibility to perform complex queries by cross-referencing different functional annotations permits the retrieval of desired subsets of splicing variant expression values that can be visualized in several ways, from simple to more informative. DBATE is intended as a novel tool to help appreciate how, and possibly why, the transcriptome expression is shaped. DATABASE URL: http://bioinformatica.uniroma2.it/DBATE/.

Alternative splicing tends to avoid partial removals of protein-protein interaction sites.

BACKGROUND: Anecdotal evidence of the involvement of alternative splicing (AS) in the regulation of protein-protein interactions has been reported by several studies. AS events have been shown to significantly occur in regions where a protein interaction domain or a short linear motif is present. Several AS variants show partial or complete loss of interface residues, suggesting that AS can play a major role in the interaction regulation by selectively targeting the protein binding sites. In the present study we performed a statistical analysis of the alternative splicing of a non-redundant dataset of human protein-protein interfaces known at molecular level to determine the importance of this way of modulation of protein-protein interactions through AS. RESULTS: Using a Cochran-Mantel-Haenszel chi-square test we demonstrated that the alternative splicing-mediated partial removal of both heterodimeric and homodimeric binding sites occurs at lower frequencies than expected, and this holds true even if we consider only those isoforms whose sequence is less different from that of the canonical protein and which therefore allow to selectively regulate functional regions of the protein. On the other hand, large removals of the binding site are not significantly prevented, possibly because they are associated to drastic structural changes of the protein. The observed protection of the binding sites from AS is not preferentially directed towards putative hot spot interface residues, and is widespread to all protein functional classes. CONCLUSIONS: Our findings indicate that protein-protein binding sites are generally protected from alternative splicing-mediated partial removals. However, some cases in which the binding site is selectively removed exist, and here we discuss one of them.

webPDBinder: a server for the identification of ligand binding sites on protein structures.

The webPDBinder (http://pdbinder.bio.uniroma2.it/PDBinder) is a web server for the identification of small ligand-binding sites in a protein structure. webPDBinder searches a protein structure against a library of known binding sites and a collection of control non-binding pockets. The number of similarities identified with the residues in the two sets is then used to derive a propensity value for each residue of the query protein associated to the likelihood that the residue is part of a ligand binding site. The predicted binding residues can be further refined using conservation scores derived from the multiple alignment of the PFAM protein family. webPDBinder correctly identifies residues belonging to the binding site in 77% of the cases and is able to identify binding pockets starting from holo or apo structures with comparable performances. This is important for all the real world cases where the query protein has been crystallized without a ligand and is also difficult to obtain clear similarities with bound pockets from holo pocket libraries. The input is either a PDB code or a user-submitted structure. The output is a list of predicted binding pocket residues with propensity and conservation values both in text and graphical format.

Identification of binding pockets in protein structures using a knowledge-based potential derived from local structural similarities.

BACKGROUND: The identification of ligand binding sites is a key task in the annotation of proteins with known structure but uncharacterized function. Here we describe a knowledge-based method exploiting the observation that unrelated binding sites share small structural motifs that bind the same chemical fragments irrespective of the nature of the ligand as a whole. RESULTS: PDBinder compares a query protein against a library of binding and non-binding protein surface regions derived from the PDB. The results of the comparison are used to derive a propensity value for each residue which is correlated with the likelihood that the residue is part of a ligand binding site. The method was applied to two different problems: i) the prediction of ligand binding residues and ii) the identification of which surface cleft harbours the binding site. In both cases PDBinder performed consistently better than existing methods. PDBinder has been trained on a non-redundant set of 1356 high-quality protein-ligand complexes and tested on a set of 239 holo and apo complex pairs. We obtained an MCC of 0.313 on the holo set with a PPV of 0.413 while on the apo set we achieved an MCC of 0.271 and a PPV of 0.372. CONCLUSIONS: We show that PDBinder performs better than existing methods. The good performance on the unbound proteins is extremely important for real-world applications where the location of the binding site is unknown. Moreover, since our approach is orthogonal to those used in other programs, the PDBinder propensity value can be integrated in other algorithms further increasing the final performance.