The ensembl regulatory build

Initial high-resolution microscopic mapping of active and inactive regulatory sequences proves non-random 3D arrangements in chromatin domain clusters

BACKGROUND

The association of active transcription regulatory elements (TREs) with DNAse I hypersensitivity (DHS[+]) and an 'open' local chromatin configuration has long been known. However, the 3D topography of TREs within the nuclear landscape of individual cells in relation to their active or inactive status has remained elusive. Here, we explored the 3D nuclear topography of active and inactive TREs in the context of a recently proposed model for a functionally defined nuclear architecture, where an active and an inactive nuclear compartment (ANC-INC) form two spatially co-aligned and functionally interacting networks.

RESULTS

Using 3D structured illumination microscopy, we performed 3D FISH with differently labeled DNA probe sets targeting either sites with DHS[+], apparently active TREs, or DHS[-] sites harboring inactive TREs. Using an in-house image analysis tool, DNA targets were quantitatively mapped on chromatin compaction shaped 3D nuclear landscapes. Our analyses present evidence for a radial 3D organization of chromatin domain clusters (CDCs) with layers of increasing chromatin compaction from the periphery to the CDC core. Segments harboring active TREs are significantly enriched at the decondensed periphery of CDCs with loops penetrating into interchromatin compartment channels, constituting the ANC. In contrast, segments lacking active TREs (DHS[-]) are enriched toward the compacted interior of CDCs (INC).

CONCLUSIONS

Our results add further evidence in support of the ANC-INC network model. The different 3D topographies of DHS[+] and DHS[-] sites suggest positional changes of TREs between the ANC and INC depending on their functional state, which might provide additional protection against an inappropriate activation. Our finding of a structural organization of CDCs based on radially arranged layers of different chromatin compaction levels indicates a complex higher-order chromatin organization beyond a dichotomic classification of chromatin into an 'open,' active and 'closed,' inactive state.

Assessment of imprinting- and genetic variation-dependent monoallelic expression using reciprocal allele descendants between human family trios

Genomic imprinting is an important epigenetic process that silences one of the parentally-inherited alleles of a gene and thereby exhibits allelic-specific expression (ASE). Detection of human imprinting events is hampered by the infeasibility of the reciprocal mating system in humans and the removal of ASE events arising from non-imprinting factors. Here, we describe a pipeline with the pattern of reciprocal allele descendants (RADs) through genotyping and transcriptome sequencing data across independent parent-offspring trios to discriminate between varied types of ASE (e.g., imprinting, genetic variation-dependent ASE, and random monoallelic expression (RME)). We show that the vast majority of ASE events are due to sequence-dependent genetic variant, which are evolutionarily conserved and may themselves play a cis-regulatory role. Particularly, 74% of non-RAD ASE events, even though they exhibit ASE biases toward the same parentally-inherited allele across different individuals, are derived from genetic variation but not imprinting. We further show that the RME effect may affect the effectiveness of the population-based method for detecting imprinting events and our pipeline can help to distinguish between these two ASE types. Taken together, this study provides a good indicator for categorization of different types of ASE, opening up this widespread and complex mechanism for comprehensive characterization.

Identification of 19 new risk loci and potential regulatory mechanisms influencing susceptibility to testicular germ cell tumor

Genome-wide association studies (GWAS) have transformed understanding of susceptibility to testicular germ cell tumors (TGCTs), but much of the heritability remains unexplained. Here we report a new GWAS, a meta-analysis with previous GWAS and a replication series, totaling 7,319 TGCT cases and 23,082 controls. We identify 19 new TGCT risk loci, roughly doubling the number of known TGCT risk loci to 44. By performing in situ Hi-C in TGCT cells, we provide evidence for a network of physical interactions among all 44 TGCT risk SNPs and candidate causal genes. Our findings implicate widespread disruption of developmental transcriptional regulators as a basis of TGCT susceptibility, consistent with failed primordial germ cell differentiation as an initiating step in oncogenesis. Defective microtubule assembly and dysregulation of KIT-MAPK signaling also feature as recurrently disrupted pathways. Our findings support a polygenic model of risk and provide insight into the biological basis of TGCT.

Methylome and transcriptome profiling in Myasthenia Gravis monozygotic twins

OBJECTIVE

To identify novel genetic and epigenetic factors associated with Myasthenia gravis (MG) using an identical twins experimental study design.

METHODS

The transcriptome and methylome of peripheral monocytes were compared between monozygotic (MZ) twins discordant and concordant for MG, as well as with MG singletons and healthy controls, all females. Sets of differentially expressed genes and differentially methylated CpGs were validated using RT-PCR for expression and target bisulfite sequencing for methylation on additional samples.

RESULTS

>100 differentially expressed genes and ∼1800 differentially methylated CpGs were detected in peripheral monocytes between MG patients and controls. Several transcripts associated with immune homeostasis and inflammation resolution were reduced in MG patients. Only a relatively few genes differed between the discordant healthy and MG co-twins, and both their expression and methylation profiles demonstrated very high similarity.

INTERPRETATION

This is the first study to characterize the DNA methylation profile in MG, and the expression profile of immune cells in MZ twins with MG. Results suggest that numerous small changes in gene expression or methylation might together contribute to disease. Impaired monocyte function in MG and decreased expression of genes associated with inflammation resolution could contribute to the chronicity of the disease. Findings may serve as potential new predictive biomarkers for disease and disease activity, as well as potential future targets for therapy development. The high similarity between the healthy and the MG discordant twins, suggests that a molecular signature might precede a clinical phenotype, and that genetic predisposition may have a stronger contribution to disease than previously assumed.

Prognostic value of CA20, a score based on centrosome amplification-associated genes, in breast tumors

Centrosome amplification (CA) is a hallmark of cancer, observable in ≥75% of breast tumors. CA drives aggressive cellular phenotypes such as chromosomal instability (CIN) and invasiveness. Thus, assessment of CA may offer insights into the prognosis of breast cancer and identify patients who might benefit from centrosome declustering agents. However, it remains unclear whether CA is correlated with clinical outcomes after adjusting for confounding factors. To gain insights, we developed a signature, “CA20”, comprising centrosome structural genes and genes whose dysregulation is implicated in inducing CA. We found that CA20 was a significant independent predictor of worse survival in two large independent datasets after adjusting for potentially confounding factors. In multivariable analyses including both CA20 and CIN25 (a gene expression-based score that correlates with aneuploidy and has prognostic value in many types of cancer), only CA20 was significant, suggesting CA20 captures the risk-predictive information of CIN25 and offers information beyond it. CA20 correlated strongly with CIN25, so a high CA20 score may reflect tumors with high CIN and potentially other aggressive features that may require more aggressive treatment. Finally, we identified processes and pathways differing between CA20-low and high groups that may be valuable therapeutic targets.

Fast, scalable prediction of deleterious noncoding variants from functional and population genomic data

Many genetic variants that influence phenotypes of interest are located outside of protein-coding genes, yet existing methods for identifying such variants have poor predictive power. Here we introduce a new computational method, called LINSIGHT, that substantially improves the prediction of noncoding nucleotide sites at which mutations are likely to have deleterious fitness consequences, and which, therefore, are likely to be phenotypically important. LINSIGHT combines a generalized linear model for functional genomic data with a probabilistic model of molecular evolution. The method is fast and highly scalable, enabling it to exploit the 'big data' available in modern genomics. We show that LINSIGHT outperforms the best available methods in identifying human noncoding variants associated with inherited diseases. In addition, we apply LINSIGHT to an atlas of human enhancers and show that the fitness consequences at enhancers depend on cell type, tissue specificity, and constraints at associated promoters.

A somatic-mutational process recurrently duplicates germline susceptibility loci and tissue-specific super-enhancers in breast cancers

Somatic rearrangements contribute to the mutagenized landscape of cancer genomes. Here, we systematically interrogated rearrangements in 560 breast cancers by using a piecewise constant fitting approach. We identified 33 hotspots of large (>100 kb) tandem duplications, a mutational signature associated with homologous-recombination-repair deficiency. Notably, these tandem-duplication hotspots were enriched in breast cancer germline susceptibility loci (odds ratio (OR) = 4.28) and breast-specific 'super-enhancer' regulatory elements (OR = 3.54). These hotspots may be sites of selective susceptibility to double-strand-break damage due to high transcriptional activity or, through incrementally increasing copy number, may be sites of secondary selective pressure. The transcriptomic consequences ranged from strong individual oncogene effects to weak but quantifiable multigene expression effects. We thus present a somatic-rearrangement mutational process affecting coding sequences and noncoding regulatory elements and contributing a continuum of driver consequences, from modest to strong effects, thereby supporting a polygenic model of cancer development.

Accurate Promoter and Enhancer Identification in 127 ENCODE and Roadmap Epigenomics Cell Types and Tissues by GenoSTAN

Accurate maps of promoters and enhancers are required for understanding transcriptional regulation. Promoters and enhancers are usually mapped by integration of chromatin assays charting histone modifications, DNA accessibility, and transcription factor binding. However, current algorithms are limited by unrealistic data distribution assumptions. Here we propose GenoSTAN (Genomic STate ANnotation), a hidden Markov model overcoming these limitations. We map promoters and enhancers for 127 cell types and tissues from the ENCODE and Roadmap Epigenomics projects, today’s largest compendium of chromatin assays. Extensive benchmarks demonstrate that GenoSTAN generally identifies promoters and enhancers with significantly higher accuracy than previous methods. Moreover, GenoSTAN-derived promoters and enhancers showed significantly higher enrichment of complex trait-associated genetic variants than current annotations. Altogether, GenoSTAN provides an easy-to-use tool to define promoters and enhancers in any system, and our annotation of human transcriptional cis-regulatory elements constitutes a rich resource for future research in biology and medicine.

GeneHancer: genome-wide integration of enhancers and target genes in GeneCards

A major challenge in understanding gene regulation is the unequivocal identification of enhancer elements and uncovering their connections to genes. We present GeneHancer, a novel database of human enhancers and their inferred target genes, in the framework of GeneCards. First, we integrated a total of 434 000 reported enhancers from four different genome-wide databases: the Encyclopedia of DNA Elements (ENCODE), the Ensembl regulatory build, the functional annotation of the mammalian genome (FANTOM) project and the VISTA Enhancer Browser. Employing an integration algorithm that aims to remove redundancy, GeneHancer portrays 285 000 integrated candidate enhancers (covering 12.4% of the genome), 94 000 of which are derived from more than one source, and each assigned an annotation-derived confidence score. GeneHancer subsequently links enhancers to genes, using: tissue co-expression correlation between genes and enhancer RNAs, as well as enhancer-targeted transcription factor genes; expression quantitative trait loci for variants within enhancers; and capture Hi-C, a promoter-specific genome conformation assay. The individual scores based on each of these four methods, along with gene–enhancer genomic distances, form the basis for GeneHancer’s combinatorial likelihood-based scores for enhancer–gene pairing. Finally, we define ‘elite’ enhancer–gene relations reflecting both a high-likelihood enhancer definition and a strong enhancer–gene association. GeneHancer predictions are fully integrated in the widely used GeneCards Suite, whereby candidate enhancers and their annotations are displayed on every relevant GeneCard. This assists in the mapping of non-coding variants to enhancers, and via the linked genes, forms a basis for variant–phenotype interpretation of whole-genome sequences in health and disease.

DATABASE URL

http://www.genecards.org/.

Candidate SNP markers of aggressiveness-related complications and comorbidities of genetic diseases are predicted by a significant change in the affinity of TATA-binding protein for human gene promoters

BACKGROUND

Aggressiveness in humans is a hereditary behavioral trait that mobilizes all systems of the body-first of all, the nervous and endocrine systems, and then the respiratory, vascular, muscular, and others-e.g., for the defense of oneself, children, family, shelter, territory, and other possessions as well as personal interests. The level of aggressiveness of a person determines many other characteristics of quality of life and lifespan, acting as a stress factor. Aggressive behavior depends on many parameters such as age, gender, diseases and treatment, diet, and environmental conditions. Among them, genetic factors are believed to be the main parameters that are well-studied at the factual level, but in actuality, genome-wide studies of aggressive behavior appeared relatively recently. One of the biggest projects of the modern science-1000 Genomes-involves identification of single nucleotide polymorphisms (SNPs), i.e., differences of individual genomes from the reference genome. SNPs can be associated with hereditary diseases, their complications, comorbidities, and responses to stress or a drug. Clinical comparisons between cohorts of patients and healthy volunteers (as a control) allow for identifying SNPs whose allele frequencies significantly separate them from one another as markers of the above conditions. Computer-based preliminary analysis of millions of SNPs detected by the 1000 Genomes project can accelerate clinical search for SNP markers due to preliminary whole-genome search for the most meaningful candidate SNP markers and discarding of neutral and poorly substantiated SNPs.

RESULTS

Here, we combine two computer-based search methods for SNPs (that alter gene expression) {i} Web service SNP_TATA_Comparator (DNA sequence analysis) and {ii} PubMed-based manual search for articles on aggressiveness using heuristic keywords. Near the known binding sites for TATA-binding protein (TBP) in human gene promoters, we found aggressiveness-related candidate SNP markers, including rs1143627 (associated with higher aggressiveness in patients undergoing cytokine immunotherapy), rs544850971 (higher aggressiveness in old women taking lipid-lowering medication), and rs10895068 (childhood aggressiveness-related obesity in adolescence with cardiovascular complications in adulthood).

CONCLUSIONS

After validation of these candidate markers by clinical protocols, these SNPs may become useful for physicians (may help to improve treatment of patients) and for the general population (a lifestyle choice preventing aggressiveness-related complications).

Genetic Adaptation and Neandertal Admixture Shaped the Immune System of Human Populations

Humans differ in the outcome that follows exposure to life-threatening pathogens, yet the extent of population differences in immune responses and their genetic and evolutionary determinants remain undefined. Here, we characterized, using RNA sequencing, the transcriptional response of primary monocytes from Africans and Europeans to bacterial and viral stimuli-ligands activating Toll-like receptor pathways (TLR1/2, TLR4, and TLR7/8) and influenza virus-and mapped expression quantitative trait loci (eQTLs). We identify numerous cis-eQTLs that contribute to the marked differences in immune responses detected within and between populations and a strong trans-eQTL hotspot at TLR1 that decreases expression of pro-inflammatory genes in Europeans only. We find that immune-responsive regulatory variants are enriched in population-specific signals of natural selection and show that admixture with Neandertals introduced regulatory variants into European genomes, affecting preferentially responses to viral challenges. Together, our study uncovers evolutionarily important determinants of differences in host immune responsiveness between human populations.

Ensembl 2017

Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access methods ensure uniform data analysis and distribution for all supported species. Together, these provide a comprehensive solution for large-scale and targeted genomics applications alike. Among many other developments over the past year, we have improved our resources for gene regulation and comparative genomics, and added CRISPR/Cas9 target sites. We released new browser functionality and tools, including improved filtering and prioritization of genome variation, Manhattan plot visualization for linkage disequilibrium and eQTL data, and an ontology search for phenotypes, traits and disease. We have also enhanced data discovery and access with a track hub registry and a selection of new REST end points. All Ensembl data are freely released to the scientific community and our source code is available via the open source Apache 2.0 license.

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.

DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation

Hematopoietic stem cells give rise to all blood cells in a differentiation process that involves widespread epigenome remodeling. Here we present genome-wide reference maps of the associated DNA methylation dynamics. We used a meta-epigenomic approach that combines DNA methylation profiles across many small pools of cells and performed single-cell methylome sequencing to assess cell-to-cell heterogeneity. The resulting dataset identified characteristic differences between HSCs derived from fetal liver, cord blood, bone marrow, and peripheral blood. We also observed lineage-specific DNA methylation between myeloid and lymphoid progenitors, characterized immature multi-lymphoid progenitors, and detected progressive DNA methylation differences in maturing megakaryocytes. We linked these patterns to gene expression, histone modifications, and chromatin accessibility, and we used machine learning to derive a model of human hematopoietic differentiation directly from DNA methylation data. Our results contribute to a better understanding of human hematopoietic stem cell differentiation and provide a framework for studying blood-linked diseases.

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Sequencing provides DNA methylation maps of hematopoietic stem and progenitor cells

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Methylation differs in HSCs from fetal liver, bone marrow, cord, and peripheral blood

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Myeloid and lymphoid progenitors are distinguished by enhancer-linked DNA methylation

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Machine learning enables data-driven reconstruction of the hematopoietic lineage

MHC class I-associated peptides derive from selective regions of the human genome

MHC class I-associated peptides (MAPs) define the immune self for CD8+ T lymphocytes and are key targets of cancer immunosurveillance. Here, the goals of our work were to determine whether the entire set of protein-coding genes could generate MAPs and whether specific features influence the ability of discrete genes to generate MAPs. Using proteogenomics, we have identified 25,270 MAPs isolated from the B lymphocytes of 18 individuals who collectively expressed 27 high-frequency HLA-A,B allotypes. The entire MAP repertoire presented by these 27 allotypes covered only 10% of the exomic sequences expressed in B lymphocytes. Indeed, 41% of expressed protein-coding genes generated no MAPs, while 59% of genes generated up to 64 MAPs, often derived from adjacent regions and presented by different allotypes. We next identified several features of transcripts and proteins associated with efficient MAP production. From these data, we built a logistic regression model that predicts with good accuracy whether a gene generates MAPs. Our results show preferential selection of MAPs from a limited repertoire of proteins with distinctive features. The notion that the MHC class I immunopeptidome presents only a small fraction of the protein-coding genome for monitoring by the immune system has profound implications in autoimmunity and cancer immunology.

A systematic comparison reveals substantial differences in chromosomal versus episomal encoding of enhancer activity

Candidate enhancers can be identified on the basis of chromatin modifications, the binding of chromatin modifiers and transcription factors and cofactors, or chromatin accessibility. However, validating such candidates as bona fide enhancers requires functional characterization, typically achieved through reporter assays that test whether a sequence can increase expression of a transcriptional reporter via a minimal promoter. A longstanding concern is that reporter assays are mainly implemented on episomes, which are thought to lack physiological chromatin. However, the magnitude and determinants of differences in cis-regulation for regulatory sequences residing in episomes versus chromosomes remain almost completely unknown. To address this systematically, we developed and applied a novel lentivirus-based massively parallel reporter assay (lentiMPRA) to directly compare the functional activities of 2236 candidate liver enhancers in an episomal versus a chromosomally integrated context. We find that the activities of chromosomally integrated sequences are substantially different from the activities of the identical sequences assayed on episomes, and furthermore are correlated with different subsets of ENCODE annotations. The results of chromosomally based reporter assays are also more reproducible and more strongly predictable by both ENCODE annotations and sequence-based models. With a linear model that combines chromatin annotations and sequence information, we achieve a Pearson's R² of 0.362 for predicting the results of chromosomally integrated reporter assays. This level of prediction is better than with either chromatin annotations or sequence information alone and also outperforms predictive models of episomal assays. Our results have broad implications for how cis-regulatory elements are identified, prioritized and functionally validated.

Aryl hydrocarbon receptor signaling modifies Toll-like receptor-regulated responses in human dendritic cells

Currently, it is not well understood how ligands of the aryl hydrocarbon receptor (AhR) modify inflammatory responses triggered by Toll-like receptor (TLR) agonists in human dendritic cells (DCs). Here, we show that AhR ligands 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), the tryptophan derivatives 6-formylindolo[3,2-b] carbazole (FICZ), kynurenine (kyn), and the natural dietary compound indole-3-carbinol (I3C) differentially modify cytokine expression in human monocyte-derived DCs (MoDCs). The results show that TLR-activated MoDCs express higher levels of AhR and are more sensitive toward the effects of AhR ligands. Depending on the cytokine, treatment with AhR ligands led to a synergistic or antagonistic effect of the TLR-triggered response in MoDCs. Thus, activation of AhR increased the expression of interleukin (IL)-1β, but decreased the expression of IL-12A in TLR-activated MoDCs. Furthermore, TCDD and FICZ may have opposite effects on the expression of cytochrome P4501A1 (CYP1A1) in TLR8-activated MoDCs indicating that the effect of the specific AhR ligand may depend on the presence of the specific TLR agonist. Gene silencing showed that synergistic effects of AhR ligands on TLR-induced expression of IL-1β require a functional AhR and the expression of NF-κB RelB. On the other hand, repression of IL-12A by TCDD and FICZ involved the induction of the caudal type homeobox 2 (CDX2) transcription factor. Additionally, the levels of DC surface markers were decreased in MoDCs by TCDD, FICZ and I3C, but not by kyn. Overall, these data demonstrate that AhR modulates TLR-induced expression of cytokines and DC-specific surface markers in MoDCs involving NFκB RelB and the immune regulatory factor CDX2.

Elevated systemic glutamic acid level in the non-obese diabetic mouse is Idd linked and induces beta cell apoptosis

Although type 1 diabetes (T1D) is a T-cell-mediated disease in the effector stage, the mechanism behind the initial beta cell assault is less understood. Metabolomic differences, including elevated levels of glutamic acid, have been observed in patients with T1D before disease onset, as well as in pre-diabetic non-obese diabetic (NOD) mice. Increased levels of glutamic acid damage both neurons and beta cells, implying that this could contribute to the initial events of T1D pathogenesis. We investigated the underlying genetic factors and consequences of the increased levels of glutamic acid in NOD mice. Serum glutamic acid levels from a (NOD×B6)F₂ cohort (n = 182) were measured. By genome-wide and Idd region targeted microsatellite mapping, genetic association was detected for six regions including Idd2, Idd4 and Idd22. In silico analysis of potential enzymes and transporters located in and around the mapped regions that are involved in glutamic acid metabolism consisted of alanine aminotransferase, glutamic-oxaloacetic transaminase, aldehyde dehydrogenase 18 family, alutamyl-prolyl-tRNA synthetase, glutamic acid transporters GLAST and EAAC1. Increased EAAC1 protein expression was observed in lysates from livers of NOD mice compared with B6 mice. Functional consequence of the elevated glutamic acid level in NOD mice was tested by culturing NOD. Rag2^-/- Langerhans' islets with glutamic acid. Induction of apoptosis of the islets was detected upon glutamic acid challenge using TUNEL assay. Our results support the notion that a dysregulated metabolome could contribute to the initiation of T1D. We suggest that targeting of the increased glutamic acid in pre-diabetic patients could be used as a potential therapy.

Epigenetic regulation of alternative promoters and enhancers in progenitor, immature, and mature gonadotrope cell lines

Gonadotrope cell identity genes emerge in a stepwise process during mouse pituitary development. Cga, encoding for the α-subunit of TSH, LH, and FSH, is initially detected at E11.5 followed by Gnrhr and steroidogenic factor Sf1 at E13.5, specifying cells engaged in a gonadotrope cell fate. Lhb and Fshb appear at E16.5 and 17.5, respectively, typifying differentiated gonadotrope cells. Using the αT1-1, αT3-1 and LβT2 cell lines recapitulating these stages of gonadotrope differentiation, DNA methylation at Gnrhr and Sf1 was investigated. Regulatory regions were found hypermethylated in progenitor αT1-1 cells and hypomethylated in differentiated LβT2 cells. Abundance of RNA polymerase II together with active histone modifications including H3K4me1, H3K4me3, and H3K27ac were strictly correlated with DNA hypomethylation. Analyses of epigenomic modifications and chromatin accessibility were further extended to Isl1, Lhx3, Gata2, and Pitx2, highlighting alternative usages of specific regulatory gene domains in progenitor αT1-1, immature αT3-1, and mature LβT2 gonadotrope cells.

The human-induced pluripotent stem cell initiative-data resources for cellular genetics

The Human Induced Pluripotent Stem Cell Initiative (HipSci) isf establishing a large catalogue of human iPSC lines, arguably the most well characterized collection to date. The HipSci portal enables researchers to choose the right cell line for their experiment, and makes HipSci's rich catalogue of assay data easy to discover and reuse. Each cell line has genomic, transcriptomic, proteomic and cellular phenotyping data. Data are deposited in the appropriate EMBL-EBI archives, including the European Nucleotide Archive (ENA), European Genome-phenome Archive (EGA), ArrayExpress and PRoteomics IDEntifications (PRIDE) databases. The project will make 500 cell lines from healthy individuals, and from 150 patients with rare genetic diseases; these will be available through the European Collection of Authenticated Cell Cultures (ECACC). As of August 2016, 238 cell lines are available for purchase. Project data is presented through the HipSci data portal (http://www.hipsci.org/lines) and is downloadable from the associated FTP site (ftp://ftp.hipsci.ebi.ac.uk/vol1/ftp). The data portal presents a summary matrix of the HipSci cell lines, showing available data types. Each line has its own page containing descriptive metadata, quality information, and links to archived assay data. Analysis results are also available in a Track Hub, allowing visualization in the context of public genomic annotations (http://www.hipsci.org/data/trackhubs).

COSMIC: High-Resolution Cancer Genetics Using the Catalogue of Somatic Mutations in Cancer

COSMIC (http://cancer.sanger.ac.uk) is an expert-curated database of somatic mutations in human cancer. Broad and comprehensive in scope, recent releases in 2016 describe over 4 million coding mutations across all human cancer disease types. Mutations are annotated across the entire genome, but expert curation is focused on over 400 key cancer genes. Now encompassing the majority of molecular mutation mechanisms in oncogenetics, COSMIC additionally describes 10 million non-coding mutations, 1 million copy-number aberrations, 9 million gene-expression variants, and almost 8 million differentially methylated CpGs. This information combines a consistent interpretation of the data from the major cancer genome consortia and cancer genome literature with exhaustive hand curation of over 22,000 gene-specific literature publications. This unit describes the graphical Web site in detail; alternative protocols overview other ways the entire database can be accessed, analyzed, and downloaded. © 2016 by John Wiley & Sons, Inc.

A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease

The interpretation of non-coding variants still constitutes a major challenge in the application of whole-genome sequencing in Mendelian disease, especially for single-nucleotide and other small non-coding variants. Here we present Genomiser, an analysis framework that is able not only to score the relevance of variation in the non-coding genome, but also to associate regulatory variants to specific Mendelian diseases. Genomiser scores variants through either existing methods such as CADD or a bespoke machine learning method and combines these with allele frequency, regulatory sequences, chromosomal topological domains, and phenotypic relevance to discover variants associated to specific Mendelian disorders. Overall, Genomiser is able to identify causal regulatory variants as the top candidate in 77% of simulated whole genomes, allowing effective detection and discovery of regulatory variants in Mendelian disease.

Candidate SNP Markers of Chronopathologies Are Predicted by a Significant Change in the Affinity of TATA-Binding Protein for Human Gene Promoters

Variations in human genome (e.g., single nucleotide polymorphisms, SNPs) may be associated with hereditary diseases, their complications, comorbidities, and drug responses. Using Web service SNP_TATA_Comparator presented in our previous paper, here we analyzed immediate surroundings of known SNP markers of diseases and identified several candidate SNP markers that can significantly change the affinity of TATA-binding protein for human gene promoters, with circadian consequences. For example, rs572527200 may be related to asthma, where symptoms are circadian (worse at night), and rs367732974 may be associated with heart attacks that are characterized by a circadian preference (early morning). By the same method, we analyzed the 90 bp proximal promoter region of each protein-coding transcript of each human gene of the circadian clock core. This analysis yielded 53 candidate SNP markers, such as rs181985043 (susceptibility to acute Q fever in male patients), rs192518038 (higher risk of a heart attack in patients with diabetes), and rs374778785 (emphysema and lung cancer in smokers). If they are properly validated according to clinical standards, these candidate SNP markers may turn out to be useful for physicians (to select optimal treatment for each patient) and for the general population (to choose a lifestyle preventing possible circadian complications of diseases).

Asparaginase-associated pancreatitis: a study on phenotype and genotype in the NOPHO ALL2008 protocol

Asparaginase (ASP)-associated pancreatitis (AAP) occurs during acute lymphoblastic leukemia treatment. Among 1285 children (1.0-17.9 years) diagnosed during July 2008-December 2014 and treated according to the Nordic/Baltic ALL2008 protocol, 86 (cumulative incidence=6.8%) developed AAP. Seventy-three cases were severe (diagnostic AAP criteria persisting >72 h) and 13 mild. Cases were older than controls (median: 6.5 vs 4.5 years; P=0.001). Pseudocysts developed in 28%. Of the 20 re-exposed to ASP, 9 (45%) developed a second AAP. After a median follow-up of 2.3 years, 8% needed permanent insulin therapy, and 7% had recurrent abdominal pain. Germline DNA on 62 cases and 638 controls was genotyped on Omni2.5exome-8-v1.2 BeadChip arrays. Overall, the ULK2 variant rs281366 showed the strongest association with AAP (P=5.8 × 10^-7; odds ratio (OR)=6.7). Cases with the rs281366 variant were younger (4.3 vs 8 years; P=0.015) and had lower risk of AAP-related complications (15% vs 43%; P=0.13) compared with cases without this variant. Among 45 cases and 517 controls <10 years, the strongest associations with AAP were found for RGS6 variant rs17179470 (P=9.8 × 10^-9; OR=7.3). Rs281366 is located in the ULK2 gene involved in autophagy, and RGS6 regulates G-protein signaling regulating cell dynamics. More than 50% of AAP cases <10 years carried one or both risk alleles.

Transgenic Overexpression of Aryl Hydrocarbon Receptor Repressor (AhRR) and AhR-Mediated Induction of CYP1A1, Cytokines, and Acute Toxicity

BACKGROUND

The aryl hydrocarbon receptor repressor (AhRR) is known to repress aryl hydrocarbon receptor (AhR) signaling, but very little is known regarding the role of the AhRR in vivo.

OBJECTIVE

This study tested the role of AhRR in vivo in AhRR overexpressing mice on molecular and toxic end points mediated through a prototypical AhR ligand.

METHODS

We generated AhRR-transgenic mice (AhRR Tg) based on the genetic background of C57BL/6J wild type (wt) mice. We tested the effect of the prototypical AhR ligand 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) on the expression of cytochrome P450 (CYP)1A1 and cytokines in various tissues of mice. We next analyzed the infiltration of immune cells in adipose tissue of mice after treatment with TCDD using flow cytometry.

RESULTS

AhRR Tg mice express significantly higher levels of AhRR compared to wt mice. Activation of AhR by TCDD caused a significant increase of the inflammatory cytokines Interleukin (IL)-1β, IL-6 and IL-10, and CXCL chemokines in white epididymal adipose tissue from both wt and AhRR Tg mice. However, the expression of IL-1β, CXCL2 and CXCL3 were significantly lower in AhRR Tg versus wt mice following TCDD treatment. Exposure to TCDD caused a rapid accumulation of neutrophils and macrophages in white adipose tissue of wt and AhRR Tg mice. Furthermore we found that male AhRR Tg mice were protected from high-dose TCDD-induced lethality associated with a reduced inflammatory response and liver damage as indicated by lower levels of TCDD-induced alanine aminotransferase and hepatic triglycerides. Females from both wt and AhRR Tg mice were less sensitive than male mice to acute toxicity induced by TCDD.

CONCLUSION

In conclusion, the current study identifies AhRR as a previously uncharacterized regulator of specific inflammatory cytokines, which may protect from acute toxicity induced by TCDD.

CITATION

Vogel CF, Chang WL, Kado S, McCulloh K, Vogel H, Wu D, Haarmann-Stemmann T, Yang GX, Leung PS, Matsumura F, Gershwin ME. 2016. Transgenic overexpression of aryl hydrocarbon receptor repressor (AhRR) and AhR-mediated induction of CYP1A1, cytokines, and acute toxicity. Environ Health Perspect 124:1071-1083; http://dx.doi.org/10.1289/ehp.1510194.

Genetic and neuroendocrine regulation of the postpartum brain

Changes in expression of hundreds of genes occur during the production and function of the maternal brain that support a wide range of processes. In this review, we synthesize findings from four microarray studies of different maternal brain regions and identify a core group of 700 maternal genes that show significant expression changes across multiple regions. With those maternal genes, we provide new insights into reward-related pathways (maternal bonding), postpartum depression, social behaviors, mental health disorders, and nervous system plasticity/developmental events. We also integrate the new genes into well-studied maternal signaling pathways, including those for prolactin, oxytocin/vasopressin, endogenous opioids, and steroid receptors (estradiol, progesterone, cortisol). A newer transcriptional regulation model for the maternal brain is provided that incorporates recent work on maternal microRNAs. We also compare the top 700 genes with other maternal gene expression studies. Together, we highlight new genes and new directions for studies on the postpartum brain.

Whole-genome sequencing of nine esophageal adenocarcinoma cell lines

Esophageal adenocarcinoma (EAC) is highly mutated and molecularly heterogeneous. The number of cell lines available for study is limited and their genome has been only partially characterized. The availability of an accurate annotation of their mutational landscape is crucial for accurate experimental design and correct interpretation of genotype-phenotype findings. We performed high coverage, paired end whole genome sequencing on eight EAC cell lines-ESO26, ESO51, FLO-1, JH-EsoAd1, OACM5.1 C, OACP4 C, OE33, SK-GT-4-all verified against original patient material, and one esophageal high grade dysplasia cell line, CP-D. We have made available the aligned sequence data and report single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number alterations, identified by comparison with the human reference genome and known single nucleotide polymorphisms (SNPs). We compare these putative mutations to mutations found in primary tissue EAC samples, to inform the use of these cell lines as a model of EAC.

The Ensembl Variant Effect Predictor

The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

The Ensembl Variant Effect Predictor

The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

ChromNet: Learning the human chromatin network from all ENCODE ChIP-seq data

A cell's epigenome arises from interactions among regulatory factors-transcription factors and histone modifications-co-localized at particular genomic regions. We developed a novel statistical method, ChromNet, to infer a network of these interactions, the chromatin network, by inferring conditional-dependence relationships among a large number of ChIP-seq data sets. We applied ChromNet to all available 1451 ChIP-seq data sets from the ENCODE Project, and showed that ChromNet revealed previously known physical interactions better than alternative approaches. We experimentally validated one of the previously unreported interactions, MYC-HCFC1. An interactive visualization tool is available at http://chromnet.cs.washington.edu.

Candidate SNP Markers of Gender-Biased Autoimmune Complications of Monogenic Diseases Are Predicted by a Significant Change in the Affinity of TATA-Binding Protein for Human Gene Promoters

Some variations of human genome [for example, single nucleotide polymorphisms (SNPs)] are markers of hereditary diseases and drug responses. Analysis of them can help to improve treatment. Computer-based analysis of millions of SNPs in the 1000 Genomes project makes a search for SNP markers more targeted. Here, we combined two computer-based approaches: DNA sequence analysis and keyword search in databases. In the binding sites for TATA-binding protein (TBP) in human gene promoters, we found candidate SNP markers of gender-biased autoimmune diseases, including rs1143627 [cachexia in rheumatoid arthritis (double prevalence among women)]; rs11557611 [demyelinating diseases (thrice more prevalent among young white women than among non-white individuals)]; rs17231520 and rs569033466 [both: atherosclerosis comorbid with related diseases (double prevalence among women)]; rs563763767 [Hughes syndrome-related thrombosis (lethal during pregnancy)]; rs2814778 [autoimmune diseases (excluding multiple sclerosis and rheumatoid arthritis) underlying hypergammaglobulinemia in women]; rs72661131 and rs562962093 (both: preterm delivery in pregnant diabetic women); and rs35518301, rs34166473, rs34500389, rs33981098, rs33980857, rs397509430, rs34598529, rs33931746, rs281864525, and rs63750953 (all: autoimmune diseases underlying hypergammaglobulinemia in women). Validation of these predicted candidate SNP markers using the clinical standards may advance personalized medicine.

Ensembl regulation resources

New experimental techniques in epigenomics allow researchers to assay a diversity of highly dynamic features such as histone marks, DNA modifications or chromatin structure. The study of their fluctuations should provide insights into gene expression regulation, cell differentiation and disease. The Ensembl project collects and maintains the Ensembl regulation data resources on epigenetic marks, transcription factor binding and DNA methylation for human and mouse, as well as microarray probe mappings and annotations for a variety of chordate genomes. From this data, we produce a functional annotation of the regulatory elements along the human and mouse genomes with plans to expand to other species as data becomes available. Starting from well-studied cell lines, we will progressively expand our library of measurements to a greater variety of samples. Ensembl’s regulation resources provide a central and easy-to-query repository for reference epigenomes. As with all Ensembl data, it is freely available at http://www.ensembl.org, from the Perl and REST APIs and from the public Ensembl MySQL database server at ensembldb.ensembl.org.

Database URL: http://www.ensembl.org

Ensembl 2016

The Ensembl project (http://www.ensembl.org) is a system for genome annotation, analysis, storage and dissemination designed to facilitate the access of genomic annotation from chordates and key model organisms. It provides access to data from 87 species across our main and early access Pre! websites. This year we introduced three newly annotated species and released numerous updates across our supported species with a concentration on data for the latest genome assemblies of human, mouse, zebrafish and rat. We also provided two data updates for the previous human assembly, GRCh37, through a dedicated website (http://grch37.ensembl.org). Our tools, in particular the VEP, have been improved significantly through integration of additional third party data. REST is now capable of larger-scale analysis and our regulatory data BioMart can deliver faster results. The website is now capable of displaying long-range interactions such as those found in cis-regulated datasets. Finally we have launched a website optimized for mobile devices providing views of genes, variants and phenotypes. Our data is made available without restriction and all code is available from our GitHub organization site (http://github.com/Ensembl) under an Apache 2.0 license.

Systems Biology Approaches for Understanding Genome Architecture

The linear and three-dimensional arrangement and composition of chromatin in eukaryotic genomes underlies the mechanisms directing gene regulation. Understanding this organization requires the integration of many data types and experimental results. Here we describe the approach of integrating genome-wide protein-DNA binding data to determine chromatin states. To investigate spatial aspects of genome organization, we present a detailed description of how to run stochastic simulations of protein movements within a simulated nucleus in 3D. This systems level approach enables the development of novel questions aimed at understanding the basic mechanisms that regulate genome dynamics.

Obesity-related known and candidate SNP markers can significantly change affinity of TATA-binding protein for human gene promoters

BACKGROUND

Obesity affects quality of life and life expectancy and is associated with cardiovascular disorders, cancer, diabetes, reproductive disorders in women, prostate diseases in men, and congenital anomalies in children. The use of single nucleotide polymorphism (SNP) markers of diseases and drug responses (i.e., significant differences of personal genomes of patients from the reference human genome) can help physicians to improve treatment. Clinical research can validate SNP markers via genotyping of patients and demonstration that SNP alleles are significantly more frequent in patients than in healthy people. The search for biomedical SNP markers of interest can be accelerated by computer-based analysis of hundreds of millions of SNPs in the 1000 Genomes project because of selection of the most meaningful candidate SNP markers and elimination of neutral SNPs.

RESULTS

We cross-validated the output of two computer-based methods: DNA sequence analysis using Web service SNP_TATA_Comparator and keyword search for articles on comorbidities of obesity. Near the sites binding to TATA-binding protein (TBP) in human gene promoters, we found 22 obesity-related candidate SNP markers, including rs10895068 (male breast cancer in obesity); rs35036378 (reduced risk of obesity after ovariectomy); rs201739205 (reduced risk of obesity-related cancers due to weight loss by diet/exercise in obese postmenopausal women); rs183433761 (obesity resistance during a high-fat diet); rs367732974 and rs549591993 (both: cardiovascular complications in obese patients with type 2 diabetes mellitus); rs200487063 and rs34104384 (both: obesity-caused hypertension); rs35518301, rs72661131, and rs562962093 (all: obesity); and rs397509430, rs33980857, rs34598529, rs33931746, rs33981098, rs34500389, rs63750953, rs281864525, rs35518301, and rs34166473 (all: chronic inflammation in comorbidities of obesity). Using an electrophoretic mobility shift assay under nonequilibrium conditions, we empirically validated the statistical significance (α < 0.00025) of the differences in TBP affinity values between the minor and ancestral alleles of 4 out of the 22 SNPs: rs200487063, rs201381696, rs34104384, and rs183433761. We also measured half-life (t1/2), Gibbs free energy change (ΔG), and the association and dissociation rate constants, ka and kd, of the TBP-DNA complex for these SNPs.

CONCLUSIONS

Validation of the 22 candidate SNP markers by proper clinical protocols appears to have a strong rationale and may advance postgenomic predictive preventive personalized medicine.

INSECT 2.0: a web-server for genome-wide cis-regulatory modules prediction

INSECT is a user-friendly web server to predict the occurrence of Cis-Regulatory Modules (CRMs), which control gene expression. Here, we present a new release of INSECT which includes several new features, such as whole genome analysis, nucleosome occupancy predictions, and which provides additional links to third-party functional tools that complement user capabilities, CRM analysis and hypothesis construction. Improvements in the core implementation have led to a faster and more efficient tool. In addition, this new release introduces a new interface designed for a more integrative and dynamic user experience.

AVAILABILITY AND IMPLEMENTATION

http://bioinformatics.ibioba-mpsp-conicet.gov.ar/INSECT2 CONTACT: pyankilevich@ibioba-mpsp-conicet.gov.ar.

PExFInS: An Integrative Post-GWAS Explorer for Functional Indels and SNPs

Expression quantitative trait loci (eQTLs) mapping and linkage disequilibrium (LD) analysis have been widely employed to interpret findings of genome-wide association studies (GWAS). With the availability of deep sequencing data of 423 lymphoblastoid cell lines (LCLs) from six global populations and the microarray expression data, we performed eQTL analysis, identified more than 228 K SNP cis-eQTLs and 21 K indel cis-eQTLs and generated a LCL cis-eQTL database. We demonstrate that the percentages of population-shared and population-specific cis-eQTLs are comparable; while indel cis-eQTLs in the population-specific subsection make more contribution to gene expression variations than those in the population-shared subsection. We found cis-eQTLs, especially the population-shared cis-eQTLs are significantly enriched toward transcription start site. Moreover, the National Human Genome Research Institute cataloged GWAS SNPs are enriched for LCL cis-eQTLs. Specifically, 32.8% GWAS SNPs are LCL cis-eQTLs, among which 12.5% can be tagged by indel cis-eQTLs, suggesting the fundamental contribution of indel cis-eQTLs to GWAS association signals. To search for functional indels and SNPs tagging GWAS SNPs, a pipeline Post-GWAS Explorer for Functional Indels and SNPs (PExFInS) has been developed, integrating LD analysis, functional annotation from public databases, cis-eQTL mapping with our LCL cis-eQTL database and other published cis-eQTL datasets.

ORegAnno 3.0: a community-driven resource for curated regulatory annotation

The Open Regulatory Annotation database (ORegAnno) is a resource for curated regulatory annotation. It contains information about regulatory regions, transcription factor binding sites, RNA binding sites, regulatory variants, haplotypes, and other regulatory elements. ORegAnno differentiates itself from other regulatory resources by facilitating crowd-sourced interpretation and annotation of regulatory observations from the literature and highly curated resources. It contains a comprehensive annotation scheme that aims to describe both the elements and outcomes of regulatory events. Moreover, ORegAnno assembles these disparate data sources and annotations into a single, high quality catalogue of curated regulatory information. The current release is an update of the database previously featured in the NAR Database Issue, and now contains 1 948 307 records, across 18 species, with a combined coverage of 334 215 080 bp. Complete records, annotation, and other associated data are available for browsing and download at http://www.oreganno.org/.

An Xist-activating antisense RNA required for X-chromosome inactivation

The transcriptional imbalance due to the difference in the number of X chromosomes between male and female mammals is remedied through X-chromosome inactivation, the epigenetic transcriptional silencing of one of the two X chromosomes in females. The X-linked Xist long non-coding RNA functions as an X inactivation master regulator; Xist is selectively upregulated from the prospective inactive X chromosome and is required in cis for X inactivation. Here we discover an Xist antisense long non-coding RNA, XistAR (XistActivating RNA), which is encoded within exon 1 of the mouse Xist gene and is transcribed only from the inactive X chromosome. Selective truncation of XistAR, while sparing the overlapping Xist RNA, leads to a deficiency in Xist RNA expression in cis during the initiation of X inactivation. Thus, the Xist gene carries within its coding sequence an antisense RNA that drives Xist expression.

The X-chromosome linked long non-coding RNA, Xist, is a master regulator of the X inactivation. Here, the authors report that XistAR, an Xist anti-sense long non-coding RNA encoded within the mouse Xist gene and transcribed only from the inactive X chromosome, regulates Xist expression.

Public data and open source tools for multi-assay genomic investigation of disease

Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition. Finally, we review bioinformatic tools that are explicitly geared toward integrative genomic data visualization and analysis. This review provides starting points for accessing publicly available data and tools to support development of needed integrative methods.

How to Use SNP_TATA_Comparator to Find a Significant Change in Gene Expression Caused by the Regulatory SNP of This Gene's Promoter via a Change in Affinity of the TATA-Binding Protein for This Promoter

The use of biomedical SNP markers of diseases can improve effectiveness of treatment. Genotyping of patients with subsequent searching for SNPs more frequent than in norm is the only commonly accepted method for identification of SNP markers within the framework of translational research. The bioinformatics applications aimed at millions of unannotated SNPs of the "1000 Genomes" can make this search for SNP markers more focused and less expensive. We used our Web service involving Fisher's Z-score for candidate SNP markers to find a significant change in a gene's expression. Here we analyzed the change caused by SNPs in the gene's promoter via a change in affinity of the TATA-binding protein for this promoter. We provide examples and discuss how to use this bioinformatics application in the course of practical analysis of unannotated SNPs from the "1000 Genomes" project. Using known biomedical SNP markers, we identified 17 novel candidate SNP markers nearby: rs549858786 (rheumatoid arthritis); rs72661131 (cardiovascular events in rheumatoid arthritis); rs562962093 (stroke); rs563558831 (cyclophosphamide bioactivation); rs55878706 (malaria resistance, leukopenia), rs572527200 (asthma, systemic sclerosis, and psoriasis), rs371045754 (hemophilia B), rs587745372 (cardiovascular events); rs372329931, rs200209906, rs367732974, and rs549591993 (all four: cancer); rs17231520 and rs569033466 (both: atherosclerosis); rs63750953, rs281864525, and rs34166473 (all three: malaria resistance, thalassemia).