Publications by authors named "Steven P Wilder"

34 Publications

Systems Genetics of Hepatic Metabolome Reveals Octopamine as a Target for Non-Alcoholic Fatty Liver Disease Treatment.

Sci Rep 2019 03 6;9(1):3656. Epub 2019 Mar 6.

Sorbonne University, University Paris Descartes, University Paris Diderot, INSERM UMR_S 1138, Cordeliers Research Centre, 75006, Paris, France.

Non-alcoholic fatty liver disease (NAFLD) is often associated with obesity and type 2 diabetes. To disentangle etiological relationships between these conditions and identify genetically-determined metabolites involved in NAFLD processes, we mapped H nuclear magnetic resonance (NMR) metabolomic and disease-related phenotypes in a mouse F2 cross derived from strains showing resistance (BALB/c) and increased susceptibility (129S6) to these diseases. Quantitative trait locus (QTL) analysis based on single nucleotide polymorphism (SNP) genotypes identified diet responsive QTLs in F2 mice fed control or high fat diet (HFD). In HFD fed F2 mice we mapped on chromosome 18 a QTL regulating liver micro- and macrovesicular steatosis and inflammation, independently from glucose intolerance and adiposity, which was linked to chromosome 4. Linkage analysis of liver metabolomic profiling data identified a QTL for octopamine, which co-localised with the QTL for liver histopathology in the cross. Functional relationship between these two QTLs was validated in vivo in mice chronically treated with octopamine, which exhibited reduction in liver histopathology and metabolic benefits, underlining its role as a mechanistic biomarker of fatty liver with potential therapeutic applications.
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http://dx.doi.org/10.1038/s41598-019-40153-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6403227PMC
March 2019

Ensembl 2017.

Nucleic Acids Res 2017 01 28;45(D1):D635-D642. Epub 2016 Nov 28.

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.

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.
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http://dx.doi.org/10.1093/nar/gkw1104DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210575PMC
January 2017

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.

Cell 2016 11;167(5):1415-1429.e19

Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK.

Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.
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http://dx.doi.org/10.1016/j.cell.2016.10.042DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5300907PMC
November 2016

Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells.

Cell 2016 11;167(5):1398-1414.e24

Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada.

Characterizing the multifaceted contribution of genetic and epigenetic factors to disease phenotypes is a major challenge in human genetics and medicine. We carried out high-resolution genetic, epigenetic, and transcriptomic profiling in three major human immune cell types (CD14 monocytes, CD16 neutrophils, and naive CD4 T cells) from up to 197 individuals. We assess, quantitatively, the relative contribution of cis-genetic and epigenetic factors to transcription and evaluate their impact as potential sources of confounding in epigenome-wide association studies. Further, we characterize highly coordinated genetic effects on gene expression, methylation, and histone variation through quantitative trait locus (QTL) mapping and allele-specific (AS) analyses. Finally, we demonstrate colocalization of molecular trait QTLs at 345 unique immune disease loci. This expansive, high-resolution atlas of multi-omics changes yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk.
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http://dx.doi.org/10.1016/j.cell.2016.10.026DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5119954PMC
November 2016

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

Cell 2016 11;167(5):1369-1384.e19

Nuclear Dynamics Programme, The Babraham Institute, Babraham Research Campus, Cambridge CB22 3AT, UK. Electronic address:

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.
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http://dx.doi.org/10.1016/j.cell.2016.09.037DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5123897PMC
November 2016

Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.

Genome Med 2016 09 30;8(1):101. Epub 2016 Sep 30.

Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Sir Alexander Fleming Building, Imperial College, London, SW7 2AZ, UK.

Background: The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits.

Methods: We used systematic metabotyping by H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block.

Results: Despite strong genomic similarities (95-99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing the shortest path length drove prioritization of biological validations by gene silencing.

Conclusions: These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulation and to characterize novel functional roles for genes determining tissue-specific metabolism.
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http://dx.doi.org/10.1186/s13073-016-0352-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5045612PMC
September 2016

Transcriptome Profiling in Rat Inbred Strains and Experimental Cross Reveals Discrepant Genetic Architecture of Genome-Wide Gene Expression.

G3 (Bethesda) 2016 Nov 8;6(11):3671-3683. Epub 2016 Nov 8.

The Wellcome Trust Centre for Human Genetics, University of Oxford, OX3 7BN, United Kingdom

To test the impact of genetic heterogeneity on - and -mediated mechanisms of gene expression regulation, we profiled the transcriptome of adipose tissue in 20 inbred congenic strains derived from diabetic Goto-Kakizaki (GK) rats and Brown-Norway (BN) controls, which contain well-defined blocks (1-183 Mb) of genetic polymorphisms, and in 123 genetically heterogeneous rats of an (GK × BN)F2 offspring. Within each congenic we identified 73-1351 differentially expressed genes (DEGs), only 7.7% of which mapped within the congenic blocks, and which may be regulated in The remainder localized outside the blocks, and therefore must be regulated in Most -regulated genes exhibited approximately twofold expression changes, consistent with monoallelic expression. Altered biological pathways were replicated between congenic strains sharing blocks of genetic polymorphisms, but polymorphisms at different loci also had redundant effects on transcription of common distant genes and pathways. We mapped 2735 expression quantitative trait loci (eQTL) in the F2 cross, including 26% predominantly -regulated genes, which validated DEGs in congenic strains. A hotspot of >300 eQTL in a 10 cM region of chromosome 1 was enriched in DEGs in a congenic strain. However, many DEGs among GK, BN and congenic strains did not replicate as eQTL in F2 hybrids, demonstrating distinct mechanisms of gene expression when alleles segregate in an outbred population or are fixed homozygous across the entire genome or in short genomic regions. Our analysis provides conceptual advances in our understanding of the complex architecture of genome expression and pathway regulation, and suggests a prominent impact of epistasis and monoallelic expression on gene transcription.
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http://dx.doi.org/10.1534/g3.116.033274DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5100866PMC
November 2016

Ensembl regulation resources.

Database (Oxford) 2016 17;2016. Epub 2016 Feb 17.

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.

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.
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http://dx.doi.org/10.1093/database/bav119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4756621PMC
October 2016

Ensembl 2016.

Nucleic Acids Res 2016 Jan 19;44(D1):D710-6. Epub 2015 Dec 19.

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.

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.
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http://dx.doi.org/10.1093/nar/gkv1157DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702834PMC
January 2016

The ensembl regulatory build.

Genome Biol 2015 Mar 24;16:56. Epub 2015 Mar 24.

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.

Most genomic variants associated with phenotypic traits or disease do not fall within gene coding regions, but in regulatory regions, rendering their interpretation difficult. We collected public data on epigenetic marks and transcription factor binding in human cell types and used it to construct an intuitive summary of regulatory regions in the human genome. We verified it against independent assays for sensitivity. The Ensembl Regulatory Build will be progressively enriched when more data is made available. It is freely available on the Ensembl browser, from the Ensembl Regulation MySQL database server and in a dedicated track hub.
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http://dx.doi.org/10.1186/s13059-015-0621-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4407537PMC
March 2015

Ensembl 2015.

Nucleic Acids Res 2015 Jan 28;43(Database issue):D662-9. Epub 2014 Oct 28.

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.

Ensembl (http://www.ensembl.org) is a genomic interpretation system providing the most up-to-date annotations, querying tools and access methods for chordates and key model organisms. This year we released updated annotation (gene models, comparative genomics, regulatory regions and variation) on the new human assembly, GRCh38, although we continue to support researchers using the GRCh37.p13 assembly through a dedicated site (http://grch37.ensembl.org). Our Regulatory Build has been revamped to identify regulatory regions of interest and to efficiently highlight their activity across disparate epigenetic data sets. A number of new interfaces allow users to perform large-scale comparisons of their data against our annotations. The REST server (http://rest.ensembl.org), which allows programs written in any language to query our databases, has moved to a full service alongside our upgraded website tools. Our online Variant Effect Predictor tool has been updated to process more variants and calculate summary statistics. Lastly, the WiggleTools package enables users to summarize large collections of data sets and view them as single tracks in Ensembl. The Ensembl code base itself is more accessible: it is now hosted on our GitHub organization page (https://github.com/Ensembl) under an Apache 2.0 open source license.
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http://dx.doi.org/10.1093/nar/gku1010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4383879PMC
January 2015

Adaptive expression of microRNA-125a in adipose tissue in response to obesity in mice and men.

PLoS One 2014 27;9(3):e91375. Epub 2014 Mar 27.

Institut National de la Santé et de la Recherche Médicale (INSERM) UMRS 872, Cordeliers Research Center, University Pierre & Marie Curie, Paris, France; Institute of Cardiometabolism & Nutrition, ICAN, Pitié-Salpêtrière Hospital, University Pierre & Marie-Curie, Paris, France.

MicroRNAs are emerging as new mediators in the regulation of adipose tissue biology and the development of obesity. An important role of microRNA-125a has been suggested in the pathogenesis of insulin resistance (IR). Here, we characterized the function of microRNA-125a in adipose tissue in a context of experimentally-induced IR and obesity in mice and in obese patients. We showed time dependent overexpression of the microRNA in adipose tissue of BALB/c and C57BL/6J mice in response to high fat diet (HFD) feeding. MicroRNA-125a expression was downregulated in vitro in insulin resistant 3T3-L1 adipocytes and ex vivo in adipose tissue of obese patients. In vitro modulation of microRNA-125a expression in 3T3-L1 adipocytes did not affect glucose uptake. Gene set enrichment analysis (GSEA) identified significantly altered expression patterns of predicted microRNA-125a gene targets in transcriptomic datasets of adipose tissue from HFD-fed mice and obese patients. Among genes that contributed to global enrichment of altered expression of microRNA-125a targets, Thyrotroph embryonic factor (Tef), Mannan-binding lectin serine peptidase 1, Reticulon 2 and Ubiquitin-conjugating enzyme E2L3 were significantly differentially expressed in adipose tissue in these groups. We showed that Tef expression is reduced in adipose tissue of obese patients following gastric bypass surgery. Our findings indicate that microRNA-125a expression in adipose tissue adapts to IR and may play a role in the development of obesity in mice and obese subjects through uncoupled regulation of the expression of microRNA-125a and its targets.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0091375PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3967993PMC
December 2015

WiggleTools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis.

Bioinformatics 2014 Apr 19;30(7):1008-9. Epub 2013 Dec 19.

European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.

Motivation: Using high-throughput sequencing, researchers are now generating hundreds of whole-genome assays to measure various features such as transcription factor binding, histone marks, DNA methylation or RNA transcription. Displaying so much data generally leads to a confusing accumulation of plots. We describe here a multithreaded library that computes statistics on large numbers of datasets (Wiggle, BigWig, Bed, BigBed and BAM), generating statistical summaries within minutes with limited memory requirements, whether on the whole genome or on selected regions.

Availability And Implementation: The code is freely available under Apache 2.0 license at www.github.com/Ensembl/Wiggletools
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http://dx.doi.org/10.1093/bioinformatics/btt737DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3967112PMC
April 2014

Nutrigenomics of high fat diet induced obesity in mice suggests relationships between susceptibility to fatty liver disease and the proteasome.

PLoS One 2013 6;8(12):e82825. Epub 2013 Dec 6.

The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.

Nutritional factors play important roles in the etiology of obesity, type 2 diabetes mellitus and their complications through genotype x environment interactions. We have characterised molecular adaptation to high fat diet (HFD) feeding in inbred mouse strains widely used in genetic and physiological studies. We carried out physiological tests, plasma lipid assays, obesity measures, liver histology, hepatic lipid measurements and liver genome-wide gene transcription profiling in C57BL/6J and BALB/c mice fed either a control or a high fat diet. The two strains showed marked susceptibility (C57BL/6J) and relative resistance (BALB/c) to HFD-induced insulin resistance and non alcoholic fatty liver disease (NAFLD). Global gene set enrichment analysis (GSEA) of transcriptome data identified consistent patterns of expression of key genes (Srebf1, Stard4, Pnpla2, Ccnd1) and molecular pathways in the two strains, which may underlie homeostatic adaptations to dietary fat. Differential regulation of pathways, including the proteasome, the ubiquitin mediated proteolysis and PPAR signalling in fat fed C57BL/6J and BALB/c suggests that altered expression of underlying diet-responsive genes may be involved in contrasting nutrigenomic predisposition and resistance to insulin resistance and NAFLD in these models. Collectively, these data, which further demonstrate the impact of gene x environment interactions on gene expression regulations, contribute to improved knowledge of natural and pathogenic adaptive genomic regulations and molecular mechanisms associated with genetically determined susceptibility and resistance to metabolic diseases.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0082825PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3855786PMC
July 2014

Ensembl 2014.

Nucleic Acids Res 2014 Jan 6;42(Database issue):D749-55. Epub 2013 Dec 6.

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD and Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.

Ensembl (http://www.ensembl.org) creates tools and data resources to facilitate genomic analysis in chordate species with an emphasis on human, major vertebrate model organisms and farm animals. Over the past year we have increased the number of species that we support to 77 and expanded our genome browser with a new scrollable overview and improved variation and phenotype views. We also report updates to our core datasets and improvements to our gene homology relationships from the addition of new species. Our REST service has been extended with additional support for comparative genomics and ontology information. Finally, we provide updated information about our methods for data access and resources for user training.
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http://dx.doi.org/10.1093/nar/gkt1196DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3964975PMC
January 2014

Integrative annotation of chromatin elements from ENCODE data.

Nucleic Acids Res 2013 Jan 5;41(2):827-41. Epub 2012 Dec 5.

Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195-5065, USA.

The ENCODE Project has generated a wealth of experimental information mapping diverse chromatin properties in several human cell lines. Although each such data track is independently informative toward the annotation of regulatory elements, their interrelations contain much richer information for the systematic annotation of regulatory elements. To uncover these interrelations and to generate an interpretable summary of the massive datasets of the ENCODE Project, we apply unsupervised learning methodologies, converting dozens of chromatin datasets into discrete annotation maps of regulatory regions and other chromatin elements across the human genome. These methods rediscover and summarize diverse aspects of chromatin architecture, elucidate the interplay between chromatin activity and RNA transcription, and reveal that a large proportion of the genome lies in a quiescent state, even across multiple cell types. The resulting annotation of non-coding regulatory elements correlate strongly with mammalian evolutionary constraint, and provide an unbiased approach for evaluating metrics of evolutionary constraint in human. Lastly, we use the regulatory annotations to revisit previously uncharacterized disease-associated loci, resulting in focused, testable hypotheses through the lens of the chromatin landscape.
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http://dx.doi.org/10.1093/nar/gks1284DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3553955PMC
January 2013

Ensembl 2013.

Nucleic Acids Res 2013 Jan 30;41(Database issue):D48-55. Epub 2012 Nov 30.

European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton Cambridge CB10 1SD, UK.

The Ensembl project (http://www.ensembl.org) provides genome information for sequenced chordate genomes with a particular focus on human, mouse, zebrafish and rat. Our resources include evidenced-based gene sets for all supported species; large-scale whole genome multiple species alignments across vertebrates and clade-specific alignments for eutherian mammals, primates, birds and fish; variation data resources for 17 species and regulation annotations based on ENCODE and other data sets. Ensembl data are accessible through the genome browser at http://www.ensembl.org and through other tools and programmatic interfaces.
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http://dx.doi.org/10.1093/nar/gks1236DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531136PMC
January 2013

ENCODE data in the UCSC Genome Browser: year 5 update.

Nucleic Acids Res 2013 Jan 27;41(Database issue):D56-63. Epub 2012 Nov 27.

Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, CA 95064, USA.

The Encyclopedia of DNA Elements (ENCODE), http://encodeproject.org, has completed its fifth year of scientific collaboration to create a comprehensive catalog of functional elements in the human genome, and its third year of investigations in the mouse genome. Since the last report in this journal, the ENCODE human data repertoire has grown by 898 new experiments (totaling 2886), accompanied by a major integrative analysis. In the mouse genome, results from 404 new experiments became available this year, increasing the total to 583, collected during the course of the project. The University of California, Santa Cruz, makes this data available on the public Genome Browser http://genome.ucsc.edu for visual browsing and data mining. Download of raw and processed data files are all supported. The ENCODE portal provides specialized tools and information about the ENCODE data sets.
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http://dx.doi.org/10.1093/nar/gks1172DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531152PMC
January 2013

Ensembl 2012.

Nucleic Acids Res 2012 Jan 15;40(Database issue):D84-90. Epub 2011 Nov 15.

European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton Cambridge CB10 1SD, UK.

The Ensembl project (http://www.ensembl.org) provides genome resources for chordate genomes with a particular focus on human genome data as well as data for key model organisms such as mouse, rat and zebrafish. Five additional species were added in the last year including gibbon (Nomascus leucogenys) and Tasmanian devil (Sarcophilus harrisii) bringing the total number of supported species to 61 as of Ensembl release 64 (September 2011). Of these, 55 species appear on the main Ensembl website and six species are provided on the Ensembl preview site (Pre!Ensembl; http://pre.ensembl.org) with preliminary support. The past year has also seen improvements across the project.
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http://dx.doi.org/10.1093/nar/gkr991DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245178PMC
January 2012

Ensembl 2011.

Nucleic Acids Res 2011 Jan 2;39(Database issue):D800-6. Epub 2010 Nov 2.

European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.

The Ensembl project (http://www.ensembl.org) seeks to enable genomic science by providing high quality, integrated annotation on chordate and selected eukaryotic genomes within a consistent and accessible infrastructure. All supported species include comprehensive, evidence-based gene annotations and a selected set of genomes includes additional data focused on variation, comparative, evolutionary, functional and regulatory annotation. The most advanced resources are provided for key species including human, mouse, rat and zebrafish reflecting the popularity and importance of these species in biomedical research. As of Ensembl release 59 (August 2010), 56 species are supported of which 5 have been added in the past year. Since our previous report, we have substantially improved the presentation and integration of both data of disease relevance and the regulatory state of different cell types.
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http://dx.doi.org/10.1093/nar/gkq1064DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3013672PMC
January 2011

ATR-X syndrome protein targets tandem repeats and influences allele-specific expression in a size-dependent manner.

Cell 2010 Oct;143(3):367-78

Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, Headington, Oxford, UK.

ATRX is an X-linked gene of the SWI/SNF family, mutations in which cause syndromal mental retardation and downregulation of α-globin expression. Here we show that ATRX binds to tandem repeat (TR) sequences in both telomeres and euchromatin. Genes associated with these TRs can be dysregulated when ATRX is mutated, and the change in expression is determined by the size of the TR, producing skewed allelic expression. This reveals the characteristics of the affected genes, explains the variable phenotypes seen with identical ATRX mutations, and illustrates a new mechanism underlying variable penetrance. Many of the TRs are G rich and predicted to form non-B DNA structures (including G-quadruplex) in vivo. We show that ATRX binds G-quadruplex structures in vitro, suggesting a mechanism by which ATRX may play a role in various nuclear processes and how this is perturbed when ATRX is mutated.
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http://dx.doi.org/10.1016/j.cell.2010.09.023DOI Listing
October 2010

Chromosomal mapping of pancreatic islet morphological features and regulatory hormones in the spontaneously diabetic (Type 2) Goto-Kakizaki rat.

Mamm Genome 2010 Oct 29;21(9-10):499-508. Epub 2010 Sep 29.

The Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Headington, Oxford, OX3 7BN, UK.

Insulin resistance and altered endocrine pancreas function are central pathophysiological features of type 2 diabetes mellitus (T2DM). The Goto-Kakizaki (GK) rat is a model of spontaneous T2DM characterised by reduced beta cell mass and genetically determined glucose intolerance and altered insulin secretion. To identify genetic determinants of endocrine pancreas histopathology, we carried out quantitative trait locus (QTL) mapping of histological phenotypes (beta cell mass -BCM and insulin-positive cell area -IPCA) and plasma concentration of hormones and growth factors in a F2 cohort derived from GK and normoglycemic Brown Norway rats. Although IPCA and BCM in the duodenal region of the pancreas were highly positively correlated (P < 10(-6)), and similarly in the splenic region, both measures were poorly correlated when comparing duodenal and splenic phenotypes. Strongest evidence of linkage to pancreas morphological traits was obtained between BCM and chromosome 10 (LOD 3.2). Evidence of significant linkage (LOD 4.2) to plasma corticosterone was detected in a region of chromosome 1 distal to other QTLs previously identified in the GK. Male-specific genetic effects were detected, including linkages (LOD > 4) to growth hormome (GH) on chromosome 6 and prolactin on chromosome 17. These data suggest independent genetic control of the structure and function of ontologically different regions of the endocrine pancreas. Novel QTLs for corticosterone, prolactin and GH may contribute to diabetes in the GK. The QTLs that we have identified in this, and previous genetic studies collectively underline the complex and multiple mechanisms involved in diabetes in the GK strain.
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http://dx.doi.org/10.1007/s00335-010-9285-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2974204PMC
October 2010

Ensembl's 10th year.

Nucleic Acids Res 2010 Jan 11;38(Database issue):D557-62. Epub 2009 Nov 11.

European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.

Ensembl (http://www.ensembl.org) integrates genomic information for a comprehensive set of chordate genomes with a particular focus on resources for human, mouse, rat, zebrafish and other high-value sequenced genomes. We provide complete gene annotations for all supported species in addition to specific resources that target genome variation, function and evolution. Ensembl data is accessible in a variety of formats including via our genome browser, API and BioMart. This year marks the tenth anniversary of Ensembl and in that time the project has grown with advances in genome technology. As of release 56 (September 2009), Ensembl supports 51 species including marmoset, pig, zebra finch, lizard, gorilla and wallaby, which were added in the past year. Major additions and improvements to Ensembl since our previous report include the incorporation of the human GRCh37 assembly, enhanced visualisation and data-mining options for the Ensembl regulatory features and continued development of our software infrastructure.
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http://dx.doi.org/10.1093/nar/gkp972DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808936PMC
January 2010

Functional annotations of diabetes nephropathy susceptibility loci through analysis of genome-wide renal gene expression in rat models of diabetes mellitus.

BMC Med Genomics 2009 Jul 9;2:41. Epub 2009 Jul 9.

The Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.

Background: Hyperglycaemia in diabetes mellitus (DM) alters gene expression regulation in various organs and contributes to long term vascular and renal complications. We aimed to generate novel renal genome-wide gene transcription data in rat models of diabetes in order to test the responsiveness to hyperglycaemia and renal structural changes of positional candidate genes at selected diabetic nephropathy (DN) susceptibility loci.

Methods: Both Affymetrix and Illumina technologies were used to identify significant quantitative changes in the abundance of over 15,000 transcripts in kidney of models of spontaneous (genetically determined) mild hyperglycaemia and insulin resistance (Goto-Kakizaki-GK) and experimentally induced severe hyperglycaemia (Wistar-Kyoto-WKY rats injected with streptozotocin [STZ]).

Results: Different patterns of transcription regulation in the two rat models of diabetes likely underlie the roles of genetic variants and hyperglycaemia severity. The impact of prolonged hyperglycaemia on gene expression changes was more profound in STZ-WKY rats than in GK rats and involved largely different sets of genes. These included genes already tested in genetic studies of DN and a large number of protein coding sequences of unknown function which can be considered as functional and, when they map to DN loci, positional candidates for DN. Further expression analysis of rat orthologs of human DN positional candidate genes provided functional annotations of known and novel genes that are responsive to hyperglycaemia and may contribute to renal functional and/or structural alterations.

Conclusion: Combining transcriptomics in animal models and comparative genomics provides important information to improve functional annotations of disease susceptibility loci in humans and experimental support for testing candidate genes in human genetics.
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http://dx.doi.org/10.1186/1755-8794-2-41DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2717999PMC
July 2009

Comparative analysis of methods for gene transcription profiling data derived from different microarray technologies in rat and mouse models of diabetes.

BMC Genomics 2009 Feb 5;10:63. Epub 2009 Feb 5.

The Wellcome Trust Centre for Human Genetics, University of Oxford, Headington, Oxford, UK.

Background: Microarray technologies are widely used to quantify the abundance of transcripts corresponding to thousands of genes. To maximise the robustness of transcriptome results, we have tested the performance and reproducibility of rat and mouse gene expression data obtained with Affymetrix, Illumina and Operon platforms.

Results: We present a thorough analysis of the degree of reproducibility provided by analysing the transcriptomic profile of the same animals of several experimental groups under different popular microarray technologies in different tissues. Concordant results from inter- and intra-platform comparisons were maximised by testing many popular computational methods for generating fold changes and significances and by only considering oligonucleotides giving high expression levels. The choice of Affymetrix signal extraction technique was shown to have the greatest effect on the concordance across platforms. In both species, when choosing optimal methods, the agreement between data generated on the Affymetrix and Illumina was excellent; this was verified using qRT-PCR on a selection of genes present on all platforms.

Conclusion: This study provides an extensive assessment of analytical methods best suited for processing data from different microarray technologies and can assist integration of technologically different gene expression datasets in biological systems.
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http://dx.doi.org/10.1186/1471-2164-10-63DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2652496PMC
February 2009

Pathophysiological, genetic and gene expression features of a novel rodent model of the cardio-metabolic syndrome.

PLoS One 2008 Aug 13;3(8):e2962. Epub 2008 Aug 13.

The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.

Background: Complex etiology and pathogenesis of pathophysiological components of the cardio-metabolic syndrome have been demonstrated in humans and animal models.

Methodology/principal Findings: We have generated extensive physiological, genetic and genome-wide gene expression profiles in a congenic strain of the spontaneously diabetic Goto-Kakizaki (GK) rat containing a large region (110 cM, 170 Mb) of rat chromosome 1 (RNO1), which covers diabetes and obesity quantitative trait loci (QTL), introgressed onto the genetic background of the normoglycaemic Brown Norway (BN) strain. This novel disease model, which by the length of the congenic region closely mirrors the situation of a chromosome substitution strain, exhibits a wide range of abnormalities directly relevant to components of the cardio-metabolic syndrome and diabetes complications, including hyperglycaemia, hyperinsulinaemia, enhanced insulin secretion both in vivo and in vitro, insulin resistance, hypertriglyceridemia and altered pancreatic and renal histological structures. Gene transcription data in kidney, liver, skeletal muscle and white adipose tissue indicate that a disproportionately high number (43-83%) of genes differentially expressed between congenic and BN rats map to the GK genomic interval targeted in the congenic strain, which represents less than 5% of the total length of the rat genome. Genotype analysis of single nucleotide polymorphisms (SNPs) in strains genetically related to the GK highlights clusters of conserved and strain-specific variants in RNO1 that can assist the identification of naturally occurring variants isolated in diabetic and hypertensive strains when different phenotype selection procedures were applied.

Conclusions: Our results emphasize the importance of rat congenic models for defining the impact of genetic variants in well-characterised QTL regions on in vivo pathophysiological features and cis-/trans- regulation of gene expression. The congenic strain reported here provides a novel and sustainable model for investigating the pathogenesis and genetic basis of risks factors for the cardio-metabolic syndrome.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0002962PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2500170PMC
August 2008

Phylometabonomic patterns of adaptation to high fat diet feeding in inbred mice.

PLoS One 2008 Feb 27;3(2):e1668. Epub 2008 Feb 27.

The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.

Insulin resistance plays a central role in type 2 diabetes and obesity, which develop as a consequence of genetic and environmental factors. Dietary changes including high fat diet (HFD) feeding promotes insulin resistance in rodent models which present useful systems for studying interactions between genetic background and environmental influences contributing to disease susceptibility and progression. We applied a combination of classical physiological, biochemical and hormonal studies and plasma (1)H NMR spectroscopy-based metabonomics to characterize the phenotypic and metabotypic consequences of HFD (40%) feeding in inbred mouse strains (C57BL/6, 129S6, BALB/c, DBA/2, C3H) frequently used in genetic studies. We showed the wide range of phenotypic and metabonomic adaptations to HFD across the five strains and the increased nutrigenomic predisposition of 129S6 and C57BL/6 to insulin resistance and obesity relative to the other strains. In contrast mice of the BALB/c and DBA/2 strains showed relative resistance to HFD-induced glucose intolerance and obesity. Hierarchical metabonomic clustering derived from (1)H NMR spectral data of the strains provided a phylometabonomic classification of strain-specific metabolic features and differential responses to HFD which closely match SNP-based phylogenetic relationships between strains. Our results support the concept of genomic clustering of functionally related genes and provide important information for defining biological markers predicting spontaneous susceptibility to insulin resistance and pathological adaptations to fat feeding.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0001668PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2244706PMC
February 2008

Direct quantitative trait locus mapping of mammalian metabolic phenotypes in diabetic and normoglycemic rat models.

Nat Genet 2007 May 15;39(5):666-72. Epub 2007 Apr 15.

Imperial College London, Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics, Faculty of Medicine, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK.

Characterizing the relationships between genomic and phenotypic variation is essential to understanding disease etiology. Information-dense data sets derived from pathophysiological, proteomic and transcriptomic profiling have been applied to map quantitative trait loci (QTLs). Metabolic traits, already used in QTL studies in plants, are essential phenotypes in mammalian genetics to define disease biomarkers. Using a complex mammalian system, here we show chromosomal mapping of untargeted plasma metabolic fingerprints derived from NMR spectroscopic analysis in a cross between diabetic and control rats. We propose candidate metabolites for the most significant QTLs. Metabolite profiling in congenic strains provided evidence of QTL replication. Linkage to a gut microbial metabolite (benzoate) can be explained by deletion of a uridine diphosphate glucuronosyltransferase. Mapping metabotypic QTLs provides a practical approach to understanding genome-phenotype relationships in mammals and may uncover deeper biological complexity, as extended genome (microbiome) perturbations that affect disease processes through transgenomic effects may influence QTL detection.
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http://dx.doi.org/10.1038/ng2026DOI Listing
May 2007

Mapping diabetes QTL in an intercross derived from a congenic strain of the Brown Norway and Goto-Kakizaki rats.

Mamm Genome 2006 Jun 12;17(6):538-47. Epub 2006 Jun 12.

The Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Headington, Oxford OX3 7BN, UK.

Genetic studies in experimental crosses derived from the inbred Goto-Kakizaki (GK) rat model of spontaneous diabetes mellitus have identified quantitative trait loci (QTL) for diabetes phenotypes in a large region of rat Chromosome (RNO) 1. To test the impact of GK variants on QTL statistical and biological features, we combined genetic and physiologic studies in a cohort of F(2) hybrids derived from a QTL substitution congenic strain (QTLSCS) carrying a 110-cM GK haplotype of RNO1 introgressed onto the genetic background of the Brown Norway (BN) strain. Glucose intolerance and altered insulin secretion in QTLSCS rats when compared with BN controls were consistent with original QTL features in a GK x BN F(2) cross. Segregating GK alleles in the QTLSCS F(2) cross account for most of these phenotypic differences between QTLSCS and BN rats. However, significant QTL for diabetes traits in both the QTLSCS and GK x BN F(2) cohorts account for a similar small proportion of their variance. Comparing results from these experimental systems provides indirect estimates of the contribution of genetic interactions and environmental factors to QTL architecture as well as locus and biological targets for future post-QTL mapping studies in congenic substrains.
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http://dx.doi.org/10.1007/s00335-005-0168-yDOI Listing
June 2006

Chromosomal mapping of quantitative trait loci controlling elastin content in rat aorta.

Hypertension 2005 Mar 24;45(3):460-6. Epub 2005 Jan 24.

The Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, United Kingdom.

Extracellular matrix molecules such as elastin and collagens provide mechanical support to the vessel wall. In addition to its structural role, elastin is a regulator that maintains homeostasis through biologic signaling. Genetically determined minor modifications in elastin and collagen in the aorta could influence the onset and evolution of arterial pathology, such as hypertension and its complications. We previously demonstrated that the inbred Brown Norway (BN) rat shows an aortic elastin deficit in both abdominal and thoracic segments, partly because of a decrease in tropoelastin synthesis when compared with the LOU rat, that elastin gene polymorphisms in these strains do not significantly account for. After a genome-wide search for quantitative trait loci (QTL) influencing the aortic elastin, collagen, and cell protein contents in an F2 population derived from BN and LOU rats, we identified on chromosomes 2 and 14, 3 QTL specifically controlling elastin levels, and a further highly significant QTL on chromosome 17 linked to the level of cell proteins. We also mapped 3 highly significant QTL linked to body weight (on chromosomes 1 and 3) and heart weight (on chromosome 1) in the cross. This study demonstrates the polygenic control of the content of key components of the arterial wall. Such information represents a first step in understanding possible mechanisms involved in dysregulation of these parameters in arterial pathology.
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http://dx.doi.org/10.1161/01.HYP.0000155213.83719.7cDOI Listing
March 2005
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