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1.  Punctuated bursts in human male demography inferred from 1,244 worldwide Y-chromosome sequences 
Nature genetics  2016;48(6):593-599.
We report the sequences of 1,244 human Y chromosomes randomly ascertained from 26 worldwide populations by the 1000 Genomes Project. We discovered more than 65,000 variants, including SNVs, MNVs, indels, STRs, and CNVs. Of these, CNVs contribute the greatest predicted functional impact. We constructed a calibrated phylogenetic tree based on binary SNVs and projected the more complex variants onto it, estimating the numbers of mutations for each class. Our phylogeny reveals bursts of extreme expansions in male numbers that have occurred independently among each of the five continental superpopulations examined, at times of known migrations and technological innovations.
PMCID: PMC4884158  PMID: 27111036
2.  Increased DNA methylation variability in type 1 diabetes across three immune effector cell types 
Nature Communications  2016;7:13555.
The incidence of type 1 diabetes (T1D) has substantially increased over the past decade, suggesting a role for non-genetic factors such as epigenetic mechanisms in disease development. Here we present an epigenome-wide association study across 406,365 CpGs in 52 monozygotic twin pairs discordant for T1D in three immune effector cell types. We observe a substantial enrichment of differentially variable CpG positions (DVPs) in T1D twins when compared with their healthy co-twins and when compared with healthy, unrelated individuals. These T1D-associated DVPs are found to be temporally stable and enriched at gene regulatory elements. Integration with cell type-specific gene regulatory circuits highlight pathways involved in immune cell metabolism and the cell cycle, including mTOR signalling. Evidence from cord blood of newborns who progress to overt T1D suggests that the DVPs likely emerge after birth. Our findings, based on 772 methylomes, implicate epigenetic changes that could contribute to disease pathogenesis in T1D.
The incidence of type 1 diabetes is increasing, potentially implicating non-genetic factors. Here the authors conduct an epigenome-wide association study in disease-discordant twins and find increased DNA methylation variability at genes associated with immune cell metabolism and the cell cycle.
PMCID: PMC5141286  PMID: 27898055
3.  Ensembl 2017 
Nucleic Acids Research  2016;45(Database issue):D635-D642.
Ensembl ( 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.
PMCID: PMC5210575  PMID: 27899575
4.  The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog) 
Nucleic Acids Research  2016;45(Database issue):D896-D901.
The NHGRI-EBI GWAS Catalog has provided data from published genome-wide association studies since 2008. In 2015, the database was redesigned and relocated to EMBL-EBI. The new infrastructure includes a new graphical user interface (, ontology supported search functionality and an improved curation interface. These developments have improved the data release frequency by increasing automation of curation and providing scaling improvements. The range of available Catalog data has also been extended with structured ancestry and recruitment information added for all studies. The infrastructure improvements also support scaling for larger arrays, exome and sequencing studies, allowing the Catalog to adapt to the needs of evolving study design, genotyping technologies and user needs in the future.
PMCID: PMC5210590  PMID: 27899670
5.  IPD-MHC 2.0: an improved inter-species database for the study of the major histocompatibility complex 
Nucleic Acids Research  2016;45(Database issue):D860-D864.
The IPD-MHC Database project ( collects and expertly curates sequences of the major histocompatibility complex from non-human species and provides the infrastructure and tools to enable accurate analysis. Since the first release of the database in 2003, IPD-MHC has grown and currently hosts a number of specific sections, with more than 7000 alleles from 70 species, including non-human primates, canines, felines, equids, ovids, suids, bovins, salmonids and murids. These sequences are expertly curated and made publicly available through an open access website. The IPD-MHC Database is a key resource in its field, and this has led to an average of 1500 unique visitors and more than 5000 viewed pages per month. As the database has grown in size and complexity, it has created a number of challenges in maintaining and organizing information, particularly the need to standardize nomenclature and taxonomic classification, while incorporating new allele submissions. Here, we describe the latest database release, the IPD-MHC 2.0 and discuss planned developments. This release incorporates sequence updates and new tools that enhance database queries and improve the submission procedure by utilizing common tools that are able to handle the varied requirements of each MHC-group.
PMCID: PMC5210539  PMID: 27899604
6.  Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells 
Chen, Lu | Ge, Bing | Casale, Francesco Paolo | Vasquez, Louella | Kwan, Tony | Garrido-Martín, Diego | Watt, Stephen | Yan, Ying | Kundu, Kousik | Ecker, Simone | Datta, Avik | Richardson, David | Burden, Frances | Mead, Daniel | Mann, Alice L. | Fernandez, Jose Maria | Rowlston, Sophia | Wilder, Steven P. | Farrow, Samantha | Shao, Xiaojian | Lambourne, John J. | Redensek, Adriana | Albers, Cornelis A. | Amstislavskiy, Vyacheslav | Ashford, Sofie | Berentsen, Kim | Bomba, Lorenzo | Bourque, Guillaume | Bujold, David | Busche, Stephan | Caron, Maxime | Chen, Shu-Huang | Cheung, Warren | Delaneau, Oliver | Dermitzakis, Emmanouil T. | Elding, Heather | Colgiu, Irina | Bagger, Frederik O. | Flicek, Paul | Habibi, Ehsan | Iotchkova, Valentina | Janssen-Megens, Eva | Kim, Bowon | Lehrach, Hans | Lowy, Ernesto | Mandoli, Amit | Matarese, Filomena | Maurano, Matthew T. | Morris, John A. | Pancaldi, Vera | Pourfarzad, Farzin | Rehnstrom, Karola | Rendon, Augusto | Risch, Thomas | Sharifi, Nilofar | Simon, Marie-Michelle | Sultan, Marc | Valencia, Alfonso | Walter, Klaudia | Wang, Shuang-Yin | Frontini, Mattia | Antonarakis, Stylianos E. | Clarke, Laura | Yaspo, Marie-Laure | Beck, Stephan | Guigo, Roderic | Rico, Daniel | Martens, Joost H.A. | Ouwehand, Willem H. | Kuijpers, Taco W. | Paul, Dirk S. | Stunnenberg, Hendrik G. | Stegle, Oliver | Downes, Kate | Pastinen, Tomi | Soranzo, Nicole
Cell  2016;167(5):1398-1414.e24.
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.
Graphical Abstract
•Genome, transcriptome, and epigenome reference panel in three human immune cell types•Identified 4,418 genes associated with epigenetic changes independent of genetics•Described genome-epigenome coordination defining cell-type-specific regulatory events•Functionally mapped disease mechanisms at 345 unique autoimmune disease loci
As part of the IHEC consortium, this study integrates genetic, epigenetic, and transcriptomic profiling in three immune cell types from nearly 200 people to characterize the distinct and cooperative contributions of diverse genomic inputs to transcriptional variation. Explore the Cell Press IHEC web portal at
PMCID: PMC5119954  PMID: 27863251
immune; monocyte; neutrophil; t-cell; EWAS; histone modification; DNA methylation; transription; allele specific; QTL
8.  The human-induced pluripotent stem cell initiative—data resources for cellular genetics 
Nucleic Acids Research  2016;45(Database issue):D691-D697.
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 ( and is downloadable from the associated FTP site ( 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 (
PMCID: PMC5210631  PMID: 27733501
9.  The international Genome sample resource (IGSR): A worldwide collection of genome variation incorporating the 1000 Genomes Project data 
Nucleic Acids Research  2016;45(Database issue):D854-D859.
The International Genome Sample Resource (IGSR; expands in data type and population diversity the resources from the 1000 Genomes Project. IGSR represents the largest open collection of human variation data and provides easy access to these resources. IGSR was established in 2015 to maintain and extend the 1000 Genomes Project data, which has been widely used as a reference set of human variation and by researchers developing analysis methods. IGSR has mapped all of the 1000 Genomes sequence to the newest human reference (GRCh38), and will release updated variant calls to ensure maximal usefulness of the existing data. IGSR is collecting new structural variation data on the 1000 Genomes samples from long read sequencing and other technologies, and will collect relevant functional data into a single comprehensive resource. IGSR is extending coverage with new populations sequenced by collaborating groups. Here, we present the new data and analysis that IGSR has made available. We have also introduced a new data portal that increases discoverability of our data—previously only browseable through our FTP site—by focusing on particular samples, populations or data sets of interest.
PMCID: PMC5210610  PMID: 27638885
10.  Functional annotation of non-coding sequence variants 
Nature methods  2014;11(3):294-296.
Identifying functionally relevant variants against the background of ubiquitous genetic variation is a major challenge in human genetics. For variants that fall in protein-coding regions our understanding of the genetic code and splicing allow us to identify likely candidates, but interpreting variants that fall outside of genic regions is more difficult. Here we present a new tool, GWAVA, which supports prioritisation of non-coding variants by integrating a range of annotations.
PMCID: PMC5015703  PMID: 24487584
11.  Mitochondrial heteroplasmy in vertebrates using ChIP-sequencing data 
Genome Biology  2016;17:139.
Mitochondrial heteroplasmy, the presence of more than one mitochondrial DNA (mtDNA) variant in a cell or individual, is not as uncommon as previously thought. It is mostly due to the high mutation rate of the mtDNA and limited repair mechanisms present in the mitochondrion. Motivated by mitochondrial diseases, much focus has been placed into studying this phenomenon in human samples and in medical contexts. To place these results in an evolutionary context and to explore general principles of heteroplasmy, we describe an integrated cross-species evaluation of heteroplasmy in mammals that exploits previously reported NGS data. Focusing on ChIP-seq experiments, we developed a novel approach to detect heteroplasmy from the concomitant mitochondrial DNA fraction sequenced in these experiments.
We first demonstrate that the sequencing coverage of mtDNA in ChIP-seq experiments is sufficient for heteroplasmy detection. We then describe a novel detection method for accurate detection of heteroplasmies, which also accounts for the error rate of NGS technology. Applying this method to 79 individuals from 16 species resulted in 107 heteroplasmic positions present in a total of 45 individuals. Further analysis revealed that the majority of detected heteroplasmies occur in intergenic regions.
In addition to documenting the prevalence of mtDNA in ChIP-seq data, the results of our mitochondrial heteroplasmy detection method suggest that mitochondrial heteroplasmies identified across vertebrates share similar characteristics as found for human heteroplasmies. Although largely consistent with previous studies in individual vertebrates, our integrated cross-species analysis provides valuable insights into the evolutionary dynamics of mitochondrial heteroplasmy.
Electronic supplementary material
The online version of this article (doi:10.1186/s13059-016-0996-y) contains supplementary material, which is available to authorized users.
PMCID: PMC4922064  PMID: 27349964
Heteroplasmy; Chromatin immunoprecipitation sequencing (ChIP-seq); mitochondrial DNA (mtDNA); Mitochondrion; Vertebrates
12.  The Ensembl gene annotation system 
The Ensembl gene annotation system has been used to annotate over 70 different vertebrate species across a wide range of genome projects. Furthermore, it generates the automatic alignment-based annotation for the human and mouse GENCODE gene sets. The system is based on the alignment of biological sequences, including cDNAs, proteins and RNA-seq reads, to the target genome in order to construct candidate transcript models. Careful assessment and filtering of these candidate transcripts ultimately leads to the final gene set, which is made available on the Ensembl website. Here, we describe the annotation process in detail.
Database URL:
PMCID: PMC4919035  PMID: 27337980
13.  Making sense of big data in health research: Towards an EU action plan 
Genome Medicine  2016;8:71.
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of “big data” for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.
PMCID: PMC4919856  PMID: 27338147
14.  The Ensembl Variant Effect Predictor 
Genome Biology  2016;17:122.
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.
PMCID: PMC4893825  PMID: 27268795
Variant annotation; NGS; Genome; SNP
15.  Divergence in gene expression within and between two closely related flycatcher species 
Molecular Ecology  2016;25(9):2015-2028.
Relatively little is known about the character of gene expression evolution as species diverge. It is for instance unclear if gene expression generally evolves in a clock‐like manner (by stabilizing selection or neutral evolution) or if there are frequent episodes of directional selection. To gain insights into the evolutionary divergence of gene expression, we sequenced and compared the transcriptomes of multiple organs from population samples of collared (Ficedula albicollis) and pied flycatchers (F. hypoleuca), two species which diverged less than one million years ago. Ordination analysis separated samples by organ rather than by species. Organs differed in their degrees of expression variance within species and expression divergence between species. Variance was negatively correlated with expression breadth and protein interactivity, suggesting that pleiotropic constraints reduce gene expression variance within species. Variance was correlated with between‐species divergence, consistent with a pattern expected from stabilizing selection and neutral evolution. Using an expression PST approach, we identified genes differentially expressed between species and found 16 genes uniquely expressed in one of the species. For one of these, DPP7, uniquely expressed in collared flycatcher, the absence of expression in pied flycatcher could be associated with a ≈20‐kb deletion including 11 of 13 exons. This study of a young vertebrate speciation model system expands our knowledge of how gene expression evolves as natural populations become reproductively isolated.
PMCID: PMC4879514  PMID: 26928872
collared flycatcher; Ficedula; gene regulation; pied flycatcher; speciation; transcriptomics
17.  An integrated map of structural variation in 2,504 human genomes 
Sudmant, Peter H. | Rausch, Tobias | Gardner, Eugene J. | Handsaker, Robert E. | Abyzov, Alexej | Huddleston, John | Zhang, Yan | Ye, Kai | Jun, Goo | Fritz, Markus Hsi-Yang | Konkel, Miriam K. | Malhotra, Ankit | Stütz, Adrian M. | Shi, Xinghua | Casale, Francesco Paolo | Chen, Jieming | Hormozdiari, Fereydoun | Dayama, Gargi | Chen, Ken | Malig, Maika | Chaisson, Mark J.P. | Walter, Klaudia | Meiers, Sascha | Kashin, Seva | Garrison, Erik | Auton, Adam | Lam, Hugo Y. K. | Mu, Xinmeng Jasmine | Alkan, Can | Antaki, Danny | Bae, Taejeong | Cerveira, Eliza | Chines, Peter | Chong, Zechen | Clarke, Laura | Dal, Elif | Ding, Li | Emery, Sarah | Fan, Xian | Gujral, Madhusudan | Kahveci, Fatma | Kidd, Jeffrey M. | Kong, Yu | Lameijer, Eric-Wubbo | McCarthy, Shane | Flicek, Paul | Gibbs, Richard A. | Marth, Gabor | Mason, Christopher E. | Menelaou, Androniki | Muzny, Donna M. | Nelson, Bradley J. | Noor, Amina | Parrish, Nicholas F. | Pendleton, Matthew | Quitadamo, Andrew | Raeder, Benjamin | Schadt, Eric E. | Romanovitch, Mallory | Schlattl, Andreas | Sebra, Robert | Shabalin, Andrey A. | Untergasser, Andreas | Walker, Jerilyn A. | Wang, Min | Yu, Fuli | Zhang, Chengsheng | Zhang, Jing | Zheng-Bradley, Xiangqun | Zhou, Wanding | Zichner, Thomas | Sebat, Jonathan | Batzer, Mark A. | McCarroll, Steven A. | Mills, Ryan E. | Gerstein, Mark B. | Bashir, Ali | Stegle, Oliver | Devine, Scott E. | Lee, Charles | Eichler, Evan E. | Korbel, Jan O.
Nature  2015;526(7571):75-81.
Structural variants (SVs) are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight SV classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype-blocks in 26 human populations. Analyzing this set, we identify numerous gene-intersecting SVs exhibiting population stratification and describe naturally occurring homozygous gene knockouts suggesting the dispensability of a variety of human genes. We demonstrate that SVs are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of SV complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex SVs with multiple breakpoints likely formed through individual mutational events. Our catalog will enhance future studies into SV demography, functional impact and disease association.
PMCID: PMC4617611  PMID: 26432246
18.  ncRNA orthologies in the vertebrate lineage 
Annotation of orthologous and paralogous genes is necessary for many aspects of evolutionary analysis. Methods to infer these homology relationships have traditionally focused on protein-coding genes and evolutionary models used by these methods normally assume the positions in the protein evolve independently. However, as our appreciation for the roles of non-coding RNA genes has increased, consistently annotated sets of orthologous and paralogous ncRNA genes are increasingly needed. At the same time, methods such as PHASE or RAxML have implemented substitution models that consider pairs of sites to enable proper modelling of the loops and other features of RNA secondary structure. Here, we present a comprehensive analysis pipeline for the automatic detection of orthologues and paralogues for ncRNA genes. We focus on gene families represented in Rfam and for which a specific covariance model is provided. For each family ncRNA genes found in all Ensembl species are aligned using Infernal, and several trees are built using different substitution models. In parallel, a genomic alignment that includes the ncRNA genes and their flanking sequence regions is built with PRANK. This alignment is used to create two additional phylogenetic trees using the neighbour-joining (NJ) and maximum-likelihood (ML) methods. The trees arising from both the ncRNA and genomic alignments are merged using TreeBeST, which reconciles them with the species tree in order to identify speciation and duplication events. The final tree is used to infer the orthologues and paralogues following Fitch's definition. We also determine gene gain and loss events for each family using CAFE. All data are accessible through the Ensembl Comparative Genomics (‘Compara’) API, on our FTP site and are fully integrated in the Ensembl genome browser, where they can be accessed in a user-friendly manner.
Database URL:
PMCID: PMC4792531  PMID: 26980512
19.  Ensembl comparative genomics resources 
Evolution provides the unifying framework with which to understand biology. The coherent investigation of genic and genomic data often requires comparative genomics analyses based on whole-genome alignments, sets of homologous genes and other relevant datasets in order to evaluate and answer evolutionary-related questions. However, the complexity and computational requirements of producing such data are substantial: this has led to only a small number of reference resources that are used for most comparative analyses. The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available.
Database URL:
PMCID: PMC4761110  PMID: 26896847
20.  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, from the Perl and REST APIs and from the public Ensembl MySQL database server at
Database URL:
PMCID: PMC4756621  PMID: 26888907
21.  Ensembl 2016 
Nucleic Acids Research  2015;44(Database issue):D710-D716.
The Ensembl project ( 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 ( 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 ( under an Apache 2.0 license.
PMCID: PMC4702834  PMID: 26687719
22.  Quantitative analysis of chromatin interaction changes upon a 4.3 Mb deletion at mouse 4E2 
BMC Genomics  2015;16:982.
Circular chromosome conformation capture (4C) has provided important insights into three dimensional (3D) genome organization and its critical impact on the regulation of gene expression. We developed a new quantitative framework based on polymer physics for the analysis of paired-end sequencing 4C (PE-4Cseq) data. We applied this strategy to the study of chromatin interaction changes upon a 4.3 Mb DNA deletion in mouse region 4E2.
A significant number of differentially interacting regions (DIRs) and chromatin compaction changes were detected in the deletion chromosome compared to a wild-type (WT) control. Selected DIRs were validated by 3D DNA FISH experiments, demonstrating the robustness of our pipeline. Interestingly, significant overlaps of DIRs with CTCF/Smc1 binding sites and differentially expressed genes were observed.
Altogether, our PE-4Cseq analysis pipeline provides a comprehensive characterization of DNA deletion effects on chromatin structure and function.
Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-2137-5) contains supplementary material, which is available to authorized users.
PMCID: PMC4654810  PMID: 26589460
23.  Regulatory Divergence of Transcript Isoforms in a Mammalian Model System 
PLoS ONE  2015;10(9):e0137367.
Phenotypic differences between species are driven by changes in gene expression and, by extension, by modifications in the regulation of the transcriptome. Investigation of mammalian transcriptome divergence has been restricted to analysis of bulk gene expression levels and gene-internal splicing. Using allele-specific expression analysis in inter-strain hybrids of Mus musculus, we determined the contribution of multiple cellular regulatory systems to transcriptome divergence, including: alternative promoter usage, transcription start site selection, cassette exon usage, alternative last exon usage, and alternative polyadenylation site choice. Between mouse strains, a fifth of genes have variations in isoform usage that contribute to transcriptomic changes, half of which alter encoded amino acid sequence. Virtually all divergence in isoform usage altered the post-transcriptional regulatory instructions in gene UTRs. Furthermore, most genes with isoform differences between strains contain changes originating from multiple regulatory systems. This result indicates widespread cross-talk and coordination exists among different regulatory systems. Overall, isoform usage diverges in parallel with and independently to gene expression evolution, and the cis and trans regulatory contribution to each differs significantly.
PMCID: PMC4560434  PMID: 26339903
24.  Epigenome data release: a participant-centered approach to privacy protection 
Genome Biology  2015;16(1):142.
Large-scale epigenome mapping by the NIH Roadmap Epigenomics Project, the ENCODE Consortium and the International Human Epigenome Consortium (IHEC) produces genome-wide DNA methylation data at one base-pair resolution. We examine how such data can be made open-access while balancing appropriate interpretation and genomic privacy. We propose guidelines for data release that both reduce ambiguity in the interpretation of open-access data and limit immediate access to genetic variation data that are made available through controlled access.
Electronic supplementary material
The online version of this article (doi:10.1186/s13059-015-0723-0) contains supplementary material, which is available to authorized users.
PMCID: PMC4504083  PMID: 26185018
25.  A Comparative Encyclopedia of DNA Elements in the Mouse Genome 
Yue, Feng | Cheng, Yong | Breschi, Alessandra | Vierstra, Jeff | Wu, Weisheng | Ryba, Tyrone | Sandstrom, Richard | Ma, Zhihai | Davis, Carrie | Pope, Benjamin D. | Shen, Yin | Pervouchine, Dmitri D. | Djebali, Sarah | Thurman, Bob | Kaul, Rajinder | Rynes, Eric | Kirilusha, Anthony | Marinov, Georgi K. | Williams, Brian A. | Trout, Diane | Amrhein, Henry | Fisher-Aylor, Katherine | Antoshechkin, Igor | DeSalvo, Gilberto | See, Lei-Hoon | Fastuca, Meagan | Drenkow, Jorg | Zaleski, Chris | Dobin, Alex | Prieto, Pablo | Lagarde, Julien | Bussotti, Giovanni | Tanzer, Andrea | Denas, Olgert | Li, Kanwei | Bender, M. A. | Zhang, Miaohua | Byron, Rachel | Groudine, Mark T. | McCleary, David | Pham, Long | Ye, Zhen | Kuan, Samantha | Edsall, Lee | Wu, Yi-Chieh | Rasmussen, Matthew D. | Bansal, Mukul S. | Keller, Cheryl A. | Morrissey, Christapher S. | Mishra, Tejaswini | Jain, Deepti | Dogan, Nergiz | Harris, Robert S. | Cayting, Philip | Kawli, Trupti | Boyle, Alan P. | Euskirchen, Ghia | Kundaje, Anshul | Lin, Shin | Lin, Yiing | Jansen, Camden | Malladi, Venkat S. | Cline, Melissa S. | Erickson, Drew T. | Kirkup, Vanessa M | Learned, Katrina | Sloan, Cricket A. | Rosenbloom, Kate R. | de Sousa, Beatriz Lacerda | Beal, Kathryn | Pignatelli, Miguel | Flicek, Paul | Lian, Jin | Kahveci, Tamer | Lee, Dongwon | Kent, W. James | Santos, Miguel Ramalho | Herrero, Javier | Notredame, Cedric | Johnson, Audra | Vong, Shinny | Lee, Kristen | Bates, Daniel | Neri, Fidencio | Diegel, Morgan | Canfield, Theresa | Sabo, Peter J. | Wilken, Matthew S. | Reh, Thomas A. | Giste, Erika | Shafer, Anthony | Kutyavin, Tanya | Haugen, Eric | Dunn, Douglas | Reynolds, Alex P. | Neph, Shane | Humbert, Richard | Hansen, R. Scott | De Bruijn, Marella | Selleri, Licia | Rudensky, Alexander | Josefowicz, Steven | Samstein, Robert | Eichler, Evan E. | Orkin, Stuart H. | Levasseur, Dana | Papayannopoulou, Thalia | Chang, Kai-Hsin | Skoultchi, Arthur | Gosh, Srikanta | Disteche, Christine | Treuting, Piper | Wang, Yanli | Weiss, Mitchell J. | Blobel, Gerd A. | Good, Peter J. | Lowdon, Rebecca F. | Adams, Leslie B. | Zhou, Xiao-Qiao | Pazin, Michael J. | Feingold, Elise A. | Wold, Barbara | Taylor, James | Kellis, Manolis | Mortazavi, Ali | Weissman, Sherman M. | Stamatoyannopoulos, John | Snyder, Michael P. | Guigo, Roderic | Gingeras, Thomas R. | Gilbert, David M. | Hardison, Ross C. | Beer, Michael A. | Ren, Bing
Nature  2014;515(7527):355-364.
As the premier model organism in biomedical research, the laboratory mouse shares the majority of protein-coding genes with humans, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications, and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of other sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases.
PMCID: PMC4266106  PMID: 25409824

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