Kevin L. Howe
European Bioinformatics Institute
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Publication
Featured researches published by Kevin L. Howe.
Nature Genetics | 2006
Florian Eckhardt; Jörn Lewin; Rene Cortese; Vardhman K. Rakyan; John Attwood; Matthias Burger; John Burton; Tony Cox; Rob Davies; Thomas A. Down; Carolina Haefliger; Roger Horton; Kevin L. Howe; David K. Jackson; Jan Kunde; Christoph Koenig; Jennifer Liddle; David Niblett; Thomas Otto; Roger Pettett; Stefanie Seemann; Christian Thompson; Tony West; Jane Rogers; Alex Olek; Kurt Berlin; Stephan Beck
DNA methylation is the most stable type of epigenetic modification modulating the transcriptional plasticity of mammalian genomes. Using bisulfite DNA sequencing, we report high-resolution methylation profiles of human chromosomes 6, 20 and 22, providing a resource of about 1.9 million CpG methylation values derived from 12 different tissues. Analysis of six annotation categories showed that evolutionarily conserved regions are the predominant sites for differential DNA methylation and that a core region surrounding the transcriptional start site is an informative surrogate for promoter methylation. We find that 17% of the 873 analyzed genes are differentially methylated in their 5′ UTRs and that about one-third of the differentially methylated 5′ UTRs are inversely correlated with transcription. Despite the fact that our study controlled for factors reported to affect DNA methylation such as sex and age, we did not find any significant attributable effects. Our data suggest DNA methylation to be ontogenetically more stable than previously thought.
Nature Biotechnology | 2008
Thomas A. Down; Vardhman K. Rakyan; Daniel J. Turner; Paul Flicek; Heng Li; Eugene Kulesha; Stefan Gräf; Nathan Johnson; Javier Herrero; Eleni M. Tomazou; Natalie P. Thorne; Liselotte Bäckdahl; Marlis Herberth; Kevin L. Howe; David K. Jackson; Marcos M Miretti; John C. Marioni; Ewan Birney; Tim Hubbard; Richard Durbin; Simon Tavaré; Stephan Beck
DNA methylation is an indispensible epigenetic modification required for regulating the expression of mammalian genomes. Immunoprecipitation-based methods for DNA methylome analysis are rapidly shifting the bottleneck in this field from data generation to data analysis, necessitating the development of better analytical tools. In particular, an inability to estimate absolute methylation levels remains a major analytical difficulty associated with immunoprecipitation-based DNA methylation profiling. To address this issue, we developed a cross-platform algorithm—Bayesian tool for methylation analysis (Batman)—for analyzing methylated DNA immunoprecipitation (MeDIP) profiles generated using oligonucleotide arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq). We developed the latter approach to provide a high-resolution whole-genome DNA methylation profile (DNA methylome) of a mammalian genome. Strong correlation of our data, obtained using mature human spermatozoa, with those obtained using bisulfite sequencing suggest that combining MeDIP-seq or MeDIP-chip with Batman provides a robust, quantitative and cost-effective functional genomic strategy for elucidating the function of DNA methylation.
PLOS Biology | 2004
Vardhman K. Rakyan; Thomas Hildmann; Kl Novik; Jörn Lewin; Jörg Tost; Antony Cox; T. Dan Andrews; Kevin L. Howe; Thomas Otto; Alexander Olek; Judith Fischer; Ivo Gut; Kurt Berlin; Stephan Beck
The Human Epigenome Project aims to identify, catalogue, and interpret genome-wide DNA methylation phenomena. Occurring naturally on cytosine bases at cytosine–guanine dinucleotides, DNA methylation is intimately involved in diverse biological processes and the aetiology of many diseases. Differentially methylated cytosines give rise to distinct profiles, thought to be specific for gene activity, tissue type, and disease state. The identification of such methylation variable positions will significantly improve our understanding of genome biology and our ability to diagnose disease. Here, we report the results of the pilot study for the Human Epigenome Project entailing the methylation analysis of the human major histocompatibility complex. This study involved the development of an integrated pipeline for high-throughput methylation analysis using bisulphite DNA sequencing, discovery of methylation variable positions, epigenotyping by matrix-assisted laser desorption/ionisation mass spectrometry, and development of an integrated public database available at http://www.epigenome.org. Our analysis of DNA methylation levels within the major histocompatibility complex, including regulatory exonic and intronic regions associated with 90 genes in multiple tissues and individuals, reveals a bimodal distribution of methylation profiles (i.e., the vast majority of the analysed regions were either hypo- or hypermethylated), tissue specificity, inter-individual variation, and correlation with independent gene expression data.
Genome Research | 2008
Vardhman K. Rakyan; Thomas A. Down; Natalie P. Thorne; Paul Flicek; Eugene Kulesha; Stefan Gräf; Eleni M. Tomazou; Liselotte Bäckdahl; Nathan Johnson; Marlis Herberth; Kevin L. Howe; David K. Jackson; Marcos M Miretti; Heike Fiegler; John C. Marioni; Ewan Birney; Tim Hubbard; Nigel P. Carter; Simon Tavaré; Stephan Beck
We report a novel resource (methylation profiles of DNA, or mPod) for human genome-wide tissue-specific DNA methylation profiles. mPod consists of three fully integrated parts, genome-wide DNA methylation reference profiles of 13 normal somatic tissues, placenta, sperm, and an immortalized cell line, a visualization tool that has been integrated with the Ensembl genome browser and a new algorithm for the analysis of immunoprecipitation-based DNA methylation profiles. We demonstrate the utility of our resource by identifying the first comprehensive genome-wide set of tissue-specific differentially methylated regions (tDMRs) that may play a role in cellular identity and the regulation of tissue-specific genome function. We also discuss the implications of our findings with respect to the regulatory potential of regions with varied CpG density, gene expression, transcription factor motifs, gene ontology, and correlation with other epigenetic marks such as histone modifications.
Nucleic Acids Research | 2016
Paul J. Kersey; James E. Allen; Irina M. Armean; Sanjay Boddu; Bruce J. Bolt; Denise R. Carvalho-Silva; Mikkel Christensen; Paul Davis; Lee J. Falin; Christoph Grabmueller; Jay Humphrey; Arnaud Kerhornou; Julia Khobova; Naveen K. Aranganathan; Nicholas Langridge; Ernesto Lowy; Mark D. McDowall; Uma Maheswari; Michael Nuhn; Chuang Kee Ong; Bert Overduin; Michael Paulini; Helder Pedro; Emily Perry; Giulietta Spudich; Electra Tapanari; Brandon Walts; Gareth Williams; Marcela Tello–Ruiz; Joshua C. Stein
Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces.
Molecular Cell | 2008
Partha P. Das; Marloes P. Bagijn; Leonard D. Goldstein; Julie R. Woolford; Nicolas J. Lehrbach; Alexandra Sapetschnig; Heeran R. Buhecha; Michael J. Gilchrist; Kevin L. Howe; Rory Stark; Nik Matthews; Eugene Berezikov; René F. Ketting; Simon Tavaré; Eric A. Miska
The Piwi proteins of the Argonaute superfamily are required for normal germline development in Drosophila, zebrafish, and mice and associate with 24-30 nucleotide RNAs termed piRNAs. We identify a class of 21 nucleotide RNAs, previously named 21U-RNAs, as the piRNAs of C. elegans. Piwi and piRNA expression is restricted to the male and female germline and independent of many proteins in other small-RNA pathways, including DCR-1. We show that Piwi is specifically required to silence Tc3, but not other Tc/mariner DNA transposons. Tc3 excision rates in the germline are increased at least 100-fold in piwi mutants as compared to wild-type. We find no evidence for a Ping-Pong model for piRNA amplification in C. elegans. Instead, we demonstrate that Piwi acts upstream of an endogenous siRNA pathway in Tc3 silencing. These data might suggest a link between piRNA and siRNA function.
Bioinformatics | 2002
Kevin L. Howe; Alex Bateman; Richard Durbin
We have written a fast implementation of the popular Neighbor-Joining tree building algorithm. QuickTree allows the reconstruction of phylogenies for very large protein families (including the largest Pfam alignment containing 27000 HIV GP120 glycoprotein sequences) that would be infeasible using other popular methods.
Database | 2016
Bronwen Aken; Sarah Ayling; Daniel Barrell; Laura Clarke; Valery Curwen; Susan Fairley; Julio Fernandez Banet; Konstantinos Billis; Carlos Giron; Thibaut Hourlier; Kevin L. Howe; Andreas Kähäri; Felix Kokocinski; Fergal Martin; Daniel N. Murphy; Rishi Nag; Magali Ruffier; Michael Schuster; Y. Amy Tang; Jan-Hinnerk Vogel; Simon White; Amonida Zadissa; Paul Flicek; Stephen M. J. Searle
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: http://www.ensembl.org/index.html
Nucleic Acids Research | 2012
Karen Yook; Todd W. Harris; Tamberlyn Bieri; Abigail Cabunoc; Juancarlos Chan; Wen J. Chen; Paul H. Davis; Norie De La Cruz; Adrian Duong; Ruihua Fang; Uma Ganesan; Christian A. Grove; Kevin L. Howe; Snehalata Kadam; Ranjana Kishore; Raymond Y. N. Lee; Yuling Li; Hans-Michael Müller; Cecilia Nakamura; Bill Nash; Philip Ozersky; Michael Paulini; Daniela Raciti; Arun Rangarajan; Gary Schindelman; Xiaoqi Shi; Erich M. Schwarz; Mary Ann Tuli; Kimberly Van Auken; Daniel Wang
Since its release in 2000, WormBase (http://www.wormbase.org) has grown from a small resource focusing on a single species and serving a dedicated research community, to one now spanning 15 species essential to the broader biomedical and agricultural research fields. To enhance the rate of curation, we have automated the identification of key data in the scientific literature and use similar methodology for data extraction. To ease access to the data, we are collaborating with journals to link entities in research publications to their report pages at WormBase. To facilitate discovery, we have added new views of the data, integrated large-scale datasets and expanded descriptions of models for human disease. Finally, we have introduced a dramatic overhaul of the WormBase website for public beta testing. Designed to balance complexity and usability, the new site is species-agnostic, highly customizable, and interactive. Casual users and developers alike will be able to leverage the public RESTful application programming interface (API) to generate custom data mining solutions and extensions to the site. We report on the growth of our database and on our work in keeping pace with the growing demand for data, efforts to anticipate the requirements of users and new collaborations with the larger science community.
Nucleic Acids Research | 2014
Paul J. Kersey; James E. Allen; Mikkel Christensen; Paul Davis; Lee J. Falin; Christoph Grabmueller; Daniel Seth Toney Hughes; Jay Humphrey; Arnaud Kerhornou; Julia Khobova; Nicholas Langridge; Mark D. McDowall; Uma Maheswari; Gareth Maslen; Michael Nuhn; Chuang Kee Ong; Michael Paulini; Helder Pedro; Iliana Toneva; Mary Ann Tuli; Brandon Walts; Gareth Williams; Derek Wilson; Ken Youens-Clark; Marcela K. Monaco; Joshua C. Stein; Xuehong Wei; Doreen Ware; Daniel M. Bolser; Kevin L. Howe
Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species. The project exploits and extends technologies for genome annotation, analysis and dissemination, developed in the context of the vertebrate-focused Ensembl project, and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. This article provides an update to the previous publications about the resource, with a focus on recent developments. These include the addition of important new genomes (and related data sets) including crop plants, vectors of human disease and eukaryotic pathogens. In addition, the resource has scaled up its representation of bacterial genomes, and now includes the genomes of over 9000 bacteria. Specific extensions to the web and programmatic interfaces have been developed to support users in navigating these large data sets. Looking forward, analytic tools to allow targeted selection of data for visualization and download are likely to become increasingly important in future as the number of available genomes increases within all domains of life, and some of the challenges faced in representing bacterial data are likely to become commonplace for eukaryotes in future.