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Kathryn Beal

Bio: Kathryn Beal is an academic researcher from Wellcome Trust Sanger Institute. The author has contributed to research in topics: Genome & Genomics. The author has an hindex of 29, co-authored 39 publications receiving 22526 citations. Previous affiliations of Kathryn Beal include Wellcome Trust & European Bioinformatics Institute.
Topics: Genome, Genomics, Human genome, Ensembl, Gene

Papers
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Journal ArticleDOI
Adam Auton1, Gonçalo R. Abecasis2, David Altshuler3, Richard Durbin4  +514 moreInstitutions (90)
01 Oct 2015-Nature
TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

12,661 citations

01 Oct 2015
TL;DR: The 1000 Genomes Project as mentioned in this paper provided a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and reported the completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole genome sequencing, deep exome sequencing and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

3,247 citations

01 Sep 2012
TL;DR: The Encyclopedia of DNA Elements project provides new insights into the organization and regulation of the authors' genes and genome, and is an expansive resource of functional annotations for biomedical research.

2,767 citations

Journal ArticleDOI
TL;DR: An overview of the project and the resources it is generating and the application of ENCODE data to interpret the human genome are provided.
Abstract: The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome.

1,446 citations

Journal ArticleDOI
Feng Yue1, Feng Yue2, Yong Cheng3, Alessandra Breschi, Jeff Vierstra4, Weisheng Wu5, Weisheng Wu1, Tyrone Ryba6, Tyrone Ryba7, Richard Sandstrom4, Zhihai Ma3, Carrie A. Davis8, Benjamin D. Pope6, Yin Shen2, Dmitri D. Pervouchine, Sarah Djebali, Robert E. Thurman4, Rajinder Kaul4, Eric Rynes4, Anthony Kirilusha9, Georgi K. Marinov9, Brian A. Williams9, Diane Trout9, Henry Amrhein9, Katherine I. Fisher-Aylor9, Igor Antoshechkin9, Gilberto DeSalvo9, Lei Hoon See8, Meagan Fastuca8, Jorg Drenkow8, Chris Zaleski8, Alexander Dobin8, Pablo Prieto, Julien Lagarde, Giovanni Bussotti, Andrea Tanzer10, Olgert Denas11, Kanwei Li11, M. A. Bender4, M. A. Bender12, Miaohua Zhang12, Rachel Byron12, Mark Groudine4, Mark Groudine12, David McCleary2, Long Pham2, Zhen Ye2, Samantha Kuan2, Lee Edsall2, Yi-Chieh Wu13, Matthew D. Rasmussen13, Mukul S. Bansal13, Manolis Kellis14, Manolis Kellis13, Cheryl A. Keller1, Christapher S. Morrissey1, Tejaswini Mishra1, Deepti Jain1, Nergiz Dogan1, Robert S. Harris1, Philip Cayting3, Trupti Kawli3, Alan P. Boyle5, Alan P. Boyle3, Ghia Euskirchen3, Anshul Kundaje3, Shin Lin3, Yiing Lin3, Camden Jansen15, Venkat S. Malladi3, Melissa S. Cline16, Drew T. Erickson3, Vanessa M. Kirkup16, Katrina Learned16, Cricket A. Sloan3, Kate R. Rosenbloom16, Beatriz Lacerda de Sousa17, Kathryn Beal, Miguel Pignatelli, Paul Flicek, Jin Lian18, Tamer Kahveci19, Dongwon Lee20, W. James Kent16, Miguel Santos17, Javier Herrero21, Cedric Notredame, Audra K. Johnson4, Shinny Vong4, Kristen Lee4, Daniel Bates4, Fidencio Neri4, Morgan Diegel4, Theresa K. Canfield4, Peter J. Sabo4, Matthew S. Wilken4, Thomas A. Reh4, Erika Giste4, Anthony Shafer4, Tanya Kutyavin4, Eric Haugen4, Douglas Dunn4, Alex Reynolds4, Shane Neph4, Richard Humbert4, R. Scott Hansen4, Marella F. T. R. de Bruijn22, Licia Selleri23, Alexander Y. Rudensky24, Steven Z. Josefowicz24, Robert M. Samstein24, Evan E. Eichler4, Stuart H. Orkin25, Dana N. Levasseur26, Thalia Papayannopoulou4, Kai Hsin Chang4, Arthur I. Skoultchi27, Srikanta Gosh27, Christine M. Disteche4, Piper M. Treuting4, Yanli Wang1, Mitchell J. Weiss, Gerd A. Blobel28, Xiaoyi Cao2, Sheng Zhong2, Ting Wang29, Peter J. Good30, Rebecca F. Lowdon30, Rebecca F. Lowdon29, Leslie B. Adams30, Leslie B. Adams31, Xiao Qiao Zhou30, Michael J. Pazin30, Elise A. Feingold30, Barbara J. Wold9, James Taylor11, Ali Mortazavi15, Sherman M. Weissman18, John A. Stamatoyannopoulos4, Michael Snyder3, Roderic Guigó, Thomas R. Gingeras8, David M. Gilbert6, Ross C. Hardison1, Michael A. Beer20, Bing Ren2 
20 Nov 2014-Nature
TL;DR: 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 as mentioned in this paper.
Abstract: The laboratory mouse shares the majority of its protein-coding genes with humans, making it the premier model organism in biomedical research, 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 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

1,335 citations


Cited by
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28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
06 Sep 2012-Nature
TL;DR: The Encyclopedia of DNA Elements project provides new insights into the organization and regulation of the authors' genes and genome, and is an expansive resource of functional annotations for biomedical research.
Abstract: The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.

13,548 citations

Journal ArticleDOI
Adam Auton1, Gonçalo R. Abecasis2, David Altshuler3, Richard Durbin4  +514 moreInstitutions (90)
01 Oct 2015-Nature
TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

12,661 citations

Journal ArticleDOI
23 Jan 2015-Science
TL;DR: In this paper, a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level.
Abstract: Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

9,745 citations

Journal ArticleDOI
Monkol Lek, Konrad J. Karczewski1, Konrad J. Karczewski2, Eric Vallabh Minikel1, Eric Vallabh Minikel2, Kaitlin E. Samocha, Eric Banks1, Timothy Fennell1, Anne H. O’Donnell-Luria3, Anne H. O’Donnell-Luria2, Anne H. O’Donnell-Luria1, James S. Ware, Andrew J. Hill2, Andrew J. Hill1, Andrew J. Hill4, Beryl B. Cummings1, Beryl B. Cummings2, Taru Tukiainen1, Taru Tukiainen2, Daniel P. Birnbaum1, Jack A. Kosmicki, Laramie E. Duncan1, Laramie E. Duncan2, Karol Estrada1, Karol Estrada2, Fengmei Zhao2, Fengmei Zhao1, James Zou1, Emma Pierce-Hoffman2, Emma Pierce-Hoffman1, Joanne Berghout5, David Neil Cooper6, Nicole A. Deflaux7, Mark A. DePristo1, Ron Do, Jason Flannick1, Jason Flannick2, Menachem Fromer, Laura D. Gauthier1, Jackie Goldstein1, Jackie Goldstein2, Namrata Gupta1, Daniel P. Howrigan1, Daniel P. Howrigan2, Adam Kiezun1, Mitja I. Kurki2, Mitja I. Kurki1, Ami Levy Moonshine1, Pradeep Natarajan, Lorena Orozco, Gina M. Peloso1, Gina M. Peloso2, Ryan Poplin1, Manuel A. Rivas1, Valentin Ruano-Rubio1, Samuel A. Rose1, Douglas M. Ruderfer8, Khalid Shakir1, Peter D. Stenson6, Christine Stevens1, Brett Thomas1, Brett Thomas2, Grace Tiao1, María Teresa Tusié-Luna, Ben Weisburd1, Hong-Hee Won9, Dongmei Yu, David Altshuler1, David Altshuler10, Diego Ardissino, Michael Boehnke11, John Danesh12, Stacey Donnelly1, Roberto Elosua, Jose C. Florez2, Jose C. Florez1, Stacey Gabriel1, Gad Getz1, Gad Getz2, Stephen J. Glatt13, Christina M. Hultman14, Sekar Kathiresan, Markku Laakso15, Steven A. McCarroll2, Steven A. McCarroll1, Mark I. McCarthy16, Mark I. McCarthy17, Dermot P.B. McGovern18, Ruth McPherson19, Benjamin M. Neale1, Benjamin M. Neale2, Aarno Palotie, Shaun Purcell8, Danish Saleheen20, Jeremiah M. Scharf, Pamela Sklar, Patrick F. Sullivan14, Patrick F. Sullivan21, Jaakko Tuomilehto22, Ming T. Tsuang23, Hugh Watkins17, Hugh Watkins16, James G. Wilson24, Mark J. Daly1, Mark J. Daly2, Daniel G. MacArthur1, Daniel G. MacArthur2 
18 Aug 2016-Nature
TL;DR: The aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC) provides direct evidence for the presence of widespread mutational recurrence.
Abstract: Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

8,758 citations