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Institution

Wellcome Trust Sanger Institute

NonprofitCambridge, United Kingdom
About: Wellcome Trust Sanger Institute is a nonprofit organization based out in Cambridge, United Kingdom. It is known for research contribution in the topics: Population & Genome. The organization has 4009 authors who have published 9671 publications receiving 1224479 citations.


Papers
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Journal ArticleDOI
Thomas J. Hudson1, Thomas J. Hudson2, Warwick Anderson3, Axel Aretz4  +270 moreInstitutions (92)
15 Apr 2010
TL;DR: Systematic studies of more than 25,000 cancer genomes will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.
Abstract: The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.

2,041 citations

Journal ArticleDOI
Robert A. Holt1, G. Mani Subramanian1, Aaron L. Halpern1, Granger G. Sutton1, Rosane Charlab1, Deborah R. Nusskern1, Patrick Wincker2, Andrew G. Clark3, José M. C. Ribeiro4, Ron Wides5, Steven L. Salzberg6, Brendan J. Loftus6, Mark Yandell1, William H. Majoros1, William H. Majoros6, Douglas B. Rusch1, Zhongwu Lai1, Cheryl L. Kraft1, Josep F. Abril, Véronique Anthouard2, Peter Arensburger7, Peter W. Atkinson7, Holly Baden1, Véronique de Berardinis2, Danita Baldwin1, Vladimir Benes, Jim Biedler8, Claudia Blass, Randall Bolanos1, Didier Boscus2, Mary Barnstead1, Shuang Cai1, Kabir Chatuverdi1, George K. Christophides, Mathew A. Chrystal9, Michele Clamp10, Anibal Cravchik1, Val Curwen10, Ali N Dana9, Arthur L. Delcher1, Ian M. Dew1, Cheryl A. Evans1, Michael Flanigan1, Anne Grundschober-Freimoser11, Lisa Friedli7, Zhiping Gu1, Ping Guan1, Roderic Guigó, Maureen E. Hillenmeyer9, Susanne L. Hladun1, James R. Hogan9, Young S. Hong9, Jeffrey Hoover1, Olivier Jaillon2, Zhaoxi Ke1, Zhaoxi Ke9, Chinnappa D. Kodira1, Kokoza Eb, Anastasios C. Koutsos12, Ivica Letunic, Alex Levitsky1, Yong Liang1, Jhy-Jhu Lin6, Jhy-Jhu Lin1, Neil F. Lobo9, John Lopez1, Joel A. Malek6, Tina C. McIntosh1, Stephan Meister, Jason R. Miller1, Clark M. Mobarry1, Emmanuel Mongin13, Sean D. Murphy1, David A. O'Brochta11, Cynthia Pfannkoch1, Rong Qi1, Megan A. Regier1, Karin A. Remington1, Hongguang Shao8, Maria V. Sharakhova9, Cynthia Sitter1, Jyoti Shetty6, Thomas J. Smith1, Renee Strong1, Jingtao Sun1, Dana Thomasova, Lucas Q. Ton9, Pantelis Topalis12, Zhijian Tu8, Maria F. Unger9, Brian P. Walenz1, Aihui Wang1, Jian Wang1, Mei Wang1, X. Wang9, Kerry J. Woodford1, Jennifer R. Wortman1, Jennifer R. Wortman6, Martin Wu6, Alison Yao1, Evgeny M. Zdobnov, Hongyu Zhang1, Qi Zhao1, Shaying Zhao6, Shiaoping C. Zhu1, Igor F. Zhimulev, Mario Coluzzi14, Alessandra della Torre14, Charles Roth15, Christos Louis12, Francis Kalush1, Richard J. Mural1, Eugene W. Myers1, Mark Raymond Adams1, Hamilton O. Smith1, Samuel Broder1, Malcolm J. Gardner6, Claire M. Fraser6, Ewan Birney13, Peer Bork, Paul T. Brey15, J. Craig Venter1, J. Craig Venter6, Jean Weissenbach2, Fotis C. Kafatos, Frank H. Collins9, Stephen L. Hoffman1 
04 Oct 2002-Science
TL;DR: Analysis of the PEST strain of A. gambiae revealed strong evidence for about 14,000 protein-encoding transcripts, and prominent expansions in specific families of proteins likely involved in cell adhesion and immunity were noted.
Abstract: Anopheles gambiae is the principal vector of malaria, a disease that afflicts more than 500 million people and causes more than 1 million deaths each year. Tenfold shotgun sequence coverage was obtained from the PEST strain of A. gambiae and assembled into scaffolds that span 278 million base pairs. A total of 91% of the genome was organized in 303 scaffolds; the largest scaffold was 23.1 million base pairs. There was substantial genetic variation within this strain, and the apparent existence of two haplotypes of approximately equal frequency ("dual haplotypes") in a substantial fraction of the genome likely reflects the outbred nature of the PEST strain. The sequence produced a conservative inference of more than 400,000 single-nucleotide polymorphisms that showed a markedly bimodal density distribution. Analysis of the genome sequence revealed strong evidence for about 14,000 protein-encoding transcripts. Prominent expansions in specific families of proteins likely involved in cell adhesion and immunity were noted. An expressed sequence tag analysis of genes regulated by blood feeding provided insights into the physiological adaptations of a hematophagous insect.

2,033 citations

Journal ArticleDOI
TL;DR: In this paper, the expression of viral entry-associated genes in single-cell RNA-sequencing data from multiple tissues from healthy human donors was investigated, and co-detected these transcripts in specific respiratory, corneal and intestinal epithelial cells, potentially explaining the high efficiency of SARS-CoV-2 transmission.
Abstract: We investigated SARS-CoV-2 potential tropism by surveying expression of viral entry-associated genes in single-cell RNA-sequencing data from multiple tissues from healthy human donors. We co-detected these transcripts in specific respiratory, corneal and intestinal epithelial cells, potentially explaining the high efficiency of SARS-CoV-2 transmission. These genes are co-expressed in nasal epithelial cells with genes involved in innate immunity, highlighting the cells' potential role in initial viral infection, spread and clearance. The study offers a useful resource for further lines of inquiry with valuable clinical samples from COVID-19 patients and we provide our data in a comprehensive, open and user-friendly fashion at www.covid19cellatlas.org.

2,024 citations

Journal ArticleDOI
Josée Dupuis1, Josée Dupuis2, Claudia Langenberg, Inga Prokopenko3  +336 moreInstitutions (82)
TL;DR: It is demonstrated that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.
Abstract: Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.

2,022 citations

Journal ArticleDOI
TL;DR: All three fast turnaround sequencers evaluated here were able to generate usable sequence, however there are key differences between the quality of that data and the applications it will support.
Abstract: Next generation sequencing (NGS) technology has revolutionized genomic and genetic research. The pace of change in this area is rapid with three major new sequencing platforms having been released in 2011: Ion Torrent’s PGM, Pacific Biosciences’ RS and the Illumina MiSeq. Here we compare the results obtained with those platforms to the performance of the Illumina HiSeq, the current market leader. In order to compare these platforms, and get sufficient coverage depth to allow meaningful analysis, we have sequenced a set of 4 microbial genomes with mean GC content ranging from 19.3 to 67.7%. Together, these represent a comprehensive range of genome content. Here we report our analysis of that sequence data in terms of coverage distribution, bias, GC distribution, variant detection and accuracy. Sequence generated by Ion Torrent, MiSeq and Pacific Biosciences technologies displays near perfect coverage behaviour on GC-rich, neutral and moderately AT-rich genomes, but a profound bias was observed upon sequencing the extremely AT-rich genome of Plasmodium falciparum on the PGM, resulting in no coverage for approximately 30% of the genome. We analysed the ability to call variants from each platform and found that we could call slightly more variants from Ion Torrent data compared to MiSeq data, but at the expense of a higher false positive rate. Variant calling from Pacific Biosciences data was possible but higher coverage depth was required. Context specific errors were observed in both PGM and MiSeq data, but not in that from the Pacific Biosciences platform. All three fast turnaround sequencers evaluated here were able to generate usable sequence. However there are key differences between the quality of that data and the applications it will support.

1,967 citations


Authors

Showing all 4058 results

NameH-indexPapersCitations
Nicholas J. Wareham2121657204896
Gonçalo R. Abecasis179595230323
Panos Deloukas162410154018
Michael R. Stratton161443142586
David W. Johnson1602714140778
Michael John Owen1601110135795
Naveed Sattar1551326116368
Robert E. W. Hancock15277588481
Julian Parkhill149759104736
Nilesh J. Samani149779113545
Michael Conlon O'Donovan142736118857
Jian Yang1421818111166
Christof Koch141712105221
Andrew G. Clark140823123333
Stylianos E. Antonarakis13874693605
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202317
202270
2021836
2020810
2019854
2018764