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Institution

Broad Institute

NonprofitCambridge, Massachusetts, United States
About: Broad Institute is a nonprofit organization based out in Cambridge, Massachusetts, United States. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 6584 authors who have published 11618 publications receiving 1522743 citations. The organization is also known as: Eli and Edythe L. Broad Institute of MIT and Harvard.


Papers
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Journal ArticleDOI
Yukinori Okada1, Yukinori Okada2, Di Wu3, Di Wu1, Di Wu2, Gosia Trynka2, Gosia Trynka1, Towfique Raj1, Towfique Raj2, Chikashi Terao4, Katsunori Ikari, Yuta Kochi, Koichiro Ohmura4, Akari Suzuki, Shinji Yoshida, Robert R. Graham5, A. Manoharan5, Ward Ortmann5, Tushar Bhangale5, Joshua C. Denny6, Robert J. Carroll6, Anne E. Eyler6, Jeff Greenberg7, Joel M. Kremer, Dimitrios A. Pappas8, Lei Jiang9, Jian Yin9, Lingying Ye9, Ding Feng Su9, Jian Yang10, Gang Xie11, E.C. Keystone11, Harm-Jan Westra12, Tõnu Esko2, Tõnu Esko1, Tõnu Esko13, Andres Metspalu13, Xuezhong Zhou14, Namrata Gupta2, Daniel B. Mirel2, Eli A. Stahl15, Dorothee Diogo1, Dorothee Diogo2, Jing Cui1, Jing Cui2, Katherine P. Liao2, Katherine P. Liao1, Michael H. Guo1, Michael H. Guo2, Keiko Myouzen, Takahisa Kawaguchi4, Marieke J H Coenen16, Piet L. C. M. van Riel16, Mart A F J van de Laar17, Henk-Jan Guchelaar18, Tom W J Huizinga18, Philippe Dieudé19, Xavier Mariette20, S. Louis Bridges21, Alexandra Zhernakova18, Alexandra Zhernakova12, René E. M. Toes18, Paul P. Tak22, Paul P. Tak23, Paul P. Tak24, Corinne Miceli-Richard20, So Young Bang25, Hye Soon Lee25, Javier Martin26, Miguel A. Gonzalez-Gay, Luis Rodriguez-Rodriguez27, Solbritt Rantapää-Dahlqvist28, Lisbeth Ärlestig28, Hyon K. Choi1, Hyon K. Choi29, Yoichiro Kamatani30, Pilar Galan19, Mark Lathrop31, Steve Eyre32, Steve Eyre33, John Bowes33, John Bowes32, Anne Barton32, Niek de Vries22, Larry W. Moreland34, Lindsey A. Criswell35, Elizabeth W. Karlson1, Atsuo Taniguchi, Ryo Yamada4, Michiaki Kubo, Jun Liu1, Sang Cheol Bae25, Jane Worthington32, Jane Worthington33, Leonid Padyukov36, Lars Klareskog36, Peter K. Gregersen37, Soumya Raychaudhuri1, Soumya Raychaudhuri2, Barbara E. Stranger38, Philip L. De Jager2, Philip L. De Jager1, Lude Franke12, Peter M. Visscher10, Matthew A. Brown10, Hisashi Yamanaka, Tsuneyo Mimori4, Atsushi Takahashi, Huji Xu9, Timothy W. Behrens5, Katherine A. Siminovitch11, Shigeki Momohara, Fumihiko Matsuda4, Kazuhiko Yamamoto39, Robert M. Plenge2, Robert M. Plenge1 
20 Feb 2014-Nature
TL;DR: A genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries provides empirical evidence that the genetics of RA can provide important information for drug discovery, and sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis.
Abstract: A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

1,910 citations

Book ChapterDOI
Le Cong1, Feng Zhang
TL;DR: This chapter presents all relevant methods including the initial site selection, molecular cloning, delivery of guide RNAs and Cas9 into mammalian cells, verification of target cleavage, and assays for detecting genomic modification including indels and homologous recombination.
Abstract: The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9 system is an adaptive immune system that exists in a variety of microbes. It could be engineered to function in eukaryotic cells as a fast, low-cost, efficient, and scalable tool for manipulating genomic sequences. In this chapter, detailed protocols are described for harnessing the CRISPR-Cas9 system from Streptococcus pyogenes to enable RNA-guided genome engineering applications in mammalian cells. We present all relevant methods including the initial site selection, molecular cloning, delivery of guide RNAs (gRNAs) and Cas9 into mammalian cells, verification of target cleavage, and assays for detecting genomic modification including indels and homologous recombination. These tools provide researchers with new instruments that accelerate both forward and reverse genetics efforts.

1,902 citations

Journal ArticleDOI
TL;DR: This article conducted a meta-analysis of genetic variants on the Metabochip, including 34,840 cases and 114,981 controls, overwhelmingly of European descent, and identified ten previously unreported T2D susceptibility loci, including two showing sex-differentiated association.
Abstract: To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip, including 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two showing sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of additional common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signaling and cell cycle regulation, in diabetes pathogenesis.

1,899 citations

Journal ArticleDOI
Naomi R. Wray1, Stephan Ripke2, Stephan Ripke3, Stephan Ripke4  +259 moreInstitutions (79)
TL;DR: A genome-wide association meta-analysis of individuals with clinically assessed or self-reported depression identifies 44 independent and significant loci and finds important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia.
Abstract: Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

1,898 citations

Journal ArticleDOI
26 Sep 2013-Nature
TL;DR: Se sequencing and deep analysis of messenger RNA and microRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project—the first uniformly processed high-throughput RNA-sequencing data from multiple human populations with high-quality genome sequences discover extremely widespread genetic variation affecting the regulation of most genes.
Abstract: Genome sequencing projects are discovering millions of genetic variants in humans, and interpretation of their functional effects is essential for understanding the genetic basis of variation in human traits. Here we report sequencing and deep analysis of messenger RNA and microRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project--the first uniformly processed high-throughput RNA-sequencing data from multiple human populations with high-quality genome sequences. We discover extremely widespread genetic variation affecting the regulation of most genes, with transcript structure and expression level variation being equally common but genetically largely independent. Our characterization of causal regulatory variation sheds light on the cellular mechanisms of regulatory and loss-of-function variation, and allows us to infer putative causal variants for dozens of disease-associated loci. Altogether, this study provides a deep understanding of the cellular mechanisms of transcriptome variation and of the landscape of functional variants in the human genome.

1,892 citations


Authors

Showing all 7146 results

NameH-indexPapersCitations
Eric S. Lander301826525976
Albert Hofman2672530321405
Frank B. Hu2501675253464
David J. Hunter2131836207050
Kari Stefansson206794174819
Mark J. Daly204763304452
Lewis C. Cantley196748169037
Matthew Meyerson194553243726
Gad Getz189520247560
Stacey Gabriel187383294284
Stuart H. Orkin186715112182
Ralph Weissleder1841160142508
Chris Sander178713233287
Michael I. Jordan1761016216204
Richard A. Young173520126642
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202337
2022628
20211,727
20201,534
20191,364
20181,107