Institution
Broad Institute
Nonprofit•Cambridge, 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 published on a yearly basis
Papers
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TL;DR: It is shown that chromosomally unstable tumour cells co-opt chronic activation of innate immune pathways to spread to distant organs by sustaining a tumour cell-autonomous response to cytosolic DNA.
Abstract: Chromosomal instability is a hallmark of cancer that results from ongoing errors in chromosome segregation during mitosis. Although chromosomal instability is a major driver of tumour evolution, its role in metastasis has not been established. Here we show that chromosomal instability promotes metastasis by sustaining a tumour cell-autonomous response to cytosolic DNA. Errors in chromosome segregation create a preponderance of micronuclei whose rupture spills genomic DNA into the cytosol. This leads to the activation of the cGAS-STING (cyclic GMP-AMP synthase-stimulator of interferon genes) cytosolic DNA-sensing pathway and downstream noncanonical NF-κB signalling. Genetic suppression of chromosomal instability markedly delays metastasis even in highly aneuploid tumour models, whereas continuous chromosome segregation errors promote cellular invasion and metastasis in a STING-dependent manner. By subverting lethal epithelial responses to cytosolic DNA, chromosomally unstable tumour cells co-opt chronic activation of innate immune pathways to spread to distant organs.
878 citations
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University of Texas Health Science Center at Houston1, Harvard University2, Broad Institute3, University of Wisconsin–Milwaukee4, University of Washington5, Washington University in St. Louis6, University of North Carolina at Chapel Hill7, Icahn School of Medicine at Mount Sinai8, University of Michigan9, Lund University10, University of Leicester11, Queen Mary University of London12, University of Oxford13, University of Milan14, University of Verona15, Merck & Co.16, National Institutes of Health17, Levanger Hospital18, Norwegian University of Science and Technology19, University of Ottawa20, Stanford University21, University of Iowa22, George Washington University23, Umeå University24, University of Dundee25, Cambridge University Hospitals NHS Foundation Trust26, Technische Universität München27, University of Kiel28, University of Lübeck29, University of Bonn30, Group Health Cooperative31, Houston Methodist Hospital32, Baylor College of Medicine33, Tufts University34, IMDEA35, University of Leeds36, King Abdulaziz University37, Wellcome Trust Sanger Institute38, University of Mississippi39, Fred Hutchinson Cancer Research Center40, University of Virginia41, University of Vermont42, Boston University43
TL;DR: Rare mutations that disrupt AP OC3 function were associated with lower levels of plasma triglycerides and APOC3, and carriers of these mutations were found to have a reduced risk of coronary heart disease.
Abstract: Background Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype. Methods We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons. Results An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G→A and IVS3+1G→T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10 − 20 ), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P = 8×10 − 10 ). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P = 4×10 − 6 ). Conclusions Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.)
877 citations
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TL;DR: Improvements in economics, resolution, and ease of use make CEL-Sequ2 uniquely suited to single-cell RNA-Seq analysis in terms of economics,resolution, and easing of use.
Abstract: Single-cell transcriptomics requires a method that is sensitive, accurate, and reproducible. Here, we present CEL-Seq2, a modified version of our CEL-Seq method, with threefold higher sensitivity, lower costs, and less hands-on time. We implemented CEL-Seq2 on Fluidigm’s C1 system, providing its first single-cell, on-chip barcoding method, and we detected gene expression changes accompanying the progression through the cell cycle in mouse fibroblast cells. We also compare with Smart-Seq to demonstrate CEL-Seq2’s increased sensitivity relative to other available methods. Collectively, the improvements make CEL-Seq2 uniquely suited to single-cell RNA-Seq analysis in terms of economics, resolution, and ease of use.
875 citations
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TL;DR: In this article, the authors investigated the localization mechanisms of the Xist lncRNA during X-chromosome inactivation (XCI), a paradigm of lncRN-mediated chromatin regulation.
Abstract: Many large noncoding RNAs (lncRNAs) regulate chromatin, but the mechanisms by which they localize to genomic targets remain unexplored. We investigated the localization mechanisms of the Xist lncRNA during X-chromosome inactivation (XCI), a paradigm of lncRNA-mediated chromatin regulation. During the maintenance of XCI, Xist binds broadly across the X chromosome. During initiation of XCI, Xist initially transfers to distal regions across the X chromosome that are not defined by specific sequences. Instead, Xist identifies these regions by exploiting the three-dimensional conformation of the X chromosome. Xist requires its silencing domain to spread across actively transcribed regions and thereby access the entire chromosome. These findings suggest a model in which Xist coats the X chromosome by searching in three dimensions, modifying chromosome structure, and spreading to newly accessible locations.
875 citations
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Northern Arizona University1, University of Minnesota2, University of California, Davis3, Woods Hole Oceanographic Institution4, Massachusetts Institute of Technology5, University of Copenhagen6, University of Trento7, Chinese Academy of Sciences8, University of California, San Francisco9, Children's Hospital of Philadelphia10, Pacific Northwest National Laboratory11, North Carolina State University12, University of Montana13, Dalhousie University14, University of British Columbia15, Shedd Aquarium16, University of Colorado Denver17, University of California, San Diego18, Michigan State University19, Stanford University20, Broad Institute21, Harvard University22, Australian National University23, University of Düsseldorf24, Sookmyung Women's University25, San Diego State University26, Howard Hughes Medical Institute27, Max Planck Society28, Cornell University29, University of Washington30, Colorado State University31, Google32, Syracuse University33, Webster University34, United States Department of Agriculture35, University of Arkansas for Medical Sciences36, Colorado School of Mines37, University of Southern Mississippi38, Atlantic Oceanographic and Meteorological Laboratory39, University of California, Merced40, Wageningen University and Research Centre41, University of Arizona42, Environment Agency43, University of Florida44, Merck & Co.45
TL;DR: QIIME 2 provides new features that will drive the next generation of microbiome research, including interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.
Abstract: We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.
875 citations
Authors
Showing all 7146 results
Name | H-index | Papers | Citations |
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Eric S. Lander | 301 | 826 | 525976 |
Albert Hofman | 267 | 2530 | 321405 |
Frank B. Hu | 250 | 1675 | 253464 |
David J. Hunter | 213 | 1836 | 207050 |
Kari Stefansson | 206 | 794 | 174819 |
Mark J. Daly | 204 | 763 | 304452 |
Lewis C. Cantley | 196 | 748 | 169037 |
Matthew Meyerson | 194 | 553 | 243726 |
Gad Getz | 189 | 520 | 247560 |
Stacey Gabriel | 187 | 383 | 294284 |
Stuart H. Orkin | 186 | 715 | 112182 |
Ralph Weissleder | 184 | 1160 | 142508 |
Chris Sander | 178 | 713 | 233287 |
Michael I. Jordan | 176 | 1016 | 216204 |
Richard A. Young | 173 | 520 | 126642 |