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.
Topics: Population, Genome-wide association study, Genome, Gene, Chromatin
Papers published on a yearly basis
Papers
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University of Düsseldorf1, University of Duisburg-Essen2, Harvard University3, University of Warsaw4, St. Vincent's Institute of Medical Research5, University of Melbourne6, Johns Hopkins University7, Swiss Institute of Bioinformatics8, The Turing Institute9, Western General Hospital10, BC Cancer Agency11, University of British Columbia12, ETH Zurich13, Leiden University Medical Center14, Delft University of Technology15, Broad Institute16, Georgia State University17, Karlsruhe Institute of Technology18, Heidelberg Institute for Theoretical Studies19, Centrum Wiskunde & Informatica20, Utrecht University21, University of Amsterdam22, Imperial College London23, Radboud University Nijmegen24, University Medical Center Groningen25, Wageningen University and Research Centre26, University of Connecticut27, Wellcome Trust Sanger Institute28, European Bioinformatics Institute29, University of Cambridge30, Max Planck Society31, Saarland University32, Zuse Institute Berlin33, German Cancer Research Center34, Leiden University35, I.M. Sechenov First Moscow State Medical University36, Princeton University37, Memorial Sloan Kettering Cancer Center38
TL;DR: This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years in single-cell data science.
Abstract: The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands-or even millions-of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.
677 citations
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Baylor College of Medicine1, Washington University in St. Louis2, University of California, San Francisco3, University of British Columbia4, University of California, Santa Cruz5, University of California, Davis6, Salk Institute for Biological Studies7, Broad Institute8, Harvard University9, Ludwig Institute for Cancer Research10, University of California, San Diego11, University of Texas at Dallas12, Max Planck Society13
TL;DR: This work combined MeDIP-seq with methylation-sensitive restriction enzyme (MRE-seq) sequencing for comprehensive methylome coverage at lower cost and detected regions with allele-specific epigenetic states, identifying most known imprinted regions and new loci with Monoallelic epigenetic marks and monoallelic expression.
Abstract: Analysis of DNA methylation patterns relies increasingly on sequencing-based profiling methods. The four most frequently used sequencing-based technologies are the bisulfite-based methods MethylC-seq and reduced representation bisulfite sequencing (RRBS), and the enrichment-based techniques methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylated DNA binding domain sequencing (MBD-seq). We applied all four methods to biological replicates of human embryonic stem cells to assess their genome-wide CpG coverage, resolution, cost, concordance and the influence of CpG density and genomic context. The methylation levels assessed by the two bisulfite methods were concordant (their difference did not exceed a given threshold) for 82% for CpGs and 99% of the non-CpG cytosines. Using binary methylation calls, the two enrichment methods were 99% concordant and regions assessed by all four methods were 97% concordant. We combined MeDIP-seq with methylation-sensitive restriction enzyme (MRE-seq) sequencing for comprehensive methylome coverage at lower cost. This, along with RNA-seq and ChIP-seq of the ES cells enabled us to detect regions with allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression.
676 citations
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TL;DR: In this article, the extracellular matrix (ECM) is a fundamental component of multicellular organisms that provides mechanical and chemical cues that orchestrate cellular and tissue organization and functions.
674 citations
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TL;DR: The results suggest that the CD association at IRGM arises from an alteration in IRGM regulation that affects the efficacy of autophagy and a common deletion polymorphism is identified as a likely causal variant.
Abstract: Following recent success in genome-wide association studies, a critical focus of human genetics is to understand how genetic variation at implicated loci influences cellular and disease processes. Crohn's disease (CD) is associated with SNPs around IRGM, but coding-sequence variation has been excluded as a source of this association. We identified a common, 20-kb deletion polymorphism, immediately upstream of IRGM and in perfect linkage disequilibrium (r2 = 1.0) with the most strongly CD-associated SNP, that causes IRGM to segregate in the population with two distinct upstream sequences. The deletion (CD risk) and reference (CD protective) haplotypes of IRGM showed distinct expression patterns. Manipulation of IRGM expression levels modulated cellular autophagy of internalized bacteria, a process implicated in CD. These results suggest that the CD association at IRGM arises from an alteration in IRGM regulation that affects the efficacy of autophagy and identify a common deletion polymorphism as a likely causal variant.
673 citations
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TL;DR: It is shown that the ability of Cpf1 to process its own CRISPR RNA (crRNA) can be used to simplify multiplexed genome editing.
Abstract: Targeting of multiple genomic loci with Cas9 is limited by the need for multiple or large expression constructs. Here we show that the ability of Cpf1 to process its own CRISPR RNA (crRNA) can be used to simplify multiplexed genome editing. Using a single customized CRISPR array, we edit up to four genes in mammalian cells and three in the mouse brain, simultaneously.
673 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 |