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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Katholieke Universiteit Leuven1, Wellcome Trust Sanger Institute2, Montreal Heart Institute3, Canterbury Christ Church University4, Wellcome Trust Centre for Human Genetics5, University of Chicago6, University of Kiel7, Peninsula College of Medicine and Dentistry8, University of Adelaide9, Royal Adelaide Hospital10, Casa Sollievo della Sofferenza11, Ludwig Maximilian University of Munich12, Johns Hopkins University13, Yale University14, Broad Institute15, Cedars-Sinai Medical Center16, University of Pittsburgh17, University of Auckland18, University of Otago19, Christchurch Hospital20, Children's Hospital of Philadelphia21, Örebro University22, Oslo University Hospital23, University of Edinburgh24, Lithuanian University of Health Sciences25, University of Western Australia26, University of Cambridge27, University of Liège28, Leiden University Medical Center29, University Medical Center Groningen30, Royal Hospital for Sick Children31, Newcastle University32, University of Toronto33, QIMR Berghofer Medical Research Institute34, Royal Brisbane and Women's Hospital35
TL;DR: The largest genotype association study, to date, in widely used clinical subphenotypes of inflammatory bowel disease with the goal of further understanding the biological relations between diseases.
563 citations
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TL;DR: This approach provides a general framework to decipher differences between classes of human tumors by decoupling cancer cell genotypes, phenotypes, and the composition of the TME.
Abstract: Tumor subclasses differ according to the genotypes and phenotypes of malignant cells as well as the composition of the tumor microenvironment (TME). We dissected these influences in isocitrate dehydrogenase (IDH)-mutant gliomas by combining 14,226 single-cell RNA sequencing (RNA-seq) profiles from 16 patient samples with bulk RNA-seq profiles from 165 patient samples. Differences in bulk profiles between IDH-mutant astrocytoma and oligodendroglioma can be primarily explained by distinct TME and signature genetic events, whereas both tumor types share similar developmental hierarchies and lineages of glial differentiation. As tumor grade increases, we find enhanced proliferation of malignant cells, larger pools of undifferentiated glioma cells, and an increase in macrophage over microglia expression programs in TME. Our work provides a unifying model for IDH-mutant gliomas and a general framework for dissecting the differences among human tumor subclasses.
563 citations
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TL;DR: In this paper, the authors applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (hg(2)) across functional categories.
Abstract: Regulatory and coding variants are known to be enriched with associations identified by genome-wide association studies (GWASs) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (hg(2)) across functional categories (while accounting for shared variance due to linkage disequilibrium). Extensive simulations showed that in contrast to current estimates from GWAS summary statistics, the variance-component approach partitions heritability accurately under a wide range of complex-disease architectures. Across the 11 diseases DNaseI hypersensitivity sites (DHSs) from 217 cell types spanned 16% of imputed SNPs (and 24% of genotyped SNPs) but explained an average of 79% (SE = 8%) of hg(2) from imputed SNPs (5.1× enrichment; p = 3.7 × 10(-17)) and 38% (SE = 4%) of hg(2) from genotyped SNPs (1.6× enrichment, p = 1.0 × 10(-4)). Further enrichment was observed at enhancer DHSs and cell-type-specific DHSs. In contrast, coding variants, which span 1% of the genome, explained <10% of hg(2) despite having the highest enrichment. We replicated these findings but found no significant contribution from rare coding variants in independent schizophrenia cohorts genotyped on GWAS and exome chips. Our results highlight the value of analyzing components of heritability to unravel the functional architecture of common disease.
562 citations
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TL;DR: Fourth-generation base editors (BE4 and SaBE4) are engineered that increase the efficiency of C:G to T:A base editing by approximately 50%, while halving the frequency of undesired by-products compared to BE3, and recommend their use in future efforts.
Abstract: We recently developed base editing, the programmable conversion of target C:G base pairs to T:A without inducing double-stranded DNA breaks (DSBs) or requiring homology-directed repair using engineered fusions of Cas9 variants and cytidine deaminases. Over the past year, the third-generation base editor (BE3) and related technologies have been successfully used by many researchers in a wide range of organisms. The product distribution of base editing-the frequency with which the target C:G is converted to mixtures of undesired by-products, along with the desired T:A product-varies in a target site-dependent manner. We characterize determinants of base editing outcomes in human cells and establish that the formation of undesired products is dependent on uracil N-glycosylase (UNG) and is more likely to occur at target sites containing only a single C within the base editing activity window. We engineered CDA1-BE3 and AID-BE3, which use cytidine deaminase homologs that increase base editing efficiency for some sequences. On the basis of these observations, we engineered fourth-generation base editors (BE4 and SaBE4) that increase the efficiency of C:G to T:A base editing by approximately 50%, while halving the frequency of undesired by-products compared to BE3. Fusing BE3, BE4, SaBE3, or SaBE4 to Gam, a bacteriophage Mu protein that binds DSBs greatly reduces indel formation during base editing, in most cases to below 1.5%, and further improves product purity. BE4, SaBE4, BE4-Gam, and SaBE4-Gam represent the state of the art in C:G-to-T:A base editing, and we recommend their use in future efforts.
560 citations
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TL;DR: It is found that ML239, originally identified in a phenotypic screen for selective cytotoxicity in breast cancer stem-like cells, most likely acts through activation of fatty acid desaturase 2 (FADS2).
Abstract: Changes in cellular gene expression in response to small-molecule or genetic perturbations have yielded signatures that can connect unknown mechanisms of action (MoA) to ones previously established. We hypothesized that differential basal gene expression could be correlated with patterns of small-molecule sensitivity across many cell lines to illuminate the actions of compounds whose MoA are unknown. To test this idea, we correlated the sensitivity patterns of 481 compounds with ∼19,000 basal transcript levels across 823 different human cancer cell lines and identified selective outlier transcripts. This process yielded many novel mechanistic insights, including the identification of activation mechanisms, cellular transporters and direct protein targets. We found that ML239, originally identified in a phenotypic screen for selective cytotoxicity in breast cancer stem-like cells, most likely acts through activation of fatty acid desaturase 2 (FADS2). These data and analytical tools are available to the research community through the Cancer Therapeutics Response Portal.
560 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 |