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Showing papers by "Broad Institute published in 2017"


Journal ArticleDOI
23 Nov 2017-Nature
TL;DR: Adenine base editors (ABEs) that mediate the conversion of A•T to G•C in genomic DNA are described and a transfer RNA adenosine deaminase is evolved to operate on DNA when fused to a catalytically impaired CRISPR–Cas9 mutant.
Abstract: The spontaneous deamination of cytosine is a major source of transitions from C•G to T•A base pairs, which account for half of known pathogenic point mutations in humans. The ability to efficiently convert targeted A•T base pairs to G•C could therefore advance the study and treatment of genetic diseases. The deamination of adenine yields inosine, which is treated as guanine by polymerases, but no enzymes are known to deaminate adenine in DNA. Here we describe adenine base editors (ABEs) that mediate the conversion of A•T to G•C in genomic DNA. We evolved a transfer RNA adenosine deaminase to operate on DNA when fused to a catalytically impaired CRISPR-Cas9 mutant. Extensive directed evolution and protein engineering resulted in seventh-generation ABEs that convert targeted A•T base pairs efficiently to G•C (approximately 50% efficiency in human cells) with high product purity (typically at least 99.9%) and low rates of indels (typically no more than 0.1%). ABEs introduce point mutations more efficiently and cleanly, and with less off-target genome modification, than a current Cas9 nuclease-based method, and can install disease-correcting or disease-suppressing mutations in human cells. Together with previous base editors, ABEs enable the direct, programmable introduction of all four transition mutations without double-stranded DNA cleavage.

2,451 citations


Journal ArticleDOI
TL;DR: Measurements of TMB from comprehensive genomic profiling are strongly reflective of measurements from whole exome sequencing and model that below 0.5 Mb the variance in measurement increases significantly, demonstrating that many disease types have a substantial portion of patients with high TMB who might benefit from immunotherapy.
Abstract: High tumor mutational burden (TMB) is an emerging biomarker of sensitivity to immune checkpoint inhibitors and has been shown to be more significantly associated with response to PD-1 and PD-L1 blockade immunotherapy than PD-1 or PD-L1 expression, as measured by immunohistochemistry (IHC). The distribution of TMB and the subset of patients with high TMB has not been well characterized in the majority of cancer types. In this study, we compare TMB measured by a targeted comprehensive genomic profiling (CGP) assay to TMB measured by exome sequencing and simulate the expected variance in TMB when sequencing less than the whole exome. We then describe the distribution of TMB across a diverse cohort of 100,000 cancer cases and test for association between somatic alterations and TMB in over 100 tumor types. We demonstrate that measurements of TMB from comprehensive genomic profiling are strongly reflective of measurements from whole exome sequencing and model that below 0.5 Mb the variance in measurement increases significantly. We find that a subset of patients exhibits high TMB across almost all types of cancer, including many rare tumor types, and characterize the relationship between high TMB and microsatellite instability status. We find that TMB increases significantly with age, showing a 2.4-fold difference between age 10 and age 90 years. Finally, we investigate the molecular basis of TMB and identify genes and mutations associated with TMB level. We identify a cluster of somatic mutations in the promoter of the gene PMS2, which occur in 10% of skin cancers and are highly associated with increased TMB. These results show that a CGP assay targeting ~1.1 Mb of coding genome can accurately assess TMB compared with sequencing the whole exome. Using this method, we find that many disease types have a substantial portion of patients with high TMB who might benefit from immunotherapy. Finally, we identify novel, recurrent promoter mutations in PMS2, which may be another example of regulatory mutations contributing to tumorigenesis.

2,304 citations


Journal ArticleDOI
28 Apr 2017-Science
TL;DR: A Cas13a-based molecular detection platform, termed Specific High-Sensitivity Enzymatic Reporter UnLOCKing (SHERLOCK), is used to detect specific strains of Zika and Dengue virus, distinguish pathogenic bacteria, genotype human DNA, and identify mutations in cell-free tumor DNA.
Abstract: Rapid, inexpensive, and sensitive nucleic acid detection may aid point-of-care pathogen detection, genotyping, and disease monitoring. The RNA-guided, RNA-targeting clustered regularly interspaced short palindromic repeats (CRISPR) effector Cas13a (previously known as C2c2) exhibits a “collateral effect” of promiscuous ribonuclease activity upon target recognition. We combine the collateral effect of Cas13a with isothermal amplification to establish a CRISPR-based diagnostic (CRISPR-Dx), providing rapid DNA or RNA detection with attomolar sensitivity and single-base mismatch specificity. We use this Cas13a-based molecular detection platform, termed Specific High-Sensitivity Enzymatic Reporter UnLOCKing (SHERLOCK), to detect specific strains of Zika and Dengue virus, distinguish pathogenic bacteria, genotype human DNA, and identify mutations in cell-free tumor DNA. Furthermore, SHERLOCK reaction reagents can be lyophilized for cold-chain independence and long-term storage and be readily reconstituted on paper for field applications.

1,946 citations


Journal ArticleDOI
30 Nov 2017-Cell
TL;DR: The expanded CMap is reported, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that is shown to be highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts.

1,943 citations


Journal ArticleDOI
05 Jul 2017-Nature
TL;DR: The feasibility, safety, and immunogenicity of a vaccine that targets up to 20 predicted personal tumour neoantigens is demonstrated and a strong rationale for further development of this approach, alone and in combination with checkpoint blockade or other immunotherapies is provided.
Abstract: Effective anti-tumour immunity in humans has been associated with the presence of T cells directed at cancer neoantigens, a class of HLA-bound peptides that arise from tumour-specific mutations. They are highly immunogenic because they are not present in normal tissues and hence bypass central thymic tolerance. Although neoantigens were long-envisioned as optimal targets for an anti-tumour immune response, their systematic discovery and evaluation only became feasible with the recent availability of massively parallel sequencing for detection of all coding mutations within tumours, and of machine learning approaches to reliably predict those mutated peptides with high-affinity binding of autologous human leukocyte antigen (HLA) molecules. We hypothesized that vaccination with neoantigens can both expand pre-existing neoantigen-specific T-cell populations and induce a broader repertoire of new T-cell specificities in cancer patients, tipping the intra-tumoural balance in favour of enhanced tumour control. Here we demonstrate the feasibility, safety, and immunogenicity of a vaccine that targets up to 20 predicted personal tumour neoantigens. Vaccine-induced polyfunctional CD4+ and CD8+ T cells targeted 58 (60%) and 15 (16%) of the 97 unique neoantigens used across patients, respectively. These T cells discriminated mutated from wild-type antigens, and in some cases directly recognized autologous tumour. Of six vaccinated patients, four had no recurrence at 25 months after vaccination, while two with recurrent disease were subsequently treated with anti-PD-1 (anti-programmed cell death-1) therapy and experienced complete tumour regression, with expansion of the repertoire of neoantigen-specific T cells. These data provide a strong rationale for further development of this approach, alone and in combination with checkpoint blockade or other immunotherapies.

1,921 citations


Journal ArticleDOI
01 Nov 2017-Nature
TL;DR: A meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project is presented, creating both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity.
Abstract: Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity.

1,676 citations


Journal ArticleDOI
A. Gordon Robertson1, Jaegil Kim2, Hikmat Al-Ahmadie3, Joaquim Bellmunt4  +167 moreInstitutions (16)
19 Oct 2017-Cell
TL;DR: An analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms identified 5 expression subtypes that may stratify response to different treatments and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology.

1,638 citations


Journal ArticleDOI
TL;DR: The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies and provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response.
Abstract: The reliability and validity of traditional taxonomies are limited by arbitrary boundaries between psychopathology and normality, often unclear boundaries between disorders, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. These taxonomies went beyond evidence available on the structure of psychopathology and were shaped by a variety of other considerations, which may explain the aforementioned shortcomings. The Hierarchical Taxonomy Of Psychopathology (HiTOP) model has emerged as a research effort to address these problems. It constructs psychopathological syndromes and their components/subtypes based on the observed covariation of symptoms, grouping related symptoms together and thus reducing heterogeneity. It also combines co-occurring syndromes into spectra, thereby mapping out comorbidity. Moreover, it characterizes these phenomena dimensionally, which addresses boundary problems and diagnostic instability. Here, we review the development of the HiTOP and the relevant evidence. The new classification already covers most forms of psychopathology. Dimensional measures have been developed to assess many of the identified components, syndromes, and spectra. Several domains of this model are ready for clinical and research applications. The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies. It also provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response. This can greatly improve the utility of the diagnosis of mental disorders. The new classification remains a work in progress. However, it is developing rapidly and is poised to advance mental health research and care significantly as the relevant science matures. (PsycINFO Database Record

1,635 citations


Journal ArticleDOI
27 Jul 2017-Cell
TL;DR: DEMETER, an analytical framework that segregates on- from off-target effects of RNAi, demonstrates the basis behind one such predictive model linking hypermethylation of the UBB ubiquitin gene to a dependency on UBC and provides a foundation for a cancer dependency map that facilitates the prioritization of therapeutic targets.

1,533 citations


Journal ArticleDOI
21 Apr 2017-Science
TL;DR: This refined analysis has identified, among others, a previously unknown dendritic cell population that potently activates T cells and reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability.
Abstract: INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.

1,468 citations



Journal ArticleDOI
Aviv Regev1, Aviv Regev2, Aviv Regev3, Sarah A. Teichmann4, Sarah A. Teichmann5, Sarah A. Teichmann6, Eric S. Lander3, Eric S. Lander2, Eric S. Lander7, Ido Amit8, Christophe Benoist7, Ewan Birney5, Bernd Bodenmiller5, Bernd Bodenmiller9, Peter J. Campbell6, Peter J. Campbell4, Piero Carninci6, Menna R. Clatworthy10, Hans Clevers11, Bart Deplancke12, Ian Dunham5, James Eberwine13, Roland Eils14, Roland Eils15, Wolfgang Enard16, Andrew Farmer, Lars Fugger17, Berthold Göttgens6, Nir Hacohen2, Nir Hacohen7, Muzlifah Haniffa18, Martin Hemberg4, Seung K. Kim19, Paul Klenerman17, Paul Klenerman20, Arnold R. Kriegstein21, Ed S. Lein22, Sten Linnarsson23, Emma Lundberg24, Emma Lundberg19, Joakim Lundeberg24, Partha P. Majumder, John C. Marioni4, John C. Marioni6, John C. Marioni5, Miriam Merad25, Musa M. Mhlanga26, Martijn C. Nawijn27, Mihai G. Netea28, Garry P. Nolan19, Dana Pe'er29, Anthony Phillipakis2, Chris P. Ponting30, Stephen R. Quake19, Wolf Reik4, Wolf Reik31, Wolf Reik6, Orit Rozenblatt-Rosen2, Joshua R. Sanes7, Rahul Satija32, Ton N. Schumacher33, Alex K. Shalek34, Alex K. Shalek3, Alex K. Shalek2, Ehud Shapiro8, Padmanee Sharma35, Jay W. Shin, Oliver Stegle5, Michael R. Stratton4, Michael J. T. Stubbington4, Fabian J. Theis36, Matthias Uhlen24, Matthias Uhlen37, Alexander van Oudenaarden11, Allon Wagner38, Fiona M. Watt39, Jonathan S. Weissman, Barbara J. Wold40, Ramnik J. Xavier, Nir Yosef38, Nir Yosef34, Human Cell Atlas Meeting Participants 
05 Dec 2017-eLife
TL;DR: An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease.
Abstract: The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

Journal ArticleDOI
Andrew I R Maas1, David K. Menon2, P. David Adelson3, Nada Andelic4  +339 moreInstitutions (110)
TL;DR: The InTBIR Participants and Investigators have provided informed consent for the study to take place in Poland.
Abstract: Additional co-authors: Endre Czeiter, Marek Czosnyka, Ramon Diaz-Arrastia, Jens P Dreier, Ann-Christine Duhaime, Ari Ercole, Thomas A van Essen, Valery L Feigin, Guoyi Gao, Joseph Giacino, Laura E Gonzalez-Lara, Russell L Gruen, Deepak Gupta, Jed A Hartings, Sean Hill, Ji-yao Jiang, Naomi Ketharanathan, Erwin J O Kompanje, Linda Lanyon, Steven Laureys, Fiona Lecky, Harvey Levin, Hester F Lingsma, Marc Maegele, Marek Majdan, Geoffrey Manley, Jill Marsteller, Luciana Mascia, Charles McFadyen, Stefania Mondello, Virginia Newcombe, Aarno Palotie, Paul M Parizel, Wilco Peul, James Piercy, Suzanne Polinder, Louis Puybasset, Todd E Rasmussen, Rolf Rossaint, Peter Smielewski, Jeannette Soderberg, Simon J Stanworth, Murray B Stein, Nicole von Steinbuchel, William Stewart, Ewout W Steyerberg, Nino Stocchetti, Anneliese Synnot, Braden Te Ao, Olli Tenovuo, Alice Theadom, Dick Tibboel, Walter Videtta, Kevin K W Wang, W Huw Williams, Kristine Yaffe for the InTBIR Participants and Investigators

01 Apr 2017
TL;DR: In this paper, the authors performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells, which led them to identify and validate six Dendritic cells (DCs) and four monocyte subtypes.
Abstract: INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.


Journal ArticleDOI
12 Oct 2017-Nature
TL;DR: It is demonstrated that the class 2 type VI RNA-guided RNA-targeting CRISPR–Cas effector Cas13a (previously known as C2c2) can be engineered for mammalian cell RNA knockdown and binding and is established as a flexible platform for studying RNA in mammalian cells and therapeutic development.
Abstract: RNA has important and diverse roles in biology, but molecular tools to manipulate and measure it are limited. For example, RNA interference can efficiently knockdown RNAs, but it is prone to off-target effects, and visualizing RNAs typically relies on the introduction of exogenous tags. Here we demonstrate that the class 2 type VI RNA-guided RNA-targeting CRISPR-Cas effector Cas13a (previously known as C2c2) can be engineered for mammalian cell RNA knockdown and binding. After initial screening of 15 orthologues, we identified Cas13a from Leptotrichia wadei (LwaCas13a) as the most effective in an interference assay in Escherichia coli. LwaCas13a can be heterologously expressed in mammalian and plant cells for targeted knockdown of either reporter or endogenous transcripts with comparable levels of knockdown as RNA interference and improved specificity. Catalytically inactive LwaCas13a maintains targeted RNA binding activity, which we leveraged for programmable tracking of transcripts in live cells. Our results establish CRISPR-Cas13a as a flexible platform for studying RNA in mammalian cells and therapeutic development.

Journal ArticleDOI
TL;DR: CERES, a computational method to estimate gene-dependency levels from CRISPR–Cas9 essentiality screens while accounting for the copy number–specific effect, is developed and found that CERES decreased false-positive results and estimated sgRNA activity for both this data set and previously published screens performed with different sg RNA libraries.
Abstract: The CRISPR-Cas9 system has revolutionized gene editing both at single genes and in multiplexed loss-of-function screens, thus enabling precise genome-scale identification of genes essential for proliferation and survival of cancer cells. However, previous studies have reported that a gene-independent antiproliferative effect of Cas9-mediated DNA cleavage confounds such measurement of genetic dependency, thereby leading to false-positive results in copy number-amplified regions. We developed CERES, a computational method to estimate gene-dependency levels from CRISPR-Cas9 essentiality screens while accounting for the copy number-specific effect. In our efforts to define a cancer dependency map, we performed genome-scale CRISPR-Cas9 essentiality screens across 342 cancer cell lines and applied CERES to this data set. We found that CERES decreased false-positive results and estimated sgRNA activity for both this data set and previously published screens performed with different sgRNA libraries. We further demonstrate the utility of this collection of screens, after CERES correction, for identifying cancer-type-specific vulnerabilities.

Journal ArticleDOI
TL;DR: It is demonstrated that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable.
Abstract: The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWASs, we used published summary statistics to calculate polygenic risk scores for eight well-studied phenotypes. We identify directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk are typically highest in the population from which summary statistics were derived. We demonstrate that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable. This work cautions that summarizing findings from large-scale GWASs may have limited portability to other populations using standard approaches and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.

Posted ContentDOI
14 Nov 2017-bioRxiv
TL;DR: A novel assembly-based approach to variant calling, the GATK HaplotypeCaller and Reference Confidence Model, that determines genotype likelihoods independently per-sample but performs joint calling across all samples within a project simultaneously, showing that the accuracy of indel variant calling is superior in comparison to other algorithms.
Abstract: Comprehensive disease gene discovery in both common and rare diseases will require the efficient and accurate detection of all classes of genetic variation across tens to hundreds of thousands of human samples. We describe here a novel assembly-based approach to variant calling, the GATK HaplotypeCaller (HC) and Reference Confidence Model (RCM), that determines genotype likelihoods independently per-sample but performs joint calling across all samples within a project simultaneously. We show by calling over 90,000 samples from the Exome Aggregation Consortium (ExAC) that, in contrast to other algorithms, the HC-RCM scales efficiently to very large sample sizes without loss in accuracy; and that the accuracy of indel variant calling is superior in comparison to other algorithms. More importantly, the HC-RCM produces a fully squared-off matrix of genotypes across all samples at every genomic position being investigated. The HC- RCM is a novel, scalable, assembly-based algorithm with abundant applications for population genetics and clinical studies.

Journal ArticleDOI
05 Jul 2017-Nature
TL;DR: Vulnerability to ferroptic cell death induced by inhibition of a lipid peroxidase pathway as a feature of therapy-resistant cancer cells across diverse mesenchymal cell-state contexts is identified.
Abstract: Cancer cells can assume different biological states, which can affect their resistance to therapies. A mesenchymal phenotype has been associated with drug resistance but the mechanism behind this state is not well understood. Stuart Schreiber and colleagues now show that tumour cells with a mesenchymal phenotype are selectively sensitive to inhibition of GPX4, an enzyme that alters lipid metabolism. GPX4 dissipates lipid peroxides and therefore prevents the iron-mediated reactions which induce ferroptotic cell death. These findings offer new perspectives on targeting cancers that have undergone a transition to a mesenchymal state to evade other therapeutic agents.

Journal ArticleDOI
TL;DR: Candida auris is an emerging healthcare-associated pathogen associated with high mortality, and WGS analysis suggests nearly simultaneous, and recent, independent emergence of different clonal populations on 3 continents.
Abstract: Background: Candida auris, a multidrug-resistant yeast that causes invasive infections, was first described in 2009 in Japan and has since been reported from several countries. Methods: To understand the global emergence and epidemiology of C. auris, we obtained isolates from 54 patients with C. auris infection from Pakistan, India, South Africa, and Venezuela during 2012-2015 and the type specimen from Japan. Patient information was available for 41 of the isolates. We conducted antifungal susceptibility testing and whole-genome sequencing (WGS). Results: Available clinical information revealed that 41% of patients had diabetes mellitus, 51% had undergone recent surgery, 73% had a central venous catheter, and 41% were receiving systemic antifungal therapy when C. auris was isolated. The median time from admission to infection was 19 days (interquartile range, 9-36 days), 61% of patients had bloodstream infection, and 59% died. Using stringent break points, 93% of isolates were resistant to fluconazole, 35% to amphotericin B, and 7% to echinocandins; 41% were resistant to 2 antifungal classes and 4% were resistant to 3 classes. WGS demonstrated that isolates were grouped into unique clades by geographic region. Clades were separated by thousands of single-nucleotide polymorphisms, but within each clade isolates were clonal. Different mutations in ERG11 were associated with azole resistance in each geographic clade. Conclusions: C. auris is an emerging healthcare-associated pathogen associated with high mortality. Treatment options are limited, due to antifungal resistance. WGS analysis suggests nearly simultaneous, and recent, independent emergence of different clonal populations on 3 continents. Risk factors and transmission mechanisms need to be elucidated to guide control measures.

Journal ArticleDOI
15 Sep 2017-Science
TL;DR: By studying colon cancer models, it is found that bacteria can metabolize the chemotherapeutic drug gemcitabine into its inactive form, 2′,2′-difluorodeoxyuridine, seen primarily in Gammaproteobacteria.
Abstract: Growing evidence suggests that microbes can influence the efficacy of cancer therapies. By studying colon cancer models, we found that bacteria can metabolize the chemotherapeutic drug gemcitabine (2',2'-difluorodeoxycytidine) into its inactive form, 2',2'-difluorodeoxyuridine. Metabolism was dependent on the expression of a long isoform of the bacterial enzyme cytidine deaminase (CDDL), seen primarily in Gammaproteobacteria. In a colon cancer mouse model, gemcitabine resistance was induced by intratumor Gammaproteobacteria, dependent on bacterial CDDL expression, and abrogated by cotreatment with the antibiotic ciprofloxacin. Gemcitabine is commonly used to treat pancreatic ductal adenocarcinoma (PDAC), and we hypothesized that intratumor bacteria might contribute to drug resistance of these tumors. Consistent with this possibility, we found that of the 113 human PDACs that were tested, 86 (76%) were positive for bacteria, mainly Gammaproteobacteria.

Journal ArticleDOI
24 Aug 2017-Nature
TL;DR: It is shown that selective CDK4/6 inhibitors not only induce tumour cell cycle arrest, but also promote anti-tumour immunity, providing a rationale for new combination regimens comprising CDK 4/6 inhibitor and immunotherapies as anti-cancer treatment.
Abstract: Cyclin-dependent kinases 4 and 6 (CDK4/6) are fundamental drivers of the cell cycle and are required for the initiation and progression of various malignancies. Pharmacological inhibitors of CDK4/6 have shown significant activity against several solid tumours. Their primary mechanism of action is thought to be the inhibition of phosphorylation of the retinoblastoma tumour suppressor, inducing G1 cell cycle arrest in tumour cells. Here we use mouse models of breast carcinoma and other solid tumours to show that selective CDK4/6 inhibitors not only induce tumour cell cycle arrest, but also promote anti-tumour immunity. We confirm this phenomenon through transcriptomic analysis of serial biopsies from a clinical trial of CDK4/6 inhibitor treatment for breast cancer. The enhanced anti-tumour immune response has two underpinnings. First, CDK4/6 inhibitors activate tumour cell expression of endogenous retroviral elements, thus increasing intracellular levels of double-stranded RNA. This in turn stimulates production of type III interferons and hence enhances tumour antigen presentation. Second, CDK4/6 inhibitors markedly suppress the proliferation of regulatory T cells. Mechanistically, the effects of CDK4/6 inhibitors both on tumour cells and on regulatory T cells are associated with reduced activity of the E2F target, DNA methyltransferase 1. Ultimately, these events promote cytotoxic T-cell-mediated clearance of tumour cells, which is further enhanced by the addition of immune checkpoint blockade. Our findings indicate that CDK4/6 inhibitors increase tumour immunogenicity and provide a rationale for new combination regimens comprising CDK4/6 inhibitors and immunotherapies as anti-cancer treatment.

Journal ArticleDOI
12 Jan 2017-Cell
TL;DR: Recent developments that extend the generality, DNA specificity, product selectivity, and fundamental capabilities of natural CRISPR systems are described.

Journal ArticleDOI
20 Sep 2017-Nature
TL;DR: A second wave of data from the National Institutes of Health Human Microbiome Project is introduced, comprising 1,631 new metagenomes (2,355 total) targeting diverse body sites with multiple time points in 265 individuals to provide new characterizations of microbiome personalization.
Abstract: The characterization of baseline microbial and functional diversity in the human microbiome has enabled studies of microbiome-related disease, diversity, biogeography, and molecular function. The National Institutes of Health Human Microbiome Project has provided one of the broadest such characterizations so far. Here we introduce a second wave of data from the study, comprising 1,631 new metagenomes (2,355 total) targeting diverse body sites with multiple time points in 265 individuals. We applied updated profiling and assembly methods to provide new characterizations of microbiome personalization. Strain identification revealed subspecies clades specific to body sites; it also quantified species with phylogenetic diversity under-represented in isolate genomes. Body-wide functional profiling classified pathways into universal, human-enriched, and body site-enriched subsets. Finally, temporal analysis decomposed microbial variation into rapidly variable, moderately variable, and stable subsets. This study furthers our knowledge of baseline human microbial diversity and enables an understanding of personalized microbiome function and dynamics.

Journal ArticleDOI
09 Nov 2017-Nature
TL;DR: It is demonstrated that a similar therapy-resistant cell state underlies the behaviour of persister cells derived from a wide range of cancers and drug treatments, and it is suggested that targeting of GPX4 may represent a therapeutic strategy to prevent acquired drug resistance.
Abstract: Acquired drug resistance prevents cancer therapies from achieving stable and complete responses. Emerging evidence implicates a key role for non-mutational drug resistance mechanisms underlying the survival of residual cancer 'persister' cells. The persister cell pool constitutes a reservoir from which drug-resistant tumours may emerge. Targeting persister cells therefore presents a therapeutic opportunity to impede tumour relapse. We previously found that cancer cells in a high mesenchymal therapy-resistant cell state are dependent on the lipid hydroperoxidase GPX4 for survival. Here we show that a similar therapy-resistant cell state underlies the behaviour of persister cells derived from a wide range of cancers and drug treatments. Consequently, we demonstrate that persister cells acquire a dependency on GPX4. Loss of GPX4 function results in selective persister cell ferroptotic death in vitro and prevents tumour relapse in mice. These findings suggest that targeting of GPX4 may represent a therapeutic strategy to prevent acquired drug resistance.

Journal ArticleDOI
15 Dec 2017-Science
TL;DR: Col colonization of human colorectal cancers with Fusobacterium and its associated microbiome—including Bacteroides, Selenomonas, and Prevotella species—is maintained in distal metastases, demonstrating microbiome stability between paired primary and metastatic tumors.
Abstract: Colorectal cancers comprise a complex mixture of malignant cells, nontransformed cells, and microorganisms. Fusobacterium nucleatum is among the most prevalent bacterial species in colorectal cancer tissues. Here we show that colonization of human colorectal cancers with Fusobacterium and its associated microbiome—including Bacteroides , Selenomonas , and Prevotella species—is maintained in distal metastases, demonstrating microbiome stability between paired primary and metastatic tumors. In situ hybridization analysis revealed that Fusobacterium is predominantly associated with cancer cells in the metastatic lesions. Mouse xenografts of human primary colorectal adenocarcinomas were found to retain viable Fusobacterium and its associated microbiome through successive passages. Treatment of mice bearing a colon cancer xenograft with the antibiotic metronidazole reduced Fusobacterium load, cancer cell proliferation, and overall tumor growth. These observations argue for further investigation of antimicrobial interventions as a potential treatment for patients with Fusobacterium -associated colorectal cancer.

Journal ArticleDOI
TL;DR: The proposed LD Hub database and accompanying web interface will ensure maximal uptake of the LD score regression methodology, provide a useful database for the public dissemination of GWAS results, and provide a method for easily screening hundreds of traits for overlapping genetic aetiologies.
Abstract: Motivation: LD score regression is a reliable and efficient method of using genome-wide association study (GWAS) summary-level results data to estimate the SNP heritability of complex traits and diseases, partition this heritability into functional categories, and estimate the genetic correlation between different phenotypes. Because the method relies on summary level results data, LD score regression is computationally tractable even for very large sample sizes. However, publicly available GWAS summary-level data are typically stored in different databases and have different formats, making it difficult to apply LD score regression to estimate genetic correlations across many different traits simultaneously. Results: In this manuscript, we describe LD Hub - a centralized database of summary-level GWAS results for 173 diseases/traits from different publicly available resources/consortia and a web interface that automates the LD score regression analysis pipeline. To demonstrate functionality and validate our software, we replicated previously reported LD score regression analyses of 49 traits/diseases using LD Hub; and estimated SNP heritability and the genetic correlation across the different phenotypes. We also present new results obtained by uploading a recent atopic dermatitis GWAS meta-analysis to examine the genetic correlation between the condition and other potentially related traits. In response to the growing availability of publicly accessible GWAS summary-level results data, our database and the accompanying web interface will ensure maximal uptake of the LD score regression methodology, provide a useful database for the public dissemination of GWAS results, and provide a method for easily screening hundreds of traits for overlapping genetic aetiologies

Journal ArticleDOI
TL;DR: chromVAR as mentioned in this paper is an R package for analyzing sparse chromatin-accessibility data by estimating gain or loss of accessibility within peaks sharing the same motif or annotation while controlling for technical biases.
Abstract: Single-cell ATAC-seq (scATAC) yields sparse data that make conventional analysis challenging. We developed chromVAR (http://www.github.com/GreenleafLab/chromVAR), an R package for analyzing sparse chromatin-accessibility data by estimating gain or loss of accessibility within peaks sharing the same motif or annotation while controlling for technical biases. chromVAR enables accurate clustering of scATAC-seq profiles and characterization of known and de novo sequence motifs associated with variation in chromatin accessibility.

Journal ArticleDOI
24 Feb 2017-Science
TL;DR: In vitro evolution experiments found that in all cases, tolerance preceded resistance, and a mathematical population-genetics model showed how tolerance boosts the chances for resistance mutations to spread in the population.
Abstract: Controlled experimental evolution during antibiotic treatment can help to explain the processes leading to antibiotic resistance in bacteria. Recently, intermittent antibiotic exposures have been shown to lead rapidly to the evolution of tolerance—that is, the ability to survive under treatment without developing resistance. However, whether tolerance delays or promotes the eventual emergence of resistance is unclear. Here we used in vitro evolution experiments to explore this question. We found that in all cases, tolerance preceded resistance. A mathematical population-genetics model showed how tolerance boosts the chances for resistance mutations to spread in the population. Thus, tolerance mutations pave the way for the rapid subsequent evolution of resistance. Preventing the evolution of tolerance may offer a new strategy for delaying the emergence of resistance.