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Recent technological advances have enabled massively parallel chromatin profiling with scATAC-seq (single-cell assay for transposase accessible chromatin by sequencing). Here we present ATAC with select antigen profiling by sequencing (ASAP-seq), a tool to simultaneously profile accessible chromatin and protein levels. Our approach pairs sparse scATAC-seq data with robust detection of hundreds of cell surface and intracellular protein markers and optional capture of mitochondrial DNA for clonal tracking, capturing three distinct modalities in single cells. ASAP-seq uses a bridging approach that repurposes antibody:oligonucleotide conjugates designed for existing technologies that pair protein measurements with single-cell RNA sequencing. Together with DOGMA-seq, an adaptation of CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) for measuring gene activity across the central dogma of gene regulation, we demonstrate the utility of systematic multi-omic profiling by revealing coordinated and distinct changes in chromatin, RNA and surface proteins during native hematopoietic differentiation and peripheral blood mononuclear cell stimulation and as a combinatorial decoder and reporter of multiplexed perturbations in primary T cells.

Characterizing the interactions that SARS-CoV-2 viral RNAs make with host cell proteins during infection can improve our understanding of viral RNA functions and the host innate immune response. Using RNA antisense purification and mass spectrometry, we identified up to 104 human proteins that directly and specifically bind to SARS-CoV-2 RNAs in infected human cells. We integrated the SARS-CoV-2 RNA interactome with changes in proteome abundance induced by viral infection and linked interactome proteins to cellular pathways relevant to SARS-CoV-2 infections. We demonstrated by genetic perturbation that cellular nucleic acid-binding protein (CNBP) and La-related protein 1 (LARP1), two of the most strongly enriched viral RNA binders, restrict SARS-CoV-2 replication in infected cells and provide a global map of their direct RNA contact sites. Pharmacological inhibition of three other RNA interactome members, PPIA, ATP1A1, and the ARP2/3 complex, reduced viral replication in two human cell lines. The identification of host dependency factors and defence strategies as presented in this work will improve the design of targeted therapeutics against SARS-CoV-2., Interactions between SARS-CoV-2 viral RNAs and host cell proteins during infection are evaluated to improve our understanding of viral RNA functions and the host innate immune response.

Many mitochondrial diseases are caused by mutations in mitochondrial DNA (mtDNA). Patients' cells contain a mixture of mutant and nonmutant mtDNA (a phenomenon called heteroplasmy). The proportion of mutant mtDNA varies across patients and among tissues within a patient. We simultaneously assayed single-cell heteroplasmy and cell state in thousands of blood cells obtained from three unrelated patients who had A3243G-associated mitochondrial encephalomyopathy, lactic acidosis, and strokelike episodes. We observed a broad range of heteroplasmy across all cell types but also found markedly reduced heteroplasmy in T cells, a finding consistent with purifying selection within this lineage. We observed this pattern in six additional patients who had heteroplasmic A3243G without strokelike episodes. (Funded by the Marriott Foundation and others.).

Existing adenine and cytosine base editors induce only a single type of modification, limiting the range of DNA alterations that can be created. Here we describe a CRISPR-Cas9-based synchronous programmable adenine and cytosine editor (SPACE) that can concurrently introduce A-to-G and C-to-T substitutions with minimal RNA off-target edits. SPACE expands the range of possible DNA sequence alterations, broadening the research applications of CRISPR base editors., Editorial summary Base editor that concurrently modifies both adenine and cytosine broadens the potential applications of base editing.

Genome-wide association studies have associated thousands of genetic variants with complex traits and diseases, but pinpointing the causal variant(s) among those in tight linkage disequilibrium with each associated variant remains a major challenge. Here, we use seven experimental assays to characterize all common variants at the multiple disease-associated TNFAIP3 locus in five disease-relevant immune cell lines, based on a set of features related to regulatory potential. Trait/disease-associated variants are enriched among SNPs prioritized based on either: (1) residing within CRISPRi-sensitive regulatory regions, or (2) localizing in a chromatin accessible region while displaying allele-specific reporter activity. Of the 15 trait/disease-associated haplotypes at TNFAIP3, 9 have at least one variant meeting one or both of these criteria, 5 of which are further supported by genetic fine-mapping. Our work provides a comprehensive strategy to characterize genetic variation at important disease-associated loci, and aids in the effort to identify trait causal genetic variants., While genome-wide association studies have yielded thousands of trait-associated loci, identifying causal variants remains challenging. Here, the authors perform seven genomics assays in various cell types to prioritize genetic variants in the TNFAIP3 locus, and report high-priority variants within disease-associated haplotypes.

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

Cytosine or adenine base editors (CBEs or ABEs) can introduce specific DNA C-to-T or A-to-G alterations1-4. However, we recently demonstrated that they can also induce transcriptome-wide guide-RNA-independent editing of RNA bases5, and created selective curbing of unwanted RNA editing (SECURE)-BE3 variants that have reduced unwanted RNA-editing activity5. Here we describe structure-guided engineering of SECURE-ABE variants with reduced off-target RNA-editing activity and comparable on-target DNA-editing activity that are also among the smallest Streptococcus pyogenes Cas9 base editors described to date. We also tested CBEs with cytidine deaminases other than APOBEC1 and found that the human APOBEC3A-based CBE induces substantial editing of RNA bases, whereas an enhanced APOBEC3A-based CBE6, human activation-induced cytidine deaminase-based CBE7, and the Petromyzon marinus cytidine deaminase-based CBE Target-AID4 induce less editing of RNA. Finally, we found that CBEs and ABEs that exhibit RNA off-target editing activity can also self-edit their own transcripts, thereby leading to heterogeneity in base-editor coding sequences.

Recent technical advancements have facilitated the mapping of epigenomes at single-cell resolution; however, the throughput and quality of these methods have limited their widespread adoption. Here we describe a high-quality (10(5) nuclear fragments per cell) droplet-microfluidics-based method for single-cell profiling of chromatin accessibility. We use this approach, named ‘droplet single-cell assay for transposase-accessible chromatin using sequencing’ (dscATAC-seq), to assay 46,653 cells for the unbiased discovery of cell types and regulatory elements in adult mouse brain. We further increase the throughput of this platform by combining it with combinatorial indexing (dsciATAC-seq), enabling single-cell studies at a massive scale. We demonstrate the utility of this approach by measuring chromatin accessibility across 136,463 resting and stimulated human bone marrow-derived cells to reveal changes in the cis- and trans-regulatory landscape across cell types and under stimulatory conditions at single-cell resolution. Altogether, we describe a total of 510,123 single-cell profiles, demonstrating the scalability and flexibility of this droplet-based platform.

Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data. We have tested STREAM on several synthetic and real datasets generated with different single-cell technologies. We further demonstrate its utility for understanding myoblast differentiation and disentangling known heterogeneity in hematopoiesis for different organisms. STREAM is an open-source software package., The increasing accessibility of single cell omics technologies beyond transcriptomics demands parallel advances in analysis. Here, the authors introduce STREAM, a pipeline for reconstruction and visualization of differentiation trajectories from both single-cell RNA-seq and ATAC-seq data.

Perturbations to mammalian switch/sucrose non-fermentable (mSWI/SNF) chromatin remodeling complexes have been widely implicated as driving events in cancer1. One such perturbation is the dual loss of the SMARCA4 and SMARCA2 ATPase subunits in small cell carcinoma of the ovary, hypercalcemic type (SCCOHT)2-5, SMARCA4-deficient thoracic sarcomas6 and dedifferentiated endometrial carcinomas7. However, the consequences of dual ATPase subunit loss on mSWI/SNF complex subunit composition, chromatin targeting, DNA accessibility and gene expression remain unknown. Here we identify an ATPase module of subunits that is required for functional specification of the Brahma-related gene-associated factor (BAF) and polybromo-associated BAF (PBAF) mSWI/SNF family subcomplexes. Using SMARCA4/2 ATPase mutant variants, we define the catalytic activity-dependent and catalytic activity-independent contributions of the ATPase module to the targeting of BAF and PBAF complexes on chromatin genome-wide. Finally, by linking distinct mSWI/SNF complex target sites to tumor-suppressive gene expression programs, we clarify the transcriptional consequences of SMARCA4/2 dual loss in SCCOHT.

Widespread linkage disequilibrium and incomplete annotation of cell-to-cell state variation represent substantial challenges to elucidating mechanisms of trait-associated genetic variation. Here we perform genetic fine-mapping for blood cell traits in the UK Biobank to identify putative causal variants. These variants are enriched in genes encoding proteins in trait-relevant biological pathways and in accessible chromatin of hematopoietic progenitors. For regulatory variants, we explore patterns of developmental enhancer activity, predict molecular mechanisms, and identify likely target genes. In several instances, we localize multiple independent variants to the same regulatory element or gene. We further observe that variants with pleiotropic effects preferentially act in common progenitor populations to direct the production of distinct lineages. Finally, we leverage fine-mapped variants in conjunction with continuous epigenomic annotations to identify trait-cell type enrichments within closely related populations and in single cells. Our study provides a comprehensive framework for single-variant and single-cell analyses of genetic associations.

Sickle cell disease (SCD) is the most common monogenic disorder in the world. Notably, there is extensive clinical heterogeneity in SCD that cannot be fully accounted for by known factors, and in particular, the extent to which the phenotypic diversity of SCD can be explained by genetic variation has not been reliably quantified. Here, in a family-based cohort of 449 patients with SCD and 755 relatives, we first show that 5 known modifiers affect 11 adverse outcomes in SCD to varying degrees. We then utilize a restricted maximum likelihood procedure to estimate the heritability of 20 hematologic traits, including fetal hemoglobin (HbF) and white blood cell count (WBC), in the clinically relevant context of inheritance from healthy carriers to SCD patients. We report novel estimations of heritability for HbF at 31.6% (±5.4%) and WBC at 41.2% (±6.8%) in our cohort. Finally, we demonstrate shared genetic bases between HbF, WBC, and other hematologic traits, but surprisingly little overlap between HbF and WBC themselves. In total, our analyses show that HbF and WBC have significant heritable components among individuals with SCD and their relatives, demonstrating the value of using family-based studies to better understand modifiers of SCD.

Sarcoidosis is a systemic inflammatory disease characterized by infiltration of immune cells into granulomas. Previous gene expression studies using heterogeneous cell mixtures lack insight into cell-type-specific immune dysregulation. We performed the first single-cell RNA-sequencing study of sarcoidosis in peripheral immune cells in 48 patients and controls. Following unbiased clustering, differentially expressed genes were identified for 18 cell types and bioinformatically assessed for function and pathway enrichment. Our results reveal persistent activation of circulating classical monocytes with subsequent upregulation of trafficking molecules. Specifically, classical monocytes upregulated distinct markers of activation including adhesion molecules, pattern recognition receptors, and chemokine receptors, as well as enrichment of immunoregulatory pathways HMGB1, mTOR, and ephrin receptor signaling. Predictive modeling implicated TGFβ and mTOR signaling as drivers of persistent monocyte activation. Additionally, sarcoidosis T cell subsets displayed patterns of dysregulation. CD4 naïve T cells were enriched for markers of apoptosis and Th17/Treg differentiation, while effector T cells showed enrichment of anergy-related pathways. Differentially expressed genes in regulatory T cells suggested dysfunctional p53, cell death, and TNFR2 signaling. Using more sensitive technology and more precise units of measure, we identify cell-type specific, novel inflammatory and regulatory pathways. Based on our findings, we suggest a novel model involving four convergent arms of dysregulation: persistent hyperactivation of innate and adaptive immunity via classical monocytes and CD4 naïve T cells, regulatory T cell dysfunction, and effector T cell anergy. We further our understanding of the immunopathology of sarcoidosis and point to novel therapeutic targets.

© 2020 Elsevier Inc. Cell differentiation and function are regulated across multiple layers of gene regulation, including modulation of gene expression by changes in chromatin accessibility. However, differentiation is an asynchronous process precluding a temporal understanding of regulatory events leading to cell fate commitment. Here we developed simultaneous high-throughput ATAC and RNA expression with sequencing (SHARE-seq), a highly scalable approach for measurement of chromatin accessibility and gene expression in the same single cell, applicable to different tissues. Using 34,774 joint profiles from mouse skin, we develop a computational strategy to identify cis-regulatory interactions and define domains of regulatory chromatin (DORCs) that significantly overlap with super-enhancers. During lineage commitment, chromatin accessibility at DORCs precedes gene expression, suggesting that changes in chromatin accessibility may prime cells for lineage commitment. We computationally infer chromatin potential as a quantitative measure of chromatin lineage-priming and use it to predict cell fate outcomes. SHARE-seq is an extensible platform to study regulatory circuitry across diverse cells in tissues.

The transcription factor Foxp3 plays crucial roles for Treg cell development and function. Conserved non-coding sequences (CNSs) at the Foxp3 locus control Foxp3 transcription, but how they developmentally contribute to Treg cell lineage specification remains obscure. Here, we show that among Foxp3 CNSs, the promoter-upstream CNS0 and the intergenic CNS3, which bind distinct transcription factors, were activated at early stages of thymocyte differentiation prior to Foxp3 promoter activation, with sequential genomic looping bridging these regions and the promoter. While deletion of either CNS0 or CNS3 partially compromised thymic Treg cell generation, deletion of both completely abrogated the generation and impaired the stability of Foxp3 expression in residual Treg cells. As a result, CNS0 and CNS3 double-deleted mice succumbed to lethal systemic autoimmunity and inflammation. Thus, hierarchical and coordinated activation of Foxp3 CNS0 and CNS3 initiates and stabilizes Foxp3 gene expression, thereby crucially controlling Treg cell development, maintenance, and consequently immunological self-tolerance.

SUMMARYMost loci identified by GWAS have been found in populations of European ancestry (EA). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EA individuals, we identified 5,552 trait-variant associations at P−9, including 71 novel loci not found in EA populations. We also identified novel ancestry-specific variants not found in EA, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional, and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EA-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations, and compared genetic architecture and the impact of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

Regulatory networks that maintain functional, differentiated cell states are often dysregulated in tumor development. Here, we use single-cell epigenomics to profile chromatin state transitions in a mouse model of lung adenocarcinoma (LUAD). We identify an epigenomic continuum representing loss of cellular identity and progression toward a metastatic state. We define co-accessible regulatory programs and infer key activating and repressive chromatin regulators of these cell states. Among these co-accessibility programs, we identify a pre-metastatic transition, characterized by activation of RUNX transcription factors, which mediates extracellular matrix remodeling to promote metastasis and is predictive of survival across human LUAD patients. Together, these results demonstrate the power of single-cell epigenomics to identify regulatory programs to uncover mechanisms and key biomarkers of tumor progression.

Summary Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation., Graphical Abstract, Highlights • Largest genome-wide association study of blood cell traits to date • Empiric assessments of omnigenic and infinitesimal models of polygenic variation • Functional insights into how genetic variants impact human hematopoiesis • Assessment of the effect of polygenic trait scores upon blood diseases, Analysis of blood cell traits in the UK Biobank and other cohorts illuminates the full genetic architecture of hematopoietic phenotypes, with evidence supporting the omnigenic model for complex traits and linking polygenic burden with monogenic blood diseases.

Mammalian SWI/SNF chromatin remodelling complexes exist in three distinct, final-form assemblies: canonical BAF (cBAF), PBAF and a newly characterized non-canonical complex (ncBAF). However, their complex-specific targeting on chromatin, functions and roles in disease remain largely undefined. Here, we comprehensively mapped complex assemblies on chromatin and found that ncBAF complexes uniquely localize to CTCF sites and promoters. We identified ncBAF subunits as synthetic lethal targets specific to synovial sarcoma and malignant rhabdoid tumours, which both exhibit cBAF complex (SMARCB1 subunit) perturbation. Chemical and biological depletion of the ncBAF subunit, BRD9, rapidly attenuates synovial sarcoma and malignant rhabdoid tumour cell proliferation. Importantly, in cBAF-perturbed cancers, ncBAF complexes maintain gene expression at retained CTCF-promoter sites and function in a manner distinct from fusion oncoprotein-bound complexes. Together, these findings unmask the unique targeting and functional roles of ncBAF complexes and present new cancer-specific therapeutic targets.

Summary Gain-of-function Notch mutations are recurrent in mature small B cell lymphomas such as mantle cell lymphoma (MCL) and chronic lymphocytic leukemia (CLL), but the Notch target genes that contribute to B cell oncogenesis are largely unknown. We performed integrative analysis of Notch-regulated transcripts, genomic binding of Notch transcription complexes, and genome conformation data to identify direct Notch target genes in MCL cell lines. This B cell Notch regulome is largely controlled through Notch-bound distal enhancers and includes genes involved in B cell receptor and cytokine signaling and the oncogene MYC , which sustains proliferation of Notch-dependent MCL cell lines via a Notch-regulated lineage-restricted enhancer complex. Expression of direct Notch target genes is associated with Notch activity in an MCL xenograft model and in CLL lymph node biopsies. Our findings provide key insights into the role of Notch in MCL and other B cell malignancies and have important implications for therapeutic targeting of Notch-dependent oncogenic pathways.

Sarcoidosis is a complex disease of unknown etiology characterized by the presence of granulomatous inflammation. Though various immune system pathways have been implicated in disease, the relationship between the genetic determinants of sarcoidosis and other inflammatory disorders has not been characterized. Herein, we examined the degree of genetic pleiotropy common to sarcoidosis and other inflammatory disorders to identify shared pathways and disease systems pertinent to sarcoidosis onset. To achieve this, we quantify the association of common variant polygenic risk scores from nine complex inflammatory disorders with sarcoidosis risk. Enrichment analyses of genes implicated in pleiotropic associations were further used to elucidate candidate pathways. In European-Americans, we identify significant pleiotropy between risk of sarcoidosis and risk of asthma (R2=2.03%; P=8.89 × 10−9), celiac disease (R2=2.03%; P=8.21 × 10−9), primary biliary cirrhosis (R2=2.43%; P=2.01 × 10−10) and rheumatoid arthritis (R2=4.32%; P=2.50 × 10−17). These associations validate in African Americans only after accounting for the proportion of genome-wide European ancestry, where we demonstrate similar effects of polygenic risk for African-Americans with the highest levels of European ancestry. Variants and genes implicated in European-American pleiotropic associations were enriched for pathways involving interleukin-12, interleukin-27 and cell adhesion molecules, corroborating the hypothesized immunopathogenesis of disease.

The work by Tang et al. provides a comprehensive, single-cell, transcriptomic analysis of kidney and blood cells from the adult zebrafish, identifying novel cell types, including two classes of NK immune cells, classically defined and erythroid-primed hematopoietic stem and progenitor cells, mucin-secreting kidney cells, and kidney stem/progenitor cells., Recent advances in single-cell, transcriptomic profiling have provided unprecedented access to investigate cell heterogeneity during tissue and organ development. In this study, we used massively parallel, single-cell RNA sequencing to define cell heterogeneity within the zebrafish kidney marrow, constructing a comprehensive molecular atlas of definitive hematopoiesis and functionally distinct renal cells found in adult zebrafish. Because our method analyzed blood and kidney cells in an unbiased manner, our approach was useful in characterizing immune-cell deficiencies within DNA–protein kinase catalytic subunit (prkdc), interleukin-2 receptor γ a (il2rga), and double-homozygous–mutant fish, identifying blood cell losses in T, B, and natural killer cells within specific genetic mutants. Our analysis also uncovered novel cell types, including two classes of natural killer immune cells, classically defined and erythroid-primed hematopoietic stem and progenitor cells, mucin-secreting kidney cells, and kidney stem/progenitor cells. In total, our work provides the first, comprehensive, single-cell, transcriptomic analysis of kidney and marrow cells in the adult zebrafish.

Two studies reveal a role for the transcriptional regulator BATF3 as a T cell–intrinsic factor mediating effective memory responses. This finding opens future avenues of investigation and opportunities to enhance cellular immunotherapy.

Our ability to track cellular dynamics in humans over time in vivo has been limited. Here, we demonstrate how somatic mutations in mitochondrial DNA (mtDNA) can be used to longitudinally track the dynamic output of hematopoietic stem and progenitor cells in humans. Over the course of 3 years of blood sampling in a single individual, our analyses reveal somatic mtDNA sequence variation and evolution reminiscent of models of hematopoiesis established by genetic labeling approaches. Furthermore, we observe fluctuations in mutation heteroplasmy, coinciding with specific clinical events, such as infections, and further identify lineage-specific somatic mtDNA mutations in longitudinally sampled circulating blood cell subsets in individuals with leukemia. Collectively, these observations indicate the significant potential of using tracking of somatic mtDNA sequence variation as a broadly applicable approach to systematically assess hematopoietic clonal dynamics in human health and disease.

A widespread assumption for single-cell analyses specifies that one cell’s nucleic acids are predominantly captured by one oligonucleotide barcode. Here, we show that ~13–21% of cell barcodes from the 10x Chromium scATAC-seq assay may have been derived from a droplet with more than one oligonucleotide sequence, which we call “barcode multiplets”. We demonstrate that barcode multiplets can be derived from at least two different sources. First, we confirm that approximately 4% of droplets from the 10x platform may contain multiple beads. Additionally, we find that approximately 5% of beads may contain detectable levels of multiple oligonucleotide barcodes. We show that this artifact can confound single-cell analyses, including the interpretation of clonal diversity and proliferation of intra-tumor lymphocytes. Overall, our work provides a conceptual and computational framework to identify and assess the impacts of barcode multiplets in single-cell data., It is assumed that single-cell analyses capture one barcode per cell. Here, the authors show that up to 21% of cell barcodes on the 10X Chromium scATAC-seq assay may be derived from barcode multiplets.

Myeloproliferative neoplasms (MPNs) are blood cancers characterized by excessive production of mature myeloid cells that result from the acquisition of somatic driver mutations in hematopoietic stem cells (HSCs)1. While substantial progress has been made to define the causal somatic mutation profile for MPNs2, epidemiologic studies indicate a significant heritable component for the disease that is among the highest known for all cancers3. However, only a limited set of genetic risk loci have been identified, and the underlying biological mechanisms leading to MPN acquisition remain unexplained. Here, to define the inherited risk profile, we conducted the largest genome-wide association study of MPNs to date (978,913 individuals with 3,224 cases) and identified 14 genome-wide significant loci, as well as a polygenic signature that increases the odds for disease acquisition by nearly 3-fold between the top and median deciles. Interestingly, we find a shared genetic architecture between MPN risk and several hematopoietic traits spanning distinct lineages, as well as an association between increased MPN risk and longer leukocyte telomere length, collectively implicating HSC function and self-renewal. Strikingly, we find a significant enrichment for risk variants mapping to accessible chromatin in HSCs compared with other hematopoietic populations. Finally, gene mapping identifies modulators of HSC biology and targeted variant-to-function analyses suggest likely roles for CHEK2 and GFI1B in altering HSC function to confer disease risk. Overall, we demonstrate the power of human genetic studies to illuminate a previously unappreciated mechanism for MPN risk through modulation of HSC function.

Myeloproliferative neoplasms (MPNs) are blood cancers that are characterized by the excessive production of mature myeloid cells and arise from the acquisition of somatic driver mutations in haematopoietic stem cells (HSCs). Epidemiological studies indicate a substantial heritable component of MPNs that is among the highest known for cancers1. However, only a limited number of genetic risk loci have been identified, and the underlying biological mechanisms that lead to the acquisition of MPNs remain unclear. Here, by conducting a large-scale genome-wide association study (3,797 cases and 1,152,977 controls), we identify 17 MPN risk loci (P

Background Recent innovations in single-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands of individual cells. scATAC-seq data analysis presents unique methodological challenges. scATAC-seq experiments sample DNA, which, due to low copy numbers (diploid in humans), lead to inherent data sparsity (1–10% of peaks detected per cell) compared to transcriptomic (scRNA-seq) data (10–45% of expressed genes detected per cell). Such challenges in data generation emphasize the need for informative features to assess cell heterogeneity at the chromatin level. Results We present a benchmarking framework that is applied to 10 computational methods for scATAC-seq on 13 synthetic and real datasets from different assays, profiling cell types from diverse tissues and organisms. Methods for processing and featurizing scATAC-seq data were compared by their ability to discriminate cell types when combined with common unsupervised clustering approaches. We rank evaluated methods and discuss computational challenges associated with scATAC-seq analysis including inherently sparse data, determination of features, peak calling, the effects of sequencing coverage and noise, and clustering performance. Running times and memory requirements are also discussed. Conclusions This reference summary of scATAC-seq methods offers recommendations for best practices with consideration for both the non-expert user and the methods developer. Despite variation across methods and datasets, SnapATAC, Cusanovich2018, and cisTopic outperform other methods in separating cell populations of different coverages and noise levels in both synthetic and real datasets. Notably, SnapATAC is the only method able to analyze a large dataset (> 80,000 cells).

Studies of allelic variation underlying genetic blood disorders have provided important insights into human hematopoiesis. Most often, the identified pathogenic mutations result in loss-of-function or missense changes. However, assessing the pathogenicity of noncoding variants can be challenging. Here, we characterize two unrelated patients with a distinct presentation of dyserythropoietic anemia and other impairments in hematopoiesis associated with an intronic mutation in GATA1 that is 24 nucleotides upstream of the canonical splice acceptor site. Functional studies demonstrate that this single-nucleotide alteration leads to reduced canonical splicing and increased use of an alternative splice acceptor site that causes a partial intron retention event. The resultant altered GATA1 contains a five–amino acid insertion at the C-terminus of the C-terminal zinc finger and has no observable activity. Collectively, our results demonstrate how altered splicing of GATA1, which reduces levels of the normal form of this master transcription factor, can result in distinct changes in human hematopoiesis.

CRISPR-guided DNA base editors enable the efficient installation of targeted single-nucleotide changes. Cytosine or adenine base editors (CBEs or ABEs), which are fusions of cytidine or adenosine deaminases to CRISPR-Cas nickases, can efficiently induce DNA C-to-T or A-to-G alterations in DNA, respectively1-4. We recently demonstrated that both the widely used CBE BE3 (harboring a rat APOBEC1 cytidine deaminase) and the optimized ABEmax editor can induce tens of thousands of guide RNA-independent, transcriptome-wide RNA base edits in human cells with high efficiencies5. In addition, we showed the feasibility of creating SElective Curbing of Unwanted RNA Editing (SECURE)-BE3 variants that exhibit substantially reduced unwanted RNA editing activities while retaining robust and more precise on-target DNA editing5. Here we describe structure-guided engineering of SECURE-ABE variants that not only possess reduced off-target RNA editing with comparable on-target DNA activities but are also the smallest Streptococcus pyogenes Cas9 (SpCas9) base editors described to date. In addition, we tested CBEs composed of cytidine deaminases other than APOBEC1 and found that human APOBEC3A (hA3A) cytidine deaminase CBE induces substantial transcriptome-wide RNA base edits with high efficiencies. By contrast, a previously described “enhanced” A3A (eA3A) cytidine deaminase CBE or a human activation-induced cytidine deaminase (hAID) CBE induce substantially reduced or near background levels of RNA edits. In sum, our work describes broadly useful SECURE-ABE and -CBE base editors and reinforces the importance of minimizing RNA editing activities of DNA base editors for research and therapeutic applications.

While recent technical advancements have facilitated the mapping of epigenomes at single-cell resolution, the throughput and quality of these methods have limited the widespread adoption of these technologies. Here, we describe a droplet microfluidics platform for single-cell assay for transposase accessible chromatin (scATAC-seq) for high-throughput single-cell profiling of chromatin accessibility. We use this approach for the unbiased discovery of cell types and regulatory elements within the mouse brain. Further, we extend the throughput of this approach by pairing combinatorial indexing with droplet microfluidics, enabling single-cell studies at a massive scale. With this approach, we measure chromatin accessibility across resting and stimulated human bone marrow derived cells to reveal changes in the cis- and trans- regulatory landscape across cell types and upon stimulation conditions at single-cell resolution. Altogether, we describe a total of 502,207 single-cell profiles, demonstrating the scalability and flexibility of this droplet-based platform.

Lineage tracing provides key insights into the fate of individual cells in complex organisms. Although effective genetic labeling approaches are available in model systems, in humans, most approaches require detection of nuclear somatic mutations, which have high error rates, limited scale, and do not capture cell state information. Here, we show that somatic mutations in mtDNA can be tracked by single-cell RNA or assay for transposase accessible chromatin (ATAC) sequencing. We leverage somatic mtDNA mutations as natural genetic barcodes and demonstrate their utility as highly accurate clonal markers to infer cellular relationships. We track native human cells both in vitro and in vivo and relate clonal dynamics to gene expression and chromatin accessibility. Our approach should allow clonal tracking at a 1,000-fold greater scale than with nuclear genome sequencing, with simultaneous information on cell state, opening the way to chart cellular dynamics in human health and disease. Using single-cell sequencing technologies, somatic mutations in mtDNA can be used as natural genetic barcodes to study cellular states and clonal dynamics., National Institutes of Health (U.S.) (Grant R33 CA202820)

Enhancer elements in the human genome control how genes are expressed in specific cell types and harbor thousands of genetic variants that influence risk for common diseases1-4. Yet, we still do not know how enhancers regulate specific genes, and we lack general rules to predict enhancer-gene connections across cell types5,6. We developed an experimental approach, CRISPRi-FlowFISH, to perturb enhancers in the genome, and we applied it to test >3,500 potential enhancer-gene connections for 30 genes. We found that a simple activity-by-contact model substantially outperformed previous methods at predicting the complex connections in our CRISPR dataset. This activity-by-contact model allows us to construct genome-wide maps of enhancer-gene connections in a given cell type, on the basis of chromatin state measurements. Together, CRISPRi-FlowFISH and the activity-by-contact model provide a systematic approach to map and predict which enhancers regulate which genes, and will help to interpret the functions of the thousands of disease risk variants in the noncoding genome.

Recent technological developments have enabled the characterization of the epigenetic landscape of single cells across a range of tissues in normal and diseased states and under various biological and chemical perturbations. While analysis of these profiles resembles methods from single-cell transcriptomic studies, unique challenges are associated with bioinformatics processing of single-cell epigenetic data, including a much larger (10-1,000×) feature set and significantly greater sparsity, requiring customized solutions. Here, we discuss the essentials of the computational methodology required for analyzing common single-cell epigenomic measurements for DNA methylation using bisulfite sequencing and open chromatin using ATAC-Seq.

The core cohesin subunit STAG2 is recurrently mutated in Ewing sarcoma but its biological role is less clear. Herein, we demonstrate that cohesin complexes containing STAG2 occupy enhancer and polycomb repressive complex (PRC2) marked regulatory regions. Genetic suppression of STAG2 leads to a compensatory increase in cohesin-STAG1 complexes, but not in enhancer rich regions, and results in reprogramming of cis-chromatin interactions. Strikingly, in STAG2 knockout cells, the oncogenic genetic program driven by the fusion transcription factor EWS/FLI1 was highly perturbed, in part due to altered enhancer-promoter contacts. Moreover, loss of STAG2 also disrupted PRC2-mediated regulation of gene expression. Combined, these transcriptional changes converged to modulate EWS/FLI1, migratory and neurodevelopmental programs. Finally, consistent with clinical observations, functional studies revealed that loss of STAG2 enhances the metastatic potential of Ewing sarcoma xenografts. Our findings demonstrate that STAG2 mutations can alter chromatin architecture and transcriptional programs to promote an aggressive cancer phenotype.

Widespread changes to DNA methylation and chromatin are well documented in cancer, but the fate of higher-order chromosomal structure remains obscure. Here we integrated topological maps for colon tumors and normal colons with epigenetic, transcriptional, and imaging data to characterize alterations to chromatin loops, topologically associated domains, and large-scale compartments. We found that spatial partitioning of the open and closed genome compartments is profoundly compromised in tumors. This reorganization is accompanied by compartment-specific hypomethylation and chromatin changes. Additionally, we identify a compartment at the interface between the canonical A and B compartments that is reorganized in tumors. Remarkably, similar shifts were evident in non-malignant cells that have accumulated excess divisions. Our analyses suggest that these topological changes repress stemness and invasion programs while inducing anti-tumor immunity genes and may therefore restrain malignant progression. Our findings call into question the conventional view that tumor-associated epigenomic alterations are primarily oncogenic.

Genome-wide association studies (GWAS) have identified thousands of variants associated with human diseases and traits. However, the majority of GWAS-implicated variants are in non-coding regions of the genome and require in depth follow-up to identify target genes and decipher biological mechanisms. Here, rather than focusing on causal variants, we have undertaken a pooled loss-of-function screen in primary hematopoietic cells to interrogate 389 candidate genes contained in 75 loci associated with red blood cell traits. Using this approach, we identify 77 genes at 38 GWAS loci, with most loci harboring 1–2 candidate genes. Importantly, the hit set was strongly enriched for genes validated through orthogonal genetic approaches. Genes identified by this approach are enriched in specific and relevant biological pathways, allowing regulators of human erythropoiesis and modifiers of blood diseases to be defined. More generally, this functional screen provides a paradigm for gene-centric follow up of GWAS for a variety of human diseases and traits.

CRISPR-Cas base-editor technology enables targeted nucleotide alterations, and is being increasingly used for research and potential therapeutic applications1,2. The most widely used cytosine base editors (CBEs) induce deamination of DNA cytosines using the rat APOBEC1 enzyme, which is targeted by a linked Cas protein-guide RNA complex3,4. Previous studies of the specificity of CBEs have identified off-target DNA edits in mammalian cells5,6. Here we show that a CBE with rat APOBEC1 can cause extensive transcriptome-wide deamination of RNA cytosines in human cells, inducing tens of thousands of C-to-U edits with frequencies ranging from 0.07% to 100% in 38-58% of expressed genes. CBE-induced RNA edits occur in both protein-coding and non-protein-coding sequences and generate missense, nonsense, splice site, and 5' and 3' untranslated region mutations. We engineered two CBE variants bearing mutations in rat APOBEC1 that substantially decreased the number of RNA edits (by more than 390-fold and more than 3,800-fold) in human cells. These variants also showed more precise on-target DNA editing than the wild-type CBE and, for most guide RNAs tested, no substantial reduction in editing efficiency. Finally, we show that an adenine base editor7 can also induce transcriptome-wide RNA edits. These results have implications for the use of base editors in both research and clinical settings, illustrate the feasibility of engineering improved variants with reduced RNA editing activities, and suggest the need to more fully define and characterize the RNA off-target effects of deaminase enzymes in base editor platforms.

Summary A complete chart of cis-regulatory elements and their dynamic activity is necessary to understand the transcriptional basis of differentiation and function of an organ system. We generated matched epigenome and transcriptome measurements in 86 primary cell types that span the mouse immune system and its differentiation cascades. This breadth of data enable variance components analysis that suggests that genes fall into two distinct classes, controlled by either enhancer- or promoter-driven logic, and multiple regression that connects genes to the enhancers that regulate them. Relating transcription factor (TF) expression to the genome-wide accessibility of their binding motifs classifies them as predominantly openers or closers of local chromatin accessibility, pinpointing specific cis-regulatory elements where binding of given TFs is likely functionally relevant, validated by chromatin immunoprecipitation sequencing (ChIP-seq). Overall, this cis-regulatory atlas provides a trove of information on transcriptional regulation through immune differentiation and a foundational scaffold to define key regulatory events throughout the immunological genome.

Schaefer et al. recently advanced the provocative conclusion that CRISPR-Cas9 nuclease can induce off-target alterations at genomic loci that do not resemble the intended on-target site. Using high-coverage whole genome sequencing (WGS), these authors reported finding SNPs and indels in two CRISPR-Cas9-treated mice that were not present in a single untreated control mouse. On the basis of this association, Schaefer et al. concluded that these sequence variants were caused by CRISPR-Cas9. This new proposed CRISPR-Cas9 off-target activity runs contrary to previously published work and, if the authors are correct, could have profound implications for research and therapeutic applications. Here we demonstrate that the simplest interpretation of Schaefer et al.9s data is that the two CRISPR-Cas9-treated mice are actually more closely related genetically to each other than to the control mouse. This strongly suggests that the so-called “unexpected mutations” simply represent SNPs and indels shared in common by these mice prior to nuclease treatment. In addition, given the genomic and sequence distribution profiles of these variants, we show that it is challenging to explain how CRISPR-Cas9 might be expected to induce such changes. Finally, we argue that the lack of appropriate controls in Schaefer et al.9s experimental design precludes assignment of causality to CRISPR-Cas9. Given these substantial issues, we urge Schaefer et al. to revise or re-state the original conclusions of their published work so as to avoid leaving misleading and unsupported statements to persist in the literature.

Mumbach et al. recently described HiChIP, a novel protein-mediated chromatin conformation assay that lowers cellular input requirements while simultaneously increasing the yield of informative reads compared to previous methods. To facilitate the dissemination and adoption of this assay, we introduce hichipper (http://aryeelab.org/hichipper), an open-source HiChIP data preprocessing tool, with features that include bias-corrected peak calling, library quality control, DNA loop calling, and output of processed data for downstream analysis and visualization.

Incomplete annotation of cell-to-cell state variance and widespread linkage disequilibrium in the human genome represent significant challenges to elucidating mechanisms of trait-associated genetic variation. Here, using data from the UK Biobank, we perform genetic fine-mapping for 16 blood cell traits to quantify posterior probabilities of association while allowing for multiple independent signals per region. We observe an enrichment of fine-mapped variants in accessible chromatin of lineage-committed hematopoietic progenitor cells. Further, we develop a novel analytic framework that identifies “core gene” cell type enrichments and show that this approach uniquely resolves relevant cell types within closely related populations. Applying our approach to single cell chromatin accessibility data, we discover significant heterogeneity within classically defined multipotential progenitor populations. Finally, using several lines of empirical evidence, we identify relevant cell types, predict target genes, and propose putative causal mechanisms for fine-mapped variants. In total, our study provides an analytic framework for single-variant and single-cell analyses to elucidate putative causal variants and cell types from GWAS and high-resolution epigenomic assays.

To the editor: In a recent issue of Blood , O’Brien et al[1][1] describe the development of an ex vivo model of Diamond-Blackfan anemia (DBA) using cultured peripheral blood CD34+ progenitor cells obtained from DBA patients. Although many useful models of DBA exist (including animal models,[2][2

Human hematopoiesis involves cellular differentiation of multipotent cells into progressively more lineage-restricted states. While the chromatin accessibility landscape of this process has been explored in defined populations, single-cell regulatory variation has been hidden by ensemble averaging. We collected single-cell chromatin accessibility profiles across 10 populations of immunophenotypically defined human hematopoietic cell types and constructed a chromatin accessibility landscape of human hematopoiesis to characterize differentiation trajectories. We find variation consistent with lineage bias toward different developmental branches in multipotent cell types. We observe heterogeneity within common myeloid progenitors (CMPs) and granulocyte-macrophage progenitors (GMPs) and develop a strategy to partition GMPs along their differentiation trajectory. Furthermore, we integrated single-cell RNA sequencing (scRNA-seq) data to associate transcription factors to chromatin accessibility changes and regulatory elements to target genes through correlations of expression and regulatory element accessibility. Overall, this work provides a framework for integrative exploration of complex regulatory dynamics in a primary human tissue at single-cell resolution.

Schaefer et al. recently advanced the provocative conclusion that CRISPR-Cas9 nuclease can induce off-target alterations at genomic loci that do not resemble the intended on-target site.1 Using high-coverage whole genome sequencing (WGS), these authors reported finding SNPs and indels in two CRISPR-Cas9-treated mice that were not present in a single untreated control mouse. On the basis of this association, Schaefer et al. concluded that these sequence variants were caused by CRISPR-Cas9. This new proposed CRISPR-Cas9 off-target activity runs contrary to previously published work2–8 and, if the authors are correct, could have profound implications for research and therapeutic applications. Here, we demonstrate that the simplest interpretation of Schaefer et al.’s data is that the two CRISPR-Cas9-treated mice are actually more closely related genetically to each other than to the control mouse. This strongly suggests that the so-called “unexpected mutations” simply represent SNPs and indels shared in common by these mice prior to nuclease treatment. In addition, given the genomic and sequence distribution profiles of these variants, we show that it is challenging to explain how CRISPR-Cas9 might be expected to induce such changes. Finally, we argue that the lack of appropriate controls in Schaefer et al.’s experimental design precludes assignment of causality to CRISPR-Cas9. Given these substantial issues, we urge Schaefer et al. to revise or re-state the original conclusions of their published work so as to avoid leaving misleading and unsupported statements to persist in the literature.

Response to antidepressant treatment in major depressive disorder (MDD) cannot be predicted currently, leading to uncertainty in medication selection, increasing costs, and prolonged suffering for many patients. Despite tremendous efforts in identifying response-associated genes in large genome-wide association studies, the results have been fairly modest, underlining the need to establish conceptually novel strategies. For the identification of transcriptome signatures that can distinguish between treatment responders and nonresponders, we herein submit a novel animal experimental approach focusing on extreme phenotypes. We utilized the large variance in response to antidepressant treatment occurring in DBA/2J mice, enabling sample stratification into subpopulations of good and poor treatment responders to delineate response-associated signature transcript profiles in peripheral blood samples. As a proof of concept, we translated our murine data to the transcriptome data of a clinically relevant human cohort. A cluster of 259 differentially regulated genes was identified when peripheral transcriptome profiles of good and poor treatment responders were compared in the murine model. Differences in expression profiles from baseline to week 12 of the human orthologues selected on the basis of the murine transcript signature allowed prediction of response status with an accuracy of 76% in the patient population. Finally, we show that glucocorticoid receptor (GR)-regulated genes are significantly enriched in this cluster of antidepressant-response genes. Our findings point to the involvement of GR sensitivity as a potential key mechanism shaping response to antidepressant treatment and support the hypothesis that antidepressants could stimulate resilience-promoting molecular mechanisms. Our data highlight the suitability of an appropriate animal experimental approach for the discovery of treatment response-associated pathways across species., Author summary Major depression is the second leading cause of disability worldwide. However, only one-third of patients with depression benefit from the first antidepressant compound they are prescribed. It is a fundamental problem that the outcomes of individual antidepressant treatments are still highly unpredictable. In clinical studies, discovery of biomarkers for antidepressant response is hampered by confounding factors such as the heterogeneity of the disease phenotype and additional environmental factors, e.g., previous life events and different schedules of psychopharmacological treatment, which reduce the power to detect true response biomarkers. To overcome some of these limitations, we have established a conceptually novel approach that allows the selection of extreme phenotypes in an antidepressant-responsive mouse strain. In the first step, we identify signatures in the transcriptome of peripheral blood associated with responses following stratification into good and poor treatment responders. As proof of concept, we translate the murine data to a population of depressed patients. We show that differences in expression profiles from baseline to week 12 of the human orthologues predict response status in patients. We finally provide evidence that sensitivity of the glucocorticoid receptor could be a potential key mechanism shaping response to antidepressant treatment.

Summary The 3D architecture of DNA within the nucleus is a key determinant of interactions between genes, regulatory elements, and transcriptional machinery. As a result, differences in DNA looping structure are associated with variation in gene expression and cell state. To systematically assess changes in DNA looping architecture between samples, we introduce diffloop, an R/Bioconductor package that provides a suite of functions for the quality control, statistical testing, annotation, and visualization of DNA loops. We demonstrate this functionality by detecting differences between ENCODE ChIA-PET samples and relate looping to variability in epigenetic state. Availability and implementation Diffloop is implemented as an R/Bioconductor package available at https://bioconductor.org/packages/release/bioc/html/diffloop.html Supplementary information Supplementary data are available at Bioinformatics online.

Normal human hematopoiesis involves cellular differentiation of multipotent cells into progressively more lineage-restricted states. While epigenomic landscapes of this process have been explored in immunophenotypically-defined populations, the single-cell regulatory variation that defines hematopoietic differentiation has been hidden by ensemble averaging. We generated single-cell chromatin accessibility landscapes across 8 populations of immunophenotypically-defined human hematopoietic cell types. Using bulk chromatin accessibility profiles to scaffold our single-cell data analysis, we constructed an epigenomic landscape of human hematopoiesis and characterized epigenomic heterogeneity within phenotypically sorted populations to find epigenomic lineage-bias toward different developmental branches in multipotent stem cell states. We identify and isolate sub-populations within classically-defined granulocyte-macrophage progenitors (GMPs) and use ATAC-seq and RNA-seq to confirm that GMPs are epigenomically and transcriptomically heterogeneous. Furthermore, we identified transcription factors andcis-regulatory elements linked to changes in chromatin accessibility within cellular populations and across a continuous myeloid developmental trajectory, and observe relatively simple TF motif dynamics give rise to a broad diversity of accessibility dynamics at cis-regulatory elements. Overall, this work provides a template for exploration of complex regulatory dynamics in primary human tissues at the ultimate level of granular specificity – the single cell.One Sentence SummarySingle cell chromatin accessibility reveals a high-resolution, continuous landscape of regulatory variation in human hematopoiesis.

SUMMARY Human erythropoiesis serves as a paradigm of physiologic cellular differentiation. This process is also of considerable interest for better understanding anemias and identifying new therapies. Here, we apply deep transcriptomic and accessible chromatin profiling to characterize a faithful ex vivo human erythroid differentiation system from hematopoietic stem and progenitor cells. We reveal stage-specific transcriptional states and chromatin accessibility during various stages of erythropoiesis, including 14,260 differentially expressed genes and 63,659 variably accessible chromatin peaks. Our analysis suggests differentiation stage-predominant roles for specific master regulators, including GATA1 and KLF1. We integrate chromatin profiles with common and rare genetic variants associated with erythroid cell traits and diseases, finding that variants regulating different erythroid phenotypes likely act at variable points during differentiation. In addition, we identify a regulator of terminal erythropoiesis, TMCC2, more broadly illustrating the value of this comprehensive analysis to improve our understanding of erythropoiesis in health and disease., In Brief Ludwig et al. chart the dynamic transcriptional and chromatin landscapes as hematopoietic stem and progenitor cells differentiate into mature red blood cells. This multi-omic profiling reveals dynamic transcription factor activities and human genetic variation that modulate this process., Graphical Abstract

The three-dimensional architecture of DNA within the nucleus is a key determinant of interactions between genes, regulatory elements, and transcriptional machinery. As a result, differences in loop structure are associated with differences in gene expression and cell state. Here, we introduce diffloop, an R/Bioconductor package for identifying differential DNA looping between samples. The package additionally provides a suite of functions for the quality control, statistical testing, annotation and visualization of DNA loops. We demonstrate this functionality by detecting differences in DNA loops between ENCODE ChIA-PET datasets and relate looping to differences in epigenetic state and gene expression.