Single-cell proteo-genomic reference maps of the hematopoietic system enable the purification and massive profiling of precisely defined cell states.

Single-cell genomics technology has transformed our understanding of complex cellular systems. However, excessive cost and a lack of strategies for the purification of newly identified cell types impede their functional characterization and large-scale profiling. Here, we have generated high-content single-cell proteo-genomic reference maps of human blood and bone marrow that quantitatively link the expression of up to 197 surface markers to cellular identities and biological processes across all main hematopoietic cell types in healthy aging and leukemia. These reference maps enable the automatic design of cost-effective high-throughput cytometry schemes that outperform state-of-the-art approaches, accurately reflect complex topologies of cellular systems and permit the purification of precisely defined cell states. The systematic integration of cytometry and proteo-genomic data enables the functional capacities of precisely mapped cell states to be measured at the single-cell level. Our study serves as an accessible resource and paves the way for a data-driven era in cytometry.

Identifying cancer cells from calling single-nucleotide variants in scRNA-seq data.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) data are widely used to study cancer cell states and their heterogeneity. However, the tumour microenvironment is usually a mixture of healthy and cancerous cells and it can be difficult to fully separate these two populations based on transcriptomics alone. If available, somatic single-nucleotide variants (SNVs) observed in the scRNA-seq data could be used to identify the cancer population and match that information with the single cells' expression profile. However, calling somatic SNVs in scRNA-seq data is a challenging task, as most variants seen in the short-read data are not somatic, but can instead be germline variants, RNA edits or transcription, sequencing, or processing errors. In addition, only variants present in actively transcribed regions for each individual cell will be seen in the data. RESULTS: To address these challenges, we develop CCLONE (Cancer Cell Labelling On Noisy Expression), an interpretable tool adapted to handle the uncertainty and sparsity of SNVs called from scRNA-seq data. CCLONE jointly identifies cancer clonal populations, and their associated variants. We apply CCLONE on two acute myeloid leukaemia datasets and one lung adenocarcinoma dataset and show that CCLONE captures both genetic clones and somatic events for multiple patients. These results show how CCLONE can be used to gather insight into the course of the disease and the origin of cancer cells in scRNA-seq data. AVAILABILITY AND IMPLEMENTATION: Source code is available at github.com/HaghverdiLab/CCLONE.

Late-onset NPM1 mutation in a MYC-amplified relapsed / refractory acute myeloid leukemia patient treated with gemtuzumab ozogamicin and glasdegib.

Not available.

Targeted Perturb-seq enables genome-scale genetic screens in single cells.

The transcriptome contains rich information on molecular, cellular and organismal phenotypes. However, experimental and statistical limitations constrain sensitivity and throughput of genetic screening with single-cell transcriptomics readout. To overcome these limitations, we introduce targeted Perturb-seq (TAP-seq), a sensitive, inexpensive and platform-independent method focusing single-cell RNA-seq coverage on genes of interest, thereby increasing the sensitivity and scale of genetic screens by orders of magnitude. TAP-seq permits routine analysis of thousands of CRISPR-mediated perturbations within a single experiment, detects weak effects and lowly expressed genes, and decreases sequencing requirements by up to 50-fold. We apply TAP-seq to generate perturbation-based enhancer-target gene maps for 1,778 enhancers within 2.5% of the human genome. We thereby show that enhancer-target association is jointly determined by three-dimensional contact frequency and epigenetic states, allowing accurate prediction of enhancer targets throughout the genome. In addition, we demonstrate that TAP-seq can identify cell subtypes with only 100 sequencing reads per cell.

Single-cell RNA sequencing of motoneurons identifies regulators of synaptic wiring in Drosophila embryos.

The correct wiring of neuronal circuits is one of the most complex processes in development, since axons form highly specific connections out of a vast number of possibilities. Circuit structure is genetically determined in vertebrates and invertebrates, but the mechanisms guiding each axon to precisely innervate a unique pre-specified target cell are poorly understood. We investigated Drosophila embryonic motoneurons using single-cell genomics, imaging, and genetics. We show that a cell-specific combination of homeodomain transcription factors and downstream immunoglobulin domain proteins is expressed in individual cells and plays an important role in determining cell-specific connections between differentiated motoneurons and target muscles. We provide genetic evidence for a functional role of five homeodomain transcription factors and four immunoglobulins in the neuromuscular wiring. Knockdown and ectopic expression of these homeodomain transcription factors induces cell-specific synaptic wiring defects that are partly phenocopied by genetic modulations of their immunoglobulin targets. Taken together, our data suggest that homeodomain transcription factor and immunoglobulin molecule expression could be directly linked and function as a crucial determinant of neuronal circuit structure.

Single-cell polyadenylation site mapping reveals 3' isoform choice variability.

Cell-to-cell variability in gene expression is important for many processes in biology, including embryonic development and stem cell homeostasis. While heterogeneity of gene expression levels has been extensively studied, less attention has been paid to mRNA polyadenylation isoform choice. 3' untranslated regions regulate mRNA fate, and their choice is tightly controlled during development, but how 3' isoform usage varies within genetically and developmentally homogeneous cell populations has not been explored. Here, we perform genome-wide quantification of polyadenylation site usage in single mouse embryonic and neural stem cells using a novel single-cell transcriptomic method, BATSeq. By applying BATBayes, a statistical framework for analyzing single-cell isoform data, we find that while the developmental state of the cell globally determines isoform usage, single cells from the same state differ in the choice of isoforms. Notably this variation exceeds random selection with equal preference in all cells, a finding that was confirmed by RNA FISH data. Variability in 3' isoform choice has potential implications on functional cell-to-cell heterogeneity as well as utility in resolving cell populations.

Deciphering the rules by which 5'-UTR sequences affect protein expression in yeast.

The 5'-untranslated region (5'-UTR) of mRNAs contains elements that affect expression, yet the rules by which these regions exert their effect are poorly understood. Here, we studied the impact of 5'-UTR sequences on protein levels in yeast, by constructing a large-scale library of mutants that differ only in the 10 bp preceding the translational start site of a fluorescent reporter. Using a high-throughput sequencing strategy, we obtained highly accurate measurements of protein abundance for over 2,000 unique sequence variants. The resulting pool spanned an approximately sevenfold range of protein levels, demonstrating the powerful consequences of sequence manipulations of even 1-10 nucleotides immediately upstream of the start codon. We devised computational models that predicted over 70% of the measured expression variability in held-out sequence variants. Notably, a combined model of the most prominent features successfully explained protein abundance in an additional, independently constructed library, whose nucleotide composition differed greatly from the library used to parameterize the model. Our analysis reveals the dominant contribution of the start codon context at positions -3 to -1, mRNA secondary structure, and out-of-frame upstream AUGs (uAUGs) to phenotypic diversity, thereby advancing our understanding of how protein levels are modulated by 5'-UTR sequences, and paving the way toward predictably tuning protein expression through manipulations of 5'-UTRs.

Mitoclone2: an R package for elucidating clonal structure in single-cell RNA-sequencing data using mitochondrial variants.

Clonal cell population dynamics play a critical role in both disease and development. Due to high mitochondrial mutation rates under both healthy and diseased conditions, mitochondrial genomic variability is a particularly useful resource in facilitating the identification of clonal population structure. Here we present mitoClone2, an all-inclusive R package allowing for the identification of clonal populations through integration of mitochondrial heteroplasmic variants discovered from single-cell sequencing experiments. Our package streamlines the investigation of this phenomenon by providing: built-in compatibility with commonly used tools for the delineation of clonal structure, the ability to directly use multiplexed BAM files as input, annotations for both human and mouse mitochondrial genomes, and helper functions for calling, filtering, clustering, and visualizing variants.

Emergence of activation or repression in transcriptional control under a fixed molecular context.

For decades, studies have noted that transcription factors (TFs) can behave as either activators or repressors of different target genes. More recently, evidence suggests TFs can act on transcription simultaneously in positive and negative ways. Here we use biophysical models of gene regulation to define, conceptualize and explore these two aspects of TF action: "duality", where TFs can be overall both activators and repressors at the level of the transcriptional response, and "coherent and incoherent" modes of regulation, where TFs act mechanistically on a given target gene either as an activator or a repressor (coherent) or as both (incoherent). For incoherent TFs, the overall response depends on three kinds of features: the TF's mechanistic effects, the dynamics and effects of additional regulatory molecules or the transcriptional machinery, and the occupancy of the TF on DNA. Therefore, activation or repression can be tuned by just the TF-DNA binding affinity, or the number of TF binding sites, given an otherwise fixed molecular context. Moreover, incoherent TFs can cause non-monotonic transcriptional responses, increasing over a certain concentration range and decreasing outside the range, and we clarify the relationship between non-monotonicity and common assumptions of gene regulation models. Using the mammalian SP1 as a case study and well controlled, synthetically designed target sequences, we find experimental evidence for incoherent action and activation, repression or non-monotonicity tuned by affinity. Our work highlights the importance of moving from a TF-centric view to a systems view when reasoning about transcriptional control.

Single-cell division tracing and transcriptomics reveal cell types and differentiation paths in the regenerating lung.

Understanding the molecular and cellular processes involved in lung epithelial regeneration may fuel the development of therapeutic approaches for lung diseases. We combine mouse models allowing diphtheria toxin-mediated damage of specific epithelial cell types and parallel GFP-labeling of functionally dividing cells with single-cell transcriptomics to characterize the regeneration of the distal lung. We uncover cell types, including Krt13+ basal and Krt15+ club cells, detect an intermediate cell state between basal and goblet cells, reveal goblet cells as actively dividing progenitor cells, and provide evidence that adventitial fibroblasts act as supporting cells in epithelial regeneration. We also show that diphtheria toxin-expressing cells can persist in the lung, express specific inflammatory factors, and transcriptionally resemble a previously undescribed population in the lungs of COVID-19 patients. Our study provides a comprehensive single-cell atlas of the distal lung that characterizes early transcriptional and cellular responses to concise epithelial injury, encompassing proliferation, differentiation, and cell-to-cell interactions.

Somatic epimutations enable single-cell lineage tracing in native hematopoiesis across the murine and human lifespan.

Current approaches to lineage tracing of stem cell clones require genetic engineering or rely on sparse somatic DNA variants, which are difficult to capture at single-cell resolution. Here, we show that targeted single-cell measurements of DNA methylation at single-CpG resolution deliver joint information about cellular differentiation state and clonal identities. We develop EPI-clone, a droplet-based method for transgene-free lineage tracing, and apply it to study hematopoiesis, capturing hundreds of clonal trajectories across almost 100,000 single-cells. Using ground-truth genetic barcodes, we demonstrate that EPI-clone accurately identifies clonal lineages throughout hematopoietic differentiation. Applied to unperturbed hematopoiesis, we describe an overall decline of clonal complexity during murine ageing and the expansion of rare low-output stem cell clones. In aged human donors, we identified expanded hematopoietic clones with and without genetic lesions, and various degrees of clonal complexity. Taken together, EPI-clone enables accurate and transgene-free single-cell lineage tracing at scale.

Biological basis of extensive pleiotropy between blood traits and cancer risk.

BACKGROUND: The immune system has a central role in preventing carcinogenesis. Alteration of systemic immune cell levels may increase cancer risk. However, the extent to which common genetic variation influences blood traits and cancer risk remains largely undetermined. Here, we identify pleiotropic variants and predict their underlying molecular and cellular alterations. METHODS: Multivariate Cox regression was used to evaluate associations between blood traits and cancer diagnosis in cases in the UK Biobank. Shared genetic variants were identified from the summary statistics of the genome-wide association studies of 27 blood traits and 27 cancer types and subtypes, applying the conditional/conjunctional false-discovery rate approach. Analysis of genomic positions, expression quantitative trait loci, enhancers, regulatory marks, functionally defined gene sets, and bulk- and single-cell expression profiles predicted the biological impact of pleiotropic variants. Plasma small RNAs were sequenced to assess association with cancer diagnosis. RESULTS: The study identified 4093 common genetic variants, involving 1248 gene loci, that contributed to blood-cancer pleiotropism. Genomic hotspots of pleiotropism include chromosomal regions 5p15-TERT and 6p21-HLA. Genes whose products are involved in regulating telomere length are found to be enriched in pleiotropic variants. Pleiotropic gene candidates are frequently linked to transcriptional programs that regulate hematopoiesis and define progenitor cell states of immune system development. Perturbation of the myeloid lineage is indicated by pleiotropic associations with defined master regulators and cell alterations. Eosinophil count is inversely associated with cancer risk. A high frequency of pleiotropic associations is also centered on the regulation of small noncoding Y-RNAs. Predicted pleiotropic Y-RNAs show specific regulatory marks and are overabundant in the normal tissue and blood of cancer patients. Analysis of plasma small RNAs in women who developed breast cancer indicates there is an overabundance of Y-RNA preceding neoplasm diagnosis. CONCLUSIONS: This study reveals extensive pleiotropism between blood traits and cancer risk. Pleiotropism is linked to factors and processes involved in hematopoietic development and immune system function, including components of the major histocompatibility complexes, and regulators of telomere length and myeloid lineage. Deregulation of Y-RNAs is also associated with pleiotropism. Overexpression of these elements might indicate increased cancer risk.

Integrative single-cell expression and functional studies unravels a sensitization to cytarabine-based chemotherapy through HIF pathway inhibition in AML leukemia stem cells.

Relapse remains a major challenge in the clinical management of acute myeloid leukemia (AML) and is driven by rare therapy-resistant leukemia stem cells (LSCs) that reside in specific bone marrow niches. Hypoxia signaling maintains cells in a quiescent and metabolically relaxed state, desensitizing them to chemotherapy. This suggests the hypothesis that hypoxia contributes to the chemoresistance of AML-LSCs and may represent a therapeutic target to sensitize AML-LSCs to chemotherapy. Here, we identify HIFhigh and HIFlow specific AML subgroups (inv(16)/t(8;21) and MLLr, respectively) and provide a comprehensive single-cell expression atlas of 119,000 AML cells and AML-LSCs in paired diagnostic-relapse samples from these molecular subgroups. The HIF/hypoxia pathway signature is attenuated in AML-LSCs compared with more differentiated AML cells but is more expressed than in healthy hematopoietic cells. Importantly, chemical inhibition of HIF cooperates with standard-of-care chemotherapy to impair AML growth and to substantially eliminate AML-LSCs in vitro and in vivo. These findings support the HIF pathway in the stem cell-driven drug resistance of AML and unravel avenues for combinatorial targeted and chemotherapy-based approaches to specifically eliminate AML-LSCs.

Disruption of stem cell niche-confined R-spondin 3 expression leads to impaired hematopoiesis.

Self-renewal and differentiation of stem and progenitor cells are tightly regulated to ensure tissue homeostasis. This regulation is enabled both remotely by systemic circulating cues, such as cytokines and hormones, and locally by various niche-confined factors. R-spondin 3 (RSPO3) is one of the most potent enhancers of Wnt signaling, and its expression is usually restricted to the stem cell niche where it provides localized enhancement of Wnt signaling to regulate stem cell expansion and differentiation. Disruption of this niche-confined expression can disturb proper tissue organization and lead to cancers. Here, we investigate the consequences of disrupting the niche-restricted expression of RSPO3 in various tissues, including the hematopoietic system. We show that normal Rspo3 expression is confined to the perivascular niche in the bone marrow. Induction of increased systemic levels of circulating RSPO3 outside of the niche results in prominent loss of early B-cell progenitors and anemia but surprisingly has no effect on hematopoietic stem cells. Using molecular, pharmacologic, and genetic approaches, we show that these RSPO3-induced hematopoietic phenotypes are Wnt and RSPO3 dependent and mediated through noncanonical Wnt signaling. Our study highlights a distinct role for a Wnt/RSPO3 signaling axis in the regulation of hematopoiesis, as well as possible challenges related to therapeutic use of RSPOs for regenerative medicine.

Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia.

Inter-patient variability and the similarity of healthy and leukemic stem cells (LSCs) have impeded the characterization of LSCs in acute myeloid leukemia (AML) and their differentiation landscape. Here, we introduce CloneTracer, a novel method that adds clonal resolution to single-cell RNA-seq datasets. Applied to samples from 19 AML patients, CloneTracer revealed routes of leukemic differentiation. Although residual healthy and preleukemic cells dominated the dormant stem cell compartment, active LSCs resembled their healthy counterpart and retained erythroid capacity. By contrast, downstream myeloid progenitors constituted a highly aberrant, disease-defining compartment: their gene expression and differentiation state affected both the chemotherapy response and leukemia's ability to differentiate into transcriptomically normal monocytes. Finally, we demonstrated the potential of CloneTracer to identify surface markers misregulated specifically in leukemic cells. Taken together, CloneTracer reveals a differentiation landscape that mimics its healthy counterpart and may determine biology and therapy response in AML.

Cellular hierarchies predict drug response in acute myeloid leukemia.

In a recent Nature Medicine study, Zeng and colleagues integrate both genomic and stem cell models of acute myeloid leukemia (AML) by deconvoluting cellular hierarchies of more than 1,000 AML samples. This work introduces a framework capable of predicting drug responses to targeted therapies in future clinical trials.

scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells.

Single-cell DNA methylation profiling currently suffers from excessive noise and/or limited cellular throughput. We developed scTAM-seq, a targeted bisulfite-free method for profiling up to 650 CpGs in up to 10,000 cells per experiment, with a dropout rate as low as 7%. We demonstrate that scTAM-seq can resolve DNA methylation dynamics across B-cell differentiation in blood and bone marrow, identifying intermediate differentiation states that were previously masked. scTAM-seq additionally queries surface-protein expression, thus enabling integration of single-cell DNA methylation information with cell atlas data. In summary, scTAM-seq is a high-throughput, high-confidence method for analyzing DNA methylation at single-CpG resolution across thousands of single cells.

Transcriptomic diversity in human medullary thymic epithelial cells.

The induction of central T cell tolerance in the thymus depends on the presentation of peripheral self-epitopes by medullary thymic epithelial cells (mTECs). This promiscuous gene expression (pGE) drives mTEC transcriptomic diversity, with non-canonical transcript initiation, alternative splicing, and expression of endogenous retroelements (EREs) representing important but incompletely understood contributors. Here we map the expression of genome-wide transcripts in immature and mature human mTECs using high-throughput 5' cap and RNA sequencing. Both mTEC populations show high splicing entropy, potentially driven by the expression of peripheral splicing factors. During mTEC maturation, rates of global transcript mis-initiation increase and EREs enriched in long terminal repeat retrotransposons are up-regulated, the latter often found in proximity to differentially expressed genes. As a resource, we provide an interactive public interface for exploring mTEC transcriptomic diversity. Our findings therefore help construct a map of transcriptomic diversity in the healthy human thymus and may ultimately facilitate the identification of those epitopes which contribute to autoimmunity and immune recognition of tumor antigens.

Decline in IGF1 in the bone marrow microenvironment initiates hematopoietic stem cell aging.

Decline in hematopoietic stem cell (HSC) function with age underlies limited health span of our blood and immune systems. In order to preserve health into older age, it is necessary to understand the nature and timing of initiating events that cause HSC aging. By performing a cross-sectional study in mice, we discover that hallmarks of aging in HSCs and hematopoiesis begin to accumulate by middle age and that the bone marrow (BM) microenvironment at middle age induces and is indispensable for hematopoietic aging. Using unbiased approaches, we find that decreased levels of the longevity-associated molecule IGF1 in the local middle-aged BM microenvironment are a factor causing HSC aging. Direct stimulation of middle-aged HSCs with IGF1 rescues molecular and functional hallmarks of aging, including restored mitochondrial activity. Thus, although decline in IGF1 supports longevity, our work indicates that this also compromises HSC function and limits hematopoietic health span.

Identification of leukemic and pre-leukemic stem cells by clonal tracking from single-cell transcriptomics.

Cancer stem cells drive disease progression and relapse in many types of cancer. Despite this, a thorough characterization of these cells remains elusive and with it the ability to eradicate cancer at its source. In acute myeloid leukemia (AML), leukemic stem cells (LSCs) underlie mortality but are difficult to isolate due to their low abundance and high similarity to healthy hematopoietic stem cells (HSCs). Here, we demonstrate that LSCs, HSCs, and pre-leukemic stem cells can be identified and molecularly profiled by combining single-cell transcriptomics with lineage tracing using both nuclear and mitochondrial somatic variants. While mutational status discriminates between healthy and cancerous cells, gene expression distinguishes stem cells and progenitor cell populations. Our approach enables the identification of LSC-specific gene expression programs and the characterization of differentiation blocks induced by leukemic mutations. Taken together, we demonstrate the power of single-cell multi-omic approaches in characterizing cancer stem cells.