Massively parallel base editing to map variant effects in human hematopoiesis.

Systematic evaluation of the impact of genetic variants is critical for the study and treatment of human physiology and disease. While specific mutations can be introduced by genome engineering, we still lack scalable approaches that are applicable to the important setting of primary cells, such as blood and immune cells. Here, we describe the development of massively parallel base-editing screens in human hematopoietic stem and progenitor cells. Such approaches enable functional screens for variant effects across any hematopoietic differentiation state. Moreover, they allow for rich phenotyping through single-cell RNA sequencing readouts and separately for characterization of editing outcomes through pooled single-cell genotyping. We efficiently design improved leukemia immunotherapy approaches, comprehensively identify non-coding variants modulating fetal hemoglobin expression, define mechanisms regulating hematopoietic differentiation, and probe the pathogenicity of uncharacterized disease-associated variants. These strategies will advance effective and high-throughput variant-to-function mapping in human hematopoiesis to identify the causes of diverse diseases.

Mapping transcriptomic vector fields of single cells.

Single-cell (sc)RNA-seq, together with RNA velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo (https://github.com/aristoteleo/dynamo-release), which infers absolute RNA velocity, reconstructs continuous vector fields that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo's power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1-GATA1 circuit. Leveraging the least-action-path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo, thus, represents an important step in advancing quantitative and predictive theories of cell-state transitions.

Single-cell nascent RNA sequencing unveils coordinated global transcription.

Transcription is the primary regulatory step in gene expression. Divergent transcription initiation from promoters and enhancers produces stable RNAs from genes and unstable RNAs from enhancers1,2. Nascent RNA capture and sequencing assays simultaneously measure gene and enhancer activity in cell populations3. However, fundamental questions about the temporal regulation of transcription and enhancer-gene coordination remain unanswered, primarily because of the absence of a single-cell perspective on active transcription. In this study, we present scGRO-seq-a new single-cell nascent RNA sequencing assay that uses click chemistry-and unveil coordinated transcription throughout the genome. We demonstrate the episodic nature of transcription and the co-transcription of functionally related genes. scGRO-seq can estimate burst size and frequency by directly quantifying transcribing RNA polymerases in individual cells and can leverage replication-dependent non-polyadenylated histone gene transcription to elucidate cell cycle dynamics. The single-nucleotide spatial and temporal resolution of scGRO-seq enables the identification of networks of enhancers and genes. Our results suggest that the bursting of transcription at super-enhancers precedes bursting from associated genes. By imparting insights into the dynamic nature of global transcription and the origin and propagation of transcription signals, we demonstrate the ability of scGRO-seq to investigate the mechanisms of transcription regulation and the role of enhancers in gene expression.

Deciphering cell states and genealogies of human haematopoiesis.

The human blood system is maintained through the differentiation and massive amplification of a limited number of long-lived haematopoietic stem cells (HSCs)1. Perturbations to this process underlie diverse diseases, but the clonal contributions to human haematopoiesis and how this changes with age remain incompletely understood. Although recent insights have emerged from barcoding studies in model systems2-5, simultaneous detection of cell states and phylogenies from natural barcodes in humans remains challenging. Here we introduce an improved, single-cell lineage-tracing system based on deep detection of naturally occurring mitochondrial DNA mutations with simultaneous readout of transcriptional states and chromatin accessibility. We use this system to define the clonal architecture of HSCs and map the physiological state and output of clones. We uncover functional heterogeneity in HSC clones, which is stable over months and manifests as both differences in total HSC output and biases towards the production of different mature cell types. We also find that the diversity of HSC clones decreases markedly with age, leading to an oligoclonal structure with multiple distinct clonal expansions. Our study thus provides a clonally resolved and cell-state-aware atlas of human haematopoiesis at single-cell resolution, showing an unappreciated functional diversity of human HSC clones and, more broadly, paving the way for refined studies of clonal dynamics across a range of tissues in human health and disease.

Inferring gene regulation from stochastic transcriptional variation across single cells at steady state.

Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation. We distinguish these temporal trends from the time-invariant covariation arising from cell states, and we delineate the experimental and technical requirements for leveraging these small but meaningful cofluctuations in the presence of measurement noise. While current technology does not yet allow adequate power for definitively detecting regulatory relationships for all TFs simultaneously in cells at steady state, we investigate a small-scale dataset to inform future experimental design. This study supports the potential value of mapping regulatory connections through stochastic variation, and it motivates further technological development to achieve its full potential.

Deciphering transcriptional and functional heterogeneity in hematopoiesis with single-cell genomics.

PURPOSE OF REVIEW: Single-cell genomic approaches have uncovered cell fate biases and heterogeneity within hematopoietic subpopulations. However, standard single-cell transcriptomics suffers from high sampling noise, which particularly skews the distribution of lowly expressed genes, such as transcription factors (TFs). This might preclude the identification of rare transcripts that define cell identity and demarcate cell fate biases. Moreover, these studies need to go hand in hand with relevant functional assays to ensure that observed gene expression changes represent biologically meaningful alterations. RECENT FINDINGS: Single-cell lineage tracing and functional validation studies have uncovered cell fate bias within transcriptionally distinct hematopoietic stem and progenitor subpopulations. Novel markers identified using these strategies have been proposed to prospectively isolate functionally distinct subpopulations, including long-term hematopoietic stem cells for ex vivo applications. Furthermore, the continuous nature of hematopoiesis has prompted the study of the relationship between stochastic transcriptional noise in hematopoietic TFs and cell fate determination. SUMMARY: An understanding of the limitations of single-cell genomic approaches and follow-up functional assays is critical to discern the technical and biological contribution of noise in hematopoietic heterogeneity, to identify rare gene expression states, and to uncover functionally distinct subpopulations within hematopoiesis. SUPPLEMENTARY VIDEO: http://links.lww.com/COH/A23.

Single-cell nascent RNA sequencing using click-chemistry unveils coordinated transcription.

Transcription is the primary regulatory step in gene expression. Divergent transcription initiation from promoters and enhancers produces stable RNAs from genes and unstable RNAs from enhancers1-5. Nascent RNA capture and sequencing assays simultaneously measure gene and enhancer activity in cell populations6-9. However, fundamental questions in the temporal regulation of transcription and enhancer-gene synchrony remain unanswered primarily due to the absence of a single-cell perspective on active transcription. In this study, we present scGRO-seq - a novel single-cell nascent RNA sequencing assay using click-chemistry - and unveil the coordinated transcription throughout the genome. scGRO-seq demonstrates the episodic nature of transcription, and estimates burst size and frequency by directly quantifying transcribing RNA polymerases in individual cells. It reveals the co-transcription of functionally related genes and leverages the replication-dependent non-polyadenylated histone genes transcription to elucidate cell-cycle dynamics. The single-nucleotide spatial and temporal resolution of scGRO-seq identifies networks of enhancers and genes and indicates that the bursting of transcription at super-enhancers precedes the burst from associated genes. By imparting insights into the dynamic nature of transcription and the origin and propagation of transcription signals, scGRO-seq demonstrates its unique ability to investigate the mechanisms of transcription regulation and the role of enhancers in gene expression.

Sequential intravenous allogeneic mesenchymal stromal cells as a potential treatment for thromboangiitis obliterans (Buerger's disease).

Thromboangiitis obliterans (TAO), also known as Buerger's Disease, is an occlusive vasculitis linked with high morbidity and amputation risk. To date, TAO is deemed incurable due to the lack of a definitive treatment. The immune system and inflammation are proposed to play a central role in TAO pathogenesis. Due to their immunomodulatory effects, mesenchymal stromal cells (MSCs) are the subject of intense research for the treatment of a wide range of immune-mediated diseases. Thus far, local intramuscular injections of autologous or allogeneic MSCs have shown promising results in TAO. However, sequential intravenous allogeneic MSC administration has not yet been explored, which we hypothesized could exert a systemic anti-inflammatory effect in the vasculature and modulate the immune response. Here, we report the first case of a TAO patient at amputation risk treated with four sequential intravenous infusions of bone marrow-derived allogeneic MSCs from a healthy donor. Following administration, there was significant regression of foot skin ulcers and improvements in rest pain, Walking Impairment Questionnaire scores, and quality of life. Sixteen months after the infusion, the patient had not required any further amputations. This report highlights the potential of sequential allogeneic MSC infusions as an effective treatment for TAO, warranting further studies to compare this approach with the more conventionally used intramuscular MSC administration and other cell-based therapies.