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The heart is a complex organ composed of multiple cell types such as cardiomyocytes and endothelial cells. Cardiovascular cells arise from Mesp1 -expressing progenitor cells. Lescroart et al. performed single-cell RNA-sequencing analysis of mouse wild-type and Mesp1 -deficient cardiovascular progenitor cells at early gastrulation (see the Perspective by Kelly and Sperling). When Mesp1 was eliminated, embryonic cells remained pluripotent and could not differentiate into cardiovascular progenitors. During gastrulation, the different Mesp1 progenitors rapidly became committed to a particular cell fate and heart region. Notch1 expression marked the earliest step of cardiovascular lineage segregation. Science , this issue p. 1177 ; see also p. 1098 Mesp1 -expressing progenitor cells commit to different heart cell fates in early gastrulation. Mouse heart development arises from Mesp1 -expressing cardiovascular progenitors (CPs) that are specified during gastrulation. The molecular processes that control early regional and lineage segregation of CPs have been unclear. We performed single-cell RNA sequencing of wild-type and Mesp1 -null CPs in mice. We showed that populations of Mesp1 CPs are molecularly distinct and span the continuum between epiblast and later mesodermal cells, including hematopoietic progenitors. Single-cell transcriptome analysis of Mesp1 -deficient CPs showed that Mesp1 is required for the exit from the pluripotent state and the induction of the cardiovascular gene expression program. We identified distinct populations of Mesp1 CPs that correspond to progenitors committed to different cell lineages and regions of the heart, identifying the molecular features associated with early lineage restriction and regional segregation of the heart at the early stage of mouse gastrulation.

Limited knowledge of cellular and molecular mechanisms underlying hematopoietic stem cell and multipotent progenitor (HSC/MPP) expansion within their native niche has impeded the application of stem cell-based therapies for hematological malignancies. Here, we constructed a spatiotemporal transcriptome map of mouse fetal liver (FL) as a platform for hypothesis generation and subsequent experimental validation of novel regulatory mechanisms. Single-cell transcriptomics revealed three transcriptionally heterogeneous HSC/MPP subsets, among which a CD93-enriched subset exhibited enhanced stem cell properties. Moreover, by employing integrative analysis of single-cell and spatial transcriptomics, we identified novel HSC/MPP ‘ p ocket- l ike’ u nit s (HSC PLUS), composed of niche cells (hepatoblasts, stromal cells, endothelial cells, and macrophages) and enriched with growth factors. Unexpectedly, macrophages showed an 11-fold enrichment in the HSC PLUS. Functionally, macrophage–HSC/MPP co-culture assay and candidate molecule testing, respectively, validated the supportive role of macrophages and growth factors (MDK, PTN, and IGFBP5) in HSC/MPP expansion. Finally, cross-species analysis and functional validation showed conserved cell–cell interactions and expansion mechanisms but divergent transcriptome signatures between mouse and human FL HSCs/MPPs. Taken together, these results provide an essential resource for understanding HSC/MPP development in FL, and novel insight into functional HSC/MPP expansion ex vivo.

How transplanted haematopoietic stem cells (HSCs) behave soon after they reside in a preconditioned host has not been studied due to technical limitations. Here, using single-cell RNA sequencing, we first obtained the transcriptome-based classifications of 28 haematopoietic cell types. We then applied them in conjunction with functional assays to track the dynamic changes of immunophenotypically purified HSCs in irradiated recipients within the first week after transplantation. Based on our transcriptional classifications, most homed HSCs in bone marrow and spleen became multipotent progenitors and, occasionally, some HSCs gave rise to megakaryocytic–erythroid or myeloid precursors. Parallel in vitro and in vivo functional experiments supported the paradigm of robust differentiation without substantial HSC expansion during the first week. Therefore, this study uncovers the previously inaccessible kinetics and fate choices of transplanted HSCs in myeloablated recipients at early stage, with implications for clinical applications of HSCs and other stem cells.Dong, Hao, Zhang, Zhu, Cheng et al. use single-cell RNA sequencing to characterize 28 haematopoietic cell populations and subsequently follow the fate and kinetics of HSCs upon transplantation in the mouse.

The sympathetic nervous system has been evolutionary selected to respond to stress and activates haematopoietic stem cells via noradrenergic signals. However, the pathways preserving haematopoietic stem cell quiescence and maintenance under proliferative stress remain largely unknown. Here we found that cholinergic signals preserve haematopoietic stem cell quiescence in bone-associated (endosteal) bone marrow niches. Bone marrow cholinergic neural signals increase during stress haematopoiesis and are amplified through cholinergic osteoprogenitors. Lack of cholinergic innervation impairs balanced responses to chemotherapy or irradiation and reduces haematopoietic stem cell quiescence and self-renewal. Cholinergic signals activate α7 nicotinic receptor in bone marrow mesenchymal stromal cells leading to increased CXCL12 expression and haematopoietic stem cell quiescence. Consequently, nicotine exposure increases endosteal haematopoietic stem cell quiescence in vivo and impairs hematopoietic regeneration after haematopoietic stem cell transplantation in mice. In humans, smoking history is associated with delayed normalisation of platelet counts after allogeneic haematopoietic stem cell transplantation. These results suggest that cholinergic signals preserve stem cell quiescence under proliferative stress. The sympathetic nervous system has been shown to respond to stress and activate haematopoietic stem cells. Here they show that cholinergic signals in the bone marrow preserve haematopoietic stem cell quiescence and self-renewal under proliferative stress.

During mouse embryonic development, pluripotent cells rapidly divide and diversify, yet the regulatory programs that define the cell repertoire for each organ remain ill-defined. To delineate comprehensive chromatin landscapes during early organogenesis, we mapped chromatin accessibility in 19,453 single nuclei from mouse embryos at 8.25 days post-fertilization. Identification of cell-type-specific regions of open chromatin pinpointed two TAL1-bound endothelial enhancers, which we validated using transgenic mouse assays. Integrated gene expression and transcription factor motif enrichment analyses highlighted cell-type-specific transcriptional regulators. Subsequent in vivo experiments in zebrafish revealed a role for the ETS factor FEV in endothelial identity downstream of ETV2 (Etsrp in zebrafish). Concerted in vivo validation experiments in mouse and zebrafish thus illustrate how single-cell open chromatin maps, representative of a mammalian embryo, provide access to the regulatory blueprint for mammalian organogenesis.Pijuan-Sala et al. present a comprehensive single-nucleus open chromatin map of early mouse embryogenesis and validate the role of ETS transcription factor FEV in endothelial identity in zebrafish.

Across the animal kingdom, gastrulation represents a key developmental event during which embryonic pluripotent cells diversify into lineage-specific precursors that will generate the adult organism. Here we report the transcriptional profiles of 116,312 single cells from mouse embryos collected at nine sequential time points ranging from 6.5 to 8.5 days post-fertilization. We construct a molecular map of cellular differentiation from pluripotency towards all major embryonic lineages, and explore the complex events involved in the convergence of visceral and primitive streak-derived endoderm. Furthermore, we use single-cell profiling to show that Tal1 −/− chimeric embryos display defects in early mesoderm diversification, and we thus demonstrate how combining temporal and transcriptional information can illuminate gene function. Together, this comprehensive delineation of mammalian cell differentiation trajectories in vivo represents a baseline for understanding the effects of gene mutations during development, as well as a roadmap for the optimization of in vitro differentiation protocols for regenerative medicine. Single-cell profiling is used to create a molecular-level atlas of cell differentiation trajectories during gastrulation and early organogenesis in the mouse.

Severe infections are a major stress on haematopoiesis, where the consequences for haematopoietic stem cells (HSCs) have only recently started to emerge. HSC function critically depends on the integrity of complex bone marrow (BM) niches; however, what role the BM microenvironment plays in mediating the effects of infection on HSCs remains an open question. Here, using a murine model of malaria and combining single-cell RNA sequencing, mathematical modelling, transplantation assays and intravital microscopy, we show that haematopoiesis is reprogrammed upon infection, whereby the HSC compartment turns over substantially faster than at steady-state and HSC function is drastically affected. Interferon is found to affect both haematopoietic and mesenchymal BM cells and we specifically identify a dramatic loss of osteoblasts and alterations in endothelial cell function. Osteo-active parathyroid hormone treatment abolishes infection-triggered HSC proliferation and—coupled with reactive oxygen species quenching—enables partial rescuing of HSC function.Haltalli et al. show that Plasmodium berghei infection induces interferon release, and affects haematopoietic stem cell proliferation and function, as well as osteoblasts and vascular integrity, in the bone marrow niche.

Haematopoietic stem cells (HSC) are situated at the apex of the haematopoietic differentiation hierarchy, ensuring the life-long supply of mature haematopoietic cells and forming a reservoir to replenish the haematopoietic system in case of emergency such as acute blood loss. To maintain a balanced production of all mature lineages and at the same time secure a stem cell reservoir, intricate regulatory programs have evolved to control multi-lineage differentiation and self-renewal in haematopoietic stem and progenitor cells (HSPCs). Leukaemogenic mutations commonly disrupt these regulatory programs causing a block in differentiation with simultaneous enhancement of proliferation. Here, we briefly summarize key aspects of HSPC regulatory programs, and then focus on their disruption by leukaemogenic fusion genes containing the mixed lineage leukaemia (MLL) gene. Using MLL as an example, we explore important questions of wider significance that are still under debate, including the importance of cell of origin, to what extent leukaemia oncogenes impose specific regulatory programs and the relevance of leukaemia stem cells for disease development and prognosis. Finally, we suggest that disruption of stem cell regulatory programs is likely to play an important role in many other pathologies including ageing-associated regenerative failure.

Adult blood contains a mixture of mature cell types, each with specialized functions. Single hematopoietic stem cells (HSCs) have been functionally shown to generate all mature cell types for the lifetime of the organism. Differentiation of HSCs toward alternative lineages must be balanced at the population level by the fate decisions made by individual cells. Transcription factors play a key role in regulating these decisions and operate within organized regulatory programs that can be modeled as transcriptional regulatory networks. As dysregulation of single HSC fate decisions is linked to fatal malignancies such as leukemia, it is important to understand how these decisions are controlled on a cell-by-cell basis. Here we developed and applied a network inference method, exploiting the ability to infer dynamic information from single-cell snapshot expression data based on expression profiles of 48 genes in 2,167 blood stem and progenitor cells. This approach allowed us to infer transcriptional regulatory network models that recapitulated differentiation of HSCs into progenitor cell types, focusing on trajectories toward megakaryocyte–erythrocyte progenitors and lymphoid-primed multipotent progenitors. By comparing these two models, we identified and subsequently experimentally validated a difference in the regulation of nuclear factor, erythroid 2 (Nfe2) and core-binding factor, runt domain, alpha subunit 2, translocated to, 3 homolog (Cbfa2t3h) by the transcription factor Gata2. Our approach confirms known aspects of hematopoiesis, provides hypotheses about regulation of HSC differentiation, and is widely applicable to other hierarchical biological systems to uncover regulatory relationships.

Background Rapid technological innovation for the generation of single-cell genomics data presents new challenges and opportunities for bioinformatics analysis. One such area lies in the development of new ways to train gene regulatory networks. The use of single-cell expression profiling technique allows the profiling of the expression states of hundreds of cells, but these expression states are typically noisier due to the presence of technical artefacts such as drop-outs. While many algorithms exist to infer a gene regulatory network, very few of them are able to harness the extra expression states present in single-cell expression data without getting adversely affected by the substantial technical noise present. Results Here we introduce BTR, an algorithm for training asynchronous Boolean models with single-cell expression data using a novel Boolean state space scoring function. BTR is capable of refining existing Boolean models and reconstructing new Boolean models by improving the match between model prediction and expression data. We demonstrate that the Boolean scoring function performed favourably against the BIC scoring function for Bayesian networks. In addition, we show that BTR outperforms many other network inference algorithms in both bulk and single-cell synthetic expression data. Lastly, we introduce two case studies, in which we use BTR to improve published Boolean models in order to generate potentially new biological insights. Conclusions BTR provides a novel way to refine or reconstruct Boolean models using single-cell expression data. Boolean model is particularly useful for network reconstruction using single-cell data because it is more robust to the effect of drop-outs. In addition, BTR does not assume any relationship in the expression states among cells, it is useful for reconstructing a gene regulatory network with as few assumptions as possible. Given the simplicity of Boolean models and the rapid adoption of single-cell genomics by biologists, BTR has the potential to make an impact across many fields of biomedical research.