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Single-cell RNA sequencing is a powerful tool to study developmental biology but does not preserve spatial information about tissue morphology and cellular interactions. Here, we combine single-cell and spatial transcriptomics with algorithms for data integration to study the development of the chicken heart from the early to late four-chambered heart stage. We create a census of the diverse cellular lineages in developing hearts, their spatial organization, and their interactions during development. Spatial mapping of differentiation transitions in cardiac lineages defines transcriptional differences between epithelial and mesenchymal cells within the epicardial lineage. Using spatially resolved expression analysis, we identify anatomically restricted expression programs, including expression of genes implicated in congenital heart disease. Last, we discover a persistent enrichment of the small, secreted peptide, thymosin beta-4, throughout coronary vascular development. Overall, our study identifies an intricate interplay between cellular differentiation and morphogenesis. Using single-cell and spatial transcriptomics in chicken hearts, here, the authors generate a census of cellular interactions from early to late four-chambered heart stage, identifying a distinct epicardial-mesenchymal cell population with a migratory phenotype.

Skeletal muscle repair is driven by the coordinated self-renewal and fusion of myogenic stem and progenitor cells. Single-cell gene expression analyses of myogenesis have been hampered by the poor sampling of rare and transient cell states that are critical for muscle repair, and do not inform the spatial context that is important for myogenic differentiation. Here, we demonstrate how large-scale integration of single-cell and spatial transcriptomic data can overcome these limitations. We created a single-cell transcriptomic dataset of mouse skeletal muscle by integration, consensus annotation, and analysis of 23 newly collected scRNAseq datasets and 88 publicly available single-cell (scRNAseq) and single-nucleus (snRNAseq) RNA-sequencing datasets. The resulting dataset includes more than 365,000 cells and spans a wide range of ages, injury, and repair conditions. Together, these data enabled identification of the predominant cell types in skeletal muscle, and resolved cell subtypes, including endothelial subtypes distinguished by vessel-type of origin, fibro-adipogenic progenitors defined by functional roles, and many distinct immune populations. The representation of different experimental conditions and the depth of transcriptome coverage enabled robust profiling of sparsely expressed genes. We built a densely sampled transcriptomic model of myogenesis, from stem cell quiescence to myofiber maturation, and identified rare, transitional states of progenitor commitment and fusion that are poorly represented in individual datasets. We performed spatial RNA sequencing of mouse muscle at three time points after injury and used the integrated dataset as a reference to achieve a high-resolution, local deconvolution of cell subtypes. We also used the integrated dataset to explore ligand-receptor co-expression patterns and identify dynamic cell-cell interactions in muscle injury response. We provide a public web tool to enable interactive exploration and visualization of the data. Our work supports the utility of large-scale integration of single-cell transcriptomic data as a tool for biological discovery.David McKellar et al. integrate single-cell and -nuclear transcriptomic analyses of mouse skeletal muscle in homeostatic conditions or following injury. The resulting transcriptomic model of myogenesis identified rare, transitional states and cell subtypes that are poorly represented in individual datasets, providing a valuable resource for the field.

Conventional scRNA-seq expression analyses rely on the availability of a high quality genome annotation. Yet, as we show here with scRNA-seq experiments and analyses spanning human, mouse, chicken, mole rat, lemur and sea urchin, genome annotations are often incomplete, in particular for organisms that are not routinely studied. To overcome this hurdle, we created a scRNA-seq analysis routine that recovers biologically relevant transcriptional activity beyond the scope of the best available genome annotation by performing scRNA-seq analysis on any region in the genome for which transcriptional products are detected. Our tool generates a single-cell expression matrix for all transcriptionally active regions (TARs), performs single-cell TAR expression analysis to identify biologically significant TARs, and then annotates TARs using gene homology analysis. This procedure uses single-cell expression analyses as a filter to direct annotation efforts to biologically significant transcripts and thereby uncovers biology to which scRNA-seq would otherwise be in the dark. Conventional single-cell RNA sequencing analysis rely on genome annotations that may be incomplete or inaccurate especially for understudied organisms. Here the authors present a bioinformatic tool that leverages single-cell data to uncover biologically relevant transcripts beyond the best available genome annotation.

DART-seq alters droplet sequencing in a simple and flexible way to simultaneously profile the transcriptome and multiplexed targeted RNAs, such as viral transcripts and immunoglobulin chains, in single cells.

A significant fraction of sudden death in children and young adults is due to viral myocarditis, an inflammatory disease of the heart. In this study, by using integrated single-cell and spatial transcriptomics, we created a high-resolution, spatially resolved transcriptome map of reovirus-induced myocarditis in neonatal mouse hearts. We assayed hearts collected at three timepoints after infection and studied the temporal, spatial and cellular heterogeneity of host–virus interactions. We further assayed the intestine, the primary site of reovirus infection, to establish a full chronology of molecular events that ultimately lead to myocarditis. We found that inflamed endothelial cells recruit cytotoxic T cells and undergo pyroptosis in the myocarditic tissue. Analyses of spatially restricted gene expression in myocarditic regions and the border zone identified immune-mediated cell-type-specific injury and stress responses. Overall, we observed a complex network of cellular phenotypes and spatially restricted cell–cell interactions associated with reovirus-induced myocarditis in neonatal mice.

Intestinal smooth muscles are the workhorse of the digestive system. Inside the millions of finger-like intestinal projections called villi, strands of smooth muscle cells contract to propel absorbed dietary fats through the adjacent lymphatic vessel, called the lacteal, sending fats into the blood circulation for energy production. Despite this vital function, how villus smooth muscles form, how they assemble alongside lacteals, and how they repair throughout life remain unknown. Here we combine single-cell RNA sequencing of the mouse intestine with quantitative lineage tracing to reveal the mechanisms of formation and differentiation of villus smooth muscle cells. Within the highly regenerative villus, we uncover a local hierarchy of subepithelial fibroblast progenitors that progress to become mature smooth muscle fibers, via an intermediate contractile myofibroblast-like phenotype. This continuum persists in the adult intestine as the major source of renewal of villus smooth muscle cells during adult life. We further found that the NOTCH3-DLL4 signaling axis governs the assembly of villus smooth muscles alongside their adjacent lacteal, and we show that this is necessary for gut absorptive function. Overall, our data shed light on the genesis of a poorly defined class of intestinal smooth muscle and pave the way for new opportunities to accelerate recovery of digestive function by stimulating muscle repair.

A significant fraction of sudden death in children and young adults is due to myocarditis, an inflammatory disease of the heart, most often caused by viral infection. Here we used integrated single-cell and spatial transcriptomics to create a high-resolution, spatially resolved map of reovirus-induced myocarditis in neonatal murine hearts. We assayed hearts collected at three timepoints after reovirus infection and studied the temporal, spatial, and cellular heterogeneity of host-virus interactions. We further assayed the intestine, the primary site of reovirus infection to establish a full chronology of molecular events that ultimately lead to myocarditis. We implemented targeted enrichment of viral transcripts to establish the cellular targets of the virus in the intestine and the heart. Our data give insight into the cell-type specificity of innate immune responses, and into the transcriptional states of inflamed cardiac cells that recruit circulating immune cells, including cytotoxic T cells which induce pyroptosis in the myocarditic tissue. Analyses of spatially restricted gene expression in myocarditic regions and the border zone around those regions identified immune-mediated cell-type specific injury and stress responses. Overall, we observe a dynamic and complex network of cellular phenotypes and cell-cell interactions associated with viral myocarditis. Competing Interest Statement The authors have declared no competing interest. Footnotes * 1. Additional validation experiment data to 3 figures. 2. Additional data panels to 11 supplementary figures. 3. Supplement file updated.

We describe Droplet Assisted RNA Targeting by single cell sequencing (DART-seq), a versatile technology that enables multiplexed amplicon sequencing and transcriptome profiling in single cells. We applied DART-seq to simultaneously characterize the non-A-tailed transcripts of a segmented dsRNA virus and the transcriptome of the infected cell. In addition, we used DART-seq to simultaneously determine the natively paired, variable region heavy and light chain amplicons and the transcriptome of B lymphocytes. Footnotes * Condensed results section and expanded Methods sections. Figures 1 and 2 updated and included supplemental documents.

Intestinal smooth muscles are the workhorse of the digestive system. Inside the millions of finger-like intestinal projections called villi, strands of smooth muscle cells contract to propel absorbed dietary fats through the adjacent lymphatic vessel, called the lacteal, sending fats into blood circulation for energy production. Despite this vital function, how villus smooth muscles form, how they assemble alongside lacteals, and how they repair throughout life remain unknown. Here we combine single-cell RNA sequencing of the mouse intestine with quantitative lineage tracing to reveal the mechanisms of formation and differentiation of villus smooth muscle cells. Within the highly regenerative villus, we uncover a local hierarchy of subepithelial fibroblast progenitors that progress to become mature smooth muscle fibers, via an intermediate contractile myofibroblast-like phenotype, a long-studied hallmark of wound healing. This continuum persists in the adult intestine as the major source of smooth muscle reservoir capable of continuous self-renewal throughout life. We further discover that the NOTCH3-DLL4 signaling axis governs the assembly of villus smooth muscles alongside their adjacent lacteal, which is necessary for gut absorptive function. Overall, our data shed light on the genesis of a poorly defined class of intestinal smooth muscle and pave the way for new opportunities to accelerate recovery of digestive function by stimulating muscle repair.Competing Interest StatementThe authors have declared no competing interest.Footnotes* https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE222122

Hormones coordinate long-range cell-cell communication in multicellular organisms and play vital roles in normal physiology, metabolism, and health. Using the newly-completed organism-wide single cell transcriptional atlas of a non-human primate, the mouse lemur (Microcebus murinus), we have systematically identified hormone-producing and -target cells for 87 classes of hormones, and have created a browsable atlas for hormone signaling that reveals previously unreported sites of hormone regulation and species-specific rewiring. Hormone ligands and receptors exhibited cell-type-dependent, stereotypical expression patterns, and their transcriptional profiles faithfully classified the discrete cell types defined by the full transcriptome, despite their comprising less than 1% of the transcriptome. Although individual cell types generally exhibited the same characteristic patterns of hormonal gene expression, a number of examples of similar or seemingly-identical cell types (e.g., endothelial cells of the lung versus of other organs) displayed different hormonal gene expression patterns. By linking ligand-expressing cells to the cells expressing the corresponding receptor, we constructed an organism-wide map of the hormonal cell-cell communication network. The hormonal cell-cell network was remarkably densely and robustly connected, and included classical hierarchical circuits (e.g. pituitary → peripheral endocrine gland → diverse cell types) as well as examples of highly distributed control. The network also included both well-known examples of feedback loops and a long list of potential novel feedback circuits. This primate hormone atlas provides a powerful resource to facilitate discovery of regulation on an organism-wide scale and at single-cell resolution, complementing the single-site-focused strategy of classical endocrine studies. The network nature of hormone regulation and the principles discovered here further emphasize the importance of a systems approach to understanding hormone regulation. Competing Interest Statement The authors have declared no competing interest.