Caenorhabditis elegans is an animal with few cells but a wide diversity of cell types. In this study, we characterize the molecular basis for their specification by profiling the transcriptomes of 86,024 single embryonic cells. We identify 502 terminal and preterminal cell types, mapping most single-cell transcriptomes to their exact position in C. elegans’ invariant lineage. Using these annotations, we find that (i) the correlation between a cell’s lineage and its transcriptome increases from middle to late gastrulation, then falls substantially as cells in the nervous system and pharynx adopt their terminal fates; (ii) multilineage priming contributes to the differentiation of sister cells at dozens of lineage branches; and (iii) most distinct lineages that produce the same anatomical cell type converge to a homogenous transcriptomic state.

Highlights d Proximal nephron segments show distinct expression profiles between the sexes d The time of nephron formation determines position and segmental cell diversity d Lineage convergence is observed at nephron-collecting system junctions d Data can be queried and viewed within an annotated anatomical database

C. elegans is an animal with few cells, but a striking diversity of cell types. Here, we characterize the molecular basis for their specification by profiling the transcriptomes of 84,625 single embryonic cells. We identify 284 terminal and pre-terminal cell types, mapping most single cell transcriptomes to their exact position in C. elegans' invariant lineage. We use these annotations to perform the first quantitative analysis of the relationship between lineage and the transcriptome for a whole organism. We find that a strong lineage-transcriptome correlation in the early embryo breaks down in the final two cell divisions as cells adopt their terminal fates and that most distinct lineages that produce the same anatomical cell type converge to a homogenous transcriptomic state. Users can explore our data with a graphical application "VisCello". Main text:To understand how cell fates are specified during development, it is essential to know the temporal sequence of gene expression in cells during their trajectories from uncommitted precursors to differentiated terminal cell types. Gene expression patterns near branch points in these trajectories can help identify candidate regulators of cell fate decisions (1). Single cell RNA sequencing (sc-RNA-seq) has made it possible to obtain comprehensive measurements of Fig 3. Developmental trajectories of ciliated neurons. (A) UMAP of ciliated neurons and precursors.Colors correspond to cell identity. Text labels indicate terminal cells. Numbers 1-13 indicate parents of 1 ADE-ADA, 2 CEP-URX 3 IL1 4 OLL 5 OLQ 6 ASJ-AUA 7 ASE 8 ASI 9 ASK 10 ADF-AWB 11 ASG-AWA 12 ADL 13 AFD-RMD. 3-5, 7-9, and 12 are listed as parents of only one cell type as the sister cells die. Numbers 14-17 indicate grandparents of 14 IL1 (= IL2 parent) 15 OLQ-URY 16, 17 ASE-ASJ-AUA. 18 indicates a progenitor cluster that includes the AWC-SAAVx and BAG-SMDVx parents, which were identified in a separate UMAP (Fig. S12C). This latter analysis also tentatively identified a few cells near the base of the ASH trajectory as the ASH-RIB parent. Late stage AUA cells cluster with non-ciliated neurons and are not included in this UMAP but are included in the heatmap in panel D. The tiny cluster of cells labeled with an asterisk (*) is putatively AWC-ON based on srt-28 expression. (B) UMAP plot colored by embryo time (colors matched to Fig. 1A) and gene expression (red indicates >0 reads for the listed gene). mcm-7 is gene associated with the cell cycle. unc-130 is known to be expressed in the ASG-AWA neuroblast but neither terminal cell (40) (C) Cartoon illustrating the lineage of the ASE, ASJ, and AUA neurons. (D) Heatmap showing patterns of differential transcription factor expression associated with branches in the ASE-ASJ-AUA lineage. Expression values are log-transformed, then centered and scaled by standard deviation for each row (gene).

Hematopoietic stem and progenitor cells (HSPCs) in the bone marrow are derived from a small population of hemogenic endothelial (HE) cells located in the major arteries of the mammalian embryo. HE cells undergo an endothelial to hematopoietic cell transition (EHT), giving rise to HSPCs that accumulate in intra-arterial clusters (IAC) before colonizing the fetal liver. To examine the cell and molecular transitions between endothelial (E), HE, and IAC cells, and the heterogeneity of HSPCs within IACs, we profiled ~37,000 cells from the caudal arteries [dorsal aorta (DA), umbilical (U), vitelline (V)] of embryonic day 9.5 (E9.5) to E11.5 mouse embryos by single-cell RNA sequencing (scRNA-Seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-Seq). We identified a continuous developmental trajectory from E to HE to IAC cells, with identifiable intermediate stages. The intermediate stage most proximal to HE, which we term pre-HE, is characterized by increased accessibility of chromatin enriched for SOX, FOX, GATA, and SMAD motifs. A developmental bottleneck separates pre-HE from HE, with RUNX1 dosage regulating the efficiency of the pre-HE to HE transition. A distal candidate Runx1 enhancer exhibits high chromatin accessibility specifically in pre-HE cells at the bottleneck, but loses accessibility thereafter. Distinct developmental trajectories within IAC cells result in two populations of CD45+ HSPCs; an initial wave of lympho-myeloid-biased progenitors, followed by precursors of hematopoietic stem cells (pre-HSCs). This multi-omics single-cell atlas significantly expands our understanding of pre-HSC ontogeny.

Single-cell RNA-seq data contain a large proportion of zeros for expressed genes. Such dropout events present a fundamental challenge for various types of data analyses. Here, we describe the SCRABBLE algorithm to address this problem. SCRABBLE leverages bulk data as a constraint and reduces unwanted bias towards expressed genes during imputation. Using both simulation and several types of experimental data, we demonstrate that SCRABBLE outperforms the existing methods in recovering dropout events, capturing true distribution of gene expression across cells, and preserving gene-gene relationship and cell-cell relationship in the data. Electronic supplementary material The online version of this article (10.1186/s13059-019-1681-8) contains supplementary material, which is available to authorized users.

Cerebral cavernous malformation (CCM) is a genetic, cerebrovascular disease. Familial CCM is caused by genetic mutations in KRIT1, CCM2 or PDCD10. Notably, disease onset is earlier and more severe in individuals with PDCD10 mutations. Recent studies have shown that lesions arise from excess Mitogen-Activated Protein Kinase Kinase Kinase 3 (MEKK3) signaling downstream of Toll-like Receptor 4 (TLR4) stimulation by lipopolysaccharide (LPS) derived from the gut microbiome. These findings suggest a gut-brain CCM disease axis but fail to define it or explain the poor prognosis of patients with PDCD10 mutations. Here, we demonstrate that the gut barrier is a primary determinant of CCM disease course, independent of microbiome configuration, that explains the increased severity of CCM disease associated with PDCD10 deficiency. Chemical disruption of the gut barrier with dextran sodium sulfate augments CCM formation in a mouse model, as does genetic loss of Pdcd10, but not Krit1, in gut epithelial cells. Loss of gut epithelial Pdcd10 results in disruption of the colonic mucosal barrier. Accordingly, loss of Mucin-2 or exposure to dietary emulsifiers that reduce the mucus barrier increase CCM burden analogous to loss of Pdcd10 in gut epithelium. Finally, we show that treatment with dexamethasone potently inhibits CCM formation in mice due to the combined effect of action at both brain endothelial cells and gut epithelial cells. These studies define a gut-brain disease axis in an experimental model of CCM in which a single gene is required for two critical components: gut epithelial function and brain endothelial signaling.

reports receiving commercial research grants from Kite, Servier, and Novartis, is listed as inventor on a patent for toxicity management for antitumor activity of CARs (WO 2014011984 A1; managed according to the University of Pennsylvania patent policy), and reports receiving other remuneration from McNaul Ebel. D.M.B. is now an employee of Tmunity Therapeutics, Inc. No potential conflicts of interest were disclosed by the other authors.Research.

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