Summary Although the function of the mammalian pancreas hinges on complex interactions of distinct cell types, gene expression profiles have primarily been described with bulk mixtures. Here we implemented a droplet-based, single-cell RNA-seq method to determine the transcriptomes of over 12,000 individual pancreatic cells from four human donors and two mouse strains. Cells could be divided into 15 clusters that matched previously characterized cell types: all endocrine cell types, including rare epsilon-cells; exocrine cell types; vascular cells; Schwann cells; quiescent and activated stellate cells; and four types of immune cells. We detected subpopulations of ductal cells with distinct expression profiles and validated their existence with immuno-histochemistry stains. Moreover, among human beta- cells, we detected heterogeneity in the regulation of genes relating to functional maturation and levels of ER stress. Finally, we deconvolved bulk gene expression samples using the single-cell data to detect disease-associated differential expression. Our dataset provides a resource for the discovery of novel cell type-specific transcription factors, signaling receptors, and medically relevant genes.

Highlights d We define two multiplet errors in single-cell RNA-seq data: ''embedded'' and ''neotypic'' d Neotypic errors can lead to misidentification of cell types or transitional states d Scrublet code identifies neotypic doublets and predicts the overall doublet rate d The algorithm is tested against several experimental methods for labeling multiplets

SUMMARY Hematopoiesis, the process of mature blood and immune cell production, is functionally organized as a hierarchy, with self-renewing hematopoietic stem cells (HSCs) and multipotent progenitor (MPP) cells sitting at the very top1,2. Multiple models have been proposed as to what the earliest lineage choices are in these primitive hematopoietic compartments, the cellular intermediates, and the resulting lineage trees that emerge from them3–10. Given that the bulk of studies addressing lineage outcomes have been performed in the context of hematopoietic transplantation, current lineage branching models are more likely to represent roadmaps of lineage potential rather than native fate. Here, we utilize transposon (Tn) tagging to clonally trace the fates of progenitors and stem cells in unperturbed hematopoiesis. Our results describe a distinct clonal roadmap in which the megakaryocyte (Mk) lineage arises largely independently of other hematopoietic fates. Our data, combined with single cell RNAseq, identify a functional hierarchy of uni- and oligolineage producing clones within the MPP population. Finally, our results demonstrate that traditionally defined long-term HSCs (LT-HSCs) are a significant source of Mk-restricted progenitors, suggesting that the Mk-lineage is the predominant native fate of LT-HSCs. Our study provides evidence for a substantially revised roadmap for unperturbed hematopoiesis, and highlights unique properties of MPPs and HSCs in situ.