The hematopoietic system follows a hierarchical organization, with multipotent long-term repopulating hematopoietic stem cells (LT-HSCs) occupying the top tier. This paradigm, developed mostly through cell transplantation assays, has recently been contested by a series of studies performed under native conditions, without transplantation. Application of systems-level single cell methods in this setting has revealed a heterogeneity of cell states within progenitors and stem cells, prompting a reevaluation of the theories of hematopoietic lineage fate decisions. We have previously described that hematopoietic stem cell fates are clonally heterogeneous under steady state and uncovered that a fraction of LT-HSCs contributes to a significant proportion of the megakaryocytic cell lineage under steady state, while rarely generating other types of progeny in unperturbed conditions. To elucidate the molecular underpinnings of this functional lineage-output heterogeneity, we developed a technique to barcode hematopoietic cells at the RNA level in order to simultaneously capture the lineage relationships and transcriptional states of HSCs. Using a droplet-based massive single cell RNAseq platform, we analyzed thousands of engrafted hematopoietic stem cells together with a sufficiently significant representation of downstream progenitor cells to measure HSC output. Inspection of the resulting "stem cell state-fate maps" revealed a variety of stem cell behaviors, including single cell quiescence, asymmetric and symmetric divisions, and clonal expansion. We also connected these behaviors with some of the previously observed heterogeneity in stem cell outcomes, including lineage bias, lineage output and clonal competition. Importantly, clustering of expression profiles revealed significant differences in the transcriptional programs related with some of these behaviors, which illuminate the molecular machineries that operate at the stem cell level to define this heterogeneity. Thus, our work has identified potential novel mediators for stem cell heterogeneity, which we are functionally analyzing in further detail to understand their molecular mechanisms.

Disclosures

No relevant conflicts of interest to declare.

Author notes

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Asterisk with author names denotes non-ASH members.

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