K.K., T.C., I.C.M., H.J.P., J.L., D.G.K., and R.K. indicative of stem cell decline alongside pro-proliferative JAK/STAT signaling. To investigate the relationship between JAK/STAT and p53 signaling, we challenged HSCs with a constitutively active form of JAK2 (V617F) and observed an expansion of the p53-positive subpopulation in old mice. Our results reveal cellular heterogeneity in the onset of HSC aging and implicate a role for JAK2V617F-driven proliferation in the p53-mediated functional decline of old HSCs. Keywords: aging, scRNA-seq, hematology, JAK2, p53, stem cells, cellular aging, cancer, leukemia, genomics Graphical Abstract Open in a separate window Introduction Organismal aging is accompanied by a gradual decline in regenerative capacities. This decline has been associated with reduced stem cell function, where the aging stem cell pool is unable to repopulate tissues upon cellular loss during physiological turnover or after tissue injury (Beerman et?al., 2010). In the hematopoietic system, stem cell aging is evident in a weakening of the adaptive immune response and a general decline of hematopoietic stem cell fitness (Beerman et?al., 2010). The weakening immune response has been attributed to a shift from a balanced lymphoid/myeloid output toward a myeloid skew with age (Rossi et?al., 2005). Although hematopoietic stem cells (HSCs) showing a skew in their myeloid/lymphoid output can also be found in young mice, the aggregate output is balanced. In contrast, with age, proportionally fewer lymphoid biased HSCs are found (Grover et?al., 2016). In addition to the lineage skew, aging of the hematopoietic system also results in reduced performance in blood Alisporivir reconstitution and engraftment, regardless of lineage output (Dykstra et?al., 2011). In addition, accumulation of DNA damage and upregulation of p53 in aged HSC populations is well documented (Dumble et?al., 2007, Rossi et?al., 2007). p53 is a key regulator of aging in hematopoiesis, with high levels of p53 leading to premature aging features, such as reduced engraftment (Dumble et?al., 2007). However, while Grover and colleagues (Grover et?al., 2016) were able to shed light on the molecular signature responsible for lineage skewing with age, little is known about the molecular basis of the functional decline of HSCs with age. It is, for example, unknown how uniformly the functional impairment is distributed within the HSC compartment, and it is unclear what factors and pathways are directly relevant to the decline. Using an Alisporivir index-sorting strategy and single-cell assays for highly purified long-term HSCs (LT-HSCs), we identified HSC?aging as a heterogeneous process by characterizing an?HSC subpopulation marked through p53 activation in old?mice. Further transcriptional description of the subcluster? shows myeloid bias as well as JAK/STAT- and Alisporivir MAPK?(mitogen-activated protein kinase)-driven Alisporivir pro-proliferative gene signatures, reminiscent of the proliferation-driven cell-cycle arrest in cellular senescence (Serrano et?al., 1997). Moreover, expansion of this old-specific subpopulation could be?triggered by constitutively activating Jak2. We propose a model whereby prolonged proliferation in HSCs driven by the?JAK/STAT pathway leads to a functionally impaired HSC?subpopulation defined by p53 pathway upregulation with age. Results The Long-Term HSC Compartment Harbors a Distinct Subpopulation with Age To determine how the transcriptional Rabbit Polyclonal to RIN3 heterogeneity in long-term HSCs is associated with age, we index-sorted single LT-HSCs using ESLAM markers (Figure?1A) from the bone marrow of mice aged 4?months old (n?= 192) and 18?months old (n?= 192). This?approach resulted in a distinct HSC population evident through comparison with two published hematopoietic single-cell transcriptome datasets of young and old HSCs (lineage-negative Sca-1+, c-Kit+, CD150+, and CD48?) (Grover et?al., 2016, Kowalczyk et?al., 2015), when projecting all datasets onto an HSC expression atlas (Nestorowa et?al., 2016) (Figure?S1A). We obtained 119/192 old and 99/192 young cells after quality control (Figure?S1B; Supplemental Experimental Procedures) and used a k-means-based consensus clustering approach for single-cell transcriptomes (SC3) (Kiselev et?al., 2017). Open in a separate window Figure?1 LT-HSCs Display.