A comprehensive single cell transcriptional landscape of human hematopoietic progenitors

Abstract

Hematopoietic Stem/Progenitor cells (HSPCs) are endowed with the role of maintaining a diverse pool of blood cells throughout the human life. Despite recent efforts, the nature of the early cell fate decisions remains contentious. Using single-cell RNA-Seq, we show that existing approaches to stratify bone marrow CD34+ cells reveal a hierarchically-structured transcriptional landscape of hematopoietic differentiation. Still, this landscape misses important early fate decisions. We here provide a broader transcriptional profiling of bone marrow lineage negative hematopoietic progenitors that recovers a key missing branchpoint into basophils and expands our understanding of the underlying structure of early adult human haematopoiesis. We also show that this map has strong similarities in topology and gene expression to that found in mouse. Finally, we identify the sialomucin CD164, as a reliable marker for the earliest branches of HSPCs specification and we showed how its use can foster the design of alternative transplantation cell products.

Quantitative and molecular differences distinguish adult human medullary and extramedullary haematopoietic stem and progenitor cell landscapes

“…Clusters within the three branches could be attributed to the main haematopoietic lineages. Consistent with other single cell studies of human HSPCs (Hay et al, 2018;Pellin et al, 2019;Popescu et al, 2019), we observed grouping of erythroid (Ery) progenitors (marked by high expression of GATA1, FCER1A and CTNNBL1), megakaryocytic (Meg) progenitors (high expression of PLEK and ITGA2B) and basophil/mast cell (Baso/MC) progenitors (high transcript levels of HDC, MS4A3 and TPSAB) in one branch of the landscape. The second branch contained myeloid (My) progenitors marked by ENO1, MPO and CEBPD and the last branch corresponded to lymphoid (Ly) clusters (identified by high expression levels of IGJ, LTB and NKG7).…”

“…Similar cluster identities and proportions were found if the cells from both datasets were combined with Scanorama instead of the Seurat alignment method (Hie et al, 2019) ( Figure S1E-G). The general structure of the HSPC landscape outlined here overall resembles that described for human HSPC hierarchies in foetal, neonatal and adult life (Hay et al, 2018;Pellin et al, 2019;Popescu et al, 2019;Velten et al, 2017;Zheng et al, 2018), and provides a reference framework on which to compare the distinct organs.…”

Re‐entering the pluripotent state from blood lineage: promises and pitfalls of blood reprogramming

“…Though CD34 generally serves as an antigen for isolation of haematopoietic stem cells, differences indeed exist, and efforts are ongoing to resolve the heterogeneity within CD34 + population [8]. To date, in both human and murine systems, reprogramming is achievable with blood progenitors as well as fully differentiated mononucleated cells.…”

“…CD34 + haematopoietic cells are one of the most commonly used cellular sources for human blood reprogramming. Though CD34 generally serves as an antigen for isolation of haematopoietic stem cells, differences indeed exist, and efforts are ongoing to resolve the heterogeneity within CD34 + population [8]. Both peripheral blood and cord blood could be used to enrich blood cells for reprogramming.…”

Genetic predisposition to myeloproliferative neoplasms implicates hematopoietic stem cell biology

“…To identify clusters of cells, we used the 'FindClusters' function from Seurat, which applies a shared nearest neighbor modularity optimization-based clustering algorithm to identify clusters based on their PCs (in this case, top 50). To infer the HSC population, we used a marker gene signature similar to one recently applied in a different scRNA-seq human hematopoiesis dataset 67 -CD34, HLF, and CRHBP. Of the 28 MPN target genes, we excluded three which were detected in less than 50 cells, resulting in an aggregate MPN signature of 25 genes.…”