Single-Cell RNA Sequencing to Disentangle the Blood System

Abstract

The blood system is often represented as a tree-like structure with stem cells that give rise to mature blood cell types through a series of demarcated steps. Although this representation has served as a model of hierarchical tissue organization for decades, single-cell technologies are shedding new light on the abundance of cell type intermediates and the molecular mechanisms that ensure balanced replenishment of differentiated cells. In this Brief Review, we exemplify new insights into blood cell differentiation generated by single-cell RNA sequencing, summarize considerations for the application of this technology, and highlight innovations that are leading the way to understand hematopoiesis at the resolution of single cells. Graphic Abstract: A graphic abstract is available for this article.

Keywords: blood cells; computational biology; hematopoiesis; stem cells; technology.

Figure.

Different approaches to describe the hematopoietic hierarchy. A, Hematopoietic cell types can be separated, for example, using flow cytometry to sort based on surface markers. In vitro differentiation and transplantation inform the lineage potential of single cells or sorted populations. These assays played a major role in establishing the hierarchical relationships between cell types. B, Molecular characterization of individual cells provides an additional method to study cellular heterogeneity. Computational analysis of these datasets indicates that cell types are more heterogeneous and that differentiation trajectories are more gradual than appreciated previously. B/NK indicates B/natural killer cell progenitor; CMP, common myeloid progenitor; DC, dendritic cell; ETP, early T-cell progenitor; GMP, granulocyte/macrophage progenitor; HSC, hematopoietic stem cell; MEP, megakaryocyte/erythroid progenitor; MLP, multilymphoid progenitor; MPP, multipotent progenitor; Prog, progenitor; RNA-seq, RNA sequencing. A, Hierarchy derived from Doulatov et al. B, K nearest neighbor graph derived from van Galen et al.