Department of Haematology and Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom.
Blood. 2019 Mar 28;133(13):1415-1426. doi: 10.1182/blood-2018-08-835355. Epub 2019 Feb 6.
Single-cell transcriptomics has recently emerged as a powerful tool to analyze cellular heterogeneity, discover new cell types, and infer putative differentiation routes. The technique has been rapidly embraced by the hematopoiesis research community, and like other technologies before, single-cell molecular profiling is widely expected to make important contributions to our understanding of the hematopoietic hierarchy. Much of this new interpretation relies on inference of the transcriptomic landscape as a representation of existing cellular states and associated transitions among them. Here we review how this model allows, under certain assumptions, charting of time-resolved differentiation trajectories with unparalleled resolution and how the landscape of multipotent cells may be rather devoid of discrete structures, challenging our preconceptions about stem and progenitor cell types and their organization. Finally, we highlight how promising technological advances may convert static differentiation landscapes into a dynamic cell flux model and thus provide a more holistic understanding of normal hematopoiesis and blood disorders.
单细胞转录组学最近成为分析细胞异质性、发现新细胞类型和推断潜在分化途径的有力工具。该技术已被造血研究界迅速接受,就像之前的其他技术一样,单细胞分子谱分析有望为我们理解造血层次结构做出重要贡献。这种新的解释在很大程度上依赖于将转录组景观推断为现有细胞状态及其之间的相关转换的代表。在这里,我们回顾了该模型如何在某些假设下允许以无与伦比的分辨率绘制时分辨化轨迹,以及多能细胞的景观可能相当缺乏离散结构,这挑战了我们对干细胞和祖细胞类型及其组织的先入之见。最后,我们强调了有前途的技术进步如何将静态分化景观转化为动态细胞通量模型,从而提供对正常造血和血液疾病的更全面理解。