Laboratory of Systems Biology and Genetics, Institute of Bioengineering and Swiss Institute of Bioinformatics, CH-1015, Lausanne, Switzerland.
ISREC (Swiss Institute for Experimental Cancer Research), School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015, Lausanne, Switzerland.
Stem Cells. 2017 Dec;35(12):2390-2402. doi: 10.1002/stem.2719. Epub 2017 Nov 6.
A long-standing question in biology is whether multipotent somatic stem and progenitor cells (SSPCs) feature molecular properties that could guide their system-independent identification. Population-based transcriptomic studies have so far not been able to provide a definite answer, given the rarity and heterogeneous nature of these cells. Here, we exploited the resolving power of single-cell RNA-sequencing to develop a computational model that is able to accurately distinguish SSPCs from differentiated cells across tissues. The resulting classifier is based on the combined expression of 23 genes including known players in multipotency, proliferation, and tumorigenesis, as well as novel ones, such as Lcp1 and Vgll4 that we functionally validate in intestinal organoids. We show how this approach enables the identification of stem-like cells in still ambiguous systems such as the pancreas and the epidermis as well as the exploration of lineage commitment hierarchies, thus facilitating the study of biological processes such as cellular differentiation, tissue regeneration, and cancer. Stem Cells 2017;35:2390-2402.
生物学中长期存在的一个问题是，多能体干细胞和祖细胞（SSPCs）是否具有可以指导其系统独立识别的分子特性。鉴于这些细胞的稀有性和异质性，基于群体的转录组研究迄今为止还无法提供明确的答案。在这里，我们利用单细胞 RNA 测序的分辨率来开发一种计算模型，该模型能够准确地区分组织中的 SSPCs 和分化细胞。由此产生的分类器基于 23 个基因的组合表达，包括多能性、增殖和肿瘤发生中的已知参与者，以及新的参与者，如我们在肠类器官中功能验证的 Lcp1 和 Vgll4。我们展示了这种方法如何能够识别仍存在模糊系统（如胰腺和表皮）中的干细胞样细胞，以及探索谱系决定层次结构，从而促进对细胞分化、组织再生和癌症等生物学过程的研究。Stem Cells 2017;35:2390-2402.
