Open AccessCross‐Tissue Identification of Somatic Stem and Progenitor Cells Using a Single‐Cell RNA‐Sequencing Derived Gene Signature
Author(s) -
Schwalie Petra C.,
OrdóñezMorán Paloma,
Huelsken Joerg,
Deplancke Bart
Publication year - 2017
Publication title -
stem cells
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.159
H-Index - 229
eISSN - 1549-4918
pISSN - 1066-5099
DOI - 10.1002/stem.2719
Subject(s) - biology , stem cell , progenitor cell , transcriptome , somatic cell , cellular differentiation , carcinogenesis , microbiology and biotechnology , cancer stem cell , adult stem cell , population , computational biology , gene , gene expression , genetics , demography , sociology
Abstract 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. S tem C ells 2017;35:2390–2402