4 years ago

Cross-Tissue Identification Of Somatic Stem And Progenitor Cells Using A Single-Cell RNA-Seq Derived Gene Signature

Cross-Tissue Identification Of Somatic Stem And Progenitor Cells Using A Single-Cell RNA-Seq Derived Gene Signature
Joerg Huelsken, Petra C. Schwalie, Bart Deplancke, Paloma Ordonez Moran
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. This article is protected by copyright. All rights reserved. Schematic representation of the developed stem and progenitor cell identification (SSPCI) approach: for any single-cell transcriptome of unknown status (grey), SSPCI, the lasso logistic regression-based classifier that we developed, predicts whether it has stem and progenitor cell characteristics (blue) or not (orange).

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/stem.2719

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