A statistical method for quantifying progenitor cells reveals incipient cell fate commitments

• Published in: Nature methods Vol. 21; no. 4; pp. 597 - 608
• Main Authors: Deng, Shanjun, Gong, Han, Zhang, Di, Zhang, Mengdong, He, Xionglei
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.04.2024; Nature Publishing Group
• Subjects: 631/114/2415; 631/114/739; 631/208/457; Animals; Bioinformatics; Biological Microscopy; Biological Techniques; Biomedical and Life Sciences; Biomedical Engineering/Biotechnology; Cell Differentiation - genetics; Cell Division; Cell fate; Cells (biology); Embryogenesis; Embryonic Development; Embryonic growth stage; Genes; Homeostasis; Life Sciences; Mathematical models; Mice; Phylogenetics; Phylogeny; Progenitor cells; Proteomics; Statistical analysis; Statistical methods; Statistics; Stem Cells; Tissues
• ISSN: 1548-7091; 1548-7105
• DOI: 10.1038/s41592-024-02189-7

Quantifying the number of progenitor cells that found an organ, tissue or cell population is of fundamental importance for understanding the development and homeostasis of a multicellular organism. Previous efforts rely on marker genes that are specifically expressed in progenitors. This strategy is, however, often hindered by the lack of ideal markers. Here we propose a general statistical method to quantify the progenitors of any tissues or cell populations in an organism, even in the absence of progenitor-specific markers, by exploring the cell phylogenetic tree that records the cell division history during development. The method, termed targeting coalescent analysis (TarCA), computes the probability that two randomly sampled cells of a tissue coalesce within the tissue-specific monophyletic clades. The inverse of this probability then serves as a measure of the progenitor number of the tissue. Both mathematic modeling and computer simulations demonstrated the high accuracy of TarCA, which was then validated using real data from nematode, fruit fly and mouse, all with related cell phylogenetic trees. We further showed that TarCA can be used to identify lineage-specific upregulated genes during embryogenesis, revealing incipient cell fate commitments in mouse embryos. Targeting coalescent analysis (TarCA) is a statistical method that quantifies the number of progenitor cells of a given population using single-cell phylogenetic data.