Quantifying Waddington's epigenetic landscape: a comparison of single-cell potency measures. (5th October 2018)

• Record Type: Journal Article
• Authors: Shi, Jifan; Teschendorff, Andrew E; Chen, Weiyan; Chen, Luonan; Li, Tiejun
• Is Part Of: Briefings in bioinformatics. Volume 21:Number 1(2020)
• Page Start: 248
• Page End: 261
• Publication Date: 2018-10-05
• Subjects: single-cell RNA-Seq -- entropy -- differentiation -- potency -- network -- Waddington; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bby093
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: Motivation: Estimating differentiation potency of single cells is a task of great biological and clinical significance, as it may allow identification of normal and cancer stem cell phenotypes. However, very few single-cell potency models have been proposed, and their robustness and reliability across independent studies have not yet been fully assessed. Results: Using nine independent single-cell RNA-Seq experiments, we here compare four different single-cell potency models to each other, in their ability to discriminate cells that ought to differ in terms of differentiation potency. Two of the potency models approximate potency via network entropy measures that integrate the single-cell RNA-Seq profile of a cell with a protein interaction network. The comparison between the four models reveals that integration of RNA-Seq data with a protein interaction network dramatically improves the robustness and reliability of single-cell potency estimates. We demonstrate that underlying this robustness is a correlation relationship, according to which high differentiation potency is positively associated with overexpression of network hubs. We further show that overexpressed network hubs are strongly enriched for ribosomal mitochondrial proteins, suggesting that their mRNA levels may provide a universal marker of a cell's potency. Thus, this study provides novel systems-biological insight into cellular potency and may provide a foundation for improved models of differentiation potency with far-reaching implications for the discovery of novel stem cell or progenitor cell phenotypes.