Jifan Shi1, Andrew E Teschendorff2, Weiyan Chen3, Luonan Chen4, Tiejun Li1. 1. School of Mathematical Sciences, Peking University, Beijing, China. 2. University College London. 3. Shanghai Institutes for Biological Sciences, Shanghai, China. 4. Key Lab for Systems Biology, Chinese Academy of Sciences, Shanghai, China.
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.
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.
Authors: Florian Halbritter; Matthias Farlik; Raphaela Schwentner; Gunhild Jug; Nikolaus Fortelny; Thomas Schnöller; Hanja Pisa; Linda C Schuster; Andrea Reinprecht; Thomas Czech; Johannes Gojo; Wolfgang Holter; Milen Minkov; Wolfgang M Bauer; Ingrid Simonitsch-Klupp; Christoph Bock; Caroline Hutter Journal: Cancer Discov Date: 2019-07-25 Impact factor: 39.397