Quantifying Waddington's epigenetic landscape: a comparison of single-cell potency measures
2020-01
Source PublicationBRIEFINGS IN BIOINFORMATICS
ISSN1467-5463
EISSN1477-4054
Volume21Issue:1Pages:248-261
Status已发表
DOI10.1093/bib/bby093
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.

Keywordsingle-cell RNA-Seq entropy differentiation potency network Waddington
URL查看原文
Indexed BySCIE
Language英语
WOS Research AreaBiochemistry & Molecular Biology ; Mathematical & Computational Biology
WOS SubjectBiochemical Research Methods ; Mathematical & Computational Biology
WOS IDWOS:000516610800019
PublisherOXFORD UNIV PRESS
Original Document TypeArticle
Citation statistics
Document Type期刊论文
Identifierhttps://kms.shanghaitech.edu.cn/handle/2MSLDSTB/243343
Collection生命科学与技术学院
生命科学与技术学院_特聘教授组_陈洛南组
Corresponding AuthorTeschendorff, Andrew E.; Chen, Luonan; Li, Tiejun
Affiliation
1.Peking Univ, Sch Math Sci, Beijing 100871, Peoples R China;
2.CAS MPG Partner Inst Computat Biol, Shanghai, Peoples R China;
3.UCL, London, England;
4.Chinese Acad Sci, Key Lab Syst Biol, Shanghai, Peoples R China;
5.Shanghai Inst Biol Sci, Shanghai, Peoples R China
6.School of Life Science and Technology, ShanghaiTech University, Shanghai 20121
Corresponding Author AffilicationSchool of Life Science and Technology
Recommended Citation
GB/T 7714
Shi, Jifan,Teschendorff, Andrew E.,Chen, Weiyan,et al. Quantifying Waddington's epigenetic landscape: a comparison of single-cell potency measures[J]. BRIEFINGS IN BIOINFORMATICS,2020,21(1):248-261.
APA Shi, Jifan,Teschendorff, Andrew E.,Chen, Weiyan,Chen, Luonan,&Li, Tiejun.(2020).Quantifying Waddington's epigenetic landscape: a comparison of single-cell potency measures.BRIEFINGS IN BIOINFORMATICS,21(1),248-261.
MLA Shi, Jifan,et al."Quantifying Waddington's epigenetic landscape: a comparison of single-cell potency measures".BRIEFINGS IN BIOINFORMATICS 21.1(2020):248-261.
Files in This Item: Download All
File Name/Size DocType Version Access License
Related Services
Usage statistics
Scholar Google
Similar articles in Scholar Google
[Shi, Jifan]'s Articles
[Teschendorff, Andrew E.]'s Articles
[Chen, Weiyan]'s Articles
Baidu academic
Similar articles in Baidu academic
[Shi, Jifan]'s Articles
[Teschendorff, Andrew E.]'s Articles
[Chen, Weiyan]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Shi, Jifan]'s Articles
[Teschendorff, Andrew E.]'s Articles
[Chen, Weiyan]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 10.1093@bib@bby093.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.