•  Home
  • Library
  • DRO home
Submit research Contact DRO

DRO

Openly accessible

Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells

Neavin, D, Nguyen, Q, Daniszewski, MS, Liang, HH, Chiu, HS, Wee, YK, Senabouth, A, Lukowski, SW, Crombie, DE, Lidgerwood, GE, Hernández, D, Vickers, JC, Cook, AL, Palpant, NJ, Pébay, A, Hewitt, AW and Powell, JE 2021, Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells, Genome Biology, vol. 22, pp. 1-19, doi: 10.1186/s13059-021-02293-3.


Title Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells
Author(s) Neavin, D
Nguyen, Q
Daniszewski, MS
Liang, HH
Chiu, HS
Wee, YK
Senabouth, A
Lukowski, SW
Crombie, DE
Lidgerwood, GE
Hernández, D
Vickers, JC
Cook, AL
Palpant, NJ
Pébay, A
Hewitt, AW
Powell, JE
Journal name Genome Biology
Volume number 22
Article ID 76
Start page 1
End page 19
Total pages 19
Publisher BioMed Central
Place of publication London, Eng.
Publication date 2021
ISSN 1474-7596
1474-760X
Keyword(s) Science & Technology
Life Sciences & Biomedicine
Biotechnology & Applied Microbiology
Genetics & Heredity
Expression quantitative trait loci (eQTLs)
Single cell RNA-sequencing (scRNA-seq)
Induced pluripotent stem cells (iPSCs)
Summary Background: The discovery that somatic cells can be reprogrammed to induced pluripotent stem cells (iPSCs) has provided a foundation for in vitro human disease modelling, drug development and population genetics studies. Gene expression plays a critical role in complex disease risk and therapeutic response. However, while the genetic background of reprogrammed cell lines has been shown to strongly influence gene expression, the effect has not been evaluated at the level of individual cells which would provide significant resolution. By integrating single cell RNA-sequencing (scRNA-seq) and population genetics, we apply a framework in which to evaluate cell type-specific effects of genetic variation on gene expression. Results: Here, we perform scRNA-seq on 64,018 fibroblasts from 79 donors and map expression quantitative trait loci (eQTLs) at the level of individual cell types. We demonstrate that the majority of eQTLs detected in fibroblasts are specific to an individual cell subtype. To address if the allelic effects on gene expression are maintained following cell reprogramming, we generate scRNA-seq data in 19,967 iPSCs from 31 reprogramed donor lines. We again identify highly cell type-specific eQTLs in iPSCs and show that the eQTLs in fibroblasts almost entirely disappear during reprogramming. Conclusions: This work provides an atlas of how genetic variation influences gene expression across cell subtypes and provides evidence for patterns of genetic architecture that lead to cell type-specific eQTL effects.
Language eng
DOI 10.1186/s13059-021-02293-3
Field of Research 05 Environmental Sciences
06 Biological Sciences
08 Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30164048

Document type: Journal Article
Collections: Faculty of Health
School of Medicine
Open Access Collection
Related Links
Link Description
Link to full-text (open access)  
Connect to Elements publication management system
Go to link with your DU access privileges
 
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 5 times in TR Web of Science
Scopus Citation Count Cited 7 times in Scopus Google Scholar Search Google Scholar
Access Statistics: 10 Abstract Views  -  Detailed Statistics
Created: Thu, 10 Mar 2022, 07:06:50 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.