Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells
Open Access
- 5 March 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Genome Biology
- Vol. 22 (1), 1-19
- https://doi.org/10.1186/s13059-021-02293-3
Abstract
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. 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. 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.Keywords
This publication has 66 references indexed in Scilit:
- STAR: ultrafast universal RNA-seq alignerBioinformatics, 2012
- Matrix eQTL: ultra fast eQTL analysis via large matrix operationsBioinformatics, 2012
- Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analysesNature Protocols, 2012
- A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing dataBioinformatics, 2011
- Hotspots of aberrant epigenomic reprogramming in human induced pluripotent stem cellsNature, 2011
- Gene Expression in Skin and Lymphoblastoid Cells: Refined Statistical Method Reveals Extensive Overlap in cis-eQTL SignalsAmerican Journal of Human Genetics, 2010
- Cell type of origin influences the molecular and functional properties of mouse induced pluripotent stem cellsNature Biotechnology, 2010
- Understanding mechanisms underlying human gene expression variation with RNA sequencingNature, 2010
- edgeR: a Bioconductor package for differential expression analysis of digital gene expression dataBioinformatics, 2009
- Genetics of global gene expressionNature Reviews Genetics, 2006