Single-cell analysis reveals airway epithelial cell-specific expression quantitative trait loci in asthma

Abstract

Background Genome wide association studies (GWAS) in asthma have found many disease-associated Single Nucleotide Polymorphisms (SNPs) but their effects often remain unknown. Many GWAS SNPs affect gene expression, acting as expression quantitative trait loci (eQTLs). However, eQTL studies using tissue samples with variable cell type composition, like airway wall biopsies, cannot disentangle cell-type specific gene expression effects. Therefore, we tested if asthma GWAS loci carry cell-type specific eQTLs using single-cell RNA-sequencing (scRNA-seq) data.

Method We performed scRNA-seq analysis on bronchial biopsies from asthma patients (7), patients in remission (12) and healthy controls (15). Sequencing data were analyzed using Seurat. Single-cell (sc-)eQTL analysis was performed on genes in asthma loci or previously identified as eQTLs1 using SNPs within 50k bases from the start and end of the gene, per cell-type using MatrixQTL. Pseudo-bulk eQTL was performed using total counts per donor.

Result sc-eQTL analysis identified 108 significant (FDR < 0.05) interactions between SNPs and expression of 11 genes in asthma GWAS loci, in 4 out of 17 cell types tested. No significant interactions were identified in the pseudo-bulk eQTL analysis.

Conclusion We show that sc-eQTL analysis can detect cell-type specific eQTLs that are not identified in matching pseudo-bulk RNA-seq data. However, low gene expression values might result in false-positive associations in this small number of donors. Understanding these cell-type specific eQTLs is important to further explore how SNPs contribute to asthma by affecting gene expression.

1. El-Husseini et al. Lancet Respir. Med. 8, 1045–1056 (2020)