Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data
Shuang Li1,2,3, Katharina T Schmid4,5, Dylan H de Vries1
1Genetics Department, University Medical Center Groningen, Groningen, the Netherlands.
Genome Biology
|April 18, 2023
Summary
This study identifies genetic variants that alter gene co-expression patterns (co-eQTLs) in single cells, revealing new insights into autoimmune disease mechanisms. A specific variant (rs1131017) impacts T cell gene regulation, offering potential therapeutic targets.
Area of Science:
- Genomics
- Immunology
- Systems Biology
Background:
- Expression quantitative trait loci (eQTL) studies link genetic variants to gene expression.
- Single-cell RNA sequencing (scRNA-seq) enables personalized co-expression network reconstruction.
- Identifying SNPs that alter co-expression patterns (co-eQTLs) is crucial for understanding regulatory processes.
Conclusions:
- Context-specific gene regulation is vital for understanding genetic variation's biological impact.
- The developed strategy and guidelines will aid future sc-eQTL studies.
- Findings offer potential explanations for rs1131017's association with autoimmune diseases and suggest therapeutic targets.
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