| Title: |
Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data |
| Authors: |
Shuang Li; Katharina T. Schmid; Dylan H. de Vries; Maryna Korshevniuk; Corinna Losert; Roy Oelen; Irene V. van Blokland; BIOS Consortium, sc-eQTLgen Consortium; Hilde E. Groot; Morris A. Swertz; Pim van der Harst; Harm-Jan Westra; Monique G.P. van der Wijst; Matthias Heinig; Lude Franke |
| Source: |
Genome Biology, Vol 24, Iss 1, Pp 1-37 (2023) |
| Publisher Information: |
BMC |
| Publication Year: |
2023 |
| Collection: |
Directory of Open Access Journals: DOAJ Articles |
| Subject Terms: |
Co-expression QTLs; scRNA-seq; eQTL; Biology (General); QH301-705.5; Genetics; QH426-470 |
| Description: |
Background Expression quantitative trait loci (eQTL) studies show how genetic variants affect downstream gene expression. Single-cell data allows reconstruction of personalized co-expression networks and therefore the identification of SNPs altering co-expression patterns (co-expression QTLs, co-eQTLs) and the affected upstream regulatory processes using a limited number of individuals. Results We conduct a co-eQTL meta-analysis across four scRNA-seq peripheral blood mononuclear cell datasets using a novel filtering strategy followed by a permutation-based multiple testing approach. Before the analysis, we evaluate the co-expression patterns required for co-eQTL identification using different external resources. We identify a robust set of cell-type-specific co-eQTLs for 72 independent SNPs affecting 946 gene pairs. These co-eQTLs are replicated in a large bulk cohort and provide novel insights into how disease-associated variants alter regulatory networks. One co-eQTL SNP, rs1131017, that is associated with several autoimmune diseases, affects the co-expression of RPS26 with other ribosomal genes. Interestingly, specifically in T cells, the SNP additionally affects co-expression of RPS26 and a group of genes associated with T cell activation and autoimmune disease. Among these genes, we identify enrichment for targets of five T-cell-activation-related transcription factors whose binding sites harbor rs1131017. This reveals a previously overlooked process and pinpoints potential regulators that could explain the association of rs1131017 with autoimmune diseases. Conclusion Our co-eQTL results highlight the importance of studying context-specific gene regulation to understand the biological implications of genetic variation. With the expected growth of sc-eQTL datasets, our strategy and technical guidelines will facilitate future co-eQTL identification, further elucidating unknown disease mechanisms. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
https://doi.org/10.1186/s13059-023-02897-x; https://doaj.org/toc/1474-760X; https://doaj.org/article/785668752d91453b926ccaf37a7d957d |
| DOI: |
10.1186/s13059-023-02897-x |
| Availability: |
https://doi.org/10.1186/s13059-023-02897-x; https://doaj.org/article/785668752d91453b926ccaf37a7d957d |
| Accession Number: |
edsbas.5D2E17C2 |
| Database: |
BASE |