Abstract
Genome-wide association studies have identified thousands of genetic variants that are associated with disease 1 . Most of these variants have small effect sizes, but their downstream expression effects, so-called expression quantitative trait loci (eQTLs), are often large 2 and celltype-specific3-5. To identify these celltype-specific eQTLs using an unbiased approach, we used single-cell RNA sequencing to generate expression profiles of ~25,000 peripheral blood mononuclear cells from 45 donors. We identified previously reported cis-eQTLs, but also identified new celltype-specific cis-eQTLs. Finally, we generated personalized co-expression networks and identified genetic variants that significantly alter co-expression relationships (which we termed 'co-expression QTLs'). Single-cell eQTL analysis thus allows for the identification of genetic variants that impact regulatory networks.
Original language | English |
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Pages (from-to) | 493-497 |
Number of pages | 5 |
Journal | Nature Genetics |
Volume | 50 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2-Apr-2018 |
Keywords
- scRNA-seq
- eQTL
- co-expression QTL
- single-cell RNA-sequencing
- gene regulation
- DRIVERS
- PANEL
- GENE-EXPRESSION
- GENOTYPE IMPUTATION
- IMMUNE CELLS
- ASSOCIATIONS
- REGULATORS
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Additional file 9 of Correction for both common and rare cell types in blood is important to identify genes that correlate with age
Pellegrino Coppola, D. (Contributor), Claringbould, A. (Contributor), Stutvoet, M. (Creator), Boomsma, D. I. (Contributor), Ikram, M. A. (Contributor), Slagboom, P. E. (Contributor), Westra, H. J. (Contributor) & Franke, L. (Creator), figshare, 15-Mar-2021
DOI: 10.6084/m9.figshare.14220887, https://springernature.figshare.com/articles/dataset/Additional_file_9_of_Correction_for_both_common_and_rare_cell_types_in_blood_is_important_to_identify_genes_that_correlate_with_age/14220887
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