Single-cell RNA sequencing identifies celltype-specific cis-eQTLs and co-expression QTLs
Genome-wide association studies have identified thousands of genetic variants that are associated with disease1. Most of these variants have small effect sizes, but their downstream expression effects, so-called expression quantitative trait loci (eQTLs), are often large and celltype-specific. 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.
To reference this project, please use the following link:
Supplementary links are provided by contributors and represent items such as additional data which can’t be hosted here; code that was used to analyze this data; or tools and visualizations associated with this specific dataset.
Downloaded and exported data is governed by the HCA Data Release Policy and licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). For more information please see our Data Use Agreement.
Analysis Portals
NoneProject Label
SingleCelleQTLCoexpressionAnalysisSpecies
Homo sapiens
Sample Type
specimens
Anatomical Entity
blood
Organ Part
Unspecified
Selected Cell Types
peripheral blood mononuclear cell
Disease Status (Specimen)
normal
Disease Status (Donor)
normal
Development Stage
human adult stage
Library Construction Method
10x 3' v2
Nucleic Acid Source
single cell
Paired End
falseAnalysis Protocol
analysis_protocol_cell_types, analysis_protocol_eQTL, analysis_protocol_eQTL_coexpression, analysis_protocol_gene_expressionFile Format
Cell Count Estimate
25.0kDonor Count
45