Single-cell eQTL mapping identifies cell type-specific genetic control of autoimmune disease.
Seyhan YazarJose Alquicira HernandezKristof WingAnne SenabouthM Grace GordonStacey AndersenQinyi LuAntonia RowsonThomas R P TaylorLinda ClarkeKatia MaccoraChristine ChenAnthony L CookChun Jimmie YeKirsten A FairfaxAlex W HewittJoseph E PowellPublished in: Science (New York, N.Y.) (2022)
The human immune system displays substantial variation between individuals, leading to differences in susceptibility to autoimmune disease. We present single-cell RNA sequencing (scRNA-seq) data from 1,267,758 peripheral blood mononuclear cells from 982 healthy human subjects. For 14 cell types, we identified 26,597 independent cis-expression quantitative trait loci (eQTLs) and 990 trans-eQTLs, with most showing cell type-specific effects on gene expression. We subsequently show how eQTLs have dynamic allelic effects in B cells that are transitioning from naïve to memory states and demonstrate how commonly segregating alleles lead to interindividual variation in immune function. Finally, using a Mendelian randomization approach, we identify the causal route by which 305 risk loci contribute to autoimmune disease at the cellular level. This work brings together genetic epidemiology with scRNA-seq to uncover drivers of interindividual variation in the immune system.
Keyphrases
- single cell
- genome wide
- rna seq
- dna methylation
- gene expression
- endothelial cells
- high throughput
- multiple sclerosis
- copy number
- drug induced
- poor prognosis
- high resolution
- induced pluripotent stem cells
- pluripotent stem cells
- working memory
- electronic health record
- mesenchymal stem cells
- machine learning
- binding protein
- cell therapy
- big data
- mass spectrometry