Genetic variants associated with cell-type-specific intra-individual gene expression variability reveal mechanisms of genome regulation

Gene expression varies substantially across cells, even within seemingly homogeneous populations. Understanding how genetic variation influences this variability is critical for elucidating mechanisms of genome regulation, yet the genetic control of cell-to-cell expression variability remains poorly characterised. Here, we introduce MEOTIVE (Mapping genetic Effects On inTra-Individual Variability of gene Expression), a statistical framework that identifies genetic effects on gene expression variability (sc-veQTLs) while modelling mean-variance dependence. Applying MEOTIVE to single-cell RNA-seq data from 1.2 million peripheral blood mononuclear cells across 980 donors in the OneK1K cohort, we identify 14–3,488 genes with significant sc-veQTLs across blood cell types, including 2,103 shared across multiple cell types. We further detect 55 SNP-gene pairs (34 genes) associated with gene expression dispersion (sc-deQTLs), enriched for immune and viral response pathways; 32 of these associations remain significant after additional adjustment for mean expression. Notably, rs1131017 in the 5′UTR of RPS26 is associated with widespread expression dispersion across cell types and reduced autoimmune disease risk. We also identify a monocyte-specific deQTL in LYZ (rs1384), which replicates in an independent cohort. MEOTIVE provides a robust framework for mapping the genetic regulation of gene-expression variability at single-cell resolution and reveals pathways linking cellular heterogeneity to autoimmune disease risk. Using over 1.2 million single immune cells, the authors identify genetic variants that influence cell-to-cell variation in gene expression, revealing a previously hidden layer of genome regulation associated with immune function and autoimmune disease.

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Publication Details

Journal
Nature Communications
Published
2026-09-21
DOI
https://doi.org/10.1038/s41467-026-77453-9
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Genetic variants associated with cell-type-specific intra-individual gene expression variability reveal mechanisms of genome regulation

Seyhan Yazar, Chun Jimmie Ye, Angli Xue, Alex William Hewitt et al.
Nature Communications
Single-cell and spatial transcriptomics
article

Genetic variants associated with cell-type-specific intra-individual gene expression variability reveal mechanisms of genome regulation

Seyhan Yazar, Chun Jimmie Ye, Angli Xue, Alex William Hewitt, M. Grace Gordon, José Alquicira-Hernández, Joseph E. Powell, Anne Senabouth, Anna S. E. Cuomo, Pooja Kathail
article en

Abstract

Gene expression varies substantially across cells, even within seemingly homogeneous populations. Understanding how genetic variation influences this variability is critical for elucidating mechanisms of genome regulation, yet the genetic control of cell-to-cell expression variability remains poorly characterised. Here, we introduce MEOTIVE (Mapping genetic Effects On inTra-Individual Variability of gene Expression), a statistical framework that identifies genetic effects on gene expression variability (sc-veQTLs) while modelling mean-variance dependence. Applying MEOTIVE to single-cell RNA-seq data from 1.2 million peripheral blood mononuclear cells across 980 donors in the OneK1K cohort, we identify 14–3,488 genes with significant sc-veQTLs across blood cell types, including 2,103 shared across multiple cell types. We further detect 55 SNP-gene pairs (34 genes) associated with gene expression dispersion (sc-deQTLs), enriched for immune and viral response pathways; 32 of these associations remain significant after additional adjustment for mean expression. Notably, rs1131017 in the 5′UTR of RPS26 is associated with widespread expression dispersion across cell types and reduced autoimmune disease risk. We also identify a monocyte-specific deQTL in LYZ (rs1384), which replicates in an independent cohort. MEOTIVE provides a robust framework for mapping the genetic regulation of gene-expression variability at single-cell resolution and reveals pathways linking cellular heterogeneity to autoimmune disease risk. Using over 1.2 million single immune cells, the authors identify genetic variants that influence cell-to-cell variation in gene expression, revealing a previously hidden layer of genome regulation associated with immune function and autoimmune disease.

Nature Communications
Brigham and Women's Hospital (US), University of Tasmania (AU), Harvard University (US), Garvan Institute of Medical Research (AU), The University of Queensland (AU), University of California, San Francisco (US), UNSW Sydney (AU), Parker Institute for Cancer Immunotherapy (US), Institute for Molecular Bioscience (AU)
Openalex Percentile: Top 18%
Single-cell and spatial transcriptomics
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