distQTL: Distribution Quantitative Trait Loci Identification by Population-Scale Single-Cell Data.

Area of Science:

• Genomics
• Transcriptomics
• Systems Biology

Background:

• Expression quantitative trait loci (eQTL) mapping links genetic variation to gene expression.
• Bulk eQTL methods average expression, masking cell-specific regulatory heterogeneity.
• Single-cell eQTL (sc eQTL) methods offer higher resolution but require advanced analytical approaches.

Purpose of the Study:

• To introduce and validate a novel method, distribution QTLs (distQTLs), for identifying genetic influences on gene expression using single-cell RNA sequencing data.
• To leverage Fréchet regression for analyzing full empirical distributions of gene expression, moving beyond traditional summary statistics.
• To compare the performance of distQTLs against existing eQTL methods in a large-scale population cohort.

Main Methods:

• Application of Fréchet regression to population-scale single-cell RNA sequencing (scRNA-seq) data from the OneK1K cohort (982 donors).
• Comparison of distQTL results with summary statistics-based eQTLs and mixed-effects modeling approaches.
• Orthogonal validation of distQTL findings using cell-type-specific epigenomic profiles.

Main Results:

• The distQTL method demonstrates superior performance across various gene expression contexts compared to traditional eQTL approaches.
• Benchmarking against the Genotype-Tissue Expression Project (GTEx) confirms the robustness and accuracy of distQTL calls.
• Validation using epigenomic data supports the biological relevance of distQTL identified genetic associations.

Conclusions:

• Distribution QTLs (distQTLs) represent a significant advancement in dissecting transcriptional regulation at single-cell resolution.
• The Fréchet regression-based distQTL approach effectively captures gene expression heterogeneity influenced by genetic variation.
• This method provides a powerful tool for understanding the genetic architecture of gene expression in complex biological systems.