Mapping dynamic regulation of gene expression using single-cell transcriptomics and application to complex disease genetics.

ABSTRACT: Single-cell transcriptome data can provide insights into how genetic variation influences biological processes involved in human physiology and disease. However, the identification of gene-level associations in distinct cell types faces several challenges, including the limited reference resources from population-scale studies, data sparsity in single-cell RNA sequencing, and the complex cell state pattern of expression within individual cell types. Here, we develop genetic models of cell-type-specific and cell-state-adjusted gene expression in mid-brain neurons undergoing differentiation from induced pluripotent stem cells. The resulting framework quantifies the dynamics of the genetic regulation of gene expression and estimates its cell-type specificity. As an application, we show that t

SUBMITTER: Abe H 

PROVIDER: S-EPMC11830375 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature