Single-cell eQTL analysis of activated T cell subsets reveals activation and cell type-dependent effects of disease-risk variants

活化 T 细胞亚群的单细胞 eQTL 分析揭示了疾病风险变异的活化和细胞类型依赖性效应

阅读:3
作者:Benjamin J Schmiedel, Cristian Gonzalez-Colin, Vicente Fajardo, Job Rocha, Ariel Madrigal, Ciro Ramírez-Suástegui, Sourya Bhattacharyya, Hayley Simon, Jason A Greenbaum, Bjoern Peters, Grégory Seumois, Ferhat Ay, Vivek Chandra, Pandurangan Vijayanand

Abstract

The impact of genetic variants on cells challenged in biologically relevant contexts has not been fully explored. Here, we activated CD4+ T cells from 89 healthy donors and performed a single-cell RNA sequencing assay with >1 million cells to examine cell type-specific and activation-dependent effects of genetic variants. Single-cell expression quantitative trait loci (sc-eQTL) analysis of 19 distinct CD4+ T cell subsets showed that the expression of over 4000 genes is significantly associated with common genetic polymorphisms and that most of these genes show their most prominent effects in specific cell types. These genes included many that encode for molecules important for activation, differentiation, and effector functions of T cells. We also found new gene associations for disease-risk variants identified from genome-wide association studies and highlighted the cell types in which their effects are most prominent. We found that biological sex has a major influence on activation-dependent gene expression in CD4+ T cell subsets. Sex-biased transcripts were significantly enriched in several pathways that are essential for the initiation and execution of effector functions by CD4+ T cells like TCR signaling, cytokines, cytokine receptors, costimulatory, apoptosis, and cell-cell adhesion pathways. Overall, this DICE (Database of Immune Cell Expression, eQTLs, and Epigenomics) subproject highlights the power of sc-eQTL studies for simultaneously exploring the activation and cell type-dependent effects of common genetic variants on gene expression (https://dice-database.org).

特别声明

1、本文转载旨在传播信息,不代表本网站观点,亦不对其内容的真实性承担责任。

2、其他媒体、网站或个人若从本网站转载使用,必须保留本网站注明的“来源”,并自行承担包括版权在内的相关法律责任。

3、如作者不希望本文被转载,或需洽谈转载稿费等事宜,请及时与本网站联系。

4、此外,如需投稿,也可通过邮箱info@biocloudy.com与我们取得联系。