Novel Single Cell Experimental Approach Links 127 Genes to Immune Diseases

June 13, 2022

From GWAS to Function

Genome-wide association studies (GWAS) can robustly identify genetic variants that correlate with a given trait or disease, but have next to no power to identify the biological function of those variants and whether or not they are causative in any way. However, disease-associated variants found in GWAS are primarily in more active regions of the genome, suggesting dynamic changes to gene expression regulation.

The effects of gene expression regulation can then be linked to genetic variants using expression quantitative trait loci (eQTLs). However, these are often applied in bulk tissues and thus fail to identify cell-type specific or more transient changes in expression that occur. Luckily, this problem is rectified with the use of single cell sequencing, where the higher resolution gives these studies more power to identify biological targets and mechanisms that may be responsible for observed patterns.

Genetic Variants, Immune Diseases and CD4+ T Cell Activation

It is common to find genetic variants associated with immune-related diseases at higher prevalence in the enhancer and promoter regions that are upregulated when CD4+ T cell activation occurs. But even within the CD4+ T cell family, there are cellular subtypes and extensive heterogeneity that makes it challenging to interpret why variants in these regions may influence disease susceptibility.

To tackle this challenge, researchers from the Wellcome Sanger Institute in Cambridge, UK mapped gene expression regulation using single-cell transcriptomics across four distinct time points of CD4+ T cell activation to capture the full, dynamic process and cellular heterogeneity.

Single Cell T Cell Analysis Links Disease-Associated Variants to Function

The study, published in Nature Genetics last month, is the first of its kind, co-localizing the eQTL gene expression regulation signatures with disease-associated variants from GWAS. From 65,349 cells, they found 2,265 genes that were dynamically regulated during T cell activation. Of those genes, 127 were found to be regulated by genetic variants associated with immune-mediated diseases.

The results paint a new picture of dysregulation of T cell activation as a standout feature of immune-related diseases, and highlights the importance of studying cell and context-specific changes to gene expression to understand the mechanisms underlying disease.

Outsourcing Bioinformatics Analysis

In spite of how useful single cell approaches are, interpreting single cell RNA-seq data is a challenging computational and bioinformatic task. Outsourcing your bioinformatic analysis to experts like our team at Bridge Informatics helps eliminate common challenges with these projects. Book a free discovery call with us today to discuss your project needs.

Jane Cook, Journalist & Content Writer, Bridge Informatics

Jane is a Content Writer at Bridge Informatics, a professional services firm that helps biotech customers implement advanced techniques in management and analysis of genomic data. Bridge Informatics focuses on data mining, machine learning, and various bioinformatic techniques to discover biomarkers and companion diagnostics. If you’re interested in reaching out, please email or


T cell illustration

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