Using immune cell type-specific gene backgrounds for refined GO enrichment analysis: an example from CD4 T cell transcriptomics of TB-infected individuals

Abstract

Abstract Gene Set Enrichment Analysis (GSEA) and its special case of GO enrichment analysis is a common step in biologically interpretation of gene lists resulting from –omics experiments. A known but under-appreciated aspect of any GSEA is the use of a background gene list, e.g. by discarding genes generally not expressed in the investigated cell type. We recently developed a web-application for interactive GO analysis of gene/protein signatures named GOnet (https://tools.dice-database.org/GOnet/). Within its framework we utilized DICE-DB (https://dice-database.org/) expression data of 15 blood cell types to allow analyzing gene signatures versus genes expressed in these cell types. To validate our approach, we applied GOnet to analyze a 74-gene transcriptomic signature of latent TB infection obtained by RNA-seq of CD4 memory T cells (Burel et al, 2018). Limiting the analysis to the background of genes expressed in CD4 T cells introduces significant differences in GO enrichment analysis results. Firstly, the category of “regulation of immunological synapse formation” is no longer enriched. As immunological synapse genes are very specific for T cells, without background correction this category can very easily seem ‘enriched’. Secondly, a more specific background renders a category of “positive regulation of MAPK cascade” significant. The latter category highlights important regulators contained in the signature. Overall we believe that using baseline gene sets based on immune cell types expression profiles is an important advancement to regular GO enrichment analysis in immunology studies, and by making relevant backgrounds readily available in GOnet, applying them becomes easier for immunologists.