Genetic variation in correlated regulatory region of Immunity

Abstract

AbstractStudying the interplay between genetic variation, epigenetic changes and regulation of gene expression in immune cells is important to understand the modification of cellular states in various conditions, including immune diseases. Here, we built cis maps of regulatory regions with coordinated activity – Cis Regulatory Domains (CRDs) – in neutrophils, monocytes and T cells. For this, we leveraged (i) whole-genome sequencing (WGS), (ii) chromatin immunoprecipitation sequencing (ChIP-seq), (iii) DNA methylation (450k arrays), and (iv) transcriptional profiles (RNA-seq) from the BLUEPRINT consortium, for up to 200 individuals.Our study uncovers 9287, 7666 and 5480 histone CRDs (hCRDs) and 6053, 6112, 5701 methyl CRDs (mCRDs) in monocytes, neutrophils and T-cells, respectively. We discovered 15294 hCRD-gene and 6185 mCRD-gene associations (5% FDR). Only 33% of hCRD-gene associations and 37% of mCRD-gene associations were shared between cell-types, revealing the dynamic nature of regulatory interactions and how similarly located regulatory regions modulate the activity of different genes on different cell types. We mapped Quantitative Trait Loci associated with CRD activity (CRD-QTLs) and found that 89% and 70% of these hCRDs and mCRDs are under genetic control highlighting the importance of genetic variation to study the coordination of cellular regulatory programs. We found CRD-QTLs to be enriched in celltype-specific transcription factor binding sites, such as SPI1, STAT3, RFX1, SOX4, ATF3 for neutrophils and monocytes and TCF4 and BCL11A for T-cells, in line with the Human protein Atlas.We integrated PCHi-C data, which showed that most significant associations discovered within gene-CRD associations and co-expressed genes associated with the same CRD, involving large genomic distances, tend to happen between genomic regions in close spatial proximity. Finally, we mapped trans regulatory associations between CRDs, which enabled the discovery of 207 trans-eQTLs across cell types. Overlapping our hits with trans eQTLs from eQTLGen Consortium meta-analysis in whole blood revealed 52 trans-eQTLs shared between the two studies. Overall, we show that mapping functional regulatory units using population genomics data allows discovering important mechanisms in the regulation of gene expression in immune cells and gain a greater understanding of cell-type specific regulatory mechanisms of immunity.