Comprehensive Cis-Regulation Analysis of Genetic Variants in Human Lymphoblastoid Cell Lines

Variants in Candidate Genes for Phenotype Heterogeneity in Patients with the 22q11.2 Deletion Syndrome

22q11.2 deletion syndrome (22q11.2DS) is a microdeletion syndrome with a broad and heterogeneous phenotype, even though most of the deletions present similar sizes, involving ∼3 Mb of DNA. In a relatively large population of a Brazilian 22q11.2DS cohort (60 patients), we investigated genetic variants that could act as genetic modifiers and contribute to the phenotypic heterogeneity, using a targeted NGS (Next Generation Sequencing) with a specific Ion AmpliSeq panel to sequence nine candidate genes (CRKL, MAPK1, HIRA, TANGO2, PI4KA, HDAC1, ZDHHC8, ZFPM2, and JAM3), mapped in and outside the 22q11.2 hemizygous deleted region. In silico prediction was performed, and the whole-genome sequencing annotation analysis package (WGSA) was used to predict the possible pathogenic effect of single nucleotide variants (SNVs). For the in silico prediction of the indels, we used the genomic variants filtered by a deep learning model in NGS (GARFIELD-NGS). We identified six variants, 4 SNVs and 2 indels, in MAPK1, JAM3, and ZFPM2 genes with possibly synergistic deleterious effects in the context of the 22q11.2 deletion. Our results provide the opportunity for the discovery of the co-occurrence of genetic variants with 22q11.2 deletions, which may influence the patients´ phenotype.

Integration of Candida albicans-induced single-cell gene expression data and secretory protein concentrations reveal genetic regulators of inflammation

Both gene expression and protein concentrations are regulated by genetic variants. Exploring the regulation of both eQTLs and pQTLs simultaneously in a context- and cell-type dependent manner may help to unravel mechanistic basis for genetic regulation of pQTLs. Here, we performed meta-analysis of Candida albicans-induced pQTLs from two population-based cohorts and intersected the results with Candida-induced cell-type specific expression association data (eQTL). This revealed systematic differences between the pQTLs and eQTL, where only 35% of the pQTLs significantly correlated with mRNA expressions at single cell level, indicating the limitation of eQTLs use as a proxy for pQTLs. By taking advantage of the tightly co-regulated pattern of the proteins, we also identified SNPs affecting protein network upon Candida stimulations. Colocalization of pQTLs and eQTLs signals implicated several genomic loci including MMP-1 and AMZ1. Analysis of Candida-induced single cell gene expression data implicated specific cell types that exhibit significant expression QTLs upon stimulation. By highlighting the role of trans-regulatory networks in determining the abundance of secretory proteins, our study serve as a framework to gain insights into the mechanisms of genetic regulation of protein levels in a context-dependent manner.

Common Polymorphism That Protects From Cardiovascular Disease Increases Fibronectin Processing and Secretion

BACKGROUND

Fibronectin (FN1) is an essential regulator of homodynamic processes and tissue remodeling that have been proposed to contribute to atherosclerosis. Moreover, recent large-scale genome-wide association studies (GWAS) have linked common genetic variants within the FN1 gene to coronary artery disease risk.

METHODS

Public databases were analyzed by 2-Sample Mendelian Randomization. Expression constructs encoding short FN1 reporter constructs and full-length plasma FN1 variants were introduced in various cell models. Secreted and cellular levels were then analyzed and quantified by SDS-PAGE and fluorescence microscopy. Mass spectrometry and glycosylation analyses were performed to probe possible posttranscriptional differences.

RESULTS

Bioinformatic analyses revealed that common coronary artery disease risk single nucleotide polymorphisms in the FN1 locus associate with circulating levels of FN1 and that higher FN1 (fibronectin 1) protein levels in plasma are linked to lower coronary artery disease risk. The coronary artery disease-associated FN1 locus encompasses a common polymorphism that translates a L15Q variant situated within the FN1 signal peptide. Introduction of FN1 reporter constructs, differing at position 15, revealed differences in secretion, with the FN1 Q15 variant being less well secreted. Moreover, the L15Q polymorphism was found to alter glycosylation in some cell models but not in human plasma.

CONCLUSIONS

In addition to providing novel functional evidence implicating FN1 in cardioprotection, these findings demonstrate that a common variant within a secretion signal peptide regulates protein function.

Tissue-specific multi-omics analysis of atrial fibrillation

Genome-wide association studies (GWAS) for atrial fibrillation (AF) have uncovered numerous disease-associated variants. Their underlying molecular mechanisms, especially consequences for mRNA and protein expression remain largely elusive. Thus, refined multi-omics approaches are needed for deciphering the underlying molecular networks. Here, we integrate genomics, transcriptomics, and proteomics of human atrial tissue in a cross-sectional study to identify widespread effects of genetic variants on both transcript (cis-eQTL) and protein (cis-pQTL) abundance. We further establish a novel targeted trans-QTL approach based on polygenic risk scores to determine candidates for AF core genes. Using this approach, we identify two trans-eQTLs and five trans-pQTLs for AF GWAS hits, and elucidate the role of the transcription factor NKX2-5 as a link between the GWAS SNP rs9481842 and AF. Altogether, we present an integrative multi-omics method to uncover trans-acting networks in small datasets and provide a rich resource of atrial tissue-specific regulatory variants for transcript and protein levels for cardiovascular disease gene prioritization.