Integration of other omics with miRNAs
miRNAs have a crucial role in regulating biological processes by modulating the expression of target genes (mRNAs). Hence, it is of great interest to investigate whether genetic variations within miRNAs (miRNA-eQTLs) are associated with the expression of coding genes, including both their host and target genes. To explore this relationship comprehensively, we conducted an extensive analysis to identify overlaps between miRNA-eQTLs and other omics layers, such as gene expression (eQTLs), protein levels (pQTLs), and metabolite levels (mQTLs) in blood/plasma.
For our analysis, we utilized summary statistics from a previous large-scale study (N=31,684) that examined genetic variants influencing mRNA transcript levels, encompassing both cis and trans-eQTLs, in whole blood. These statistics enabled us to identify miRNA-eQTLs that impact the expression of other genes. Furthermore, we obtained summary statistics for protein-QTL analyses (pQTLs) from the work by Sun et al. (https://www.phpc.cam.ac.uk/ceu/proteins/) and the SCALLOP consortium (https://zenodo.org/record/2615265/). To identify miRNA-eQTLs affecting metabolic pathways, we leveraged summary statistics from GWAS studies on plasma levels of metabolites. This included over 500 metabolites analyzed in the Metabolon platform by Shin et al. (N=7,824) and nearly 250 metabolites in the Nightingale platform by Kettunen et al. (N>20,000), and data from the UK Biobank study (N=115,078).
Search all data using a miRNA ID
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Here, you can access the complete summary statistics from our genome-wide association study (GWAS) conducted on plasma levels of miRNAs within the population-based Rotterdam Study cohort, where we have linked these miRNA-eQTLs to the blood/plasma expression of genes, proteins, and metabolites by integrating QTLs data.
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