miRnomics Atlas

Genetic regulation of microRNAs

Genetic variants could influence the transcription and function of miRNAs, which may affect miRNA-mediated gene regulation and lead to phenotypes and diseases. Integration of genomics and miRNAs data enables interrogation of the genetic architecture of miRNAs, revealing their clinical importance, and providing valuable resources for future studies on clinical significance of miRNAs in human disease. Here we present the results of our genome-wide association studies on >2000 circulating miRNAs in plasma measured by RNA-sequencing in the Rotterdam Study. We report both cis and trans  miRNA-expression quantitative trait loci (miRNA-eQTLs) at the nominal significance level (p-value < 0.05) and those that have been replicated across two independent cohorts (see Ref). The consequences of perturbation in miRNA transcription on a wide range of clinical conditions are systematically investigated in phenome-wide association studies, with their causality tested using Mendelian randomization in the UK Biobank. Moreover, we found several miRNA-eQTLs overlaping with gene expression, protein, and metabolite-QTLs and with disease-associated variants reported in previous GWAS studies (see the disease association and omics integration parts).

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Cis-eQTL

Search for 1000 top cis-miRNA-eQTLs

miRNA

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Heritability

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Trans-eQTL

Search for 1000 top trans-miRNA-eQTLs

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SNP

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miRNA

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DataBase

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Here you are able to access the full summary statistics of a genome-wide association study (GWAS) conducted on plasma levels of 2083 miRNAs in the population-based Rotterdam Study cohort, which consists of 2178 participants. Additionally, we provide your access to the replication of our results in two independent cohorts. The data frame will include SNPs associated with miRNAs at a p-value threshold of less than 1E-5, after filtering out SNPs with an Rsq value higher than 0.7 and a minor allele frequency (MAF) greater than 0.05. In total, there will be 131,677 rows in this dataset.

To access the data, you can download cis-miR-eQTLs and trans-miR-eQTLs separately, or obtain all miR-eQTL data at once. The links to download the data and replication results in two independent cohorts will be provided on this website as soon as the paper is accepted (see the link to our paper below).

Citation

If you use the data on this website, please cite our paper: Mustafa R., (…), Ghanbari , M.; 2022; An atlas of genetic regulation and disease associations of microRNAs. medRxiv 2022.11.10.22282180

Contact

For questions, bug reports, or requests, please contact Mohsen Ghanbari (m.ghanbari@erasmusmc.nl) or Rima Mustafa (r.mustafa@imperial.ac.uk)

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