Genetic architecture of microRNA expression: implications for the transcriptome and complex traits

Abstract

We sought to comprehensively and systematically characterize the relationship between genetic variation, miRNA expression, and mRNA expression. Genome-wide expression profiling of samples of European and African ancestry identified in each population hundreds of miRNAs whose increased expression is correlated with correspondingly reduced expression of target mRNAs. We scanned 3' UTR SNPs with a potential functional effect on miRNA binding for cis-acting expression quantitative trait loci (eQTLs) for the corresponding proximal target genes. To extend sequence-based, localized analyses of SNP effect on miRNA binding, we proceeded to dissect the genetic basis of miRNA expression variation; we mapped miRNA expression levels-as quantitative traits-to loci in the genome as miRNA eQTLs, demonstrating that miRNA expression is under significant genetic control. We found that SNPs associated with miRNA expression are significantly enriched with those SNPs already shown to be associated with mRNA. Moreover, we discovered that many of the miRNA-associated genetic variations identified in our study are associated with a broad spectrum of human complex traits from the National Human Genome Research Institute catalog of published genome-wide association studies. Experimentally, we replicated miRNA-induced mRNA expression inhibition and the cis-eQTL relationship to the target gene for several identified relationships among SNPs, miRNAs, and mRNAs in an independent set of samples; furthermore, we conducted miRNA overexpression and inhibition experiments to functionally validate the miRNA-mRNA relationships. This study extends our understanding of the genetic regulation of the transcriptome and suggests that genetic variation might underlie observed relationships between miRNAs and mRNAs more commonly than has previously been appreciated.

Figure 1

Distribution of the p Values for the Association between a Potential Confounder and miRNA Expression Level in the HapMap CEU LCLs (A) A Q-Q plot of the p values for the association between intrinsic cellular-growth rate (generated from a mixed-effects modeling of cellular proliferation) and miRNA expression level shows that cellular proliferation is not associated with miRNA expression levels. (B) A Q-Q plot of the p values for the association between EBV copy number and miRNA expression level shows one miRNA reaching significance in association with EBV copy number. (C) To test for the presence of significant EBV confounding, we performed permutation analyses and generated a Q-Q plot for each of 1,000 replicates (shown as gray dots) and for the actual data (shown as blue dots); we demonstrate that the observed off-diagonal phenomenon (shown in Figure 1B) is within what is expected by chance.

Figure 2

A Schematic Diagram of the Analysis (A) Genome-wide analysis for the identification of SNPs located in the 3′ UTR of potential miRNA targets. (B) Genome-wide evaluation of SNP-miRNA-mRNA relationships.

Figure 3

Discovered and Replicated 3′ UTR SNPs that Potentially Affect miRNA Binding to the Corresponding Gene (A and E) The relationship between rs4240334 genotype and GYPE expression in the discovery (CEU I/II) and replication (CEU III) samples, respectively. (B and F) The negative correlation between the expression of miR-185 and of GYPE in the discovery CEU I/II and replication CEU III samples, respectively. (C and G) The relationship between rs16990301 genotype and SLC23A2 expression in the discovery (YRI I/II) and replication (YRI III) samples, respectively. (D and H) The negative correlation between the expression of miR-30d and of SLC23A2 in the discovery YRI I/II and replication YRI III samples, respectively. Exiqon and Exon arrays were used for obtaining miRNA and gene-expression data, whereas real-time PCR was used for the quantification of miRNA and mRNA expression in the replication samples.

Figure 4

Effect of miRNA Mimic and Inhibitor on the Expression of miR-30d and Target Gene SLC23A2 miR-30d is represented in (A), and SLC23A2 is represented in (B). These experiments were performed in a randomly selected LCL sample (GM18861). The x axis describes the type of experiment. The y axis illustrates the percent change in expression level when compared to scramble control in each experiment either for miRNAs or for target genes.

Figure 5

The Chromosomal Location of miRNA-Expression-Associated SNPs A miRNA-associated SNP in CEU samples is denoted by a red line, whereas that in YRI samples is denoted by a blue line. All SNPs shown here meet the criteria p < 1 × 10⁻⁸ with miRNA expression.

Figure 6

miRNA eQTLs Are Significantly Enriched with mRNA eQTLs The histogram shows the empirical distribution from 1,000 sets of allele-frequency-matched SNPs. The black dot represents the observed overlap count. This plot illustrates the enrichment of mRNA-associated SNPs in miRNA eQTLs in CEU samples (p < 0.001).

Figure 7

A Comparison of the Distribution of the Explained-Variance Score between the Observed Data and Simulated Data Note that we observed a higher explained-variance score (M_G) compared to what was expected.

Figure 8

Discovered and Replicated Relationships between SNPs, miRNA, and mRNA (A and B) The relationship between the rs10022802 genotype and CHPT1 expression in the CEU I/II discovery (A) and CEU III replication (B) samples. (C and D) The positive correlation between miR-378 and KCNIP2 expression in the discovery (C) and replication (D) YRI samples.