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And Trans-Regulatory Variation Modulating Microrna Expression Levels in Human Fibroblasts Downloaded from genome.cshlp.org on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press Research Identification of cis- and trans-regulatory variation modulating microRNA expression levels in human fibroblasts Christelle Borel,1 Samuel Deutsch,1 Audrey Letourneau, Eugenia Migliavacca, Stephen B. Montgomery, Antigone S. Dimas,2 Charles E. Vejnar, Homa Attar, Maryline Gagnebin, Corinne Gehrig, Emilie Falconnet, Yann Dupre´, Emmanouil T. Dermitzakis, and Stylianos E. Antonarakis3 Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva 1211, Switzerland MicroRNAs (miRNAs) are regulatory noncoding RNAs that affect the production of a significant fraction of human mRNAs via post-transcriptional regulation. Interindividual variation of the miRNA expression levels is likely to influence the expression of miRNA target genes and may therefore contribute to phenotypic differences in humans, including susceptibility to common disorders. The extent to which miRNA levels are genetically controlled is largely unknown. In this report, we assayed the expression levels of miRNAs in primary fibroblasts from 180 European newborns of the GenCord project and performed association analysis to identify eQTLs (expression quantitative traits loci). We detected robust expression for 121 miRNAs out of 365 interrogated. We have identified significant cis- (10%) and trans- (11%) eQTLs. Furthermore, we detected one genomic locus (rs1522653) that influences the expression levels of five miRNAs, thus unraveling a novel mechanism for coregulation of miRNA expression. [Supplemental material is available online at http://www.genome.org. The miRNA expression data from this study has been submitted to the NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) under accession no. GSE24610. The genotyping data from this study have been submitted to the EMBL-EBI European Genome-phenome Archive (http://www.ebi.ac.uk/ega/) under accession no. EGAS00000000056.] The discovery of microRNAs (miRNAs) (19- to 25-nt-long single- Recent genetic analyses have demonstrated that transcription stranded RNA molecules) has revealed a new mechanism for the levels of protein-coding genes behave as heritable quantitative regulation of protein-coding gene expression (Ambros 2004; Bartel traits and display significant associations with genetic variants, 2004; Baek et al. 2008; Selbach et al. 2008). Dosage alterations of including single nucleotide polymorphisms (SNPs) and copy num- miRNA levels are thought to be involved in human disease path- ber variants (CNVs) (Morley et al. 2004; Cheung et al. 2005; Deutsch ogenesis (Bartel 2004; Kloosterman and Plasterk 2006; Bushati and et al. 2005; Stranger et al. 2007; Dermitzakis 2008). Cohen 2007; Bartel 2009; Xiao and Rajewsky 2009). One of the In this study, we conducted an association analysis using least understood aspects of miRNA biogenesis concerns the regu- mature miRNA expression levels as the primary phenotype, with lation of its expression levels. Approximately half of the miRNAs the aim of identifying regulatory polymorphic variants (expres- identified to date are located in intergenic regions and are there- sion quantitative traits loci [eQTLs]) significantly associated with fore likely to possess their own promoter and enhancer elements. miRNA expression levels in human primary fibroblasts. The remaining miRNAs map to introns of protein-coding genes and are transcribed from the same strand (Saini et al. 2008). How- Results ever, it is not yet clear whether these miRNAs are the by-products of protein-coding gene transcription or whether their transcrip- Primary fibroblasts were derived from the umbilical cord of 180 tion is controlled by independent regulatory elements. Since newborns of western European origin recruited for the GenCord miRNA genes are transcribed by RNA polymerase II, it is likely project (see Methods). All samples were genotyped using the Illu- that they share a similar mode of regulation with protein-coding mina Hap550 SNP array. Mature miRNA expression phenotypes mRNAs. were generated using the micro-fluidics-based TaqMan Human The goal of this study was to identify genetic variation asso- MiRNA Array v1.0 (Applied Biosystems). For each sample, the ciated with miRNA levels, as a way to dissect the elements and expression levels for 365 known human mature miRNAs were mechanisms governing miRNA expression. assayed (Supplemental Table S1). We detected expression above the background for 57% (n = 208) of the miRNAs in cultured pri- mary fibroblasts. These were further filtered to include miRNAs with expression above the background in at least 50% of the 1These authors contributed equally to this work. 2Present address: Wellcome Trust Centre for Human Genetics, samples (n = 90). One hundred twenty-one miRNAs were retained Oxford OX3 7BN, UK. for association analysis. 3 Corresponding author. We identified cis-eQTLs, by testing for association between E-mail [email protected]. Article published online before print. Article and publication date are at expression levels and SNP genotypes, within 1 Mb 59 and 39 of each http://www.genome.org/cgi/doi/10.1101/gr.109371.110. miRNA. SNPs were considered to be significantly associated with 21:000–000 Ó 2011 by Cold Spring Harbor Laboratory Press; ISSN 1088-9051/11; www.genome.org Genome Research 1 www.genome.org Downloaded from genome.cshlp.org on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press Borel et al. miRNA expression levels (i.e., eQTLs) if they passed the 0.05 per- levels of all miRNAs (preserving the miRNA expression matrix mutation level threshold for 10,000 permutations (see Methods). per individual) and performed GWAS for each permuted data set. Twelve (i.e., 10%) of the 121 miRNAs tested showed signifi- From this, we estimated the empirical significance of our master cant evidence for cis-regulatory variation (permutated P-value < regulator to be equal to 0.005 (Fig. 3; see Methods). 0.05) (Table 1A; Fig. 1; Supplemental Fig. S1). Given that we tested Remarkably, rs1522653 is an intergenic SNP, located in a large 121 miRNAs and we expect 5% of them to have significant cis- gene desert (3.29 Mb with no annotated protein-coding or non- associations by chance at the permutation level 0.05, we estimate coding RNAs); the nearest gene, FAM181B, maps 1.59 Mb away that our false-discovery rate (FDR) is about 50% of the 12 miRNA (Supplemental Fig. S2). The identification of regulatory variants signals. associated with the expression levels of multiple miRNAs may Examples of these cis-eQTLs are shown in Figure 1. The most point to potential ‘‘master regulatory’’ properties and suggests that highly significant cis-eQTL detected was rs10750218, intronic to the expression levels of groups of miRNAs may be coordinated UBASH3B, which associates with levels of miR-100 533 kb away through the use of common regulatory elements. This hypothesis (Fig. 1). The distance between the cis-eQTLs and their respective predicts that the five miRNAs associated with rs1522653 should miRNA was variable and ranged from 13.6 kb to 886 kb (Table 1A). display related expression profiles. To test this hypothesis, we In one case (miR-218-1), cis-eQTLs mapped within the protein- compared the average of the correlation values of the five miRNAs coding sequences of SLIT2 that also contain the miRNA sequence. associated with rs1522653 to 10,000 sets of five randomly selected This raises the interesting question of whether both the miR-218-1 miRNAs. We found that the observed average correlation of 0.44 and the SLIT2 mRNA share regulatory sequences (Table 1). To ad- is higher than that expected by chance (permutated P-value of dress this, we investigated whether the specific cis-eQTL for the 0.0012) (Supplemental Fig. S3). We also examined whether the miRNA was also associated with SLIT2 mRNA levels. Transcrip- predicted target transcripts of the five miRNAs associated with a tion levels of protein-coding genes were assayed using Illumina’s master regulator share molecular functions. We investigated Gene WG-6 v3 Expression BeadChip array (Dimas et al. 2009). We found Ontology (GO) terms from computational target predictions of the no evidence of shared regulatory variation between mRNA and five coregulated miRNAs (miRanda [John et al. 2004] from the miRNA, and no correlation between the miR-218-1 and SLIT2 miRBase-Targets database [Griffiths-Jones et al. 2008]). This anal- mRNA levels was observed (Pearson correlation = À0.023, n = 55), ysis revealed that the mRNA targets for these five miRNAs are sig- implyingabsenceofcoregulationofthesetwotranscriptsin nificantly enriched for ‘‘protein-binding process’’ (P = 4.4 3 10À8, fibroblasts. Fisher’s exact test), ‘‘transcription regulator activity’’ (P = 7.8 3 We then aimed to identify trans-eQTLs by performing a ge- 10À8), and ‘‘transcription factor activity’’ (P = 1.2 3 10À6) (Sup- nome-wide association study (GWAS) for the 121 miRNA expres- plemental Table S3). sion phenotypes. We observed 18 significant trans-eQTLs for 13 We therefore propose a model in which certain eQTLs act miRNAs (10.7%) after Bonferroni correction for multiple testing as master regulators by comodulating the expression of multiple at the 95% significance level (Table 1B; Supplemental Fig. S2). miRNAs, thus revealing a novel mechanism for coregulation of Since under the null hypotheses we would expect on average six miRNA expression. associations, we can estimate our FDR at about 30%
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