Polymorphisms in microRNA targets: a source of new molecular markers for male reproduction.

Herein we discuss the impact of microRNA (miRNA) target genetic variability in male infertility genes, which can represent a source of novel molecular-genetic markers that can be used for the diagnosis of male infertility. Male-factor infertility accounts for 30%–40% of infertility cases. The causes of spermatogenetic failure found in most cases of non-obstructive azoospermia or severe oligozoospermia still remain idiopathic. Significant progress has recently been made by utilizing small RNAs, e.g., small interfering RNAs, miRNAs and piwi-interacting RNAs, to elucidate the molecular mechanisms that regulate spermatogenesis. The miRNAs repress protein synthesis from targeted messenger RNAs (mRNAs) and control approximately 30% of human genes. Single-nucleotide polymorphisms (SNPs) of miRNA precursors and their target sites, as well as the silencing machinery, interfere with miRNA function and are likely to affect phenotypic variation, including disease susceptibility. The term miR-SNP refers to the variation that occurs in the miRNA gene sequence, whereas miR-TS-SNP refers to the SNP within the miRNA target site (TS) or binding site. miR-TS-SNPs have been associated with many diseases, including tumour susceptibility; however, mir-TS-SNPs have not yet been shown to affect male fertility. The aim of this study was to explore in silico genetic variability of 39UTR miRNA target sites of the selected (in)fertility related candidate genes to determine whether miR-TS-SNPs could represent a starting point for the discovery of novel genetic markers that affect male fertility phenotypes via miRNA regulation. This analysis was performed on the 34 candidate genes associated with this trait most frequently. Using online tools, the selected candidate human and mouse orthologs were analyzed for the following: (i) testicular expression levels obtained using BioGPS (Genomic Institute of the Novartis Research Foundation; GNF) (http://biogps.gnf.org/); (ii) conserved miRNA target sites using TargetScan (http://www.targetscan.org/); and (iii) polymorphic miRNA target sites using Patrocles (http://www.patrocles.org/). The results of the analyses are presented in Table 1. TargetScan, which predicts biological targets of miRNAs by searching for the presence of conserved sites across several species that match the miRNAs seed regions, revealed that more than two-thirds of the analyzed candidate genes in human (76%; 26/34) and mouse (68%; 23/34) genomes comprise conserved miRNA-binding sites. Candidate genes were further analyzed for miR-TS-SNPs within the 39-UTRs of human and mouse orthologs using Patrocles. The search revealed 55 and 33 miR-TS-SNPs in humans and mice, respectively. More than half (62%; 21/34) of the analyzed human candidate genes contained miR-TS-SNPs; the most polymorphic were KIT ligand (KITL, 12 SNPs), actin beta (ACTB, 5 SNPs), angiotensin I converting enzyme (peptidyl-dipeptidase A) 1 (ACE, 4 SNPs), calcium/calmodulin-dependent protein kinase IV (CAMK4, 4 SNPs), oestrogen receptor 1 (ESR1, 4 SNPs) and 5,10methylenetetrahydrofolate reductase (MTHFR, 4 SNPs) (Table 1). For example, the highly polymorphic 39-UTR of KITL spans a region of only 3740 bp; therefore, sequencing such a region could be highly informative in the context of discovering novel genetic markers. In mice, nearly half (41%; 14/34) of the genes contained miR-TS-SNP; the most polymorphic were prolactin receptor (PRLR, 7 SNPs), oestrogen receptor 1 (ESR1, 6 SNPs) and KIT ligand (KITL, 5 SNPs). Despite the known problem of a low overlap between the target prediction tools, TargetScan and Patrocles predicted several overlapping miRNA-target pairs: AKT1 (miR-25 and miR-32), DAZL (miR-1269), ESR1 (miR-211 and miR204) and RAD23A (miR-361-5p). However, predicted miRNA-mRNA pairs described in the present study have not been experimentally validated thus far, and the validation status of several SNPs is still unknown. Furthermore, predicted miR-TS-SNPs and conserved target sites were compared to an miRNA expression study performed in nonobstructive azoospermic patients and compared to fertile controls. Notably, it was possible to determine infertility-related miRNA-target pairs; Patrocles revealed miR-TS-SNPs in the analyzed candidates that are targeted by miRNAs previously reported as being either upor downregulated in azoospermic patients. There were miR-TS-SNPs for three upregulated miRNAs, miR-129-5p (having predicted polymorphic target site in DAZL), miR-302a (ESR1) and miR-557 (PRM2), as well as for 10 downregulated miRNAs, mir-31* (ACE), miR-32 (AKT1), miR-199b-5p (APRT), miR-153, miR-425, miR-448 (all in CREM), miR-515-5p (KITL), miR-363* (MTHFR), miR-31 (PRM1) and miR-374a* (RAD23A). Additionally, TargetScan predicted conserved target sites in human orthologs of infertility candidate genes for three upregulated miRNAs, miR-302a (predicted target in AKT1), miR-129-5p (CAMK4) and miR-557 (DAZL), as well as for 14 downregulated miRNAs, miR-145 (ACTB), miR-302d, miR-372, miR-373 (all in AKT1), miR-301b and miR-454 (both in AR), miR-1 (CREM), miR-548a-3p (DAZ-family), miR-548c-3p (DAZ-family and