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MicroRNAs (miRNAs) are a class of non-coding RNA that plays an important role in posttranscriptional regulation of mRNA. Evidence has shown that miRNA gene variability might interfere with its function resulting in phenotypic variation and disease susceptibility. A major role in miRNA target recognition is ascribed to complementarity with the miRNA seed region that can be affected by polymorphisms. In the present study, we developed an online tool for the detection of miRNA polymorphisms (miRNA SNiPer) in vertebrates (http://www.integratomics-time.com/miRNA-SNiPer) and generated a catalog of miRNA seed region polymorphisms (miR-seed-SNPs) consisting of 149 SNPs in six species. Although a majority of detected polymorphisms were due to point mutations, two consecutive nucleotide substitutions (double nucleotide polymorphisms, DNPs) were also identified in nine miRNAs. We determined that miR-SNPs are frequently located within the quantitative trait loci (QTL), chromosome fragile sites, and cancer susceptibility loci, indicating their potential role in the genetic control of various complex traits. To test this further, we performed an association analysis between the mmu-miR-717 seed SNP rs30372501, which is polymorphic in a large number of standard inbred strains, and all phenotypic traits in these strains deposited in the Mouse Phenome Database. Analysis showed a significant association between the mmu-miR-717 seed SNP and a diverse array of traits including behavior, blood-clinical chemistry, body weight size and growth, and immune system suggesting that seed SNPs can indeed have major pleiotropic effects. The bioinformatics analyses, data and tools developed in the present study can serve researchers as a starting point in testing more targeted hypotheses and designing experiments using optimal species or strains for further mechanistic studies.[1]
MicroRNAs are a class of non-coding RNAs that post-transcriptionally regulate target gene expression. Previous studies have shown that microRNA gene variability can interfere with its function, resulting in phenotypic variation. Polymorphisms within microRNA genes present a source of novel biomarkers for phenotypic traits in animal breeding. However, little is known about microRNA genetic variability in livestock species, which is also due to incomplete data in genomic resource databases. Therefore, the aim of this study was to perform a genome-wide in silico screening of genomic sources and determine the genetic variability of microRNA genes in livestock species using mirna sniper 3.0 (http://www.integratomics-time.com/miRNA-SNiPer/), a new version of our previously developed tool. By examining Ensembl and miRBase genome builds, it was possible to design a tool-based generated search of 16 genomes including four livestock species: pig, horse, cattle and chicken. The analysis revealed 65 polymorphisms located within mature microRNA regions in these four species, including 28% within the seed region in cattle and chicken. Polymorphic microRNA genes in cattle and chicken were further examined for mapping to quantitative trait loci regions associated with production and health traits. The developed bioinformatics tool enables the analysis of polymorphic microRNA genes and prioritization of potential regulatory polymorphisms and therefore contributes to the development of microRNA-based biomarkers in livestock species. The assembled catalog and the developed tool can serve the animal science community to efficiently select microRNA SNPs for further quantitative and molecular genetic evaluations of their phenotypic effects and causal associations with livestock production traits.[2]
