Genome‐wide in silico screening for microRNA genetic variability in livestock species. (19th July 2013)

• Record Type: Journal Article
• Authors: Jevsinek Skok, D.; Godnic, I.; Zorc, M.; Horvat, S.; Dovc, P.; Kovac, M.; Kunej, T.
• Is Part Of: Animal genetics. Volume 44:Number 6(2013:Dec.)
• Page Start: 669
• Page End: 677
• Publication Date: 2013-07-19
• Subjects: cattle -- chicken -- pig -- horse -- double nucleotide polymorphism (DNP) -- prioritization -- seed region -- single nucleotide polymorphism (SNP) -- phenotypic traits -- genetic markers; Animal genetics -- Periodicals; 572.8
• DOI: 10.1111/age.12072
• Languages: English
• ISSNs: 0268-9146

Abstract

Summary: 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 usingmirna 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.