Copy number variation detection in sheep genome by using ovine BeadChip 50k
Abstract:
Introduction Recently, genomic research in livestock is focused on genomic variation and its effect on phenotypic performance in economic traits. Copy number variation (CNV) is one of these variations in genome including insertion, deletion and duplication of 1 kb to 1 Mb segment with more than 90% similarity. CNVs can change gene structure and dosage, can regulate gene expression and function and (1, 4). In mammals, it is important source of variability in genomes and it contains 0.4-25% of whole genome variation. Some researches carried out in livestock have been demonstrated that CNV affecting genes or gene regions are associated with several phenotypic traits. For example, CNV in intron 1 of the SOX5 gene causes the pea-comb phenotype in chicken. CNV affects also the Agouti locus in sheep and goats and contributes to the variability of coat color in these two species. The late feathering locus in this avian species includes a partial duplication of the PRLR and SPEF2 genes and Dominant white locus in pigs includes alleles determined by duplications of the KIT gene (2, 5, 6). In spite of, many researches carried out in human represent association between CNV with both complex genetic diseases and traits; however, far too little attention has been paid to CNV in farm animal. This paper will focused on detecting of CNV in sheep genome.
Materials and method The sheep genomic DNA was extracted from blood of 360 Italian ewes using DNA Purification kit (Promega Corporation, Madison, WI). Markers were genotyped by Illumina ovineSNP50 BeadChip according to instructions. It is containing 54,241 markers that uniformly span the entire ovine genome (Illumina, Inc., USA). After completion of the assay, the BeadChips were scanned with a two-color, confocal Bead Array reader. Scanned image intensities were loaded directly into Illumina’s BeadStudio 1.2 software. When normalization was completed, the clustering process was performed to assess cluster position for each marker and to determine individual genotypes. LRR and BAF of sample were reported. The PFB file was calculated based on the BAF of each marker in these populations. The sheep GC model file was generated by calculating the GC content of the1 Mb genomic region surrounding each marker (500 Kb each side). CNVs were inferred using a PennCNV (http: //www.openbioinformatics. org/penncnv/). Penn CNV quality filters were applied after CNV detection. High quality samples with a standard deviation (SD) of LRR
Language:
Persian
Published:
Iranian Journal of Animal Science Reaserch, Volume:8 Issue: 3, 2017
Page:
489
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