Year 2020, Volume 5, Issue 2
| Year : | 2020 |
| Volume : | 5 |
| Issue : | 2 |
| Authors : | Barbora OLŠANSKÁ, Radovan KASARDA, Kristína LEHOCKÁ, Nina MORAVČÍKOVÁ |
| Title : | DETECTION OF SELECTION SIGNALS IN CATTLE POPULATIONS BY PCA |
| Abstract : | The presented study provides a genome-wide scan of selection signals in cattle by principal component analysis (PCA). The aim was to identify SNP affected by intensive selection based on package PCAdapt implemented under software R. This analysis provided insight into the association between the SNP frequencies related to population differentiation. The four cattle populations were involved in the analysis (Slovak Spotted cattle, Ayrshire, Swiss Simmental and Holstein) with overall 272 of genotyped individuals. After applying quality control, the final dataset consisted of 35 675 SNPs, with an overall length of 2496.14 Mb and average space between adjacent SNP 70.03 ± 76.1 kb. After performing PCA analysis, the uniqueness of the breeds was revealed. On the other hand, a close genetic relationship and eleven SNPs affected by selection were found, with a position close to 162 genes involved in the various biological processes. The majority of genes were involved in the positive regulation of adenylate cyclase activity, embryo development and somatic diversification of immune receptors via somatic mutation. Several candidate genes for genetic control of the immune system (DNAJB9), muscle development (SEPT7, TRIM32, ROCK1, NRAP, PZDZ8, HSPA12A and FGFR2), milk production (SOCS5, CD46), reproduction (LHCGR, EEPD1, FSHR) and coat colour (KIT) were identified. Our results provide insights into the regions of the genome affected by the intensive selection of analysed cattle populations. |
| For citation : | Olšanská, B., Kasarda, R., Lehocká, K., Moravčíková, N. (2020). Detection of selection signals in cattle populations by PCA. AGROFOR International Journal, Volume 5. Issue No. 2. pp. 88-96. DOI:10.7251/AGRENG2002090O |
| Keywords : | biological process, Bos Taurus, footprints of selection, PCAdapt, production traits |
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ISSN 2490-3434 (Printed)
ISSN 2490-3442 (Online)
ISSN 2490-3442 (Online)
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