Assessing footprints of natural selection through PCA analysis in cattle

Abstract

Received: 2016-05-24 | Accepted: 2016-07-28 | Available online: 2017-06-20
http://dx.doi.org/10.15414/afz.2017.20.01.23-27

The aim of this study was to determine the population structure and to perform genome-wide scan of footprints of natural selection in cattle using principal component analysis. The applied statistics to identify the SNPs associated with selection pressure focused mainly on the extreme values of F_ST index. In our study the alternative individual-based approach adopted in the PCAdapt R package has been used. This approach is based on the assumption that markers extremely related to the population structure are also candidates for local adaptation of the population. The genotype data of 350 animals originating from four historically or geographically connected populations (Austrian Pinzgau, Slovak Pinzgau, Brown Swiss, Tyrol Grey) have been used to test this approach in cattle. As expected based on breed's origin the principal component analysis showed the division of animals in to the 3 separate clusters and the eigenvalues suggested to use of K=3 as optimal number. The analysis of genomic regions harbouring signals revealed the candidate genes previously associated with muscle formation and immunity system. Detecting signals of adaptation that were also the targets of historical selection will allow in the future a better understanding of cattle origin.

Keywords: local adaptation, selection, cattle, SNP50 BeadChip, PCAdapt, population subdivision

References

AKEY, J. M. et al. (2002) Interrogating a high-density SNP map for signatures of natural selection. Genome Research, vol. 12, pp. 1805-1814. doi:http://dx.doi.org/10.1101/gr.631202

ALLENDORF, F. W., HOHENLOHE, P. A. and LUIKART, G. (2010) Genomics and the future of conservation genetics. Nature Reviews Genetics, vol. 11, no. 10, pp. 697-709. doi:http://dx.doi.org/10.1038/nrg2844

BIERNE, N., ROZE, D. and WELCH, J. J. (2013) Pervasive selection or is it . . .? Why are F_ST outliers sometimes so frequent?. Molecular Ecology, vol. 22, pp. 2061-2064. doi:http://dx.doi.org/10.1111/mec.12241

DRUET, T. et al. (2013). Identification of large selective sweeps associated with major genes in cattle. Animal Genetics, vol. 44, pp. 758-762. doi:http://dx.doi.org/10.1111/age.12073

DUFORET-FREBOURG, N. et al. (2015) Detecting genomic signatures of natural selection with principal component analysis: application to the 1000 genomes data. Molecular biology and evolution, vol. 33, pp. 1082-1093. doi:http://dx.doi.org/10.1093/molbev/msv334

DUFORET-FREBOURG, N., BAZIN, E. and BLUM, M. G. B. (2014) Genome scans for detecting footprints of local adaptation using a bayesian factor model. Molecular biology and evolution, vol. 31, pp. 2483-2495. doi:http://dx.doi.org/10.1093/molbev/msu182

FERENČAKOVIĆ, M., SOLKNER, J. and CURIK, I. (2013) Estimating autozygosity from high-throughput information: effects of SNP density and genotyping errors. Genetic Selection Evolution, vol. 45, no. 1, pp. 42. doi:http://dx.doi.org/10.1186/1297-9686-45-42

Flori, L. et al. (2009) The genome response to artificial selection: a case study in dairy cattle. PLoS One, vol. 4, e6595. doi:http://dx.doi.org/10.1371/journal.pone.0006595

GIUSTI, J. et al. (2013) Expression of genes related to quality of Longissimus dorsi muscle meat in Nellore (Bos indicus) and Canchim (5/8 Bos taurus × 3/8 Bos indicus) cattle. Meat Science, vol. 94, no. 2, pp. 247-252. doi:http://dx.doi.org/10.1016/j.meatsci.2013.02.006

GOWANE, G. R. et al. (2014) The Expression of IL6 and 21 in Crossbred Calves Upregulated by Inactivated Trivalent FMD Vaccine. Animal Biotechnology, vol. 25, no. 2, pp. 108-118. doi:http://dx.doi.org/10.1080/10495398.2013.834826

GUTIÉRREZ-GIL, B., ARRANZ, J. J. and WIENER, P. (2015) An interpretive review of selective sweep studies in Bos taurus cattle populations: identification of unique and shared selection signals across breeds. Frontiers genetics, vol. 6, pp. 167. doi:http://dx.doi.org/10.3389/fgene.2015.00167

LUU, K., BAZIN, E. and BLUM, M. G. B. (2016) pcadapt: An R package for performing genome scans for selection based on principal component analysis. bioRxiv. doi:http://dx.doi.org/10.1101/056135

MANCINI, G. et al. (2014) Signatures of selection in five Italian cattle breeds detected by a 54K SNP panel. Molecular Biology Reports, vol. 41, pp. 957-965. doi:http://dx.doi.org/10.1007/s11033-013-2940-5

MARTINS, H. et al. (2016) Identifying outlier loci in admixed and in continuous populations using ancestral population differentiation statistics. bioRxiv, p. 054585. doi:http://dx.doi.org/10.1101/054585

MCCLURE, M. C. et al. (2012) Genome-wide association analysis for quantitative trait loci influencing Warner–Bratzler shear force in five taurine cattle breeds. Animal Genetics, vol. 43, no. 6, pp. 662-673. doi:http://dx.doi.org/10.1111/j.1365-2052.2012.02323.x

NIELSEN, R. (2005) Molecular signatures of natural selection. Annual Review of Genetics, vol. 39, pp. 197-218. doi:http://dx.doi.org/10.1146/annurev.genet.39.073003.112420

NOVEMBRE, J. et al. (2008) Genes mirror geography within Europe. Nature, vol. 456, pp. 98-101. doi:http://dx.doi.org/10.1038/nature07566

OLEKSYK, T. K., SMITH, M. W. and O'BRIEN, S. J. (2010) Genome-wide scan for footprints of natural selection. Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 365, pp. 185-205. doi:http://dx.doi.org/10.1098/rstb.2009.0219

QANBARI, S. et al. (2011) Application of site and haplotype-frequency based approaches for detecting selection signatures in cattle. BMC Genomics, vol. 12, pp. 318. doi:http://dx.doi.org/10.1186/1471-2164-12-318

STELLA, A. et al. (2010) Identification of selection signatures in cattle breeds selected for dairy production. Genetics, vol. 185, pp. 1451-1461. doi:http://dx.doi.org/10.1534/genetics.110.116111

STOREY, J. D. (2002) A direct approach to false discovery rates. Journal of the Royal Statistical Society, Series B, vol. 64, pp. 479-498. doi:http://dx.doi.org/10.1111/1467-9868.00346

WAPLES, R. S. and GAGGIOTTI, O. (2006) What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity. Molecular Ecology, vol. 15, pp. 1419-1439. doi:http://dx.doi.org/10.1111/j.1365-294x.2006.02890.x

WEIR, B. S. et al. (2005). Measures of human population structure show heterogeneity among genomic regions. Genome Research, vol. 15, no. 11, pp. 1468-1476. doi:http://dx.doi.org/10.1101/gr.4398405

ZHAO, F. et al. (2015) Detection of selection signatures in dairy and beef cattle using high-density genomic information. Genetic Selection Evolution, vol.  47, pp. 49. doi:http://dx.doi.org/10.1186/s12711-015-0127-3