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Conservation Genetics

, Volume 18, Issue 4, pp 893–910 | Cite as

Genomic characterization of Pinzgau cattle: genetic conservation and breeding perspectives

  • Veronika Kukučková
  • Nina Moravčíková
  • Maja Ferenčaković
  • Mojca Simčič
  • Gábor Mészáros
  • Johann Sölkner
  • Anna Trakovická
  • Ondrej Kadlečík
  • Ino Curik
  • Radovan Kasarda
Research Article

Abstract

A genome-wide scan of Slovak Pinzgau cattle was prepared for the first time in order to estimate their genetic diversity at a more detailed level compared to previously published studies. The aim of this study was to describe the genetic diversity based on the runs of homozygosity (ROHs), linkage disequilibrium (LD) and effective population size (NeLD) using genome-wide data. Moreover, Bayesian clustering algorithms and multivariate methods were used to detect the population structure, potential admixture level and relationship between Austrian and Slovak Pinzgau cattle with respect to a large meta-population consisting of 15 European cattle breeds. The proportion of ROH segments ranged from 0.43 to 1.91% in Slovak Pinzgau, depending on the minimum size of an ROH. The genomic inbreeding coefficients were higher than the pedigree ones possibly due to the limited number of available generations in pedigree data. The observed NeLD was close to the limit value characterizing the endangerment status, based both on genomic and pedigree data. Population structure within analyzed breeds based on the Wright’s FST index, Nei’s genetic distances, and unsupervised as well as supervised analysis has been established. Overall, these analyses clearly distinguished populations based on their origin. A detailed analysis of the introgression of each breed into the Pinzgau breeds prepared using a Bayesian approach showed that the contribution of Holstein cattle in Austrian as well as Slovak Pinzgau was larger than contribution of beef breeds. A possible reason is the recent usage of Holstein sires to increase milk production. There are considerable differences between well-defined regions that clearly distinguish Austrian and Slovak Pinzgau, despite their close common history. Generally, the breeding program of Austrian Pinzgau is more focused on meat production than Slovak Pinzgau, which was clearly reflected in the obtained autozygosity islands. Considering the genetic establishment of Slovak Pinzgau population the genetic potential of the breed is insufficiently used. On a long term, more global breeding program including very close populations will be more efficient providing higher genetic progress and diversity. Established methodology how to distinguish genealogically close populations on high-throughput molecular information based of Slovak and Austrian Pinzgau can be proposed as general for analysis of differences in all highly related breeds.

Keywords

Autozygosity BovineSNP50 BeadChip Genetic distance Linkage disequilibrium Effective population size 

Notes

Acknowledgements

Thanks to anonymous reviewers that constructively improved final version of this manuscript.

Funding

This study was supported by the Slovak Research and Development Agency under the Contract no. APVV-0636-11 and APVV-14-0054.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10592_2017_935_MOESM1_ESM.zip (967 kb)
Supplementary material 1 (ZIP 966 KB)

References

  1. Barbato M, Orozco-terWengel P, Tapio M, Bruford MW (2015) SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data. Front Genet 6:109. doi: 10.3389/fgene.2015.00109 CrossRefPubMedPubMedCentralGoogle Scholar
  2. Barendse W, Harrison B, Bunch R, Thomas M, Turner L (2009) Genome wide signatures of positive selection: The comparison of independent samples and the identification of regions associated to traits. BMC Genom 10(1):178. doi: 10.1186/1471-2164-10-178 CrossRefGoogle Scholar
  3. Baumung R, Simianer H, Hoffmann I (2004) Genetic diversity studies in farm animals—a survey. J Anim Breed Genet 121(6):361–373. doi: 10.1111/j.1439-0388.2004.00479.x CrossRefGoogle Scholar
  4. Beghain J, Boitard S, Weiss B, Boussaha M, Gut I, Rocha D (2012) Genome wide linkage disequilibrium in the Blonde d’Aquitaine cattle breed. J Anim Breed Genet 130(4):294–302. doi: 10.1111/j.1439-0388.2012.01020.x CrossRefPubMedGoogle Scholar
  5. Bjelland DW, Weigel KA, Vukasinovic N, Nkrumah JD (2013) Evaluation of inbreeding depression in Holstein cattle using whole-genome SNP markers and alternative measures of genomic inbreeding. J Dairy Sci 96(7):4697–4706. doi: 10.3168/jds.2012-6435 CrossRefPubMedGoogle Scholar
  6. Biscarini F, Biffani S, Nicolazzi EL, Morandi N (2014) Applying runs of homozygosity to the detection of associations between genotype and phenotype in farm animals. Proceedings of the 10th World Congress on Genetics Applied to Livestock Production 675:1–3.Google Scholar
  7. Bohmanova J, Sargolzaei M, Schenkel FS (2010) Characteristics of linkage disequilibrium in North American Holsteins. BMC Genom 11(1):421. doi: 10.1186/1471-2164-11-421 CrossRefGoogle Scholar
  8. Charlesworth D, Willis JH (2009) The genetics of inbreeding depression. Nat Rev Genet 10(11):783–796. doi: 10.1038/nrg2664 CrossRefPubMedGoogle Scholar
  9. Cole JB, VanRaden PM, O’Connell JR, Van Tassell CP, Sonstegard TS, Schnabel RD, Taylor JF, Wiggans GR (2009) Distribution and location of genetic effects for dairy traits. J Dairy Sci 92(6):2931–2946. doi: 10.3168/jds.2008-1762 CrossRefPubMedGoogle Scholar
  10. Corander J, Waldmann P, Sillanpää MJ (2003) Bayesian analysis of genetic differentiation between populations. Genetics 163:367–374PubMedPubMedCentralGoogle Scholar
  11. Corander J, Waldmann P, Marttinen P, Sillanpä MJ (2004) BAPS 2: enhanced possibilities for the analysis of genetic population structure. Bioinformatics 20:2363–2369. doi: 10.1093/bioinformatics/bth250 CrossRefPubMedGoogle Scholar
  12. Corander J, Marttinen P, Sirén J, Tang J (2008) Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. BMC Bioinf 9:539. doi: 10.1186/1471-2105-9-539 CrossRefGoogle Scholar
  13. Corbin LJ, Liu AYH, Bishop SC, Wooliams JA (2012) Estimation of historical effective population size using linkage disequilibrium with marker data. J Anim Breed Genet 129(4):257–270. doi: 10.1111/j.1439-0388.2012.01003.x CrossRefPubMedGoogle Scholar
  14. Curik I, Ferenčaković M, Sölkner J (2014) Inbreeding and runs of homozygosity: A possible solution to an old problem. Livest Sci 166:26–34. doi: 10.1016/j.livsci.2014.05.034 CrossRefGoogle Scholar
  15. Dadar M, Mahyari SA, Rokouei M (2014) Rates of inbreeding and genetic diversity in Iranian Holstein Cattle. Anim Sci J 85(1):888–894. doi: 10.1111/asj.12228 CrossRefPubMedGoogle Scholar
  16. De Roos APW, Hayes BJ, Spelman RJ, Goddard ME (2008) Linkage disequilibrium and persistence of phase in Holstein-Friesian, Jersey and Angus Cattle. Genetics 179:1503–1512. doi: 10.1534/genetics.107.084301 CrossRefPubMedPubMedCentralGoogle Scholar
  17. Decker JE, McKay SD, Rolf MM, Kim J, Alcalá AM, Sonstegard TS, Hanotte O, Götherström A, Seabury CM, Praharani L, Babar ME, Regitano LCdA, Yildiz MA, Heaton MP, Liu W, Lei C, Reecy JM, Saif-Ur-Rehman M, Schnabel RD, Taylor JF (2014) Worldwide patterns of ancestry, divergence, and admixture in domesticated cattle. PloS Genet 10(3):e1004254. doi: 10.1371/journal.pgen.1004254 CrossRefPubMedPubMedCentralGoogle Scholar
  18. Edea Z, Dadi H, Kim S-W, Dessie T, Lee T, Kim H, Kim J-J, Kim K-S (2013) Genetic diversity, population structure and relationships in indigenous cattle populations of Ethiopia and Korean Hanwoo breeds using SNP markers. Front Genet 4:1–9. doi: 10.3389/fgene.2013.00035 CrossRefGoogle Scholar
  19. Farnir F, Coppieters W, Arranz JJ, Berzi P, Cambisano N, Grisart B, Karim L, Marcq F, Moreau L, Mni M, Nezer C, Simon P, Vanmanshoven P, Wagenaar D, Georges M (2000) Extensive genome-wide linkage disequilibrium in cattle. Genome Res 10:220–227. doi: 10.1101/gr.10.2.220 CrossRefPubMedGoogle Scholar
  20. Ferenčaković M, Hamzić E, Gredler B, Solberg TR, Klemetsdal G, Curik I, Sölkner J (2013a) Estimates of autozygosity derived from runs of homozygosity: empirical evidence from selected cattle populations. J Anim Breed Genet 130:286–293. doi: 10.1111/jbg.12012 CrossRefPubMedGoogle Scholar
  21. Ferenčaković M, Solkner J, Curik I (2013b) Estimating autozygosity from high-throughput information: effects of SNP density and genotyping errors. Genet Sel Evol 45(1):42. doi: 10.1186/1297-9686-45-42 CrossRefPubMedPubMedCentralGoogle Scholar
  22. Flury C, Tapio M, Sonstegard C, Drogemuller C, Leeb T, Simianer H, Hanotte O, Rieder S (2010) Effective population size of an indigenous Swiss cattle breed estimated from linkage disequilibrium. J Anim Breed Genet 127:339–347. doi: 10.1111/j.1439-0388.2010.00862.x CrossRefPubMedGoogle Scholar
  23. Gautier M, Laloë D, Moazami-Goudarzi K (2010) Insights into the genetic history of French cattle from dense SNP data on 47 worldwide breeds. PloS ONE 5(9):e13038. doi: 10.1371/journal.pone.0013038 CrossRefPubMedPubMedCentralGoogle Scholar
  24. Golden Helix Inc (2014) SNP & Variation Suite (Version 8.1) [Software] (2014) Bozeman, MT. Available from: http://www.goldenhelix.com
  25. Gutiérrez-Gil B, Arranz JJ, Wiener P. (2015) An interpretive review of selective sweep studies in Bos Taurus cattle populations: identification of unique and shared selection signals across breeds. Front Genet. 6. doi: 10.3389/fgene.2015.00167
  26. Gutiérrez JP, Goyache F (2005) A note on ENDOG: a computer program for analysing pedigree information. J Anim Breed Genet 122:172–176. doi: 10.1111/j.1439-0388.2005.00512.x CrossRefPubMedGoogle Scholar
  27. Hall SJG (2004) Livestock biodiversity: genetic resources for the farming of the future. Blackwell Science Ltd, Oxford 217. ISBN 0-632-05499-9.CrossRefGoogle Scholar
  28. Hayes BJ, Visscher PM, McPartlan HC, Goddard ME (2003) Novel multilocus measure of linkage disequilibrium to estimate past effective population size. Genome Res 13:635–643. doi: 10.1101/gr.387103 CrossRefPubMedPubMedCentralGoogle Scholar
  29. Hayes BJ, Bowman PJ, Chamberlain AJ, Goddard ME (2009) Genomic selection in dairy cattle: progress and challenges. J Dairy Sci 92:433–443. doi: 10.3168/jds.2008-1646 CrossRefPubMedGoogle Scholar
  30. Hiemstra SJ, de Haas Y, Mäki-Tanila A, Gandini G (2010) Local cattle breeds in Europe. Wageningen Academic Publishers, Wageningen 154. ISBN: 978-90-8686-144-6.CrossRefGoogle Scholar
  31. Hill WG, Robertson A (1968) Linkage disequilibrium in finite populations. Theor Appl Genet 38:226–231. doi: 10.1007/BF01245622 CrossRefPubMedGoogle Scholar
  32. Howard JT, Maltecca C, Haile-Mariam M, Hayes BJ, Pryce JE (2015) Characterizing homozygosity across United States, New Zealand and Australian Jersey cow and bull populations. BMC Genom 16:187. doi: 10.1186/s12864 CrossRefGoogle Scholar
  33. Jemma SM, Boussaha M, Mehdi MB, Lee JH, Lee S-H (2015) Genome-wide insights into population structure and genetic history of tunisian local cattle using the illumina bovinesnp50 beadchip. BMC Genom 16:677. doi: 10.1186/s12864-015-1638-6 CrossRefGoogle Scholar
  34. Jombart T, Ahmed I (2011) Adegenet 1.3–1: new tools for the analysis of genome-wide SNP data. Bioinformatics 1:3070–3071. doi: 10.1093/bioinformatics/btr521 CrossRefGoogle Scholar
  35. Jombart T, Collins C (2015) A tutorial for discriminant analysis of principal components (DAPC) using adegenet 2.0.0. 43. adegenet.r-forge.r-project.orgGoogle Scholar
  36. Kadlečík O, Hazuchová E, Pavlík I, Kasarda R (2013) Diversity of cattle breeds in Slovakia. The 1st international scientific conference biotechnology of Farm Animal, Slovak. J Anim Sci 46(4):145–150Google Scholar
  37. Kantanen J, Olsaker I, Holm L-E, Lien S, Vilkki J, Brusgaard K, Eythorsdottir E, Danell B, Adalsteinsson S (2000) Genetic diversity and population structure of 20 North European cattle breeds. J Hered 91(6):446–457. doi: 10.1093/jhered/91.6.446 CrossRefPubMedGoogle Scholar
  38. Karimi K, Koshkoiyeh AE, Fozi MA, Porto-Neto LR, Gondro C (2016) Prioritization for conservation of Iranian native cattle breeds based on genome-wide SNP data. Conserv Genet 17:77–89. doi: 10.1007/s10592-015-0762-9 CrossRefGoogle Scholar
  39. Kasarda R, Mészáros G, Kadlečík O, Hazuchová E, Šidlová V, Pavlík I (2014) Influence of mating systems and selection intensity on the extent of inbreeding and genetic gain in the Slovak Pinzgau cattle. Czech. J Anim Sci 59(5):219–226Google Scholar
  40. Khatkar MS, Nicholas FM, Collins AR, Zenger KR, Cavanagh JA, Berris W, Schnabel RD, Taylor JF, Raadsma HW (2008) Extent of genome-wide linkage disequilibrium in Australian Holstein-Friesian cattle based on a high-density SNP panel. BMC Genom 9:187. doi: 10.1186/1471-2164-9-161 CrossRefGoogle Scholar
  41. Kim E-S, Rothschild MF (2014) Genomic adaptation of admixed dairy cattle in East Africa. Front Genet 5:443, doi: 10.3389/fgene.2014.0044311 PubMedPubMedCentralGoogle Scholar
  42. Kim E-S, Cole JB, Huson H, Wiggans GR, VanTassell CP, Crooker BA, Liu G, Da Y, Sonstegard TS (2013) Effect of artificial selection on runs of homozygosity in U.S. Holstein Cattle. PLoS ONE 8(11):e80813. doi: 10.1371/journal.pone.0080813 CrossRefPubMedPubMedCentralGoogle Scholar
  43. Krupová Z, Krupa E, Michaličková M, Wolfová M, Kasarda R (2016) Economic values for health and feed efficiency traits of dual-purpose cattle in marginal areas. J Dairy Sci 99:644–656. doi: 10.3168/jds.2015-9951 CrossRefPubMedGoogle Scholar
  44. Luikart G, Ryman N, Tallmon DA, Schwartz MK, Allendorf FW (2010) Estimation of census and effective population sizes: the increasing usefulness of DNA-based approaches. Conserv Genet 11:355–373. doi: 10.1007/s10592-010-0050-7 CrossRefGoogle Scholar
  45. Makina SO, Taylor JF, van Marle-Köster E, Muchadeyi FC, Makgahlela ML, MacNeil MD, Maiwashe, A (2015) Extent of linkage disequilibrium and effective population size in four South African Sanga cattle breeds. Front Genet 6:337. doi: 10.3389/fgene.2015.00337 CrossRefPubMedPubMedCentralGoogle Scholar
  46. Mancini G, Gargani M, Chillemi G, Nicolazzi EL, Marsan PA, Valentini A, Pariset L (2014) Signatures of selection in five Italian cattle breeds detected by a 54 K SNP panel. Mol Biol Rep 41:957–965. doi: 10.1007/s11033-013-2940-5 CrossRefPubMedPubMedCentralGoogle Scholar
  47. Mastrangelo S, Saura M, Tolone M, Salces-Ortiz J, Di Gerlando R, Bertolini F, Fontanesi L, Sardina MT, Serrano M, Portolano B (2014) The genome-wide structure of two economically important indigenous Sicilian cattle breeds. J Anim Sci 92:4833–4842. doi: 10.2527/jas.2014-7898 CrossRefPubMedGoogle Scholar
  48. Mbole-Kariuki MN, Sonstegard T, Orth A, Thumbi SM, Bronsvoort BM, Kiara H, Toye P, Conradie I, Jennings A, Coetzer K, Woolhouse ME, Hanotte O, Tapio M (2014) Genome-wide analysis reveals the ancient and recent admixture history of East African Shorthorn Zebu from Western Kenya. Heredity 113(4):297–305. doi: 10.1038/hdy.2014.31 CrossRefPubMedPubMedCentralGoogle Scholar
  49. McQuillan R, Leutenegger A, Abdel-Rahman R, Franklin C, Pericic M, Barac-Lauc L, Smolej-Narancic N, Janicijevic B, Polasek O, Tenesa A, Macleod A, Farrington S, Rudan P, Hayward C, Vitart V, Rudan I, Wild S, Dunlop M, Wright A, Campbell H, Wilson J (2008) Runs of homozygosity in European populations. Am J Hum Genet 83:359–372. doi: 10.1016/j.ajhg.2008.08.007 CrossRefPubMedPubMedCentralGoogle Scholar
  50. McTavish EJ, Decker JE, Schnabel RD, Taylor JF, Hillis DM (2013a) New world cattle show ancestry from multiple independent domestication events. PNAS 110(15):E1398–E1406. doi: 10.1073/pnas.1303367110 CrossRefPubMedPubMedCentralGoogle Scholar
  51. McTavish EJ, Decker JE, Schnabel RD, Taylor JF, Hillis DM (2013b) New World cattle show ancestry from multiple independent domestication events. Dryad Digit Repos doi: 10.5061/dryad.42tr0.2 Google Scholar
  52. McVean G, Awadalla P, Fearnhead P (2002) A coalescent-based method for detecting and estimating recombination from gene sequences. Genetics 160(3):1231–1241PubMedPubMedCentralGoogle Scholar
  53. Mészáros G, Boison SA, Pérez O´Brian AM, Ferenčaković M, Curik I, da Silva MVB, Utsunoomiya YT, Garcia JF, Solkner J (2015) Genomic analysis for managing small and endangered populations: a case study in Tyrol Grey cattle. Front Genet 6:173. doi: 10.3389/fgene.2015.00173 PubMedPubMedCentralGoogle Scholar
  54. Nei M, Tajima F, Tateno Y (1983) Accuracy of estimated phylogenetic trees from molecular data. II. Gene frequency data. J Mol Evol 19(2):153–170. doi: 10.1007/bf02300753 CrossRefPubMedGoogle Scholar
  55. Paradis E, Claude J, Strimmer K (2004) APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20:289–290. doi: 10.1093/bioinformatics/btg412 CrossRefPubMedGoogle Scholar
  56. Pavlík I, Sölkner J, Kadlečík O, Kasarda R, Mészáros G, Fuerst Ch, Fuerst-Waltl B (2014) Joint genealogical analysis as a tool for diversity evaluation in Pinzgau cattle populations. Arch Tierz 57(14):1–12. doi: 10.7482/0003-9438-57-014 Google Scholar
  57. Pembleton LW, Cogan NOI, Forster JW (2013) StAMPP: an R package for calculation of genetic differentiation and structure of mixed-ploidy level populations. Mol Ecol Res 13(5):946–952. doi: 10.1111/1755-0998.12129 CrossRefGoogle Scholar
  58. Pérez O´Brian AM, Höller D, Boison SA, Milanesi M, Bomba L, Utsunomiya YT, Carvalheiro R, Neves HHR, da Silva MVB, Van Tassell CP, Sonstegard TS, Mészáros G, Ajmone-Marsan P, Garcia F, Sölkner J (2015) Low levels of taurine introgression in the current Brazilian Nelore and Gir indicine cattle populations. Genet Sel Evol 47:31. doi: 10.1186/s12711-015-0109-5 CrossRefGoogle Scholar
  59. Pryce JE, Haile-Mariam M, Goddard ME, Hayes BJ (2014) Identification of genomic regions associated with inbreeding depression in Holstein and Jersey dairy cattle. Genet Sel Evol 46:71. doi: 10.1186/s12711-014-0071-7 CrossRefPubMedPubMedCentralGoogle Scholar
  60. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ, Sham PC (2007) PLINK: a toolset for whole-genome association and population-based linkage analysis. Am J Hum Genet 81:559–575. doi: 10.1086/519795 CrossRefPubMedPubMedCentralGoogle Scholar
  61. Purfield DC, Berry DP, McParland S, Bradley DG (2012) Runs of homozygosity and population history in cattle. BMC Genet 13:70. doi: 10.1186/1471-2156-13-70 pmid:22888858CrossRefPubMedPubMedCentralGoogle Scholar
  62. Qanbari S, Pimentel EC, Tetens J, Thaller G, Lichtner P, Sharifi AR, Simianer H (2010) The pattern of linkage disequilibrium in German Holstein cattle. Anim Genet 41:346–356. doi: 10.1111/j.1365-2052.2009.02011.x PubMedGoogle Scholar
  63. Qanbari S, Gianola D, Hayes B, Schenkel F, Miller S, Moore S, Thaller G, Simianer H (2011) Application of site and haplotype-frequency based approaches for detecting selection signatures in cattle. BMC Genom 12:318. doi: 10.1186/1471-2164-12-318 CrossRefGoogle Scholar
  64. Randhawa IAS, Khatkar MS, Thomson PC, Raadsma HW. (2016) A meta-assembly of selection signatures in Cattle. PLoS ONE 11(4):e0153013. doi: 10.1371/journal.pone.0153013 CrossRefPubMedPubMedCentralGoogle Scholar
  65. Sargolzaei M, Schenkel FS, Jansen GB, Schaeffer LR (2008) Extent of linkage disequilibrium in Holstein cattle in North America. J Dairy Sci 91:2106–2117. doi: 10.3168/jds.2007-0553 CrossRefPubMedGoogle Scholar
  66. Simčič M, Smetko A, Sölkner J, Seichter D, Gorjanc G, Kompan D, Medugorac I (2015) Recovery of native genetic background in admixed populations using haplotypes, phenotypes, and pedigree information—using cika cattle as a case breed. PLoS ONE 10(4):e123253. doi: 10.1371/journal.pone.0123253 Google Scholar
  67. Sved JA (1971) Linkage disequilibrium and homozygosity of chromosome segments in finite populations. Theor Popul Biol 2:125–141. doi: 10.1016/0040-5809(71)90011-6 CrossRefPubMedGoogle Scholar
  68. Sved JA (2009) Correlation measures for linkage disequilibrium within and between populations. Genet Res 9(3):183–192. doi: 10.1017/S0016672309000159 CrossRefGoogle Scholar
  69. Tenesa A, Knott SA, Ward D, Smith D, Williams JL, Visscher PM (2003) Estimation of linkage disequilibrium in a sample of the United Kingdom dairy cattle population using unphased genotypes. J Anim Sci 81:617–623CrossRefPubMedGoogle Scholar
  70. Tenesa A, Navarro P, Hayes BJ, Duffy DL, Clarke GM, Goddard ME, Visscher PM (2007) Recent human effective population size estimated from linkage disequilibrium. Genome Res 17:520–526. doi: 10.1101/gr.6023607 CrossRefPubMedPubMedCentralGoogle Scholar
  71. Toosi A, Fernando RL, Dekkers JCM (2010) Genomic selection in admixed and crossbred populations. J Anim Sci 88:32–46. doi: 10.2527/jas.2009-1975 CrossRefPubMedGoogle Scholar
  72. Uimari P, Tapio M (2011) Extent of linkage disequilibrium and effective population size in Finnish Landrace and Finnish Yorkshire pig breeds. J Anim Sci 89:609–614. doi: 10.2527/jas.2010-3249 CrossRefPubMedGoogle Scholar
  73. Waples RS (2006) A bias correction for estimates of effective population size based on linkage disequilibrium at unlinked gene loci. Conserv Genet 7(2):167–184. doi: 10.1007/s10592-005-9100-y CrossRefGoogle Scholar
  74. Weir BS (2008) Linkage disequilibrium and association mapping. Annu Rev Genom Hum Genet 9:129–142. doi: 10.1146/annurev.genom.9.081307.164347 CrossRefGoogle Scholar
  75. Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evol Int J org Evol 38(6):1358–1370. doi: 10.2307/2408641 Google Scholar
  76. Weir BS, Hill WG (1980) Effect of mating structure on variation in linkage disequilibrium. Genetics 95:477–488PubMedPubMedCentralGoogle Scholar
  77. Wilkinson S, Haley C, Alderson L, Wiener P (2011) An empirical assessment of individual-based population genetic statistical techniques: application to British pig breeds. Heredity 106:261–269. doi: 10.1038/hdy.2010.80 CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Veronika Kukučková
    • 1
  • Nina Moravčíková
    • 1
  • Maja Ferenčaković
    • 2
  • Mojca Simčič
    • 3
  • Gábor Mészáros
    • 4
  • Johann Sölkner
    • 4
  • Anna Trakovická
    • 1
  • Ondrej Kadlečík
    • 1
  • Ino Curik
    • 2
  • Radovan Kasarda
    • 1
  1. 1.Department of Animal Genetics and Breeding BiologySlovak University of Agriculture in NitraNitraSlovakia
  2. 2.Department of Animal ScienceUniversity of ZagrebZagrebCroatia
  3. 3.Department of Animal Science, Biotechnical FacultyUniversity of LjubljanaLjubljanaSlovenia
  4. 4.Division of Livestock SciencesUniversity of Natural Sciences and Life SciencesViennaAustria

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