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Runs of Homozygosity and NetView analyses provide new insight into the genome-wide diversity and admixture of three German cattle breeds


Autoři: Sowah Addo aff001;  Stefanie Klingel aff003;  Dirk Hinrichs aff002;  Georg Thaller aff001
Působiště autorů: Institute of Animal Breeding and Husbandry, Kiel University, Kiel, Germany aff001;  Department of Animal Breeding, University of Kassel, Witzenhausen, Germany aff002;  Center for Rare and Endangered Domestic Animals, Arche Warder, Warder, Germany aff003
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0225847

Souhrn

Angler (RVA) and Red-and-White dual-purpose (RDN) cattle were in the past decades crossed with influential Red Holstein (RH) sires. However, genome-wide diversity studies in these breeds are lacking. The objective of the present study was to elucidate the genome-wide diversity and population structure of the three German cattle breeds. Using 40,851 single nucleotide polymorphism markers scored in 337 individuals, runs of homozygosity (ROH) were analysed in each breed. Clustering and a high-resolution network visualisation analyses were performed on an extended dataset that included 11 additional (outgroup) breeds. Genetic diversity levels were high with observed heterozygosity above 0.35 in all three breeds. Only RVA had a recent past effective population size (Ne) estimate above 100 at 5 generations ago. ROH length distribution followed a similar pattern across breeds and the majority of ROH were found in the length class of >5 to 10 Mb. Estimates of average inbreeding calculated from ROH (FROH) were 0.021 (RVA), 0.045 (RDN) and 0.053 (RH). Moderate to high positive correlations were found between FROH and pedigree inbreeding (FPED) and between FROH and inbreeding derived from the excess of homozygosity (FHOM), while the intercept of the regression of FROH on FPED was above zero. The population structure analysis showed strong evidence of admixture between RVA and RH. Introgression of RDN with RH genes was minimally detected and for the first time, the study uncovered Norwegian Red Cattle ancestry in RVA. Highly heterogeneous genetic background was found for RVA and RH and as expected, the breeds of the extended dataset effectively differentiated mostly based on geographical origin, validating our findings. The results of this study confirm the impact of RH sires on RVA and RDN populations. Furthermore, a close monitoring is suggested to curb further reduction of Ne in the breeds.

Klíčová slova:

Animal husbandry – Cattle – Effective population size – Europe – Heterozygosity – Inbreeding – Population genetics – Species diversity


Zdroje

1. Gautier M, Laloë D, Moazami-Goudarzi K. Insights into the genetic history of French cattle from dense SNP data on 47 worldwide breeds. PLoS One. 2010;5: e13038. doi: 10.1371/journal.pone.0013038 20927341

2. Ajmone-Marsan P, Garcia JF, Lenstra JA. On the origin of cattle: How aurochs became cattle and colonized the world. Evol Anthropol. 2010;19: 148–157. doi: 10.1002/evan.20267

3. Kukučková V, Moravčíková N, Ferenčaković M, Simčič M, Mészáros G, Sölkner J, et al. Genomic characterization of Pinzgau cattle: genetic conservation and breeding perspectives. Conserv Genet. 2017;18: 893–910. doi: 10.1007/s10592-017-0935-9

4. Felius M, Beerling M-L, Buchanan DS, Theunissen B, Koolmees PA, Lenstra JA. On the history of cattle genetic resources. Diversity. 2014;6: 705–750. doi: 10.3390/d6040705

5. Adamczyk K, Felenczak A, Jamrozy J, Szarek J, Bulla J. Conservation of Polish Red cattle. Slovak J Anim Sci. 2008;41: 72–76.

6. Bay E, Colinet F, Gengler N. Dual Purpose Red and White [Internet]. EU GENRES 870/04; 2010. Available: http://www.regionalcattlebreeds.eu/wp/documents/WP1-Breedcase-DP-RedandWhite.pdf

7. Bennewitz J, Meuwissen THE. Estimation of extinction probabilities of five German cattle breeds by population viability analysis. J Dairy Sci. Elsevier; 2005;88: 2949–2961. doi: 10.3168/jds.S0022-0302(05)72975-1 16027209

8. Andresen U, Bartjen A, Kaske M. German Red and White Coloured Dual Purpose an alternative for a sustainable milk production? Tierarztl Umsch. 2014;69: 537–542.

9. Addo S, Schäler J, Hinrichs D, Thaller G. Genetic Diversity and Ancestral History of the German Angler and the Red-and-White Dual-Purpose Cattle Breeds Assessed through Pedigree Analysis. Agric Sci. 2017;8: 1033–1047.

10. Wang Y, Segelke D, Emmerling R, Bennewitz J, Wellmann R. Long-Term Impact of Optimum Contribution Selection Strategies on Local Livestock Breeds with Historical Introgression Using the Example of German Angler Cattle. G3 (Bethesda). 2017;7: 4009–4018. doi: 10.1534/g3.117.300272 29089375

11. Kawęcka A, Gurgul A, Miksza-Cybulska A. The Use of SNP Microarrays for Biodiversity Studies of Sheep–A Review. Ann Anim Sci. De Gruyter Open; 2016;16: 975–987. doi: 10.1515/aoas-2016-0017

12. Lenstra JA, Groeneveld LF, Eding H, Kantanen J, Williams JL, Taberlet P, et al. Molecular tools and analytical approaches for the characterization of farm animal genetic diversity. Anim Genet. 2012;43: 483–502. doi: 10.1111/j.1365-2052.2011.02309.x 22497351

13. LaFramboise T. Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances. Nucleic Acids Res. 2009;37: 4181–4193. doi: 10.1093/nar/gkp552 19570852

14. Forutan M, Mahyari SA, Baes C, Melzer N, Schenkel FS, Sargolzaei M. Inbreeding and runs of homozygosity before and after genomic selection in North American Holstein cattle. BMC Genomics. 2018;19: 98. doi: 10.1186/s12864-018-4453-z 29374456

15. Mastrangelo S, Ciani E, Marsan PA, Bagnato A, Battaglini L, Bozzi R, et al. Conservation status and historical relatedness of Italian cattle breeds. Genet Sel Evol. 2018;50: 35. doi: 10.1186/s12711-018-0406-x 29940848

16. Orozco-terWengel P, Barbato M, Nicolazzi E, Biscarini F, Milanesi M, Davies W, et al. Revisiting demographic processes in cattle with genome-wide population genetic analysis. Front Genet. 2015;6: 191. doi: 10.3389/fgene.2015.00191 26082794

17. Signer-Hasler H, Burren A, Neuditschko M, Frischknecht M, Garrick D, Stricker C, et al. Population structure and genomic inbreeding in nine Swiss dairy cattle populations. Genet Sel Evol. 2017;49: 83. doi: 10.1186/s12711-017-0358-6 29115934

18. Purfield DC, McParland S, Wall E, Berry DP. The distribution of runs of homozygosity and selection signatures in six commercial meat sheep breeds. PLoS One. 2017;12: e0176780. Available: doi: 10.1371/journal.pone.0176780 28463982

19. Deniskova TE, Dotsev A V, Selionova MI, Kunz E, Medugorac I, Reyer H, et al. Population structure and genetic diversity of 25 Russian sheep breeds based on whole-genome genotyping. Genet Sel Evol. 2018;50: 29. doi: 10.1186/s12711-018-0399-5 29793424

20. Edea Z, Dessie T, Dadi H, Do K-T, Kim K-S. Genetic Diversity and Population Structure of Ethiopian Sheep Populations Revealed by High-Density SNP Markers. Front Genet. 2017;8: 218. Available: doi: 10.3389/fgene.2017.00218 29312441

21. Manunza A, Noce A, Serradilla JM, Goyache F, Martínez A, Capote J, et al. A genome-wide perspective about the diversity and demographic history of seven Spanish goat breeds. Genet Sel Evol. 2016;48: 52. doi: 10.1186/s12711-016-0229-6 27455838

22. Burren A, Neuditschko M, Signer‐Hasler H, Frischknecht M, Reber I, Menzi F, et al. Genetic diversity analyses reveal first insights into breed-specific selection signatures within Swiss goat breeds. Anim Genet. 2016;47: 727–739. doi: 10.1111/age.12476 27436146

23. Grilz-Seger G, Mesarič M, Cotman M, Neuditschko M, Druml T, Brem G. Runs of Homozygosity and Population History of Three Horse Breeds With Small Population Size. J Equine Vet Sci. 2018;71: 27–34. https://doi.org/10.1016/j.jevs.2018.09.004

24. Druml T, Neuditschko M, Grilz-Seger G, Horna M, Ricard A, Mesarič M, et al. Population networks associated with runs of homozygosity reveal new insights into the breeding history of the Haflinger horse. J Hered. 2017;109: 384–392.

25. Alexander DH, Novembre J, Lange K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 2009;19: 1655–64. doi: 10.1101/gr.094052.109 19648217

26. Neuditschko M, Khatkar MS, Raadsma HW. NetView: a high-definition network-visualization approach to detect fine-scale population structures from genome-wide patterns of variation. PLoS One. 2012;7: e48375. doi: 10.1371/journal.pone.0048375 23152744

27. Steinig EJ, Neuditschko M, Khatkar MS, Raadsma HW, Zenger KR. netview p: a network visualization tool to unravel complex population structure using genome‐wide SNPs. Mol Ecol Resour. 2015;16: 216–227. doi: 10.1111/1755-0998.12442 26129944

28. McQuillan R, Leutenegger A-L, Abdel-Rahman R, Franklin CS, Pericic M, Barac-Lauc L, et al. Runs of homozygosity in European populations. Am J Hum Genet. 2008;83: 359–372. doi: 10.1016/j.ajhg.2008.08.007 18760389

29. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81: 559–575. doi: 10.1086/519795 17701901

30. Sempéré G, Moazami-Goudarzi K, Eggen A, Laloë D, Gautier M, Flori L. WIDDE: a Web-Interfaced next generation database for genetic diversity exploration, with a first application in cattle. BMC Genomics. BioMed Central; 2015;16: 940.

31. Gautier M, Flori L, Riebler A, Jaffrézic F, Laloé D, Gut I, et al. A whole genome Bayesian scan for adaptive genetic divergence in West African cattle. BMC Genomics. 2009;10: 550. doi: 10.1186/1471-2164-10-550 19930592

32. Matukumalli LK, Lawley CT, Schnabel RD, Taylor JF, Allan MF, Heaton MP, et al. Development and characterization of a high density SNP genotyping assay for cattle. PLoS One. 2009;4: e5350. doi: 10.1371/journal.pone.0005350 19390634

33. Barbato M, Orozco-terWengel P, Tapio M, Bruford MW. SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data. Front Genet. 2015;6: 109. Available: https://www.frontiersin.org/article/10.3389/fgene.2015.00109 25852748

34. Corbin LJ, Liu AYH, Bishop SC, Woolliams JA. Estimation of historical effective population size using linkage disequilibria with marker data. J Anim Breed Genet. 2012;129: 257–270. doi: 10.1111/j.1439-0388.2012.01003.x 22775258

35. Hayes BJ, Visscher PM, McPartlan HC, Goddard ME. Novel multilocus measure of linkage disequilibrium to estimate past effective population size. Genome Res. 2003;13: 635–643. doi: 10.1101/gr.387103 12654718

36. Sved JA, Feldman MW. Correlation and probability methods for one and two loci. Theor Popul Biol. 1973;4: 129–132. doi: 10.1016/0040-5809(73)90008-7 4726005

37. Mészáros G, Boison SA, Pérez O’Brien AM, Ferenčaković M, Curik I, Da Silva MVB, et al. Genomic analysis for managing small and endangered populations: a case study in Tyrol Grey cattle. Front Genet. 2015;6: 173. doi: 10.3389/fgene.2015.00173 26074948

38. Keller MC, Visscher PM, Goddard ME. Quantification of inbreeding due to distant ancestors and its detection using dense SNP data. Genetics. 2011;189: 237–249. doi: 10.1534/genetics.111.130922 21705750

39. Meuwissen THE, Luo Z. Computing inbreeding coefficients in large populations. Genet Sel Evol. 1992;24: 305. doi: 10.1186/1297-9686-24-4-305

40. Boichard D. PEDIG: a fortran package for pedigree analysis suited for large populations. Proc 7th world Congr Genet Appl to Livest Prod. 2002;32: 525–528.

41. Francis RM. POPHELPER: an R package and web app to analyse and visualize population structure. Mol Ecol Resour. 2017;17: 27–32. doi: 10.1111/1755-0998.12509 26850166

42. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. Cold Spring Harbor Lab; 2003;13: 2498–2504. doi: 10.1101/gr.1239303 14597658

43. Iso‐Touru T, Tapio M, Vilkki J, Kiseleva T, Ammosov I, Ivanova Z, et al. Genetic diversity and genomic signatures of selection among cattle breeds from Siberia, eastern and northern Europe. Anim Genet. 2016;47: 647–657. doi: 10.1111/age.12473 27629771

44. Yurchenko A, Yudin N, Aitnazarov R, Plyusnina A, Brukhin V, Soloshenko V, et al. Genome-wide genotyping uncovers genetic profiles and history of the Russian cattle breeds. Heredity (Edinb). 2018;120: 125–137.

45. Arbeitsgemeinschaft Deutscher Rinderzüchter. Rinderproduktion in Deutschland 2017. Arbeitsgemeinschaft Deutscher Rinderzüchter e.V. (ADR), Bonn, Germany; 2018.

46. Wright S. Coefficients of inbreeding and relationship. Amer Nat. 1922;56. doi: 10.1086/279872

47. Kardos M, Luikart G, Allendorf FW. Measuring individual inbreeding in the age of genomics: marker-based measures are better than pedigrees. Heredity (Edinb). 2015;115: 63.

48. Zhang Q, Calus MP, Guldbrandtsen B, Lund MS, Sahana G. Estimation of inbreeding using pedigree, 50k SNP chip genotypes and full sequence data in three cattle breeds. BMC Genet. 2015;16. doi: 10.1186/s12863-015-0168-1

49. Purfield DC, Berry DP, McParland S, Bradley DG. Runs of homozygosity and population history in cattle. BMC Genet. 2012;13: 70. doi: 10.1186/1471-2156-13-70 22888858

50. Wang J. Marker-based estimates of relatedness and inbreeding coefficients: an assessment of current methods. J Evol Biol. 2014;27: 518–530. doi: 10.1111/jeb.12315 24444019

51. Marras G, Gaspa G, Sorbolini S, Dimauro C, Ajmone-Marsan P, Valentini A, et al. Analysis of runs of homozygosity and their relationship with inbreeding in five cattle breeds farmed in Italy. Anim Genet. 2015;46. doi: 10.1111/age.12259 25530322

52. Ferenčaković M, Hamzić E, Gredler B, Solberg TR, Klemetsdal G, Curik I, et al. Estimates of autozygosity derived from runs of homozygosity: empirical evidence from selected cattle populations. J Anim Breed Genet. 2013;130: 286–293. doi: 10.1111/jbg.12012 23855630

53. Porter V, Alderson L, Hall SJG, Sponenberg DP. Mason’s World Encyclopedia of Livestock Breeds and Breeding: 2 Volume Pack. 6th ed. Boston: Cabi; 2016.

54. Burren A, Signer-Hasler H, Neuditschko M, Tetens J, Kijas J, Drögemüller C, et al. Fine-scale population structure analysis of seven local Swiss sheep breeds using genome-wide SNP data. Anim Genet Resour. 2014;55: 67–76.


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