Hostname: page-component-7c8c6479df-nwzlb Total loading time: 0 Render date: 2024-03-27T15:52:29.669Z Has data issue: false hasContentIssue false

Genetic diversity and admixture among Canadian, Mountain and Moorland and Nordic pony populations

Published online by Cambridge University Press:  26 July 2011

J. M. Prystupa*
Affiliation:
Department of Animal and Poultry Science, University of Saskatchewan, Saskatoon, Saskatchewan S7N 5A8, Canada Agriculture & Agri-Food Canada, Saskatoon, Saskatchewan S7N 0X2, Canada
R. Juras
Affiliation:
College of Veterinary Medicine & Biomedical Sciences, Texas A & M University, College Station, Texas 77848-4458, USA
E. G. Cothran
Affiliation:
College of Veterinary Medicine & Biomedical Sciences, Texas A & M University, College Station, Texas 77848-4458, USA
F. C. Buchanan
Affiliation:
Department of Animal and Poultry Science, University of Saskatchewan, Saskatoon, Saskatchewan S7N 5A8, Canada
Y. Plante
Affiliation:
Department of Animal and Poultry Science, University of Saskatchewan, Saskatoon, Saskatchewan S7N 5A8, Canada Agriculture & Agri-Food Canada, Saskatoon, Saskatchewan S7N 0X2, Canada
*
Get access

Abstract

As part of the requirements of the Convention on Biological Diversity, Canada has been investigating the genetic diversity of its native equine and pony populations. Along with examining four indigenous Canadian equine populations (Canadian horse, Lac La Croix pony, Newfoundland pony and Sable Island population), another 10 Mountain and Moorland, three Nordic, four horse and two feral equine populations (thought to have influenced some pony breeds) were also investigated. In total, 821 individuals were genotyped at 38 microsatellite loci. Results of the analysis of molecular variance indicated that 13.3% of genetic diversity was explained by breed differences, whereas 84.6% and 2.1% of diversity came from within and among individuals, respectively. The average effective number of alleles and allelic richness was the lowest in the Eriskay (2.51 and 3.98) and Lac La Croix (2.83 and 4.01) populations, whereas it was highest in the New Forest (4.31 and 6.01) and Welsh (4.33 and 5.87) breeds, followed closely by the Newfoundland-CDN (4.23 and 5.86) population. Expected heterozygosities varied from 0.61 in the Lac La Croix to 0.74 in the Welsh and in Newfoundland. Observed heterozygosities ranged from 0.57 in the Exmoor and 0.58 in the Sable Island herd to 0.77 in the Kerry Bog and 0.76 in the New Forest breeds. Structure and admixture analyses revealed that the most likely number of clusters was 21, although some substructure was also observed when K = 16, compared with the 24 predefined populations. Information gathered from this study should be combined with other available phenotypic and pedigree data to develop, or amend, a suitable conservation strategy for all populations examined.

Type
Full Paper
Copyright
Copyright © The Animal Consortium 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aberle, KS, Hamann, H, Drögemüller, C, Distl, O 2004. Genetic diversity in German draught horse breeds compared with a group of primitive, riding and wild horses by means of microsatellite DNA markers. Animal Genetics 35, 270277.Google Scholar
Achmann, R, Curik, I, Dovc, P, Kavar, T, Bodo, I, Habe, F, Marti, E, Sölkner, J, Brem, G 2004. Microsatellite diversity, population subdivision and gene flow in the Lipizzan horse. Animal Genetics 35, 285292.Google Scholar
Behl, R, Behl, J, Gupta, N, Gupta, SC 2008. Evaluation of microsatellite genotyping based individual assignment in five Indian horse breeds. Indian Journal of Animal Sciences 78, 384387.Google Scholar
Bowcock, AM, Ruiz-Linares, A, Tomfohrde, J, Minch, E, Kidd, JR, Cavalli-Sforza, LL 1994. High resolution of human evolutionary trees with polymorphic microsatellites. Nature 368, 455457.Google Scholar
Caballero, A, Toro, MA 2002. Analysis of genetic diversity for the management of conserved subdivided populations. Conservation Genetics 3, 289299.Google Scholar
Cañon, J, Checa, ML, Carleos, C, Vega-Pla, JL, Vallejo, M, Dunner, S 2000. The genetic structure of Spanish Celtic horse breeds inferred from microsatellite data. Animal Genetics 31, 3948.Google Scholar
Cothran, EG 2004. Genetic analysis of the Lac La Croix pony. Retrieved February 24, 2011, from http://www.laclacroixindianpony.com/pdfs/cothranDNAreport.pdfGoogle Scholar
D'Arnoldi, CT, Foulley, JL, Ollivier, L 1998. An overview of the Weitzman approach to diversity. Un apercu sur l'approche de la diversite selon Weitzman 30, 149161.Google Scholar
DeAssis, JB, DeLaat, DM, Peixoto, MG, Bergmann, JA, Fonseca, CG, Carvalho, MR 2009. Genetic diversity and population structure in Brazilian Mangalarga Marchador horses. Genetics and Molecular Research 8, 15191524.Google Scholar
Dieringer, D, Schlötterer, C 2003. Microsatellite Analyser (MSA): a platform independent analysis tool for large microsatellite data sets. Molecular Ecology Notes 3, 167169.Google Scholar
Earl, DA 2009. Structure Harvester. Retrieved February 24, 2011, from http://taylor0.biology.ucla.edu/struct_harvest/Google Scholar
Eggert, LS, Powell, DM, Ballou, JD, Malo, AF, Turner, A, Kumer, J, Zimmerman, C, Fleischer, RC, Maldonado, JE 2010. Pedigrees and the study of the wild horse population of assateague island national seashore. Journal of Wildlife Management 74, 963973.Google Scholar
Eriskay Pony Mother Stud Book Society 2010. Our Stallions1. Retrieved February 24, 2011, from http://www.eriskaypony.org.uk/Google Scholar
Equus Survival Trust 2008. Equine conservation list. Retrieved February 24, 2011, from http://www.equus-survival-trust.org/Google Scholar
Evanno, G, Regnaut, S, Goudet, J 2005. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Molecular Ecology 14, 26112620.Google Scholar
Excoffier, L, Lischer, HEL 2010. Arlequin suite ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources 10, 564567.Google Scholar
Food and Agriculture Organization (FAO) 2007. The State of the World's Animal Genetic Resources for Food and Agriculture (ed. Rischkowsky B and Pilling D). FAO, Rome.Google Scholar
Felsenstein, J 1989–2006. ‘Phylip’(phylogeny inference package) v. 3.66. Retrieved February 24, 2011, from http://evolution.genetics.washington.edu/phylip/getme.htmlGoogle Scholar
Glowatzki-Mullis, ML, Muntwyler, J, Pfister, W, Marti, E, Rieder, S, Poncet, PA, Gaillard, C 2006. Genetic diversity among horse populations with a special focus on the Franches–Montagnes breed. Animal Genetics 37, 3339.Google Scholar
Goudet, J 2001. FSTAT: a program to estimate and test gene diversities and fixation indices, version 2.9.3. Retrieved February 24, 2011, from http://www2.unil.ch/popgen/softwares/fstat.htmGoogle Scholar
Gutiérrez, JP, Royo, LJ, Álvarez, I, Goyache, F 2005. MolKin v2.0: a computer program for genetic analysis of populations using molecular coancestry information. Journal of Heredity 96, 718721.Google Scholar
Hoffmann, I, Ajmone Marsan, P, Barker, SF, Cothran, EG, Hanotte, O, Lenstra, JA, Milan, D, Weigend, S, Simianer, H 2004. New MoDaD marker sets to be used in diversity studies for the major farm animal species: recommendations of a joint ISAG/FAO working group. Proceedings of 29th International Conference on Animal Genetics, Tokyo, Japan, 107pp.Google Scholar
Huson, DH 1998. SplitsTree: Analyzing and visualizing evolutionary data. Bioinformatics 14, 6873.Google Scholar
Huson, DH, Bryant, D 2006. Application of phylogenetic networks in evolutionary studies. Molecular Biology and Evolution 23, 254267.Google Scholar
Jakobsson, M, Rosenberg, NA 2007. CLUMPP: A cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23, 18011806.Google Scholar
Leroy, G, Callède, L, Verrier, E, Mériaux, JC, Ricard, A, Danchin-Burge, C, Rognon, X 2009. Genetic diversity of a large set of horse breeds raised in France assessed by microsatellite polymorphism. Genetics Selection Evolution 41, 5.Google Scholar
Lucas, ZL, McLoughlin, PD, Coltman, DW, Barber, C 2009. Multiscale analysis reveals restricted gene flow and a linear gradient in heterozygosity for an island population of feral horses. Canadian Journal of Zoology 87, 310316.Google Scholar
Luís, C, Juras, R, Oom, MM, Cothran, EG 2007. Genetic diversity and relationships of Portuguese and other horse breeds based on protein and microsatellite loci variation. Animal Genetics 38, 2027.Google Scholar
Lynghaug, F 2009. The official horse breeds standards guide: the complete guide to the standards of all North American equine breed associations. Voyageur Press, Minneapolis, MN, USA.Google Scholar
McGahern, AM, Edwards, CJ, Bower, MA, Heffernan, A, Park, SDE, Brophy, PO, Bradley, DG, MacHugh, DE, Hill, EW 2006. Mitochondrial DNA sequence diversity in extant Irish horse populations and in ancient horses. Animal Genetics 37, 498502.Google Scholar
Nei, M 1972. Genetic distance between populations. American Naturalist 106, 283292.Google Scholar
Nei, M, Tajima, F, Tateno, Y 1983. Accuracy of estimated phylogenetic trees from molecular data. II. Gene frequency data. Journal of Molecular Evolution 19, 153170.Google Scholar
Nova Scotia Museum of Natural History 2001. Sable Island. Retrieved February 24, 2011, from http://museum.gov.ns.ca/mnh/nature/sableisland/english_en/nature_na/horses_ho/index_ho.htmGoogle Scholar
Paetkau, D, Calvert, W, Stirling, I, Strobeck, C 1995. Microsatellite analysis of population structure in Canadian polar bears. Molecular Ecology 4, 347354.Google Scholar
Paetkau, D, Slade, R, Burden, M, Estoup, A 2004. Genetic assignment methods for the direct, real-time estimation of migration rate: A simulation-based exploration of accuracy and power. Molecular Ecology 13, 5565.Google Scholar
Peakall, R, Smouse, PE 2006. GENALEX 6: Genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6, 288295.Google Scholar
Petit, RJ, Mousadik, AEL, Pons, O 1998. Identifying populations for conservation on the basis of genetic markers. Conservation Biology 12, 844855.Google Scholar
Plante, Y, Vega-Pla, JL, Lucas, Z, Colling, D, De March, B, Buchanan, F 2007. Genetic diversity in a feral horse population from Sable Island, Canada. Journal of Heredity 98, 594602.Google Scholar
Pritchard, JK, Stephens, M, Donnelly, P 2000. Inference of population structure using multilocus genotype data. Genetics 155, 945959.Google Scholar
Rare Breeds Canada 2009. Horse breeds. Retrieved February 24, 2011 from http://www.rarebreedscanada.ca/horsebreeds.htmGoogle Scholar
Raymond, M, Rousset, F 1995. GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. Journal of Heredity 86, 248249.Google Scholar
Reynolds, J, Weir, BS, Cockerham, CC 1983. Estimation of the coancestry coefficient: Basis for a short-term genetic distance. Genetics 105, 767779.Google Scholar
Rosenberg, NA 2004. DISTRUCT: a program for the graphical display of population structure. Molecular Ecology Notes 4, 137138.Google Scholar
Rousset, F 2008. Genepop'007: a complete reimplementation of the Genepop software for Windows and Linux. Molecular Ecology Resources 8, 103106.Google Scholar
Saitou, N, Nei, M 1987. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Molecular biology and evolution 4, 406425.Google Scholar
Solis, A, Jugo, BM, Mériaux, JC, Iriondo, M, Mazón, LI, Aguirre, AI, Vicario, A, Estomba, A 2005. Genetic diversity within and among four south European native horse breeds based on microsatellite DNA analysis: implications for conservation. Journal of Heredity 96, 670678.Google Scholar
Tamura, K, Dudley, J, Nei, M, Kumar, S 2007. MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Molecular Biology and Evolution 24, 15961599.Google Scholar
Troy, CS, MacHugh, DE, Bailey, JF, Magee, DA, Loftus, RT, Cunningham, P, Chamberlain, AT, Sykes, BC, Bradley, DG 2001. Genetic evidence for near-eastern origins of European cattle. Nature 410, 10881091.Google Scholar
Van Oosterhout, C, Hutchinson, WF, Wills, DPM, Shipley, P 2004. MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes 4, 535538.Google Scholar
Weitzman, ML 1992. On Diversity. The Quarterly Journal of Economics 107, 363405.Google Scholar
Weitzman, ML 1993. What to preserve? An application of diversity theory to crane conservation. The Quarterly Journal of Economics 108, 157183.Google Scholar
Supplementary material: File

Prystupa Supplementary Table 1

Supplementary Table 1 A detail summary including the multiplex, location, primer sequence, allele size (ISAG markers have been standardized), dye, volume and reference of each microsatellite locus utilized this study (taken and modified from Glowatzki-Mullis et al. (2006).

Download Prystupa Supplementary Table 1(File)
File 192.5 KB
Supplementary material: File

Prystupa Supplementary Table 2

Supplementary Table 2 A overall summary of the statistics parameters estimated including: average number of alleles (Na), effective number of alleles (Ne), observed heterzygosity (Ho), expected heterzygosity (He), and F indices (FIS, FST, FIT) for each individual locus tested where P=0.05

Download Prystupa Supplementary Table 2(File)
File 107.5 KB