FREE SHIPPING over $40
OVER 10000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Veterinary sciences2025; 12(8); 776; doi: 10.3390/vetsci12080776

Population Structure and Genetic Diversity Among Shagya Arabian Horse Genealogical Lineages in Bulgaria Based on Microsatellite Genotyping.

Abstract: The Shagya Arabian horse breed was created to address the need of Imperial Hussars (Hungarian light horsemen) for a horse with the intelligence, essential characteristics, and endurance of the Arabian breed, but also of a bigger size and having a better weight-carrying capacity and jumping ability. The present study aimed to explore the genetic variability and population structure of the uninvestigated Shagya Arabian horse population in Bulgaria based on genotyping at 15 equine microsatellite markers. A total of 140 horses belonging to six genealogical lines (Dahoman, Gazal, Ibrahim, Kuhailan Zaid, O'Bajan, and Shagya) were included in the survey. Genetic distances, analysis of molecular variance, principal coordinates analysis, and a Bayesian method were applied. The mean number of alleles in the individual subpopulations ranged from 3.67 in the Shagya to 5.13 in the Ibrahim sire line. The F index was negative or close to 0 for the entire population and was -0.202. The overall was 0.014, indicating a low level of genetic differentiation between the subpopulations. The results of the principal components and the STRUCTURE analysis showed some level of admixture among the subpopulations in almost all genealogical lines. However, structural analysis also indicated a genetic similarity between the Ibrahim, Kuhailan Zaid, and Shagya lineages, while it showed a completely different genetic profile regarding the other three sire lines. Due to the higher admixture and the discovery of more distinct genetic clusters, it can be assumed that there is a higher gene flow from one lineage to another in the Shagya Arabian horse population in Bulgaria and that there is sufficient genetic variability and diversity to suggest adequate measures for preserving this rare breed. In addition, this study may highlight the risk of the loss of gene diversity in this population and help to implement suitable breeding programs to preserve genetic diversity.
Get Full Text
Publication Date: 2025-08-19 PubMed ID: 40872726PubMed Central: PMC12390109DOI: 10.3390/vetsci12080776Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

Overview

  • This study examined the genetic diversity and population structure of the Shagya Arabian horse population in Bulgaria by analyzing 15 microsatellite markers across six genealogical lineages.
  • The research found a generally low genetic differentiation between lineages and evidence of gene flow among them, indicating sufficient genetic variability but a need for conservation efforts to maintain this rare breed.

Introduction and Objectives

  • The Shagya Arabian horse breed was originally developed to meet the demands of Imperial Hussars for horses combining Arabian traits with larger size, enhanced endurance, and better jumping and weight-carrying abilities.
  • The breed’s genealogy consists of several sire lines or ancestral lineages, which have not been genetically analyzed in Bulgaria before this study.
  • The goal was to investigate the genetic variability among six different genealogical lineages of Shagya Arabian horses in Bulgaria using microsatellite genotyping to better understand their population structure and genetic diversity.

Materials and Methods

  • Sample: 140 horses representing six genealogical lines—Dahoman, Gazal, Ibrahim, Kuhailan Zaid, O’Bajan, and Shagya.
  • Marker Type: 15 equine microsatellite markers, commonly used for genetic diversity and population structure studies due to their high variability.
  • Analyses Conducted:
    • Calculation of allele numbers per lineage to estimate genetic diversity.
    • F-statistics (F index) to determine inbreeding and population differentiation.
    • Pairwise genetic distances and analysis of molecular variance (AMOVA) to assess differentiation among lineages.
    • Principal Coordinates Analysis (PCA) to visualize genetic relationships between lineages.
    • Bayesian clustering method using STRUCTURE software to detect population structure and admixture.

Key Findings

  • Allelic Diversity: The mean allele number per lineage ranged from 3.67 (Shagya) to 5.13 (Ibrahim), indicating some variation in genetic diversity across lineages.
  • Inbreeding and Differentiation:
    • The F index was close to zero or negative (-0.202 overall), suggesting low inbreeding or possibly some outbreeding.
    • The overall F_ST was 0.014, reflecting very low genetic differentiation among lineages, meaning they share much genetic material.
  • Genetic Structure and Admixture:
    • PCA and STRUCTURE analysis revealed admixture among almost all genealogical lines, indicating gene flow between lineages.
    • Specifically, Ibrahim, Kuhailan Zaid, and Shagya lineages showed genetic similarity, clustering closely together.
    • The other three lineages (Dahoman, Gazal, and O’Bajan) displayed distinct genetic profiles, separate from the above group.

Interpretation and Implications

  • The low genetic differentiation implies a shared genetic pool among the Shagya Arabian horses in Bulgaria, with ongoing gene flow between lineages.
  • The detectable admixture suggests the lineages are not fully isolated but interbreeding occurs, which helps maintain genetic diversity.
  • Given the Shagya Arabian horse is a rare breed, the observed genetic variability is encouraging for breed preservation.
  • However, because of the risk of genetic diversity loss over time, the study recommends:
    • Implementing structured breeding programs that monitor and maintain genetic variation.
    • Carefully managing gene flow to avoid inbreeding depression and loss of unique lineage traits.

Conclusion

  • This study provides the first insight into the genetic structure of Shagya Arabian horses in Bulgaria, highlighting a relatively rich gene pool across different genealogical lineages despite some differentiation.
  • The findings support future conservation strategies aimed at preserving the breed by maintaining its genetic health and diversity through informed breeding management.

Cite This Article

APA
(2025). Population Structure and Genetic Diversity Among Shagya Arabian Horse Genealogical Lineages in Bulgaria Based on Microsatellite Genotyping. Vet Sci, 12(8), 776. https://doi.org/10.3390/vetsci12080776

Publication

Veterinary sciences
ISSN: 2306-7381
NlmUniqueID: 101680127
Country: Switzerland
Language: English
Volume: 12
Issue: 8
PII: 776

Researcher Affiliations

Conflict of Interest Statement

The authors declare no conflicts of interest.

References

This article includes 61 references
  1. Druml T, Horna M, Grilz-Seger G, Dobretsberger M, Brem G. Association of body shape with amount of Arabian genetic contribution in the Lipizzan horse.. Arch. Anim. Breed. 2018;61:79–85.
    doi: 10.5194/aab-61-79-2018google scholar: lookup
  2. Hendricks B.L.. International Encyclopedia of Horse Breeds. University of Oklahoma Press; Norman, OK, USA: 1995. p. 486.
  3. ISG-Shagya-Araber. 2024. [(accessed on 17 June 2019)]. Available online: http://isg-shagya-araber.de/index.php?entstehungsgeschichte-der-isg-2.
  4. Petrov A.. Contribution to Horse-Breeding Study in Bulgaria—Kabiuk. Government Press; Sofia, Bulgaria: 1927.
  5. Sabeva I.. Origin and Development of Arabian and Shagya Breeds in Bulgaria. June Express; Shumen, Bulgaria: 2009. p. 246.
  6. Abdul-Muneer P.M. Application of microsatellite markers in conservation genetics and fisheries management: Recent advances in population structure analysis and conservation strategies.. Genet. Res. Int. 2014;691759:1–11.
    doi: 10.1155/2014/691759pmc: PMC3997932pubmed: 24808959google scholar: lookup
  7. Putman A.I., Carbone I. Challenges in analysis and interpretation of microsatellite data for population genetic studies.. Ecol. Evol. 2014;4:4399–4428.
    doi: 10.1002/ece3.1305pmc: PMC4267876pubmed: 25540699google scholar: lookup
  8. Vieira M.L.C., Santini L., Diniz A.L., Munhoz C.D.F.. Microsatellite markers: What they mean and why they are so useful.. Genet. Mol. Biol. 2016;39:312–328.
    doi: 10.1590/1678-4685-GMB-2016-0027pmc: PMC5004837pubmed: 27561112google scholar: lookup
  9. Rasoarahona R., Wattanadilokchatkun P., Panthum T., Thong T., Singchat W., Ahmad S.F., Chaiyes A., Han K., Kraichak E., Muangmai N.. Optimizing microsatellite marker panels for genetic diversity and population genetic studies: An ant colony algorithm approach with polymorphic information content.. Biology 2023;12:1280.
    doi: 10.3390/biology12101280pmc: PMC10604496pubmed: 37886990google scholar: lookup
  10. Aberle K.S., Distl O. Domestication of the horse: Results based on microsatellite and mitochondrial DNA markers.. Arch. Anim. Breed. 2004;47:517–535.
    doi: 10.5194/aab-47-517-2004google scholar: lookup
  11. Balloux F., Lugon-Moulin N. The estimation of population differentiation with microsatellite markers.. Mol. Ecol. 2002;11:155–165.
    doi: 10.1046/j.0962-1083.2001.01436.xpubmed: 11856418google scholar: lookup
  12. Cunningham E.P., Dooley J.J., Splan R.K., Bradley D.G. Microsatellite diversity, pedigree relatedness and the contributions of founder lineages to thoroughbred horses.. Anim. Genet. 2001;32:360–364.
    doi: 10.1046/j.1365-2052.2001.00785.xpubmed: 11736806google scholar: lookup
  13. Wallner B., Piumi F., Brem G., Müller M., Achmann R. Isolation of Y chromosome-specific microsatellites in the horse and cross-species amplification in the genus Equus.. J. Hered. 2004;95:158–164.
    doi: 10.1093/jhered/esh020pubmed: 15073232google scholar: lookup
  14. Katsoulakou M.E., Papachristou D., Kostaras N., Laliotis G., Bizelis I., Cothran E.G., Juras R., Koutsouli P. Genetic variability of small horse populations from Greek islands.. BSJ Agri. 2023;6:117–125.
    doi: 10.47115/bsagriculture.1165045google scholar: lookup
  15. Sanger F., Nicklen S., Coulson A.R. DNA sequencing with chain-terminating inhibitors.. Proc. Natl. Acad. Sci. USA. 1977;74:5463–5467.
    doi: 10.1073/pnas.74.12.5463pmc: PMC431765pubmed: 271968google scholar: lookup
  16. Ellegren H. Microsatellites: Simple sequences with complex evolution. Nat. Rev. Genet. 2004;5:435–445.
    doi: 10.1038/nrg1348pubmed: 15153996google scholar: lookup
  17. Haasl RJ, Payseur BA. Multi-locus inference of population structure: A comparison between single nucleotide polymorphisms and microsatellites. Heredity 2011;106:158–171.
    doi: 10.1038/hdy.2010.21pmc: PMC2892635pubmed: 20332809google scholar: lookup
  18. Ablondi M, Vasini M, Beretti V, Superchi P, Sabbioni A. Exploring genetic diversity in an Italian Horse native breed to develop strategies for preservation and management. J. Anim. Breed. Genet. 2018;135:450–459.
    doi: 10.1111/jbg.12357pubmed: 30136312google scholar: lookup
  19. Baena MM, Gervásio IC, Rocha RDFB, Procópio AM, De Moura RS, Meirelles SLC. Population structure and genetic diversity of Mangalarga Marchador horses. Livest. Sci. 2020;239:104109.
    doi: 10.1016/j.livsci.2020.104109google scholar: lookup
  20. Ivanković A, Bittante G, Konjačić M, Kelava Ugarković N, Pećina M, Ramljak J. Evaluation of the Conservation Status of the Croatian Posavina horse breed based on pedigree and microsatellite data. Animals 2021;11:2130.
    doi: 10.3390/ani11072130pmc: PMC8300408pubmed: 34359258google scholar: lookup
  21. Stasiol LD, Perrotta G, Blasi M, Lisa C. Genetic characterization of the Bardigiano horse using microsatellite markers. Ital. J. Anim. Sci. 2008;7:243–250.
    doi: 10.4081/ijas.2008.243google scholar: lookup
  22. Janova E, Futas J, Klumplerova M, Putnova L, Vrtkova I, Vyskocil M, Frolkova P, Horin P. Genetic diversity and conservation in a small endangered horse population. J. Appl. Genet. 2013;54:285–292.
    doi: 10.1007/s13353-013-0151-3pubmed: 23649723google scholar: lookup
  23. Seo J-H, Park K-D, Lee H-K, Kong H-S. Genetic diversity of Halla horses using microsatellite markers. J. Anim. Sci. Technol. 2016;58:40.
    doi: 10.1186/s40781-016-0120-6pmc: PMC5114825pubmed: 27891245google scholar: lookup
  24. Seyedabadi HR, Sofla SS. Microsatellite analysis for parentage verification and genetic characterization of the Turkmen horse population. Kafkas Univ. Vet. Fak. Derg. 2017;23:467–471.
  25. Machmoum M, Boujenane I, Azelhak R, Badaoui B, Petit D, Piro M. Genetic Diversity and population structure of Arabian horse populations using microsatellite markers. J. Equine Vet. Sci. 2020;93:103200.
    doi: 10.1016/j.jevs.2020.103200pubmed: 32972687google scholar: lookup
  26. Fornal A, Kowalska K, Zabek T, Piestrzynska-Kajtoch A, Musiał AD, Ropka-Molik K. Genetic diversity and population structure of Polish Konik horse based on individuals from all the male founder lines and microsatellite markers. Animals 2020;10:1569.
    doi: 10.3390/ani10091569pmc: PMC7552212pubmed: 32899310google scholar: lookup
  27. Nadeem M.A., Nawaz M.A., Shahid M.Q., Doğan Y., Comertpay G., Yıldız M., Hatipoğlu R., Ahmad F., Alsaleh A., Labhane N.. DNA molecular markers in plant breeding: Current status and recent advancements in genomic selection and genome editing. Biotechnol. Biotechnol. Equip. 2018;32:261–285.
    doi: 10.1080/13102818.2017.1400401google scholar: lookup
  28. Amiteye S.. Basic Concepts and methodologies of DNA marker systems in plant molecular breeding. Heliyon 2021;7:e08093.
    doi: 10.1016/j.heliyon.2021.e08093pmc: PMC8569399pubmed: 34765757google scholar: lookup
  29. Alves S.I.A., Dantas C.W.D., Macedo D.B., Ramos R.T.J.. What are microsatellites and how to choose the best tool: A user-friendly review of SSR and 74 SSR mining tools. Front. Genet. 2024;15:1474611.
    doi: 10.3389/fgene.2024.1474611pmc: PMC11599195pubmed: 39606018google scholar: lookup
  30. Khanshour A., Conant E., Juras R., Cothran E.G.. Microsatellite analysis of genetic diversity and population structure of Arabian horse populations. J. Hered. 2013;104:386–398.
    doi: 10.1093/jhered/est003pubmed: 23450090google scholar: lookup
  31. Raguz N., Korabi N., Lukić B., Drzaic I., Vostry L., Moravcikova N., Curik I., Kasarda R., Cubric-Curik V.. Genomic characterization and population structure of Croatian Arabian horse. Livest. Sci. 2023;277:105343.
    doi: 10.1016/j.livsci.2023.105343google scholar: lookup
  32. Binns M.M., Holmes N.G., Holliman A., Scott A.M.. Genetic diversity in Bulgarian Thoroughbred using microsatellite DNA markers. Br. Vet. J. 1995;151:9–15.
    doi: 10.1016/S0007-1935(05)80057-0pubmed: 7735875google scholar: lookup
  33. Bowling A.T., Eggleston-Stott M.L., Byrns G., Clark R.S., Dileanis S., Wictum E.. Validation of microsatellite markers for routine horse parentage testing. Anim. Genet. 1997;28:247–252.
    doi: 10.1111/j.1365-2052.1997.00123.xpubmed: 9345720google scholar: lookup
  34. Irvin Z., Giffard J., Brandon R., Breen M., Bell K.. Equine dinucleotide repeat polymorphisms at loci ASB 21, 23, 25 and 37-43. Anim. Genet. 1998;29:67.
    pubmed: 9682459
  35. Guerin G., Bertaud M., Amigues Y.. Characterization of seven new horse microsatellites: HMS1, HMS2, HMS3, HMS5, HMS6, HMS7 and HMS8. Anim. Genet. 1994;25:62.
    pubmed: 8161034
  36. Ellegren H., Johansson M., Sandberg K., Andersson L.. Cloning of highly polymorphic microsatellites in the horse. Anim. Genet. 1992;23:133–142.
    doi: 10.1111/j.1365-2052.1992.tb00032.xpubmed: 1443772google scholar: lookup
  37. Marklund S., Ellegren H., Eriksson S., Sandberg K., Andersson L.. Parentage testing and linkage analysis in the horse using a set of highly polymorphic microsatellites. Anim. Genet. 1994;25:19–23.
    doi: 10.1111/j.1365-2052.1994.tb00442.xpubmed: 8161016google scholar: lookup
  38. Peakall R., Smouse P.E.. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 2012;28:2537–2539.
    doi: 10.1093/bioinformatics/bts460pmc: PMC3463245pubmed: 22820204google scholar: lookup
  39. Nei M., Tajima F., Tateno Y.. Accuracy of estimated phylogenetic trees from molecular data. J. Mol. Evol. 1983;19:19153–19170.
    doi: 10.1007/BF02300753pubmed: 6571220google scholar: lookup
  40. Rodrigáñez J., Barragán C., Alves E., Gortázar C., Toro M.A., Silió L.. Genetic diversity and allelic richness in Spanish wild and domestic pig population estimated from microsatellite markers. Span. J. Agric. Res. 2008;6:107–115.
    doi: 10.5424/sjar/200806S1-379google scholar: lookup
  41. Kalinowski S.T.. HP-Rare: A computer program for performing rarefaction on measures of allelic diversity. Mol. Ecol. Notes 2005;5:187–189.
    doi: 10.1111/j.1471-8286.2004.00845.xgoogle scholar: lookup
  42. Weir B.S., Cockerham C.C.. Estimating F-statistics for the analysis of population structure. Evolution 1984;38:1358–1370.
    doi: 10.2307/2408641pubmed: 28563791google scholar: lookup
  43. Botstein D., White R.L., Skolnick M., Davis R.W.. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am. J. Hum. Genet. 1980;32:314–331.
    pmc: PMC1686077pubmed: 6247908
  44. Kalinowski S.T., Taper M.L., Marshall T.C.. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol. Ecol. 2007;16:1099–1106.
    doi: 10.1111/j.1365-294X.2007.03089.xpubmed: 17305863google scholar: lookup
  45. Pritchard J.K., Stephens M., Donnelly P.. Inference of population structure using multilocus genotype data. Genetics 2000;155:945–959.
    doi: 10.1093/genetics/155.2.945pmc: PMC1461096pubmed: 10835412google scholar: lookup
  46. Kopelman N.M., Mayzel J., Jakobsson M., Rosenberg N.A., Mayrose I.. Clumpak: A program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Resour. 2015;15:1179–1191.
    doi: 10.1111/1755-0998.12387pmc: PMC4534335pubmed: 25684545google scholar: lookup
  47. Rosenberg N.A.. Distruct: A program for the graphical display of population structure. Mol. Ecol. Notes 2004;4:137–138.
    doi: 10.1046/j.1471-8286.2003.00566.xgoogle scholar: lookup
  48. Evanno G., Regnaut S., Goudet J.. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 2005;14:2611–2620.
    doi: 10.1111/j.1365-294X.2005.02553.xpubmed: 15969739google scholar: lookup
  49. Puechmaille S.J.. The program structure does not reliably recover the correct population structure when sampling is uneven: Subsampling and new estimators alleviate the problem. Mol. Ecol. Resour. 2016;16:608–627.
    doi: 10.1111/1755-0998.12512pubmed: 26856252google scholar: lookup
  50. Yarali C., Köseman A., Özşensoy Y., Şeker İ., Toprak B., Zengin K.. Parentage verification and genetic diversity of the Arabian and Thoroughbred horse populations in Türkiye using microsatellite analysis. Schweiz. Arch. Tierheilkd. 2023;165:716–725.
    pubmed: 37905573
  51. Sargious M., El-Shawarby R., Abo-Salem M., EL-Shewy E., Ahmed H., Hagag N., Ramadan S.I.. Genetic diversity of Egyptian Arabian horses from El-Zahraa stud based on 14 TKY microsatellite markers. Slo. Vet. Res. 2021;58:2.
    doi: 10.26873/SVR-1041-2020google scholar: lookup
  52. Chapman J.R., Nakagawa S., Coltman D.W., Slate J., Sheldon B.C.. A Quantitative review of heterozygosity–fitness correlations in animal populations. Mol. Ecol. 2009;18:2746–2765.
    doi: 10.1111/j.1365-294X.2009.04247.xpubmed: 19500255google scholar: lookup
  53. Barker J.S.F.. Conservation and management of genetic diversity: A domestic animal perspective. Can. J. Forest. Res. 2001;31:588–595.
    doi: 10.1139/x00-180google scholar: lookup
  54. Gasca-Pineda J., Cassaigne I., Alonso R.A., Eguiarte L.E.. Effective population size, genetic variation, and their relevance for conservation: The bighorn sheep in Tiburon Island and comparisons with managed artiodactyls. PLoS ONE 2013;8:e78120.
    doi: 10.1371/journal.pone.0078120pmc: PMC3795651pubmed: 24147115google scholar: lookup
  55. Hong E.P., Park J.W.. Sample Size and Statistical Power Calculation in Genetic Association Studies. Genom. Inform. 2012;10:117.
    doi: 10.5808/GI.2012.10.2.117pmc: PMC3480678pubmed: 23105939google scholar: lookup
  56. Landguth E.L., Fedy B.C., Oyler-McCANCE S.J., Garey A.L., Emel S.L., Mumma M., Wagner H.H., Fortin M., Cushman S.A.. Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern. Mol. Ecol. Resour. 2012;12:276–284.
    doi: 10.1111/j.1755-0998.2011.03077.xgoogle scholar: lookup
  57. Meirmans P.G.. AMOVA-based clustering of population genetic data. J. Hered. 2012;103:744–750.
    doi: 10.1093/jhered/ess047pubmed: 22896561google scholar: lookup
  58. Valera M., Molina A., Gutierrez J.P., Gomez J., Goyache F.. Pedigree analysis in the Andalusian horse: Population structure, genetic variability and influence of the Carthusian strain. Livest. Prod. Sci. 2005;95:57–66.
    doi: 10.1016/j.livprodsci.2004.12.004google scholar: lookup
  59. Cosgrove E.J., Sadeghi R., Schlamp F., Holl H.M., Moradi-Shahrbabak M., Miraei-Ashtiani S.R., Abdalla S., Shykind B., Troedsson M., Stefaniuk-Szmukier M.. Genome Diversity and the Origin of the Arabian Horse. Sci. Rep. 2020;10:9702.
    doi: 10.1038/s41598-020-66232-1pmc: PMC7298027pubmed: 32546689google scholar: lookup
  60. Hristov P., Radoslavov G., Mehandjyiski I., Salkova D., Yordanov G.. Genetic diversity and population structure among Arabian horse genealogical lineages in Bulgaria. Diversity 2024;16:281.
    doi: 10.3390/d16050281pubmed: 40872726google scholar: lookup
  61. Głażewska I., Gralak B., Naczk A.M., Prusak B.. Genetic diversity and population structure of Polish Arabian horses assessed through breeding and microsatellite data. Anim. Sci. J. 2018;89:735–742.
    doi: 10.1111/asj.12983pubmed: 29392792google scholar: lookup

Citations

This article has been cited 1 times.
  1. Jlassi M, Dhifalli I, Ouled Ahmed H, Lasfar F, El Gtari M, Jemmali B. Genetic Characterization of the Arabian Horse Population in Tunisia Using Microsatellites. Life (Basel) 2025 Dec 16;15(12).
    doi: 10.3390/life15121925pubmed: 41465863google scholar: lookup
Subscribe to our newsletter
Join 99,911 horse owners like you who receive our email updates on horse health and nutrition.