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Genetica2026; 154(1); 16; doi: 10.1007/s10709-026-00266-7

Genetic diversity in the Criollo Argentino horse from SNP array data.

Abstract: The Criollo Argentino horse is a national symbol and a heritage breed that represents both cultural identity and a key component of traditional production systems in Argentina. This study aimed to assess the genetic differentiation of the Criollo Argentino relative to other horse breeds and to infer potential factors shaping its diversity through the genomic analysis of 24 representative animals. Samples were genotyped using a medium-density SNP array containing 65,157 markers, and genetic diversity analyses were conducted across autosomal SNP sets filtered under different criteria. Contemporary effective population size was estimated using both linkage disequilibrium from SNP data (Ne = 155.6) and pedigree analysis (fe = 157.7), showing remarkable consistency between genomic and genealogical approaches. Measures of expected heterozygosity, Hardy–Weinberg equilibrium, and linkage disequilibrium showed that Criollo Argentino horses retain moderate to high levels of genetic variability. Results further revealed that the Criollo Argentino is a genetically well-defined population with high within-individual diversity and clear differentiation from other breeds. In addition, the Criollo Argentino population was compared with eight other horse breeds to evaluate genetic distance and population structure. Estimates of genetic distance, population structure, and fixation index values were consistent with the documented history and development of the breed, while PCA and Bayesian clustering analyses supported a shared origin between the Criollo Argentino and the Peruvian Paso, both derived from Iberian horses introduced to the Americas during colonization. Overall, this work provides genomic evidence that strengthens the historical and biological characterization of the Criollo Argentino and supports informed decision-making for breeding, management, genetic improvement, and conservation programs for the breed.
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Publication Date: 2026-04-11 PubMed ID: 41965490PubMed Central: 2708199DOI: 10.1007/s10709-026-00266-7Google Scholar: Lookup
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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.

This study used genome-wide DNA markers to show that the Criollo Argentino horse is a genetically distinct breed with moderate-to-high diversity and a contemporary effective population size around 156, consistent between genomic and pedigree-based estimates. Analyses of population structure indicate clear differentiation from other breeds and a shared Iberian-derived origin with the Peruvian Paso.

What the researchers set out to do and why it matters

  • Evaluate how genetically distinct the Criollo Argentino is relative to other horse breeds and quantify its genetic diversity.
  • Provide genomic evidence to support breeding, management, genetic improvement, and conservation decisions for a culturally and economically important heritage breed.

Data and sampling

  • Sample: 24 representative Criollo Argentino horses.
  • Genotyping platform: medium-density SNP array with 65,157 markers covering the autosomes.
  • Comparative context: Criollo Argentino analyzed alongside eight other horse breeds to assess genetic distance and structure.

Quality control and analytical framework

  • Autosomal SNP sets were filtered under different criteria (e.g., missingness, minor allele frequency, Hardy–Weinberg equilibrium, and possibly linkage pruning) to ensure robust inference across sensitivity analyses.
  • Core population genetics metrics were computed, including expected heterozygosity, Hardy–Weinberg equilibrium tests, and linkage disequilibrium patterns.
  • Contemporary effective population size was estimated two ways:
    • From genome-wide linkage disequilibrium (Ne = 155.6).
    • From pedigree-based analysis (reported as fe = 157.7), providing a genealogical counterpart.
  • Population differentiation and structure were characterized via:
    • Genetic distance and fixation index (FST) among breeds.
    • Principal component analysis (PCA) for visualizing genomic variation.
    • Bayesian clustering (e.g., STRUCTURE/ADMIXTURE-style) to infer shared ancestry and admixture patterns.

Key concepts and how to interpret them

  • Expected heterozygosity: a measure of genetic variability; moderate-to-high values indicate a healthy reservoir of allelic diversity.
  • Hardy–Weinberg equilibrium: concordance suggests no strong recent inbreeding, assortative mating, or unmodeled substructure within the sampled group.
  • Linkage disequilibrium (LD): lower LD typically reflects larger effective population sizes and recombination breaking down allele associations; LD-based Ne translates the genome-wide LD signal into a recent population size proxy.
  • Effective population size (Ne): the size of an idealized population experiencing the same rate of genetic drift as the real population; it guides how fast diversity is lost and inbreeding accumulates.
  • Fixation index (FST) and genetic distance: quantify differentiation between breeds; higher values indicate more distinct gene pools.
  • PCA and Bayesian clustering: complementary tools to reveal relationships, ancestry components, and whether a population forms a tight, well-defined genetic cluster.

Main findings about the Criollo Argentino

  • Genetic diversity: Criollo Argentino horses show moderate-to-high variability (consistent with heterozygosity estimates and HWE tests), indicating a relatively diverse gene pool.
  • Effective size: The LD-based Ne of 155.6 closely matches the pedigree-derived estimate (fe = 157.7), demonstrating strong agreement between genomic and genealogical assessments of recent population size.
  • Population definition: The breed forms a genetically well-defined cluster, with high within-individual diversity and clear separation from other breeds.
  • Consistency across filters: Analyses repeated with differently filtered SNP sets converged on similar conclusions, supporting robustness.

Breed relationships and historical context

  • Differentiation: Genetic distance and FST values place the Criollo Argentino as distinct from the other eight comparison breeds, aligning with breed records and development history.
  • Shared origins: PCA and Bayesian clustering support a shared Iberian-derived origin between the Criollo Argentino and the Peruvian Paso, consistent with introductions of Iberian horses to the Americas during colonization.
  • Population structure: Clear clustering with limited recent admixture reinforces the notion of a managed, cohesive breeding population.

Implications for breeding, management, and conservation

  • Maintain diversity: The observed diversity and Ne are favorable, but continued monitoring is needed to avoid drift and inbreeding (e.g., balanced use of sires, avoiding genetic bottlenecks).
  • Use genomic data: Incorporate SNP data into selection and mate allocation to retain heterozygosity while achieving breeding goals.
  • Conservation planning: The breed’s distinctiveness justifies targeted conservation measures, including preservation of underrepresented lineages and cryo-banking of genetic material.
  • Breed improvement: Genomic tools can support selection for performance and health traits without eroding genetic variability.
  • Documentation and traceability: Align pedigree records with genomic information to validate ancestry and manage relatedness.

Strengths and limitations of the study

  • Strengths:
    • Concordance between genomic and pedigree-based estimates strengthens confidence in recent demographic inferences.
    • Multiple diversity metrics and cross-breed comparisons provide a comprehensive view of population status and distinctiveness.
    • Use of genome-wide SNPs enables fine-scale structure and ancestry analyses.
  • Limitations and cautions:
    • Sample size (n = 24) is modest; broader sampling across lines, regions, and management groups would refine estimates.
    • SNP arrays can introduce ascertainment bias (markers discovered in certain breeds may underrepresent variation unique to others), potentially affecting diversity metrics.
    • Ne reflects recent demographic signals; historical fluctuations or very recent management changes may require time-series monitoring to detect.

Recommended next steps

  • Expand sampling to capture all sublines and geographic regions within the breed.
  • Integrate whole-genome sequencing or high-density genotyping to reduce ascertainment bias and better resolve rare variation.
  • Implement routine genomic monitoring of Ne, inbreeding coefficients, runs of homozygosity, and relatedness to guide mating plans.
  • Map functional variation relevant to health and performance to balance selection objectives with diversity conservation.
  • Deepen comparative analyses across additional Latin American and Iberian-derived breeds to refine historical reconstructions.

Bottom line

  • The Criollo Argentino is a genetically distinct, well-structured breed with moderate-to-high diversity and a contemporary effective size near 156, corroborated by both genomic and pedigree analyses; these findings provide a solid foundation for informed breeding, management, and conservation strategies.

Cite This Article

APA
(2026). Genetic diversity in the Criollo Argentino horse from SNP array data. Genetica, 154(1), 16. https://doi.org/10.1007/s10709-026-00266-7

Publication

Genetica
ISSN: 1573-6857
NlmUniqueID: 0370740
Country: Netherlands
Language: English
Volume: 154
Issue: 1
PII: 16

Researcher Affiliations

Grant Funding

  • PICT2012-2610 / Agencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la Innovación

Conflict of Interest Statement

Declarations. Conflict of interest: The authors declare that they have no conflict of interest. Informed consent: Not applicable. Institutional Review Board Statement: The animal study protocol was approved by the Comité Institucional para el Cuidado y Uso de Animales de Laboratorio (CICUAL), Facultad de Ciencias Veterinarias de la Universidad Nacional de La Plata, Argentina (Protocol Number 89-2-18T, 2018-11-07).

References

This article includes 44 references
  1. Binns MM, Boehler DA, Bailey E, Lear TL, Cardwell JM, Lambert DH. Inbreeding in the Thoroughbred horse. Anim Genet 43(3):340–342.
    doi: 10.1111/j.1365-2052.2011.02259.xpubmed: 22486509google scholar: lookup
  2. Boichard D. PEDIG: a fortran package for pedigree analysis suited for large populations. In: Proceedings of the 7th world congress on genetics applied to livestock production, pp 28–13.
    doi: 10.5555/20033053742google scholar: lookup
  3. Boichard D, Maignel L, Verrier É. The value of using probabilities of gene origin to measure genetic variability in a population. Genet Sel Evol 29:5–23.
    doi: 10.1186/1297-9686-29-1-5pmc: 2708199google scholar: lookup
  4. Corbin LJ, Blott SC, Swinburne JE, Vaudin M, Bishop SC, Woolliams JA. Linkage disequilibrium and historical effective population size in the Thoroughbred horse. Anim Genet 41:8–15.
    doi: 10.1111/j.1365-2052.2010.02092.xpubmed: 21070270google scholar: lookup
  5. Cortés O, Dunner S, Gama LT, Martínez AM, Delgado JV, Ginja C, Vega-Pla JL. The legacy of Columbus in American horse populations assessed by microsatellite markers. J Anim Breed Genet 134:340–350.
    doi: 10.1111/jbg.12255pubmed: 28194814google scholar: lookup
  6. Dapper AL, Payseur BA. Effects of demographic history on the detection of recombination hotspots from linkage disequilibrium. Mol Biol Evol 35:335–353.
    doi: 10.1093/molbev/msx272google scholar: lookup
  7. Díaz S. Estudio comparativo de la variabilidad genética en poblaciones de equinos de diferentes razas mediante sus polimorfismos genéticos sanguíneos. Dissertation, Universidad Nacional de Misiones, Argentina.
  8. Díaz S. Estudio del polimorfismo y poligenismo de los loci DRB en caballos criollo argentino. Doctoral dissertation, Universidad Nacional de La Plata, La Plata.
    doi: 10.35537/10915/4578google scholar: lookup
  9. Díaz S, Giovambattista G, Dulout FN, Peral-García P. Genetic variation of the second exon of ELA-DRB genes in Argentine Creole horses. Anim Genet 32:257–263.
    doi: 10.1046/j.1365-2052.2001.00779.xpubmed: 11683711google scholar: lookup
  10. Díaz S, Ripoli MV, Peral García P, Giovambattista G. Marcadores genéticos para resistencia y susceptibilidad a enfermedades infecciosas en animales domésticos. Analecta Vet 25:40–52.
  11. Do C, Waples RS, Peel D, Macbeth GM, Tillett BJ, Ovenden JR. NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Mol Ecol Resour 14:209–214.
    doi: 10.1111/1755-0998.12157pubmed: 23992227google scholar: lookup
  12. Dowdall CR. Criando Criollos. Hemisferio Sur, Buenos Aires.
  13. Excoffier L, Lischer HEL. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour 10:564–567.
    doi: 10.1111/j.1755-0998.2010.02847.xpubmed: 21565059google scholar: lookup
  14. Excoffier L, Smouse PE, Quattro JM. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131:479–491.
    doi: 10.1093/genetics/131.2.479pubmed: 1644282pmc: 1205020google scholar: lookup
  15. Go YY, Bailey E, Cook F, Timoney P, Coleman S, MacLeod J, Balasuriya UBR. Genome-wide association study among four horse breeds identifies a common haplotype in ECA11 associated with CD3+ T-cell susceptibility/resistance to equine arteritis virus infection. J Equine Vet Sci 32:S74–S75.
    doi: 10.1128/jvi.06068-11google scholar: lookup
  16. Grilz-Seger G, Druml T, Neuditschko M, Mesarič M, Cotman M, Brem G. Analysis of ROH patterns in the Noriker horse breed reveals signatures of selection for coat color and body size. Anim Genet 50:334–346.
    doi: 10.1111/age.12797pubmed: 31199540pmc: 6617995google scholar: lookup
  17. Han H, McGivney BA, Farries G, Katz LM, MacHugh DE, Randhawa IA, Hill EW. Selection in Australian Thoroughbred horses acts on a locus associated with early two-year-old speed. PLoS ONE 15:e0227212.
    doi: 10.1371/journal.pone.0227212pubmed: 32049967pmc: 7015314google scholar: lookup
  18. James JW. Computation of genetic contributions from pedigrees. Theor Appl Genet 42:272–273.
    doi: 10.1007/BF00277555pubmed: 24431023google scholar: lookup
  19. Kienast ME. Estudio de polimorfismos genéticos en poblaciones equinas de Argentina. .
    doi: 10.35537/10915/1566google scholar: lookup
  20. Luis C, Bastos-Silveira C, Cothran EG, Oom MDM. Iberian origins of New World horse breeds. J Hered 97:107–113.
    doi: 10.1093/jhered/esj020pubmed: 16489143google scholar: lookup
  21. McCue ME, Bannasch DL, Petersen JL, Gurr J, Bailey E, Binns MM, Leeb T. A high-density SNP array for the domestic horse and extant Perissodactyla: utility for association mapping, genetic diversity, and phylogeny studies. PLoS Genet 8:e1002451.
    doi: 10.1371/journal.pgen.1002451pubmed: 22253606pmc: 3257288google scholar: lookup
  22. McGivney BA, Han H, Corduff LR, Katz LM, Tozaki T, MacHugh DE, Hill EW. Genomic inbreeding trends, influential sire lines and selection in the global Thoroughbred horse population. Sci Rep 10:466.
    doi: 10.1038/s41598-019-57389-5pubmed: 31949252pmc: 6965197google scholar: lookup
  23. Metzger J, Karwath M, Tonda R, Beltran S, Águeda L, Gut M, Gut IG, Distl O. Runs of homozygosity reveal signatures of positive selection for reproduction traits in breed and non-breed horses. BMC Genomics 16:764.
    doi: 10.1186/s12864-015-1977-3pubmed: 26452642pmc: 4600213google scholar: lookup
  24. Mirol PM, Peral-García P, Vega-Pla JL, Dulout FN. Phylogenetic relationships of Argentinean Creole horses and other South American and Spanish breeds inferred from mitochondrial DNA sequences. Anim Genet 33:356–363.
    doi: 10.1046/j.1365-2052.2002.00884.xpubmed: 12354144google scholar: lookup
  25. Nei M, Maruyama T, Chakraborty R. The bottleneck effect and genetic variability in populations. Evolution 29:1–10.
    doi: 10.2307/2407137pubmed: 28563291google scholar: lookup
  26. Orr N, Back W, Gu J, Leegwater P, Govindarajan P, Conroy J, Brama PAJ. Genome-wide SNP association-based localization of a dwarfism gene in Friesian dwarf horses. Anim Genet 41:2–7.
    doi: 10.1111/j.1365-2052.2010.02091.xpubmed: 21070269google scholar: lookup
  27. Paz SA, Abbiati NN, Topayan MV, Refojo D, Trigo P. Evaluación de la aplicación de técnicas de vinculación y aprendizaje no traumáticas en dos razas equinas durante la ventana de aprendizaje. Rev Divulg Tecn Agropecu Agroind Ambient 5:10–22.
  28. Peral García P. Caracterización racial de equinos de pura raza criolla. .
  29. Peral García P, Kienast ME, Villegas Castagnasso EE, Díaz S, Dulout FN. Genetic relationship between horse breeds through multivaried analysis. Agro Sur 24:39–47.
  30. Petersen JL, Mickelson JR, Cothran EG, Andersson LS, Axelsson J, Bailey E, McCue ME. Genetic diversity in the modern horse illustrated from genome-wide SNP data. PLoS ONE 8:e54997.
    doi: 10.1371/journal.pone.0054997pubmed: 23383025pmc: 3559798google scholar: lookup
  31. Petersen JL, Mickelson JR, Rendahl AK, Valberg SJ, Andersson LS, Axelsson J, Bailey E, Bannasch D, Binns MM, Borges AS, Brama P, da Câmara Machado A, Capomaccio S, Cappelli K, Cothran EG, Distl O, Fox-Clipsham L, Graves KT, Guérin G, Haase B, Hasegawa T, Hemmann K, Hill EW, Leeb T, Lindgren G, Lohi H, Lopes MS, McGivney BA, Mikko S, Orr N, Penedo MCT, Piercy RJ, Raekallio M, Rieder S, Røed KH, Swinburne J, Tozaki T, Vaudin M, Wade CM, McCue ME. Genome-wide analysis reveals selection for important traits in domestic horse breeds. PLoS Genet 9(1):e1003211.
    doi: 10.1371/journal.pgen.1003211pubmed: 23349635pmc: 3547851google scholar: lookup
  32. Pilot M, Greco C, Vonholdt BM, Jędrzejewska B, Randi E, Jędrzejewski W. Genome-wide signatures of population bottlenecks and diversifying selection in European wolves. Heredity 112:428–442.
    doi: 10.1038/hdy.2013.122pubmed: 24346500google scholar: lookup
  33. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Sham PC. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575.
    doi: 10.1086/519795pubmed: 17701901pmc: 1950838google scholar: lookup
  34. Raj A, Stephens M, Pritchard JK. fastSTRUCTURE: variational inference of population structure in large SNP data sets. Genetics 197:573–589.
    doi: 10.1534/genetics.114.164350pubmed: 24700103pmc: 4063916google scholar: lookup
  35. Rockwell H, Mack M, Famula T, Sandmeyer L, Bauer B, Dwyer A, Bellone RR. Genetic investigation of equine recurrent uveitis in Appaloosa horses. Anim Genet 51:111–116.
    doi: 10.1111/age.12883pubmed: 31793009google scholar: lookup
  36. RStudio Team. RStudio: Integrated Development for R. .
  37. Sadaba S. Estudio de la composición genética de caballos de biotipo deportivo de la raza Árabe en Argentina mediante la caracterización de haplotipos de clase II del MHC y haplotipos de ADN mitocondrial. .
  38. Schurink A, Shrestha M, Eriksson S, Bosse M, Bovenhuis H, Back W, Ducro BJ. The genomic makeup of nine horse populations sampled in the Netherlands. Genes 10:480.
    doi: 10.3390/genes10060480pubmed: 31242710pmc: 6627704google scholar: lookup
  39. Steensma MJ, Doekes HP, Pook T, Derks MF, Bakker N, Ducro BJ. Evaluation of breeding strategies to reduce the inbreeding rate in the Friesian horse population. J Anim Breed Genet 141:668–684.
    doi: 10.1111/jbg.12872pubmed: 38745529google scholar: lookup
  40. Villegas Castagnasso EE. Asociación entre marcadores genéticos y la producción de gonadotrofina coriónica equina (eCG). .
  41. Wade CM, Giulotto E, Sigurdsson S, Zoli M, Gnerre S, Imsland F, Lindblad-Toh K. Genome sequence, comparative analysis, and population genetics of the domestic horse. Science 326:865–867.
    doi: 10.1126/science.1178158pubmed: 19892987pmc: 3785132google scholar: lookup
  42. Wang W, Wang S, Hou C, Xing Y, Cao J, Wu K, Zhou H. Genome-wide detection of copy number variations among diverse horse breeds by array CGH. PLoS ONE 9:e86860.
    doi: 10.1371/journal.pone.0086860pubmed: 24497987pmc: 3907382google scholar: lookup
  43. Wolfsberger WW, Ayala NM, Castro-Marquez SO, Irizarry-Negron VM, Potapchuk A, Shchubelka K, Potish L, Majeske AJ, Oliver LF, Lameiro AD, Martínez-Cruzado JC, Lindgren G, Oleksyk TK. Genetic diversity and selection in Puerto Rican horses. Sci Rep 12(1):515.
    doi: 10.1038/s41598-021-04537-5pubmed: 35017609pmc: 8752667google scholar: lookup
  44. Wright S. The theory of gene frequencies. .

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