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Genes2025; 16(9); 1054; doi: 10.3390/genes16091054

Insights into Genomic Patterns of Homozygosity in the Endangered Dülmen Wild Horse Population.

Abstract: Dülmen wild horses are kept in a fenced wooden and marsh area around Dülmen in Westphalia, Germany, since 1856. Previous analyses supported early genetic divergence from other domesticated horse populations and the Przewalski horse. Therefore, the objective of this study was to evaluate genetic diversity using high-density genomic data. Methods: We collected 337 one-year-old male Dülmen wild horses, captured at 12 annual auctions, for genotyping on the Illumina GGP Equine Plus Beadchip. All analyses were performed for 63,123 autosomal SNPs. Results: On average, each horse had 27.96 ROH with an average length of 8.237 Mb, resulting in an average genomic inbreeding coefficient F of 0.107. ROH with a length of 2-4 Mb were most frequent, and the next frequent ROH fall into the length categories of 4-8 and 8-16 Mb. The effective population size (N) steadily decreased in the last 100 generations by 4.57 individuals per generation from 498 to 41. We identified 10 ROH islands on equine chromosomes 1, 4, 5, 7, 9, and 10. Only one ROH island on ECA 1 was shared by 45% of the horses. Overrepresented genes of ROH islands were associated with glycerophospholipid catabolism through genes, skeletal muscle contraction (, ), synapse activity and structure (), regulation of inflammatory response ( genes), and genes, which are involved in many cellular processes and may also act as tumor suppressors and oncogenes. Conclusions: This study highlights the development of genomic inbreeding and shows the importance of the stallions selected for breeding on the genetic diversity of the Dülmen wild horses. The results of this study should be used to develop strategies to slow down increase in inbreeding and prevent transmitting unfavorable alleles from the stallions to the next generation.
Publication Date: 2025-09-08 PubMed ID: 41009997PubMed Central: PMC12469691DOI: 10.3390/genes16091054Google Scholar: Lookup
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  • Journal Article

Summary

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Overview

  • This study investigates the genetic diversity and patterns of genomic homozygosity in the endangered Dülmen wild horse population using high-density genomic data.
  • The research aims to understand inbreeding levels, population size changes, and the genetic regions under homozygosity to inform conservation management strategies.

Background and Objective

  • The Dülmen wild horses have been maintained in a restricted fenced habitat in Westphalia, Germany, since 1856.
  • Previous studies showed that Dülmen wild horses genetically diverged early from domesticated horses and the Przewalski horse, indicating a unique genetic lineage.
  • The primary goal was to assess genetic diversity and inbreeding using detailed genomic data to better understand population structure and risks.

Methods

  • Sampling: 337 one-year-old male Dülmen wild horses were sampled over 12 annual auctions for this study.
  • Genotyping: Horses were genotyped using the Illumina GGP Equine Plus Beadchip, covering 63,123 autosomal single nucleotide polymorphisms (SNPs).
  • Analysis focused on runs of homozygosity (ROH) to measure genomic inbreeding and identify regions of the genome consistent across horses.

Key Findings

  • Each horse carried an average of about 28 ROHs with an average ROH length of 8.237 megabases (Mb).
  • The average genomic inbreeding coefficient (F) across the population was 0.107, indicating moderate inbreeding levels.
  • More frequent ROHs were shorter (2-4 Mb), with many also occurring in length categories of 4-8 Mb and 8-16 Mb, suggesting a mix of recent and older inbreeding events.
  • Effective population size (Ne) steadily declined over the last 100 generations, decreasing by approximately 4.57 individuals each generation, from 498 to around 41.
  • Ten highly homozygous genomic regions known as ROH islands were detected on six chromosomes (ECA 1, 4, 5, 7, 9, and 10), with one island on chromosome 1 present in 45% of horses.

Functional Insights from ROH Islands

  • Genes in ROH islands were linked to important biological pathways and functions, including:
    • Glycerophospholipid catabolism – critical in membrane lipid metabolism.
    • Skeletal muscle contraction – relevant for horse mobility and strength.
    • Synapse activity and structure – involved in neuronal signaling and brain function.
    • Regulation of inflammatory response – important for immune system function.
    • Genes with roles in cellular processes that may act as tumor suppressors or oncogenes, indicating possible impacts on health and disease susceptibility.

Conclusions and Conservation Implications

  • The study demonstrates that genomic inbreeding in the Dülmen wild horse population is increasing due to a reduction in effective population size and possibly breeding choices.
  • Stallions have a considerable influence on genetic diversity, highlighting the need for careful selection to avoid propagating deleterious alleles.
  • Findings emphasize the importance of monitoring genomic inbreeding and incorporating genetic information into breeding programs to maintain diversity and reduce risks of genetic disorders.
  • These insights can help guide conservation strategies to slow down inbreeding and preserve the health and vitality of this endangered horse population.

Cite This Article

APA
Duderstadt S, Distl O. (2025). Insights into Genomic Patterns of Homozygosity in the Endangered Dülmen Wild Horse Population. Genes (Basel), 16(9), 1054. https://doi.org/10.3390/genes16091054

Publication

ISSN: 2073-4425
NlmUniqueID: 101551097
Country: Switzerland
Language: English
Volume: 16
Issue: 9
PII: 1054

Researcher Affiliations

Duderstadt, Silke
  • Institute of Animal Breeding and Genetics, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany.
Distl, Ottmar
  • Institute of Animal Breeding and Genetics, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany.

MeSH Terms

  • Animals
  • Horses / genetics
  • Male
  • Endangered Species
  • Homozygote
  • Polymorphism, Single Nucleotide
  • Inbreeding
  • Genome
  • Genomics / methods
  • Animals, Wild / genetics
  • Germany

Conflict of Interest Statement

The authors declare no conflicts of interest.

References

This article includes 48 references
  1. Opora J. Die Wildbahngestüte Westfalens: Geschichte, Entwicklung und Zukunft.. Ph.D. Thesis. Tierärztliche Hochschule Hannover; Hannover, Germany: 2006.
  2. Duderstadt S, Distl O. Genetic Diversity and Population Structure of Dülmen Wild, Liebenthal and Polish Konik Horses in Comparison with Przewalski, Sorraia, German Draught and Riding Horses.. Animals 2024;14:2221.
    doi: 10.3390/ani14152221pmc: PMC11311111pubmed: 39123746google scholar: lookup
  3. Duderstadt S, Distl O. Influence of Sires on Population Substructure in Dülmen Wild Horses.. Animals 2024;14:2904.
    doi: 10.3390/ani14192904pmc: PMC11475081pubmed: 39409853google scholar: lookup
  4. 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
  5. Fornal A, Kowalska K, Zabek T, Piestrzynska-Kajtoch A, Musiał AD, Ropka-Molik K. Genetic Variability and Population Structure of Polish Konik Horse Maternal Lines Based on Microsatellite Markers.. Genes 2021;12:546.
    doi: 10.3390/genes12040546pmc: PMC8069725pubmed: 33918718google scholar: lookup
  6. Aberle KS, Hamann H, Drögemuller C, Distl O. Genetic diversity in German draught horse breeds compared with a group of primitive, riding and wild horses by means of microsatellite DNA markers.. Anim. Genet. 2004;35:270–277.
  7. Druml T, Curik I, Baumung R, Aberle K, Distl O, Sölkner J. Individual-based assessment of population structure and admixture in Austrian, Croatian and German draught horses.. Heredity 2007;98:114–122.
    doi: 10.1038/sj.hdy.6800910pubmed: 17035951google scholar: lookup
  8. Howard JT, Pryce JE, Baes C, Maltecca C. Invited review: Inbreeding in the genomics era: Inbreeding, inbreeding depression, and management of genomic variability.. J. Dairy Sci. 2017;100:6009–6024.
    doi: 10.3168/jds.2017-12787pubmed: 28601448google scholar: lookup
  9. Gurgul A, Jasielczuk I, Semik-Gurgul E, Pawlina-Tyszko K, Stefaniuk-Szmukier M, Szmatoła T, Polak G, Tomczyk-Wrona I, Bugno-Poniewierska M. A genome-wide scan for diversifying selection signatures in selected horse breeds.. PLoS ONE 2019;14:e0210751.
  10. Polak G, Gurgul A, Jasielczuk I, Szmatoła T, Krupiński J, Bugno-Poniewierska M. Suitability of pedigree information and genomic methods for analyzing inbreeding of Polish cold-blooded horses covered by conservation programs.. Genes 2021;12:429.
    doi: 10.3390/genes12030429pmc: PMC8002693pubmed: 33802830google scholar: lookup
  11. Kaminski S, Hering DM, Jaworski Z, Zabolewicz T, Rusc A, Kaminski S, Hering DM, Jaworski Z, Zabolewicz T, Rusc A. Assessment of genomic inbreeding in Polish Konik horses.. Pol. J. Vet. Sci. 2017;20:603–605.
    doi: 10.1515/pjvs-2017-0074pubmed: 29166287google scholar: lookup
  12. Szmatoła T, Gurgul A, Jasielczuk I, Oclon E, Ropka-Molik K, Stefaniuk-Szmukier M, Polak G, Tomczyk-Wrona I, Bugno-Poniewierska M. Assessment and distribution of runs of homozygosity in horse breeds representing different utility types.. Animals 2022;12:3293.
    doi: 10.3390/ani12233293pmc: PMC9736150pubmed: 36496815google scholar: lookup
  13. Druml T, Neuditschko M, Grilz-Seger G, Horna M, Ricard A, Mesarič M, Cotman M, Pausch H, Brem G. Population networks associated with runs of homozygosity reveal new insights into the breeding history of the Haflinger horse.. J. Hered. 2018;109:384–392.
    doi: 10.1093/jhered/esx114pubmed: 29294044google scholar: lookup
  14. Grilz-Seger G, Neuditschko M, Ricard A, Velie B, Lindgren G, Mesarič M, Cotman M, Horna M, Dobretsberger M, Brem G. Genome-wide homozygosity patterns and evidence for selection in a set of European and near eastern horse breeds.. Genes 2019;10:491.
    doi: 10.3390/genes10070491pmc: PMC6679042pubmed: 31261764google scholar: lookup
  15. Kasarda R, Moravčíková N, Kadlečík O, Trakovická A, Halo M, Candrák J. Level of inbreeding in Norik of Muran horse: Pedigree vs. genomic data.. Acta Univ. Agric. Silvic. Mendel. Brun. 2019;67:1457–1463.
  16. Mancin E, Ablondi M, Mantovani R, Pigozzi G, Sabbioni A, Sartori C. Genetic variability in the Italian heavy draught horse from pedigree data and genomic information.. Animals 2020;10:1310.
    doi: 10.3390/ani10081310pmc: PMC7460293pubmed: 32751586google scholar: lookup
  17. Gmel A.I., Mikko S, Ricard A, Velie B.D., Gerber V, Hamilton N.A., Neuditschko M. Using high-density SNP data to unravel the origin of the Franches-Montagnes horse breed.. Genet. Sel. Evol. 2024;56:53.
    doi: 10.1186/s12711-024-00922-6pmc: PMC11238448pubmed: 38987703google scholar: lookup
  18. Schurink A, Shrestha M, Eriksson S, Bosse M, Bovenhuis H, Back W, Johansson A.M., Ducro B.J. The genomic makeup of nine horse populations sampled in the Netherlands.. Genes 2019;10:480.
    doi: 10.3390/genes10060480pmc: PMC6627704pubmed: 31242710google scholar: lookup
  19. Grilz-Seger G, Druml T, Neuditschko M, Dobretsberger M, Horna M, Brem G. High-resolution population structure and runs of homozygosity reveal the genetic architecture of complex traits in the Lipizzan horse.. BMC Genom. 2019;20:174.
    doi: 10.1186/s12864-019-5564-xpmc: PMC6402180pubmed: 30836959google scholar: lookup
  20. Curik I, Ferenčaković M, Sölkner J. Inbreeding and runs of homozygosity: A possible solution to an old problem.. Livest. Sci. 2014;166:26–34.
  21. Ablondi M, Dadousis C, Vasini M, Eriksson S, Mikko S, Sabbioni A. Genetic diversity and signatures of selection in a native italian horse breed based on SNP data.. Animals 2020;10:1005.
    doi: 10.3390/ani10061005pmc: PMC7341496pubmed: 32521830google scholar: lookup
  22. 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. 2019;50:334–346.
    doi: 10.1111/age.12797pmc: PMC6617995pubmed: 31199540google scholar: lookup
  23. Metzger J, Karwath M, Tonda R, Beltran S, Águeda L, Gut M, Gut I.G., Distl O. Runs of homozygosity reveal signatures of positive selection for reproduction traits in breed and non-breed horses.. BMC Genom. 2015;16:764.
    doi: 10.1186/s12864-015-1977-3pmc: PMC4600213pubmed: 26452642google scholar: lookup
  24. Sigurðardóttir H, Ablondi M, Kristjansson T, Lindgren G, Eriksson S. Genetic diversity and signatures of selection in Icelandic horses and Exmoor ponies.. BMC Genom. 2024;25:772.
    pmc: PMC11308356pubmed: 39118059
  25. Ablondi M, Viklund Å, Lindgren G, Eriksson S, Mikko S. Signatures of selection in the genome of Swedish warmblood horses selected for sport performance.. BMC Genom. 2019;20:717.
    doi: 10.1186/s12864-019-6079-1pmc: PMC6751828pubmed: 31533613google scholar: lookup
  26. Nolte W, Thaller G, Kuehn C. Selection signatures in four German warmblood horse breeds: Tracing breeding history in the modern sport horse.. PLoS ONE 2019;14:e0215913.
  27. Sievers J, Distl O. Genomic patterns of Homozygosity and Genetic Diversity in the Rhenish German Draught Horse.. Genes 2025;16:327.
    doi: 10.3390/genes16030327pmc: PMC11942601pubmed: 40149478google scholar: lookup
  28. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M.A., Bender D, Maller J, Sklar P, De Bakker P.I., Daly M.J. PLINK: A tool set for whole-genome association and population-based linkage analyses.. Am. J. Hum. Genet. 2007;81:559–575.
    doi: 10.1086/519795pmc: PMC1950838pubmed: 17701901google scholar: lookup
  29. Meyermans R, Gorssen W, Buys N, Janssens S. How to study runs of homozygosity using PLINK? A guide for analyzing medium density SNP data in livestock and pet species.. BMC Genom. 2020;21:94.
    doi: 10.1186/s12864-020-6463-xpmc: PMC6990544pubmed: 31996125google scholar: lookup
  30. Lencz T, Lambert C, DeRosse P, Burdick K.E., Morgan T.V., Kane J.M., Kucherlapati R, Malhotra A.K. Runs of homozygosity reveal highly penetrant recessive loci in schizophrenia.. Proc. Natl. Acad. Sci. USA 2007;104:19942–19947.
    doi: 10.1073/pnas.0710021104pmc: PMC2148402pubmed: 18077426google scholar: lookup
  31. Purfield DC, Berry DP, McParland S, Bradley DG. Runs of homozygosity and population history in cattle. BMC Genet 2012;13:70.
    doi: 10.1186/1471-2156-13-70pmc: PMC3502433pubmed: 22888858google scholar: lookup
  32. McQuillan R, Leutenegger A-L, Abdel-Rahman R, Franklin CS, Pericic M, Barac-Lauc L, Smolej-Narancic N, Janicijevic B, Polasek O, Tenesa A. Runs of homozygosity in European populations. Am. J. Hum. Genet. 2008;83:359–372.
    doi: 10.1016/j.ajhg.2008.08.007pmc: PMC2556426pubmed: 18760389google scholar: lookup
  33. Sved J. Linkage disequilibrium and homozygosity of chromosome segments in finite populations. Theor. Popul. Biol. 1971;2:125–141.
    doi: 10.1016/0040-5809(71)90011-6pubmed: 5170716google scholar: lookup
  34. Gutiérrez J, Cervantes I, Goyache F. Improving the estimation of realized effective population sizes in farm animals. J. Anim. Breed. Genet. 2009;126:327–332.
  35. Doekes HP, Curik I, Nagy I, Farkas J, Kövér G, Windig JJ. Revised calculation of Kalinowski’s ancestral and new inbreeding coefficients. Diversity 2020;12:155.
    doi: 10.3390/d12040155google scholar: lookup
  36. Harrison PW, Amode MR, Austine-Orimoloye O, Azov AG, Barba M, Barnes I, Becker A, Bennett R, Berry A, Bhai J. Ensembl 2024. Nucleic Acids Res. 2024;52:D891–D899.
    doi: 10.1093/nar/gkad1049pmc: PMC10767893pubmed: 37953337google scholar: lookup
  37. Thomas PD, Ebert D, Muruganujan A, Mushayahama T, Albou LP, Mi H. PANTHER: Making genome-scale phylogenetics accessible to all. Protein Sci. 2022;31:8–22.
    doi: 10.1002/pro.4218pmc: PMC8740835pubmed: 34717010google scholar: lookup
  38. Mi H, Muruganujan A, Huang X, Ebert D, Mills C, Guo X, Thomas PD. Protocol Update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0). Nat. Protoc. 2019;14:703–721.
    doi: 10.1038/s41596-019-0128-8pmc: PMC6519457pubmed: 30804569google scholar: lookup
  39. Howard JT, Tiezzi F, Huang Y, Gray KA, Maltecca C. A heuristic method to identify runs of homozygosity associated with reduced performance in livestock. J. Anim. Sci. 2017;95:4318–4332.
    doi: 10.2527/jas2017.1664pubmed: 29108032google scholar: lookup
  40. Baes CF, Makanjuola BO, Miglior F, Marras G, Howard JT, Fleming A, Maltecca C. Symposium review: The genomic architecture of inbreeding: How homozygosity affects health and performance. J. Dairy Sci. 2019;102:2807–2817.
    doi: 10.3168/jds.2018-15520pubmed: 30660425google scholar: lookup
  41. Tian X, Pascal G, Monget P. Evolution and functional divergence of NLRP genes in mammalian reproductive systems. BMC Evol. Biol. 2009;9:202.
    doi: 10.1186/1471-2148-9-202pmc: PMC2735741pubmed: 19682372google scholar: lookup
  42. Tong Z-B, Gold L, Pfeifer KE, Dorward H, Lee E, Bondy CA, Dean J, Nelson LM. Mater, a maternal effect gene required for early embryonic development in mice. Nat. Genet. 2000;26:267–268.
    doi: 10.1038/81547pubmed: 11062459google scholar: lookup
  43. Peng H, Liu F, Li W, Zhang W. Knockdown of NLRP5 arrests early embryogenesis in sows. Anim. Reprod. Sci. 2015;163:151–156.
  44. Romar R, De Santis T, Papillier P, Perreau C, Thélie A, Dell’Aquila ME, Mermillod P, Dalbiès-Tran R. Expression of maternal transcripts during bovine oocyte in vitro maturation is affected by donor age. Reprod. Domest. Anim. 2011;46:e23–e30.
  45. Ponsuksili S, Brunner RM, Goldammer T, Kühn C, Walz C, Chomdej S, Tesfaye D, Schellander K, Wimmers K, Schwerin M. Bovine NALP5, NALP8, and NALP9 genes: Assignment to a QTL region and the expression in adult tissues, oocytes, and preimplantation embryos. Biol. Reprod. 2006;74:577–584.
    doi: 10.1095/biolreprod.105.045096pubmed: 16339045google scholar: lookup
  46. Cassandri M, Smirnov A, Novelli F, Pitolli C, Agostini M, Malewicz M, Melino G, Raschellà G. Zinc-finger proteins in health and disease. Cell Death Discov. 2017;3:17071.
    doi: 10.1038/cddiscovery.2017.71pmc: PMC5683310pubmed: 29152378google scholar: lookup
  47. Emerson RO, Thomas JH. Adaptive evolution in zinc finger transcription factors. PLoS Genet. 2009;5:e1000325.
  48. Kamaliyan Z, Clarke TL. Zinc finger proteins: Guardians of genome stability. Front. Cell Dev. Biol. 2024;12:1448789.
    doi: 10.3389/fcell.2024.1448789pmc: PMC11306022pubmed: 39119040google scholar: lookup

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