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Home / Equine Research Bank / Animals (Basel) / SNP-Based Heritability of Osteochondrosis Dissecans in Hanov...
Animals : an open access journal from MDPI2023; 13(9); doi: 10.3390/ani13091462

SNP-Based Heritability of Osteochondrosis Dissecans in Hanoverian Warmblood Horses.

Abstract: Before the genomics era, heritability estimates were performed using pedigree data. Data collection for pedigree analysis is time consuming and holds the risk of incorrect or incomplete data. With the availability of SNP-based arrays, heritability can now be estimated based on genotyping data. We used SNP array and 1.6 million imputed genotype data with different minor allele frequency restrictions to estimate heritabilities for osteochondrosis dissecans in the fetlock, hock and stifle joints of 446 Hanoverian warmblood horses. SNP-based heritabilities were estimated using a genomic restricted maximum likelihood (GREML) method and accounting for patterns of regional linkage disequilibrium in the equine genome. In addition, we employed GREML for family data to account for different degrees of relatedness in the study population. Our results indicate that we were able to capture a larger proportion of additive genetic variance compared to pedigree-based estimates in the same population of Hanoverian horses. Heritability estimates on the linear scale for fetlock-, hock- and stifle-osteochondrosis dissecans were 0.41-0.43, 0.62-0.63, and 0.23-0.25, respectively, with standard errors of 0.11-0.14. Accounting for linkage disequilibrium patterns had an upward effect on the imputed data and a downward impact on the SNP array genotype data. GREML for family data resulted in higher heritability estimates for fetlock-osteochondrosis dissecans and slightly higher estimates for hock-osteochondrosis dissecans, but had no effect on stifle-osteochondrosis dissecans. The largest and most consistent heritability estimates were obtained when we employed GREML for family data with genomic relationship matrices weighted through patterns of regional linkage disequilibrium. Estimation of SNP-based heritability should be recommended for traits that can only be phenotyped in smaller samples or are cost-effective.
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Publication Date: 2023-04-25 PubMed ID: 37174498PubMed Central: PMC10177438DOI: 10.3390/ani13091462Google Scholar: Lookup
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  • 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.

The study focuses on using a new method (genotype data from SNP arrays) to estimate the heritability of osteochondrosis dissecans, a common joint disorder in Hanoverian warmblood horses, and shows that this method provides more accurate estimates compared to the traditional pedigree analysis.

Background and Methodology

  • The researchers conducted an investigation on osteochondrosis dissecans, a common ailment in Hanoverian warmblood horses, affecting the fetlock, hock, and stifle joints. The aim was to use Single Nucleotide Polymorphism (SNP)-based genotyping data to estimate the heritability of this disorder in these horses.
  • In the past, heritability estimates relied largely on pedigree data – a slow, possibly imprecise method due to potential inaccuracies or omissions in the data.
  • Using SNP array and 1.6 million imputed genotype data with varied minor allele frequency restrictions enabled the researchers to utilize a contemporary method for the heritability estimation.
  • The application of a genomic restricted maximum likelihood (GREML) method, which takes into account the regional correlation within the genes (termed “linkage disequilibrium”), was instrumental in SNP-based heritability estimation.
  • Also, this study factored in different relationships in the horse population by utilizing GREML for family data.

Results and Implication

  • The SNP-based heritability method showed better capture of the additive genetic variance when compared to pedigree-based estimates, depicting it as a more precise approach.
  • This study provided distinct heritability estimates for each osteochondrosis dissecans type. The fetlock, hock, and stifle estimates were 0.41-0.43, 0.62-0.63, and 0.23-0.25, respectively.
  • Careful consideration of linkage disequilibrium patterns influenced the accuracy of the data. They elevated the imputed data’s effect and reduced the impact of the SNP array genotype data.
  • GREML for family data significantly increased the heritability estimates for fetlock- and hock-osteochondrosis dissecans, but made no difference for stifle-osteochondrosis dissecans.
  • The study indicated that the most accurate heritability estimates resulted from implementing GREML for family data, especially when genomic relationship matrices were weighted by patterns of regional linkage disequilibrium.
  • The abstract concludes by advocating for the use of SNP-based heritability estimation methods for traits prone to be phenotyped in smaller samples or for cost-effective pursuits.

Cite This Article

APA
Zimmermann E, Distl O. (2023). SNP-Based Heritability of Osteochondrosis Dissecans in Hanoverian Warmblood Horses. Animals (Basel), 13(9). https://doi.org/10.3390/ani13091462

Publication

Animals : an open access journal from MDPI
ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 13
Issue: 9

Researcher Affiliations

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

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 53 references
  1. Distl O. The genetics of equine osteochondrosis.. Vet. J. 2013;197:13–18.
    doi: 10.1016/j.tvjl.2013.03.036pubmed: 23809989google scholar: lookup
  2. van Weeren R. Fifty years of osteochondrosis.. Equine Vet. J. 2018;50:554–555.
    doi: 10.1111/evj.12821pubmed: 29956851google scholar: lookup
  3. Naccache F, Metzger J, Distl O. Genetic risk factors for osteochondrosis in various horse breeds.. Equine Vet. J. 2018;50:556–563.
    doi: 10.1111/evj.12824pubmed: 29498750google scholar: lookup
  4. Ahmadi F, Mirshahi A, Mohri M, Sardari K, Sharifi K. Osteochondrosis dissecans (OCD) in horses: Hormonal and biochemical study (19 cases). Vet. Res. Forum. 2021;12:325–331.
    doi: 10.30466/vrf.2020.104046.2495pmc: PMC8576161pubmed: 34815844google scholar: lookup
  5. Hilla D, Distl O. Heritabilities and genetic correlations between fetlock, hock and stifle osteochondrosis and fetlock osteochondral fragments in Hanoverian Warmblood horses.. J. Anim. Breed. Genet. 2013;131:71–81.
    doi: 10.1111/jbg.12062pubmed: 24236645google scholar: lookup
  6. Schougaard H, Ronne J.F, Phillipson J. A radiographic survey of tibiotarsal osteochondrosis in a selected population of trotting horses in Denmark and its possible genetic significance.. Equine Vet. J. 1990;22:288–289.
    doi: 10.1111/j.2042-3306.1990.tb04270.xpubmed: 2209527google scholar: lookup
  7. Grøndahl A.M, Engeland A. Influence of radiographically detectable orthopedic changes on racing performance in standardbred trotters.. J. Am. Vet. Med. Assoc. 1995;206:1013–1017.
    pubmed: 7768708
  8. Philipsson J, Andréasson E, Sandgren B, Dalin G, Carlsten J. Osteochondrosis in the tarsocrural joint and osteochondral fragments in the fetlock joints in Standardbred trotters. II. Heritability.. Equine Vet. J. 1993;25:38–41.
    doi: 10.1111/j.2042-3306.1993.tb04852.xgoogle scholar: lookup
  9. Teyssèdre S, Dupuis M.C, Guérin G, Schibler L, Denoix J.M, Elsen J.M, Ricard A. Genome-wide association studies for osteochondrosis in French Trotter horses1.. J. Anim. Sci. 2012;90:45–53.
    doi: 10.2527/jas.2011-4031pubmed: 21841084google scholar: lookup
  10. Pieramati C, Pepe M, Silvestrelli M, Bolla A. Heritability estimation of osteochondrosis dissecans in Maremmano horses.. Livest. Prod. Sci. 2003;79:249–255.
    doi: 10.1016/S0301-6226(02)00151-3google scholar: lookup
  11. Stock K.F, Hamann H, Distl O. Estimation of genetic parameters for the prevalence of osseous fragments in limb joints of Hanoverian Warmblood horses.. J. Anim. Breed. Genet. 2005;122:271–280.
    doi: 10.1111/j.1439-0388.2005.00527.xpubmed: 16060495google scholar: lookup
  12. Stock K.F, Distl O. Genetic correlations between osseous fragments in fetlock and hock joints, deforming arthropathy in hock joints and pathologic changes in the navicular bones of Warmblood riding horses.. Livest. Sci. 2006;105:35–43.
    doi: 10.1016/j.livsci.2006.04.027google scholar: lookup
  13. Winter D.B.E, Glodek P, Hertsch B. Genetic disposition of bone diseases in sport horses.. Züchtungskunde. 1996;68:92–108.
  14. Willms F, Röhe R, Kalm E. Genetic analysis of different traits in horse breeding by considering radiographic findings - 1st communication: Importance of radiographic findings in breeding sport horses.. Züchtungskunde. 1999;71:330–345.
  15. Schober M. Schätzung von Genetischen Effekten Beim Auftreten von Osteochondrosis Dissecans Beim Warmblutpferd.. Georg-August-Universität Göttingen; Göttingen, Germany: 2003.
  16. van Grevenhof E.M, Schurink A, Ducro B.J, van Weeren P.R, van Tartwijk J.M, Bijma P, van Arendonk J.A. Genetic variables of various manifestations of osteochondrosis and their correlations between and within joints in Dutch warmblood horses.. J. Anim. Sci. 2009;87:1906–1912.
    doi: 10.2527/jas.2008-1199pubmed: 19213707google scholar: lookup
  17. Jönsson L, Dalin G, Egenvall A, Näsholm A, Roepstorff L, Philipsson J. Equine hospital data as a source for study of prevalence and heritability of osteochondrosis and palmar/plantar osseous fragments of Swedish Warmblood horses.. Equine Vet. J. 2011;43:695–700.
    doi: 10.1111/j.2042-3306.2010.00354.xpubmed: 21615779google scholar: lookup
  18. Wittwer C, Hamann H, Rosenberger E, Distl O. Genetic parameters for the prevalence of osteochondrosis in the limb joints of South German Coldblood horses.. J. Anim. Breed. Genet. 2007;124:302–307.
    doi: 10.1111/j.1439-0388.2007.00670.xpubmed: 17868083google scholar: lookup
  19. Russell J, Matika O, Russell T, Reardon R.J. Heritability and prevalence of selected osteochondrosis lesions in yearling Thoroughbred horses.. Equine Vet. J. 2017;49:282–287.
    doi: 10.1111/evj.12613pmc: PMC5412687pubmed: 27448988google scholar: lookup
  20. McCoy A.M, Norton E.M, Kemper A.M, Beeson S.K, Mickelson J.R, McCue M.E. SNP-based heritability and genetic architecture of tarsal osteochondrosis in North American Standardbred horses.. Anim. Genet. 2019;50:78–81.
    doi: 10.1111/age.12738pubmed: 30353927google scholar: lookup
  21. Wypchło M, Korwin-Kossakowska A, Bereznowski A, Hecold M, Lewczuk D. Polymorphisms in selected genes and analysis of their relationship with osteochondrosis in Polish sport horse breeds.. Anim. Genet. 2018;49:623–627.
    doi: 10.1111/age.12715pubmed: 30152531google scholar: lookup
  22. Lewczuk D, Hecold M, Ruść A, Frąszczak M, Bereznowski A, Korwin-Kossakowska A, Kamiński S, Szyda J. Single nucleotide polymorphisms associated with osteochondrosis dissecans in Warmblood horses at different stages of training.. Anim. Prod. Sci. 2017;57:608–613.
    doi: 10.1071/AN15450google scholar: lookup
  23. Falconer D.S. Introduction to Quantitative Genetics.. 4th ed. Pearson Education Limited; Essex, England: 1996.
  24. Zaitlen N, Kraft P, Patterson N, Pasaniuc B, Bhatia G, Pollack S, Price A.L. Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits.. PLoS Genet. 2013;9:e1003520.
    doi: 10.1371/journal.pgen.1003520pmc: PMC3667752pubmed: 23737753google scholar: lookup
  25. Manolio T.A, Collins F.S, Cox N.J, Goldstein D.B, Hindorff L.A, Hunter D.J, McCarthy M.I, Ramos E.M, Cardon L.R, Chakravarti A. Finding the missing heritability of complex diseases.. Nature. 2009;461:747–753.
    doi: 10.1038/nature08494pmc: PMC2831613pubmed: 19812666google scholar: lookup
  26. Maher B. Personal genomes: The case of the missing heritability.. Nature. 2008;456:18–21.
    doi: 10.1038/456018apubmed: 18987709google scholar: lookup
  27. Speed D, Cai N, Johnson M.R, Nejentsev S, Balding D.J. Reevaluation of SNP heritability in complex human traits.. Nat. Genet. 2017;49:986–992.
    doi: 10.1038/ng.3865pmc: PMC5493198pubmed: 28530675google scholar: lookup
  28. Barry C.S, Walker V.M, Cheesman R, Davey Smith G, Morris T.T, Davies N.M. How to estimate heritability: A guide for genetic epidemiologists.. Int. J. Epidemiol. 2023;52:624–632.
    doi: 10.1093/ije/dyac224pmc: PMC10114051pubmed: 36427280google scholar: lookup
  29. Evans L.M, Tahmasbi R, Vrieze S.I, Abecasis G.R, Das S, Gazal S, Bjelland D.W, de Candia T.R, Goddard M.E, Neale B.M. Comparison of methods that use whole genome data to estimate the heritability and genetic architecture of complex traits.. Nat. Genet. 2018;50:737–745.
    doi: 10.1038/s41588-018-0108-xpmc: PMC5934350pubmed: 29700474google scholar: lookup
  30. Yang J, Lee S.H, Goddard M.E, Visscher P.M. GCTA: A tool for genome-wide complex trait analysis.. Am. J. Hum. Genet. 2011;88:76–82.
    doi: 10.1016/j.ajhg.2010.11.011pmc: PMC3014363pubmed: 21167468google scholar: lookup
  31. Yang J, Zeng J, Goddard M.E, Wray N.R, Visscher P.M. Concepts, estimation and interpretation of SNP-based heritability.. Nat. Genet. 2017;49:1304–1310.
    doi: 10.1038/ng.3941pubmed: 28854176google scholar: lookup
  32. Speed D, Hemani G, Johnson M.R, Balding D.J. Improved heritability estimation from genome-wide SNPs.. Am. J. Hum. Genet. 2012;91:1011–1021.
    doi: 10.1016/j.ajhg.2012.10.010pmc: PMC3516604pubmed: 23217325google scholar: lookup
  33. Slatkin M. Linkage disequilibrium—Understanding the evolutionary past and mapping the medical future.. Nat. Rev. Genet. 2008;9:477–485.
    doi: 10.1038/nrg2361pmc: PMC5124487pubmed: 18427557google scholar: lookup
  34. Ren D, Cai X, Lin Q, Ye H, Teng J, Li J, Ding X, Zhang Z. Impact of linkage disequilibrium heterogeneity along the genome on genomic prediction and heritability estimation.. Genet. Sel. Evol. 2022;54:47.
    doi: 10.1186/s12711-022-00737-3pmc: PMC9235212pubmed: 35761182google scholar: lookup
  35. Lee S.H, DeCandia T.R, Ripke S, Yang J, Sullivan P.F, Goddard M.E, Keller M.C, Visscher P.M, Wray N.R. Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs.. Nat. Genet. 2012;44:247–250.
    doi: 10.1038/ng.1108pmc: PMC3327879pubmed: 22344220google scholar: lookup
  36. Yang J, Bakshi A, Zhu Z, Hemani G, Vinkhuyzen A.A, Lee S.H, Robinson M.R, Perry J.R, Nolte I.M, van Vliet-Ostaptchouk J.V. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index.. Nat. Genet. 2015;47:1114–1120.
    doi: 10.1038/ng.3390pmc: PMC4589513pubmed: 26323059google scholar: lookup
  37. Mancuso N, Rohland N, Rand K.A, Tandon A, Allen A, Quinque D, Mallick S, Li H, Stram A, Sheng X. The contribution of rare variation to prostate cancer heritability.. Nat. Genet. 2016;48:30–35.
    doi: 10.1038/ng.3446pmc: PMC7534691pubmed: 26569126google scholar: lookup
  38. Lee S.H, Yang J, Chen G.-B, Ripke S, Stahl E.A, Hultman C.M, Sklar P, Visscher P.M, Sullivan P.F, Goddard M.E. Estimation of SNP Heritability from Dense Genotype Data.. Am. J. Hum. Genet. 2013;93:1151–1155.
    doi: 10.1016/j.ajhg.2013.10.015pmc: PMC3852919pubmed: 24314550google scholar: lookup
  39. Hilla D, Distl O. Prevalence of osteochondral fragments, osteochondrosis dissecans and palmar/plantar osteochondral fragments in Hanoverian Warmblood horses.. Berl. Munch. Tierarztl. Wochenschr. 2013;126:236–244.
    pubmed: 23758039
  40. Hilla D, Distl O. Genetic parameters for osteoarthrosis, radiographic changes of the navicular bone and sidebone, and their correlation with osteochondrosis and osteochondral fragments in Hanoverian warmblood horses.. Livest. Sci. 2014;169:19–26.
    doi: 10.1016/j.livsci.2014.09.015google scholar: lookup
  41. Browning B.L, Zhou Y, Browning S.R. A One-Penny Imputed Genome from Next-Generation Reference Panels.. Am. J. Hum. Genet. 2018;103:338–348.
    doi: 10.1016/j.ajhg.2018.07.015pmc: PMC6128308pubmed: 30100085google scholar: lookup
  42. Chang C.C, Chow C.C, Tellier L.C.A.M, Vattikuti S, Purcell S.M, Lee J.J. Second-generation PLINK: Rising to the challenge of larger and richer datasets.. GigaScience. 2015;4:7.
    doi: 10.1186/s13742-015-0047-8pmc: PMC4342193pubmed: 25722852google scholar: lookup
  43. Purcell S, Chang C. PLINK 1.9.. Purcell Lab; Melbourne, Australia: 2023.
  44. Yang J, Benyamin B, McEvoy B.P, Gordon S, Henders A.K, Nyholt D.R, Madden P.A, Heath A.C, Martin N.G, Montgomery G.W. Common SNPs explain a large proportion of the heritability for human height.. Nat. Genet. 2010;42:565–569.
    doi: 10.1038/ng.608pmc: PMC3232052pubmed: 20562875google scholar: lookup
  45. Zhang Q, Privé F, Vilhjálmsson B, Speed D. Improved genetic prediction of complex traits from individual-level data or summary statistics.. Nat. Commun. 2021;12:4192.
    doi: 10.1038/s41467-021-24485-ypmc: PMC8263809pubmed: 34234142google scholar: lookup
  46. Min A, Thompson E, Basu S. Comparing heritability estimators under alternative structures of linkage disequilibrium.. G3. 2022;12:jkac134.
    doi: 10.1093/g3journal/jkac134pmc: PMC9339317pubmed: 35674391google scholar: lookup
  47. McCoy A.M, Beeson S.K, Splan R.K, Lykkjen S, Ralston S.L, Mickelson J.R, McCue M.E. Identification and validation of risk loci for osteochondrosis in standardbreds.. BMC Genom. 2016;17:41.
    doi: 10.1186/s12864-016-2385-zpmc: PMC4709891pubmed: 26753841google scholar: lookup
  48. McCue M.E, Bannasch D.L, Petersen J.L, Gurr J, Bailey E, Binns M.M, Distl O, Guérin G, Hasegawa T, Hill E.W. A High Density SNP Array for the Domestic Horse and Extant Perissodactyla: Utility for Association Mapping, Genetic Diversity, and Phylogeny Studies.. PLoS Genet. 2012;8:e1002451.
    doi: 10.1371/journal.pgen.1002451pmc: PMC3257288pubmed: 22253606google scholar: lookup
  49. Wray N.R. Allele Frequencies and the r2 Measure of Linkage Disequilibrium: Impact on Design and Interpretation of Association Studies.. Twin. Res. Hum. Genet. 2005;8:87–94.
    doi: 10.1375/twin.8.2.87pubmed: 15901470google scholar: lookup
  50. Tang M, Wang T, Zhang X. A review of SNP heritability estimation methods.. Brief. Bioinform. 2022;23:bbac067.
    doi: 10.1093/bib/bbac067pubmed: 35289357google scholar: lookup
  51. Visscher P.M, Hill W.G, Wray N.R. Heritability in the genomics era—Concepts and misconceptions.. Nat. Rev. Genet. 2008;9:255–266.
    doi: 10.1038/nrg2322pubmed: 18319743google scholar: lookup
  52. Zhu H, Zhou X. Statistical methods for SNP heritability estimation and partition: A review.. Comput. Struct. Biotechnol. J. 2020;18:1557–1568.
    doi: 10.1016/j.csbj.2020.06.011pmc: PMC7330487pubmed: 32637052google scholar: lookup
  53. Falconer D.S. The inheritance of liability to certain diseases, estimated from the incidence among relatives.. Ann. Hum. Genet. 1965;29:51–76.
    doi: 10.1111/j.1469-1809.1965.tb00500.xgoogle scholar: lookup
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