FREE SHIPPING over $40
OVER 10000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Genetics, selection, evolution : GSE2012; 44(1); 31; doi: 10.1186/1297-9686-44-31

Genome-wide association study of insect bite hypersensitivity in two horse populations in the Netherlands.

Abstract: Insect bite hypersensitivity is a common allergic disease in horse populations worldwide. Insect bite hypersensitivity is affected by both environmental and genetic factors. However, little is known about genes contributing to the genetic variance associated with insect bite hypersensitivity. Therefore, the aim of our study was to identify and quantify genomic associations with insect bite hypersensitivity in Shetland pony mares and Icelandic horses in the Netherlands. Methods: Data on 200 Shetland pony mares and 146 Icelandic horses were collected according to a matched case-control design. Cases and controls were matched on various factors (e.g. region, sire) to minimize effects of population stratification. Breed-specific genome-wide association studies were performed using 70 k single nucleotide polymorphisms genotypes. Bayesian variable selection method Bayes-C with a threshold model implemented in GenSel software was applied. A 1 Mb non-overlapping window approach that accumulated contributions of adjacent single nucleotide polymorphisms was used to identify associated genomic regions. Results: The percentage of variance explained by all single nucleotide polymorphisms was 13% in Shetland pony mares and 28% in Icelandic horses. The 20 non-overlapping windows explaining the largest percentages of genetic variance were found on nine chromosomes in Shetland pony mares and on 14 chromosomes in Icelandic horses. Overlap in identified associated genomic regions between breeds would suggest interesting candidate regions to follow-up on. Such regions common to both breeds (within 15 Mb) were found on chromosomes 3, 7, 11, 20 and 23. Positional candidate genes within 2 Mb from the associated windows were identified on chromosome 20 in both breeds. Candidate genes are within the equine lymphocyte antigen class II region, which evokes an immune response by recognizing many foreign molecules. Conclusions: The genome-wide association study identified several genomic regions associated with insect bite hypersensitivity in Shetland pony mares and Icelandic horses. On chromosome 20, associated genomic regions in both breeds were within 2 Mb from the equine lymphocyte antigen class II region. Increased knowledge on insect bite hypersensitivity associated genes will contribute to our understanding of its biology, enabling more efficient selection, therapy and prevention to decrease insect bite hypersensitivity prevalence.
Get Full Text
Publication Date: 2012-10-30 PubMed ID: 23110538PubMed Central: PMC3524047DOI: 10.1186/1297-9686-44-31Google 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
  • Research Support
  • Non-U.S. Gov't

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 research study aims to identify genomic associations with insect bite hypersensitivity in two horse populations, Shetland pony mares and Icelandic horses, in the Netherlands.

Objectives of the Study

  • The primary goal was to better understand the genetic factors contributing to insect bite hypersensitivity in horses, a common allergic condition.
  • The research hoped to uncover specific genes and genomic regions associated with this hypersensitivity.
  • By identifying these genes, the study aimed to enhance our understanding of the disease’s biology, thereby providing insights into more efficient selection, therapy, and prevention techniques.

Methods

  • The researchers collected data on 200 Shetland pony mares and 146 Icelandic horses.
  • They used a matched case-control design to account for potential effects of population stratification. This means cases and controls were deliberately matched on various factors like region and sire to ensure comparability.
  • The researchers performed breed-specific genome-wide association studies using 70,000 single nucleotide polymorphisms (SNPs) genotypes, genetic variations that could be associated with the hypersensitivity.
  • They applied the Bayesian variable selection method Bayes-C with a threshold model in GenSel software.
  • A non-overlapping window approach was used, which entails assessing the contributions of adjacent SNPs to identify associated genomic regions.

Results

  • All single nucleotide polymorphisms together explained 13% of the variance in Shetland pony mares and 28% in Icelandic horses, highlighting genetic contributions to the hypersensitivity.
  • The research identified the 20 non-overlapping windows that contributed the most to genetic variance on nine chromosomes in Shetland pony mares and 14 chromosomes in Icelandic horses.
  • Genomic regions associated with hypersensitivity were found on chromosomes 3, 7, 11, 20, and 23 in both breeds.
  • Specifically on chromosome 20 in both breeds, candidate genes were identified within 2 Megabases (Mb) of the associated windows, located within the equine lymphocyte antigen class II region, which plays a significant role in immune response.

Conclusion

  • The genome-wide association study identified several genomic regions associated with insect bite hypersensitivity in Shetland pony mares and Icelandic horses.
  • This understanding can provide a foundation for further genetic research on insect bite hypersensitivity and offers potential insights into treatments and prevention strategies.

Cite This Article

APA
Schurink A, Wolc A, Ducro BJ, Frankena K, Garrick DJ, Dekkers JC, van Arendonk JA. (2012). Genome-wide association study of insect bite hypersensitivity in two horse populations in the Netherlands. Genet Sel Evol, 44(1), 31. https://doi.org/10.1186/1297-9686-44-31

Publication

Genetics, selection, evolution : GSE
ISSN: 1297-9686
NlmUniqueID: 9114088
Country: France
Language: English
Volume: 44
Issue: 1
Pages: 31

Researcher Affiliations

Schurink, Anouk
  • Animal Breeding and Genomics Centre, Wageningen University, P,O, Box 338, Wageningen, 6700 AH, the Netherlands.
Wolc, Anna
    Ducro, Bart J
      Frankena, Klaas
        Garrick, Dorian J
          Dekkers, Jack C M
            van Arendonk, Johan A M

              MeSH Terms

              • Analysis of Variance
              • Animals
              • Case-Control Studies
              • Chromosomes, Mammalian
              • Genome-Wide Association Study / veterinary
              • Horse Diseases / genetics
              • Horses
              • Hypersensitivity / genetics
              • Hypersensitivity / veterinary
              • Insect Bites and Stings / immunology
              • Insect Bites and Stings / veterinary
              • Models, Genetic
              • Netherlands
              • Polymorphism, Single Nucleotide
              • Population / genetics
              • Quantitative Trait Loci

              References

              This article includes 49 references
              1. Gortel K. Equine parasitic hypersensitivity.. Equine Pract 1998;20:14–16.
              2. Meiswinkel R, Baylis M, Labuschagne K. Stabling and the protection of horses from Culicoides bolitinos (Diptera: Ceratopogonidae), a recently identified vector of African horse sickness.. Bull Ent Res 2000;90:509–515.
                pubmed: 11107252
              3. de Raat IJ, van den Boom R, van Poppel M, van Oldruitenborgh-Oosterbaan MM S. The effect of a topical insecticide containing permethrin on the number of Culicoides midges caught near horses with and without insect bite hypersensitivity in the Netherlands.. Tijdschr Diergeneeskd 2008;133:838–842.
                pubmed: 18975624
              4. van den Boom R, Kempenaars M, Sloet van Oldruitenborgh-Oosterbaan MM. The healing effects of a topical phytogenic ointment on insect bite hypersensitivity lesions in horses.. Tijdschr Diergeneeskd 2011;136:20–26.
                pubmed: 21294393
              5. Papadopoulos E, Rowlinson M, Bartram D, Carpenter S, Mellor P, Wall R. Treatment of horses with cypermethrin against the biting flies Culicoides nubeculosus, Aedes aegypti and Culex quinquefasciatus.. Vet Parasitol 2010;169:165–171.
                doi: 10.1016/j.vetpar.2009.12.023pubmed: 20074858google scholar: lookup
              6. Eriksson S, Grandinson K, Fikse WF, Lindberg L, Mikko S, Broström H, Frey R, Sundquist M, Lindgren G. Genetic analysis of insect bite hypersensitivity (summer eczema) in Icelandic horses.. Animal 2008;2:360–365.
                pubmed: 22445037
              7. Schurink A, van Grevenhof EM, Ducro BJ, van Arendonk JAM. Heritability and repeatability of insect bite hypersensitivity in Dutch Shetland breeding mares.. J Anim Sci 2009;87:484–490.
                pubmed: 18791140
              8. Schurink A, Ducro BJ, Heuven HCM, van Arendonk JAM. Genetic parameters of insect bite hypersensitivity in Dutch Friesian broodmares.. J Anim Sci 2011;89:1286–1293.
                doi: 10.2527/jas.2010-3222pubmed: 21239662google scholar: lookup
              9. Unkel M, Simon D, Mayer M, Sommer H. Studies on the genetic basis of sweet itch in Island horses.. Z Tierzücht Züchtungsbiol 1987;104:217–230.
              10. Andersson LS, Swinbune JE, Meadows JRS, Broström H, Eriksson S, Fikse WF, Frey R, Sundquist M, Tseng CT, Mikko S, Lindgren G. The same ELA class II risk factors confer equine insect bite hypersensitivity in two distinct populations.. Immunogenetics 2012;64:201–208.
                doi: 10.1007/s00251-011-0573-1pmc: PMC3276761pubmed: 21947540google scholar: lookup
              11. Halldórsdóttir S, Lazary S, Gunnarsson E, Larsen HJ. Distribution of leucocyte antigens in Icelandic horses affected with summer eczema compared to non-affected horses.. Equine Vet J 1991;23:300–302.
                doi: 10.1111/j.2042-3306.1991.tb03722.xpubmed: 1915232google scholar: lookup
              12. Marti E, Gerber H, Lazary S. On the genetic basis of equine allergic diseases: II. Insect bite dermal hypersensitivity.. Equine Vet J 1992;24:113–117.
                doi: 10.1111/j.2042-3306.1992.tb02794.xpubmed: 1582388google scholar: lookup
              13. Bailey E, Marti E, Fraser DG, Antczak DF, Lazary S. Immunogenetics of the horse. In: The Genetics of the Horse. Bowling AT, Ruvinsky A, editor. CABI Publishing, New York; 2000. pp. 123–155.
              14. Schurink A, Ducro BJ, Bastiaansen JWM, Frankena K, van Arendonk JAM. Genome-wide association study of insect bite hypersensitivity in Dutch Shetland pony mares.. Anim Genet in press.
                pubmed: 22582722
              15. Karlsson EK, Lindblad-Toh K. Leader of the pack: gene mapping in dogs and other model organisms.. Nat Rev Genet 2008;9:713–725.
                pubmed: 18714291
              16. Hayes B, Goddard M. Genome-wide association and genomic selection in animal breeding.. Genome 2010;53:876–883.
                doi: 10.1139/G10-076pubmed: 21076503google scholar: lookup
              17. van den Boom R, Ducro B, van Sloet Oldruitenborgh-Oosterbaan MM. Identification of factors associated with the development of insect bite hypersensitivity in horses in the Netherlands.. Tijdschr Diergeneeskd 2008;133:554–559.
                pubmed: 18649782
              18. Aulchenko YS, Ripke S, Isaacs A, van Duijn CM. GenABEL: an R library for genome-wide association analysis.. Bioinformatics 2007;23:1294–1296.
                doi: 10.1093/bioinformatics/btm108pubmed: 17384015google scholar: lookup
              19. Gower JC. Some distance properties of latent root and vector methods used in multivariate analysis.. Biometrika 1966;53:325–338.
              20. Kizilkaya K, Fernando RL, Garrick DJ. Genomic prediction of simulated multibreed and purebred performance using observed fifty thousand single nucleotide polymorphism genotypes.. J Anim Sci 2010;88:544–551.
                doi: 10.2527/jas.2009-2064pubmed: 19820059google scholar: lookup
              21. Fernando RL, Garrick DJ. GenSel – User manual for a portfolio of genomic selection related analyses.. Animal Breeding and Genetics, Iowa State University, Ames 2008.
              22. Fan B, Onteru SK, Du ZQ, Garrick DJ, Stalder KJ, Rothschild MF. Genome-wide association study identifies loci for body composition and structural soundness traits in pigs.. PLoS ONE 2011;6:e14726.
                doi: 10.1371/journal.pone.0014726pmc: PMC3044704pubmed: 21383979google scholar: lookup
              23. Onteru SK, Fan B, Du Z-Q, Garrick DJ, Stalder KJ, Rothschild MF. A whole-genome association study for pig reproductive traits.. Anim Genet 2011;43:18–26.
                pubmed: 22221021
              24. Meuwissen THE, Hayes BJ, Goddard ME. Prediction of total genetic value using genome-wide dense marker maps.. Genetics 2001;157:1819–1829.
                pmc: PMC1461589pubmed: 11290733
              25. Sorensen DA, Andersen S, Gianola D, Korsgaard I. Bayesian inference in threshold models using Gibbs sampling.. Genet Sel Evol 1995;27:229–249.
                doi: 10.1186/1297-9686-27-3-229google scholar: lookup
              26. Gianola D, de los Campos G, Hill WG, Manfredi E, Fernando R. Additive genetic variability and the Bayesian alphabet.. Genetics 2009;183:347–363.
                doi: 10.1534/genetics.109.103952pmc: PMC2746159pubmed: 19620397google scholar: lookup
              27. Sun X, Habier D, Fernando RL, Garrick DJ, Dekkers JCM. Genomic breeding value prediction and QTL mapping of QTLMAS2010 data using Bayesian methods.. BMC Proc 2011;5:S13.
                pmc: PMC3103198pubmed: 21624169
              28. Wolc A, Arango J, Settar P, Fulton JE, O’Sullivan NP, Preisinger R, Habier D, Fernando R, Garrick DJ, Hill WG, Dekkers JCM. Genome-wide association analysis and genetic architecture of egg weight and egg uniformity in layer chickens.. Anim Genet 2012;43:87–96.
                pubmed: 22742506
              29. Pilsworth RC, Knottenbelt DC. Equine insect hypersensitivity.. Equine Vet Educ 2004;16:324–325.
              30. Hirschhorn JN, Daly MJ. Genome-wide association studies for common diseases and complex traits.. Nat Rev Genet 2005;6:95–108.
                pubmed: 15716906
              31. Toosi A, Fernando RL, Dekkers JCM. Genomic selection in admixed and crossbred populations.. J Anim Sci 2010;88:32–46.
                doi: 10.2527/jas.2009-1975pubmed: 19749023google scholar: lookup
              32. Broström H, Larsson Å, Troedsson M. Allergic dermatitis (sweet itch) of Icelandic horses in Sweden: an epidemiological study.. Equine Vet J 1987;19:229–236.
                doi: 10.1111/j.2042-3306.1987.tb01389.xpubmed: 3608962google scholar: lookup
              33. Marti E, Gerber V, Wilson AD, Lavoie JP, Horohov D, Crameri R, Lunn DP, Antczak D, Björnsdóttir S, Björnsdóttir TS, Cunningham F, Dérer M, Frey R, Hamza E, Horin P, Heimann M, Kolm-Stark G, Ólafsdóttir G, Ramery E, Russell C, Schaffartzik A, Svansson V, Torsteinsdóttir S, Wagner B. Report of the 3rd Havemeyer workshop on allergic diseases of the Horse, Hólar, Iceland, June 2007.. Vet Immunol Immunopathol 2008;126:351–361.
                doi: 10.1016/j.vetimm.2008.07.008pubmed: 18775570google scholar: lookup
              34. Björnsdóttir S, Sigvaldadóttir J, Broström H, Langvad B, Sigurðsson Á. Summer eczema in exported Icelandic horses: influence of environmental and genetic factors.. Acta Vet Scand 2006;48:3.
                doi: 10.1186/1751-0147-48-3pmc: PMC1513129pubmed: 16987399google scholar: lookup
              35. Mucha S, Pszczoła M, Strabel T, Wolc A, Paczyńska P, Szydlowski M. Comparison of analyses of the QTLMAS XIV common dataset. II: QTL analysis.. BMC Proc 2011;5:S2.
                pmc: PMC3103201pubmed: 21624172
              36. Sahana G, Guldbrandtsen B, Janss L, Lund MS. Comparison of association mapping methods in a complex pedigreed population.. Genet Epidemiol 2010;34:455–462.
                doi: 10.1002/gepi.20499pubmed: 20568276google scholar: lookup
              37. He W, Fernando RL, Dekkers JCM, Gilbert H. A gene frequency model for QTL mapping using Bayesian inference.. Genet Sel Evol 2010;42:21.
                doi: 10.1186/1297-9686-42-21pmc: PMC2901203pubmed: 20540762google scholar: lookup
              38. Smith AV, Thomas DJ, Munro HM, Abecasis GR. Sequence features in regions of weak and strong linkage disequilibrium.. Genome Res 2005;15:1519–1534.
                doi: 10.1101/gr.4421405pmc: PMC1310640pubmed: 16251462google scholar: lookup
              39. Bohmanova J, Sargolzaei M, Schenkel FS. Characteristics of linkage disequilibrium in North American Holsteins.. BMC Genomics 2010;11:421.
                doi: 10.1186/1471-2164-11-421pmc: PMC2996949pubmed: 20609259google scholar: lookup
              40. Dekkers JCM, Hospital F. The use of molecular genetics in the improvement of agricultural populations.. Nat Rev Genet 2002;3:22–32.
                doi: 10.1038/nrg701pubmed: 11823788google scholar: lookup
              41. de Roos APW, Hayes BJ, Spelman RJ, Goddard ME. Linkage disequilibrium and persistence of phase in Holstein-Friesian, Jersey and Angus cattle.. Genetics 2008;179:1503–1512.
                doi: 10.1534/genetics.107.084301pmc: PMC2475750pubmed: 18622038google scholar: lookup
              42. van de Goor LHP, van Haeringen WA, Lenstra JA. Population studies of 17 equine STR for forensic and phylogenetic analysis.. Anim Genet 2011;42:627–633.
                doi: 10.1111/j.1365-2052.2011.02194.xpubmed: 22035004google scholar: lookup
              43. Hill WG, Robertson A. Linkage disequilibrium in finite populations.. Theor Appl Genet 1968;38:226–231.
                doi: 10.1007/BF01245622pubmed: 24442307google scholar: lookup
              44. Wade CM, Giulotto E, Sigurdsson S, Zoli M, Gnerre S, Imsland F, Lear TL, Adelson DL, Bailey E, Bellone RR, Blöcker H, Distl O, Edgar RC, Garber M, Leeb T, Mauceli E, MacLeod JN, Penedo MCT, Raison JM, Sharpe T, Vogel J, Andersson L, Antczak DF, Biagi T, Binns MM, Chowdhary BP, Coleman SJ, Della Valle G, Fryc S, Guérin G. Genome sequence, comparative analysis, and population genetics of the domestic horse.. Science 2009;326:865–867.
                doi: 10.1126/science.1178158pmc: PMC3785132pubmed: 19892987google scholar: lookup
              45. Andersson LS, Högström C, Mikko S, Eriksson S, Grandinson K, Broström H, Frey R, Sundquist M, Lindgren G. Polymorphisms in SPINK5 do not associate with insect bite hypersensitivity in Icelandic horses born in Sweden.. Anim Genet 2009;40:790–791.
                doi: 10.1111/j.1365-2052.2009.01890.xpubmed: 19397509google scholar: lookup
              46. Hořín P, Smola J, Matiašovic J, Vyskočil M, Lukeszová L, Tomanová K, Králík P, Glasnák V, Schröffelová D, Knoll A, Sedlinská M, Křenková L, Jahn P. Polymorphisms in equine immune response genes and their associations with infections.. Mamm Genome 2004;15:843–850.
                doi: 10.1007/s00335-004-2356-6pubmed: 15520887google scholar: lookup
              47. Marti E, Glowatzki-Mullis ML, Curik I, Torsteinsdottir S, Binns MM. Investigating the genetic background for insect bite hypersensitivity in Icelandic horses.. Proceedings of the 6th International Equine Gene Mapping Workshop. Dublin; 2005.
              48. Chowdhary BP, Raudsepp T. The horse genome derby: racing from map to whole genome sequence.. Chromosome Res 2008;16:109–127.
                doi: 10.1007/s10577-008-1204-zpubmed: 18274866google scholar: lookup
              49. Dekkers JCM. Commercial application of marker- and gene-assisted selection in livestock: strategies and lessons.. J Anim Sci 2004;82:E313–E328.
                pubmed: 15471812

              Citations

              This article has been cited 20 times.
              1. Park J. Comprehensive genome-wide analysis of genetic loci and candidate genes associated with litter traits in purebred Berkshire pigs of Korea. Anim Biosci 2024 Oct;37(10):1702-1711.
                doi: 10.5713/ab.24.0046pubmed: 39164087google scholar: lookup
              2. Cox A, Stewart AJ. Insect Bite Hypersensitivity in Horses: Causes, Diagnosis, Scoring and New Therapies. Animals (Basel) 2023 Aug 4;13(15).
                doi: 10.3390/ani13152514pubmed: 37570323google scholar: lookup
              3. Vasoya D, Tzelos T, Benedictus L, Karagianni AE, Pirie S, Marr C, Oddsdóttir C, Fintl C, Connelley T. High-Resolution Genotyping of Expressed Equine MHC Reveals a Highly Complex MHC Structure. Genes (Basel) 2023 Jul 10;14(7).
                doi: 10.3390/genes14071422pubmed: 37510326google scholar: lookup
              4. Trevisoli PA, Moreira GCM, Boschiero C, Cesar ASM, Petrini J, Margarido GRA, Ledur MC, Mourão GB, Garrick D, Coutinho LL. A Missense Mutation in the MYBPH Gene Is Associated With Abdominal Fat Traits in Meat-Type Chickens. Front Genet 2021;12:698163.
                doi: 10.3389/fgene.2021.698163pubmed: 34456973google scholar: lookup
              5. Vostry L, Vostra-Vydrova H, Citek J, Gorjanc G, Curik I. Association of inbreeding and regional equine leucocyte antigen homozygosity with the prevalence of insect bite hypersensitivity in Old Kladruber horse. Anim Genet 2021 Aug;52(4):422-430.
                doi: 10.1111/age.13075pubmed: 33970495google scholar: lookup
              6. 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 (Basel) 2020 Jul 30;10(8).
                doi: 10.3390/ani10081310pubmed: 32751586google scholar: lookup
              7. 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 (Basel) 2020 Jun 8;10(6).
                doi: 10.3390/ani10061005pubmed: 32521830google scholar: lookup
              8. Raudsepp T, Finno CJ, Bellone RR, Petersen JL. Ten years of the horse reference genome: insights into equine biology, domestication and population dynamics in the post-genome era. Anim Genet 2019 Dec;50(6):569-597.
                doi: 10.1111/age.12857pubmed: 31568563google scholar: lookup
              9. François L, Hoskens H, Velie BD, Stinckens A, Tinel S, Lamberigts C, Peeters L, Savelkoul HFJ, Tijhaar E, Lindgren G, Janssens S, Ducro BJ, Buys N, Schurink AA. Genomic Regions Associated with IgE Levels against Culicoides spp. Antigens in Three Horse Breeds. Genes (Basel) 2019 Aug 8;10(8).
                doi: 10.3390/genes10080597pubmed: 31398914google scholar: lookup
              10. Schurink A, da Silva VH, Velie BD, Dibbits BW, Crooijmans RPMA, Franҫois L, Janssens S, Stinckens A, Blott S, Buys N, Lindgren G, Ducro BJ. Copy number variations in Friesian horses and genetic risk factors for insect bite hypersensitivity. BMC Genet 2018 Jul 30;19(1):49.
                doi: 10.1186/s12863-018-0657-0pubmed: 30060732google scholar: lookup
              11. Lomas HR, Robinson PA. A Pilot Qualitative Investigation of Stakeholders' Experiences and Opinions of Equine Insect Bite Hypersensitivity in England. Vet Sci 2018 Jan 9;5(1).
                doi: 10.3390/vetsci5010003pubmed: 29315275google scholar: lookup
              12. Sadeghi R, Moradi-Shahrbabak M, Miraei Ashtiani SR, Miller DC, Antczak DF. MHC haplotype diversity in Persian Arabian horses determined using polymorphic microsatellites. Immunogenetics 2018 May;70(5):305-315.
                doi: 10.1007/s00251-017-1039-xpubmed: 29170799google scholar: lookup
              13. Sollero BP, Junqueira VS, Gomes CCG, Caetano AR, Cardoso FF. Tag SNP selection for prediction of tick resistance in Brazilian Braford and Hereford cattle breeds using Bayesian methods. Genet Sel Evol 2017 Jun 15;49(1):49.
                doi: 10.1186/s12711-017-0325-2pubmed: 28619006google scholar: lookup
              14. Viļuma A, Mikko S, Hahn D, Skow L, Andersson G, Bergström TF. Genomic structure of the horse major histocompatibility complex class II region resolved using PacBio long-read sequencing technology. Sci Rep 2017 Mar 31;7:45518.
                doi: 10.1038/srep45518pubmed: 28361880google scholar: lookup
              15. Velie BD, Shrestha M, Franҫois L, Schurink A, Tesfayonas YG, Stinckens A, Blott S, Ducro BJ, Mikko S, Thomas R, Swinburne JE, Sundqvist M, Eriksson S, Buys N, Lindgren G. Using an Inbred Horse Breed in a High Density Genome-Wide Scan for Genetic Risk Factors of Insect Bite Hypersensitivity (IBH). PLoS One 2016;11(4):e0152966.
                doi: 10.1371/journal.pone.0152966pubmed: 27070818google scholar: lookup
              16. Sharma A, Lee JS, Dang CG, Sudrajad P, Kim HC, Yeon SH, Kang HS, Lee SH. Stories and Challenges of Genome Wide Association Studies in Livestock - A Review. Asian-Australas J Anim Sci 2015 Oct;28(10):1371-9.
                doi: 10.5713/ajas.14.0715pubmed: 26194229google scholar: lookup
              17. Finno CJ, Aleman M, Higgins RJ, Madigan JE, Bannasch DL. Risk of false positive genetic associations in complex traits with underlying population structure: a case study. Vet J 2014 Dec;202(3):543-9.
                doi: 10.1016/j.tvjl.2014.09.013pubmed: 25278384google scholar: lookup
              18. Kizilkaya K, Fernando RL, Garrick DJ. Reduction in accuracy of genomic prediction for ordered categorical data compared to continuous observations. Genet Sel Evol 2014 Jun 9;46(1):37.
                doi: 10.1186/1297-9686-46-37pubmed: 24912924google scholar: lookup
              19. Finno CJ, Bannasch DL. Applied equine genetics. Equine Vet J 2014 Sep;46(5):538-44.
                doi: 10.1111/evj.12294pubmed: 24802051google scholar: lookup
              20. van den Berg I, Fritz S, Boichard D. QTL fine mapping with Bayes C(π): a simulation study. Genet Sel Evol 2013 Jun 19;45(1):19.
                doi: 10.1186/1297-9686-45-19pubmed: 23782975google scholar: lookup
              Subscribe to our newsletter
              Join 99,928 horse owners like you who receive our email updates on horse health and nutrition.