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Home / Equine Research Bank / Genet Sel Evol / Genomic measures of inbreeding in the Norwegian-Swedish Cold...
Genetics, selection, evolution : GSE2019; 51(1); 22; doi: 10.1186/s12711-019-0465-7

Genomic measures of inbreeding in the Norwegian-Swedish Coldblooded Trotter and their associations with known QTL for reproduction and health traits.

Abstract: Since the 1950s, the Norwegian-Swedish Coldblooded trotter (NSCT) has been intensively selected for harness racing performance. As a result, the racing performance of the NSCT has improved remarkably; however, this improved racing performance has also been accompanied by a gradual increase in inbreeding level. Inbreeding in NSCT has historically been monitored by using traditional methods that are based on pedigree analysis, but with recent advancements in genomics, the NSCT industry has shown interest in adopting molecular approaches for the selection and maintenance of this breed. Consequently, the aims of the current study were to estimate genomic-based inbreeding coefficients, i.e. the proportion of runs of homozygosity (ROH), for a sample of NSCT individuals using high-density genotyping array data, and subsequently to compare the resulting rate of genomic-based F (F) to that of pedigree-based F (F) coefficients within the breed. Results: A total of 566 raced NSCT were available for analyses. Average F ranged from 1.78 to 13.95%. Correlations between F and F were significant (P < 0.001) and ranged from 0.27 to 0.56, with F and F from 2000 to 2009 increasing by 1.48 and 3.15%, respectively. Comparisons of ROH between individuals yielded 1403 regions that were present in at least 95% of the sampled horses. The average percentage of a single chromosome covered in ROH ranged from 9.84 to 18.82% with chromosome 31 and 18 showing, respectively, the largest and smallest amount of homozygosity. Conclusions: Genomic inbreeding coefficients were higher than pedigree inbreeding coefficients with both methods showing a gradual increase in inbreeding level in the NSCT breed between 2000 and 2009. Opportunities exist for the NSCT industry to develop programs that provide breeders with easily interpretable feedback on regions of the genome that are suboptimal from the perspective of genetic merit or that are sensitive to inbreeding within the population. The use of molecular data to identify genomic regions that may contribute to inbreeding depression in the NSCT will likely prove to be a valuable tool for the preservation of its genetic diversity in the long term.
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Publication Date: 2019-05-27 PubMed ID: 31132983PubMed Central: PMC6537210DOI: 10.1186/s12711-019-0465-7Google 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.

This research studied the levels of inbreeding in the Norwegian-Swedish Coldblooded Trotter (NSCT) horse breed. The researchers used advanced genomics to estimate these levels and compared it with traditional pedigree-based methods, finding that inbreeding increased between 2000 and 2009 and highlighting the potential for identifying genetically weak areas in the breed’s gene pool for improvement.

Objective and Methodology

  • The study investigated the levels of inbreeding in the Norwegian-Swedish Coldblooded Trotter (NSCT), a breed of horse that has been selectively bred for harness racing since the 1950s.
  • The primary objectives were to estimate genomic-based inbreeding coefficients using a high-density genotyping array data, and to compare these with traditional pedigree-based inbreeding coefficients.
  • By comparing these two methods, the researchers hoped to provide valuable insights for maintaining the genetic diversity within this breed.

Results and Findings

  • A total of 566 raced NSCT were available for analyses. The average genomic inbreeding coefficient ranged from 1.78 to 13.95%.
  • The correlation between genomic-based (F) and pedigree-based (F) inbreeding coefficients were found to be statistically significant, with values ranging between 0.27 and 0.56.
  • The largest amount of homozygosity was found on chromosome 31, with the smallest on chromosome 18.
  • The study found that genomic inbreeding coefficients were higher than pedigree inbreeding coefficients, indicating that traditional methods may underestimate the extent of inbreeding.

Conclusions and Future Directions

  • Both methods showed a gradual increase in inbreeding level in the NSCT breed between 2000 and 2009. This presents an opportunity for the NSCT industry to develop schemes that provide breeders with feedback on regions of the genome that are suboptimal from the perspective of genetic merit.
  • Use of molecular data to localize genomic regions that may contribute to inbreeding depression in the NSCT will likely be a valuable tool for preserving the breed’s genetic diversity in the long term.
  • The findings of the study offer implications for the NSCT industry, potentially informing breeding practices to mitigate the effects of inbreeding and protect the breed’s genetic diversity.

Cite This Article

APA
Velie BD, Solé M, Fegraeus KJ, Rosengren MK, Røed KH, Ihler CF, Strand E, Lindgren G. (2019). Genomic measures of inbreeding in the Norwegian-Swedish Coldblooded Trotter and their associations with known QTL for reproduction and health traits. Genet Sel Evol, 51(1), 22. https://doi.org/10.1186/s12711-019-0465-7

Publication

Genetics, selection, evolution : GSE
ISSN: 1297-9686
NlmUniqueID: 9114088
Country: France
Language: English
Volume: 51
Issue: 1
Pages: 22
PII: 22

Researcher Affiliations

Velie, Brandon D
  • School of Life and Environmental Sciences, University of Sydney, Sydney, Australia. brandon.velie@sydney.edu.au.
  • Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden. brandon.velie@sydney.edu.au.
Solé, Marina
  • Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Fegraeus, Kim Jäderkvist
  • Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Rosengren, Maria K
  • Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Røed, Knut H
  • Department of Basic Sciences and Aquatic Medicine, Norwegian University of Life Sciences, Oslo, Norway.
Ihler, Carl-Fredrik
  • Department of Companion Animal Clinical Sciences, Norwegian University of Life Sciences, Oslo, Norway.
Strand, Eric
  • Department of Companion Animal Clinical Sciences, Norwegian University of Life Sciences, Oslo, Norway.
Lindgren, Gabriella
  • Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
  • Livestock Genetics, Department of Biosystems, KU Leuven, Leuven, Belgium.

MeSH Terms

  • Animals
  • Female
  • Genome-Wide Association Study / methods
  • Homozygote
  • Horses / genetics
  • Horses / physiology
  • Inbreeding
  • Male
  • Pedigree
  • Quantitative Trait Loci
  • Selective Breeding

Grant Funding

  • H-15-47-075 / Swedish-Norwegian Foundation for Equine Research

Conflict of Interest Statement

The authors have the following interests: GL is a co-inventor on a granted patent concerning commercial testing of the DMRT3 mutation: A method to predict the pattern of locomotion in horses. PCT EP 12,747,875.8. European patent registration date: 2011-05-05, US patent registration date: 2011-08-03. There are no further patents, products in development, or marketed products to declare.

References

This article includes 36 references
  1. Solé M, Gori AS, Faux P, Bertrand A, Farnir F, Gautier M, Druet T. Age-based partitioning of individual genomic inbreeding levels in Belgian Blue cattle.. Genet Sel Evol 2017 Dec 22;49(1):92.
    doi: 10.1186/s12711-017-0370-xpmc: PMC5741860pubmed: 29273000google scholar: lookup
  2. Luan T, Yu X, Dolezal M, Bagnato A, Meuwissen TH. Genomic prediction based on runs of homozygosity.. Genet Sel Evol 2014 Oct 4;46(1):64.
    doi: 10.1186/s12711-014-0064-6pmc: PMC4189176pubmed: 25284459google scholar: lookup
  3. Pryce JE, Haile-Mariam M, Goddard ME, Hayes BJ. Identification of genomic regions associated with inbreeding depression in Holstein and Jersey dairy cattle.. Genet Sel Evol 2014 Nov 18;46(1):71.
    doi: 10.1186/s12711-014-0071-7pmc: PMC4234836pubmed: 25407532google scholar: lookup
  4. 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 Aug;100(8):6009-6024.
    doi: 10.3168/jds.2017-12787pubmed: 28601448google scholar: lookup
  5. Peripolli E, Munari DP, Silva MVGB, Lima ALF, Irgang R, Baldi F. Runs of homozygosity: current knowledge and applications in livestock.. Anim Genet 2017 Jun;48(3):255-271.
    doi: 10.1111/age.12526pubmed: 27910110google scholar: lookup
  6. Kim ES, Sonstegard TS, Van Tassell CP, Wiggans G, Rothschild MF. The Relationship between Runs of Homozygosity and Inbreeding in Jersey Cattle under Selection.. PLoS One 2015;10(7):e0129967.
    doi: 10.1371/journal.pone.0129967pmc: PMC4496098pubmed: 26154171google scholar: lookup
  7. Kardos M, Åkesson M, Fountain T, Flagstad Ø, Liberg O, Olason P, Sand H, Wabakken P, Wikenros C, Ellegren H. Genomic consequences of intensive inbreeding in an isolated wolf population.. Nat Ecol Evol 2018 Jan;2(1):124-131.
    doi: 10.1038/s41559-017-0375-4pubmed: 29158554google scholar: lookup
  8. Ayroles JF, Hughes KA, Rowe KC, Reedy MM, Rodriguez-Zas SL, Drnevich JM, Cáceres CE, Paige KN. A genomewide assessment of inbreeding depression: gene number, function, and mode of action.. Conserv Biol 2009 Aug;23(4):920-30.
    doi: 10.1111/j.1523-1739.2009.01186.xpubmed: 19627320google scholar: lookup
  9. Charlesworth D, Willis JH. The genetics of inbreeding depression.. Nat Rev Genet 2009 Nov;10(11):783-96.
    doi: 10.1038/nrg2664pubmed: 19834483google scholar: lookup
  10. Ponsart C, Le Bourhis D, Knijn H, Fritz S, Guyader-Joly C, Otter T, Lacaze S, Charreaux F, Schibler L, Dupassieux D, Mullaart E. Reproductive technologies and genomic selection in dairy cattle.. Reprod Fertil Dev 2013;26(1):12-21.
    doi: 10.1071/RD13328pubmed: 24305173google scholar: lookup
  11. Jäderkvist Fegraeus K, Velie BD, Axelsson J, Ang R, Hamilton NA, Andersson L, Meadows JRS, Lindgren G. A potential regulatory region near the EDN3 gene may control both harness racing performance and coat color variation in horses.. Physiol Rep 2018 May;6(10):e13700.
    doi: 10.14814/phy2.13700pmc: PMC5974718pubmed: 29845762google scholar: lookup
  12. Klemetsdal G. Norwegian trotter breeding and estimation of breeding values. In: State of breeding evaluation in trotters. In Proceedings of the European Federation of Animal Science Symposium of the Commission on Horse Production: 27 June–1 July 1988; Helsinki.; 1989. pp 95–105.
  13. Arnason T, Bendroth M, Philipsson J, Henriksson K, Darenius A. Genetic evaluation of Swedish trotters. In State of breeding evaluation in trotters. In Proceedings of the European Federation of Animal Science Symposium of the Commission on Horse Production: 27 June–1 July 1988; Helsinki.; 1989. pp 106–30.
  14. Svensk Travsport. 2018. https://www.travsport.se/wicket/bookmarkable/se.atg.web.travsport.page.polopoly.ArticlePage?6&cid=2.255. Accessed 1 Sept 2018.
  15. Klemetsdal G. The effect of inbreeding on racing performance in Norwegian cold-blooded trotters. Genet Sel Evol 1998;30:351–366.
    doi: 10.1186/1297-9686-30-4-351google scholar: lookup
  16. Sargolzaei M, Iwaisaki H, Colleau JJ. CFC, A tool for monitoring genetic diversity. In: Proceedings of the 8th World Congress on Genetics Applied to Livestock Production: 13–18 August 2006; Belo Horizonte; 2006.
  17. Forneris NS, Steibel JP, Legarra A, Vitezica ZG, Bates RO, Ernst CW, Basso AL, Cantet RJ. A comparison of methods to estimate genomic relationships using pedigree and markers in livestock populations.. J Anim Breed Genet 2016 Dec;133(6):452-462.
    doi: 10.1111/jbg.12217pubmed: 27135179google scholar: lookup
  18. Druml T, Neuditschko M, Grilz-Seger G, Horna M, Ricard A, Mesaric 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 May 11;109(4):384-392.
    doi: 10.1093/jhered/esx114pubmed: 29294044google scholar: lookup
  19. Keller MC, Visscher PM, Goddard ME. Quantification of inbreeding due to distant ancestors and its detection using dense single nucleotide polymorphism data.. Genetics 2011 Sep;189(1):237-49.
    doi: 10.1534/genetics.111.130922pmc: PMC3176119pubmed: 21705750google scholar: lookup
  20. Ferenčaković M, Sölkner J, Curik I. Estimating autozygosity from high-throughput information: effects of SNP density and genotyping errors.. Genet Sel Evol 2013 Oct 29;45(1):42.
    doi: 10.1186/1297-9686-45-42pmc: PMC4176748pubmed: 24168655google scholar: lookup
  21. 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 2015 Oct 9;16:764.
    doi: 10.1186/s12864-015-1977-3pmc: PMC4600213pubmed: 26452642google scholar: lookup
  22. Kamiński S, Hering DM, Jaworski Z, Zabolewicz T, Ruść A. Assessment of genomic inbreeding in Polish Konik horses.. Pol J Vet Sci 2017 Sep 26;20(3):603-605.
    doi: 10.1515/pjvs-2017-0074pubmed: 29166287google scholar: lookup
  23. R Development Core Team. R-A Language and environment for statistical computing. 2018 https://www.r-project.org/. Accessed 1 April 2018.
  24. Hu ZL, Park CA, Reecy JM. Developmental progress and current status of the Animal QTLdb.. Nucleic Acids Res 2016 Jan 4;44(D1):D827-33.
    doi: 10.1093/nar/gkv1233pmc: PMC4702873pubmed: 26602686google scholar: lookup
  25. Neph S, Kuehn MS, Reynolds AP, Haugen E, Thurman RE, Johnson AK, Rynes E, Maurano MT, Vierstra J, Thomas S, Sandstrom R, Humbert R, Stamatoyannopoulos JA. BEDOPS: high-performance genomic feature operations.. Bioinformatics 2012 Jul 15;28(14):1919-20.
    doi: 10.1093/bioinformatics/bts277pmc: PMC3389768pubmed: 22576172google scholar: lookup
  26. Kardos M, Luikart G, Allendorf FW. Measuring individual inbreeding in the age of genomics: marker-based measures are better than pedigrees.. Heredity (Edinb) 2015 Jul;115(1):63-72.
    doi: 10.1038/hdy.2015.17pmc: PMC4815495pubmed: 26059970google scholar: lookup
  27. Department of Agriculture. Delmål för husdjursgenetiska resurser åren 2010 till 2020. 2009. http://www.jordbruksverket.se/download/18.2958036f1211efb32978000308/rapport%2B070511.pdf. Accessed 1 Sept 2018.
  28. Svensk Travsport; 2018 https://www.travsport.se/artikel/kvalificerings-_&_premielopp. Accessed 1 Sept 2018.
  29. Det Norske Travselskap; 2018 https://www.travsport.no. Accessed 1 Sept 2018.
  30. Dierks C, Komm K, Lampe V, Distl O. Fine mapping of a quantitative trait locus for osteochondrosis on horse chromosome 2.. Anim Genet 2010 Dec;41 Suppl 2:87-90.
    doi: 10.1111/j.1365-2052.2010.02113.xpubmed: 21070281google scholar: lookup
  31. Orr N, Hill EW, Gu J, Govindarajan P, Conroy J, van Grevenhof EM, Ducro BJ, van Arendonk JA, Knaap JH, van Weeren PR, Machugh DE, Ennis S, Brama PA. Genome-wide association study of osteochondrosis in the tarsocrural joint of Dutch Warmblood horses identifies susceptibility loci on chromosomes 3 and 10.. Anim Genet 2013 Aug;44(4):408-12.
    doi: 10.1111/age.12016pubmed: 23278111google scholar: lookup
  32. Lykkjen S, Dolvik NI, McCue ME, Rendahl AK, Mickelson JR, Roed KH. Genome-wide association analysis of osteochondrosis of the tibiotarsal joint in Norwegian Standardbred trotters.. Anim Genet 2010 Dec;41 Suppl 2:111-20.
    doi: 10.1111/j.1365-2052.2010.02117.xpubmed: 21070284google scholar: lookup
  33. Lampe V, Dierks C, Distl O. Refinement of a quantitative gene locus on equine chromosome 16 responsible for osteochondrosis in Hanoverian warmblood horses.. Animal 2009 Sep;3(9):1224-31.
    doi: 10.1017/S1751731109004765pubmed: 22444898google scholar: lookup
  34. Fritz KL, McCue ME, Valberg SJ, Rendahl AK, Mickelson JR. Genetic mapping of recurrent exertional rhabdomyolysis in a population of North American Thoroughbreds.. Anim Genet 2012 Dec;43(6):730-8.
    doi: 10.1111/j.1365-2052.2012.02351.xpmc: PMC3665002pubmed: 22497487google scholar: lookup
  35. Gottschalk M, Metzger J, Martinsson G, Sieme H, Distl O. Genome-wide association study for semen quality traits in German Warmblood stallions.. Anim Reprod Sci 2016 Aug;171:81-6.
    doi: 10.1016/j.anireprosci.2016.06.002pubmed: 27334685google scholar: lookup
  36. de Simoni Gouveia JJ, da Silva MV, Paiva SR, de Oliveira SM. Identification of selection signatures in livestock species.. Genet Mol Biol 2014 Jun;37(2):330-42.
    doi: 10.1590/S1415-47572014000300004pmc: PMC4094609pubmed: 25071397google scholar: lookup

Citations

This article has been cited 7 times.
  1. Lindsay-McGee V, Sanchez-Molano E, Banos G, Clark EL, Piercy RJ, Psifidi A. Genetic characterisation of the Connemara pony and the Warmblood horse using a within-breed clustering approach.. Genet Sel Evol 2023 Aug 17;55(1):60.
    doi: 10.1186/s12711-023-00827-wpubmed: 37592264google scholar: lookup
  2. Cardinali I, Giontella A, Tommasi A, Silvestrelli M, Lancioni H. Unlocking Horse Y Chromosome Diversity.. Genes (Basel) 2022 Dec 2;13(12).
    doi: 10.3390/genes13122272pubmed: 36553539google scholar: lookup
  3. Perdomo-González DI, Laseca N, Demyda-Peyrás S, Valera M, Cervantes I, Molina A. Fine-tuning genomic and pedigree inbreeding rates in equine population with a deep and reliable stud book: the case of the Pura Raza Española horse.. J Anim Sci Biotechnol 2022 Nov 7;13(1):127.
    doi: 10.1186/s40104-022-00781-5pubmed: 36336696google scholar: lookup
  4. Laseca N, Molina A, Ramón M, Valera M, Azcona F, Encina A, Demyda-Peyrás S. Fine-Scale Analysis of Runs of Homozygosity Islands Affecting Fertility in Mares.. Front Vet Sci 2022;9:754028.
    doi: 10.3389/fvets.2022.754028pubmed: 35252415google scholar: lookup
  5. Laseca N, Anaya G, Peña Z, Pirosanto Y, Molina A, Demyda Peyrás S. Impaired Reproductive Function in Equines: From Genetics to Genomics.. Animals (Basel) 2021 Feb 3;11(2).
    doi: 10.3390/ani11020393pubmed: 33546520google scholar: lookup
  6. 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
  7. Grilz-Seger G, Neuditschko M, Ricard A, Velie B, Lindgren G, Mesarič M, Cotman M, Horna M, Dobretsberger M, Brem G, Druml T. Genome-Wide Homozygosity Patterns and Evidence for Selection in a Set of European and Near Eastern Horse Breeds.. Genes (Basel) 2019 Jun 28;10(7).
    doi: 10.3390/genes10070491pubmed: 31261764google scholar: lookup
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