FREE SHIPPING over $40
OVER 10000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Animal genetics2023; 54(4); 470-482; doi: 10.1111/age.13332

Long-read sequencing assays designed to detect potential gene editing events in the myostatin gene revealed distinct haplotype signatures in the Thoroughbred horse population.

Abstract: We present here the use of targeted, long-read sequencing of the myostatin (MSTN) gene as a model to detect potential gene editing events in Thoroughbred horses. MSTN is a negative regulator of muscle development, making the gene a prime candidate target for gene doping. By sequencing the complete gene in one PCR product, we can catalogue all mutations without the need to produce short-fragment libraries. A panel of reference material fragments with defined mutations was constructed and successfully sequenced by both Oxford Nanopore and Illumina-based methods, showing that gene doping editing events can be detected using this technology. To ascertain the normal variation within the population, we sequenced the MSTN gene in 119 UK Thoroughbred horses. Variants from the reference genome were assigned to haplotypes and eight distinct patterns, designated Hap1 (reference genome) to Hap8, were determined with haplotypes Hap2 and Hap3 (which includes the 'speed gene' variant) being far the most prevalent. Hap3 was most abundant in flat-racing horses, whereas Hap2 was most abundant in jump-racing. Within this data set, results for 105 racehorses from out-of-competition sampling were compared between matrices of extracted DNA and direct PCR of whole blood from lithium heparin gel tubes, and strong agreement was found between the two methods. The direct-blood PCR was achieved without compromising the sample prior to plasma separation for analytical chemistry, and could thus be used as part of a routine screening workflow for gene editing detection.
© 2023 Stichting International Foundation for Animal Genetics.
Get Full Text
Publication Date: 2023-06-08 PubMed ID: 37288798DOI: 10.1111/age.13332Google 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

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 paper uncovers how long-read sequencing of the myostatin (MSTN) gene can be utilized to detect potential gene editing events in Thoroughbred horses and portrays the variation within the gene in the Thoroughbred population through eight distinct haplotype patterns.

Methodology

  • The researchers employed targeted, long-read sequencing of the MSTN gene to discover potential gene “doping”. MSTN is known to negatively regulate muscle growth, therefore making it a suitable target for gene doping.
  • Complete gene sequencing allowed the researchers to record all mutations without having to create short-fragment libraries.
  • A panel of defined, referential mutation fragments was constructed and sequenced through the use of both Oxford Nanopore and Illumina methodologies.

Results

  • The researchers sequenced the MSTN gene in 119 UK Thoroughbred horses in order to understand the standard variation within the breed.
  • Divergent from the reference genome, these variants were assigned to haplotypes. Eight unique patterns, named Hap1 (reference genome) to Hap8, were identified.
  • The two most commonplace haplotypes were Hap2 and Hap3, which contains the ‘speed gene’ variant. Hap2 was most abundant in jump-racing horses while Hap3 was most common in flat-racing horses.
  • Within this data set, the researchers compared the results for 105 racehorses collected from out-of-competition sampling between matrices of extracted DNA and direct PCR of whole blood from lithium heparin gel tubes, finding a strong agreement between the two methods.

Implications

  • The direct blood PCR was executed without compromising the sample prior to plasma separation for chemical analysis.
  • Therefore, this sampling method could be exploited as a part of a regular screening workflow to detect gene editing.

The findings of this study indicate that long-read sequencing techniques can be effectively used to detect potential gene editing events in Thoroughbred horses, aiding in the fight against gene doping in horse racing.

Cite This Article

APA
Maniego J, Giles O, Hincks P, Stewart G, Proudman C, Ryder E. (2023). Long-read sequencing assays designed to detect potential gene editing events in the myostatin gene revealed distinct haplotype signatures in the Thoroughbred horse population. Anim Genet, 54(4), 470-482. https://doi.org/10.1111/age.13332

Publication

Animal genetics
ISSN: 1365-2052
NlmUniqueID: 8605704
Country: England
Language: English
Volume: 54
Issue: 4
Pages: 470-482

Researcher Affiliations

Maniego, Jillian
  • Sport and Specialised Analytical Services, LGC Assure, Cambridgeshire, UK.
Giles, Orla
  • Sport and Specialised Analytical Services, LGC Assure, Cambridgeshire, UK.
Hincks, Pamela
  • Sport and Specialised Analytical Services, LGC Assure, Cambridgeshire, UK.
Stewart, Graham
  • School of Biosciences and Medicine, University of Surrey, Guildford, UK.
Proudman, Christopher
  • School of Veterinary Medicine, University of Surrey, Guildford, UK.
Ryder, Edward
  • Sport and Specialised Analytical Services, LGC Assure, Cambridgeshire, UK.

MeSH Terms

  • Horses / genetics
  • Animals
  • Haplotypes
  • Myostatin / genetics
  • Gene Editing
  • DNA
  • Base Sequence

Grant Funding

  • British Horseracing Authority

References

This article includes 59 references
  1. Ammar R, Paton TA, Torti D, Shlien A, Bader GD. Long read nanopore sequencing for detection of HLA and CYP2D6 variants and haplotypes. F1000Research 2015, 4, 17.
    doi: 10.12688/f1000research.6037.2google scholar: lookup
  2. Clop A, Marcq F, Takeda H, Pirottin D, Tordoir X, Bibé B. A mutation creating a potential illegitimate microRNA target site in the myostatin gene affects muscularity in sheep. Nature Genetics 2006, 38(7), 813-818.
    doi: 10.1038/ng1810google scholar: lookup
  3. Cornelis S, Gansemans Y, Deleye L, Deforce D, van Nieuwerburgh F. Forensic SNP genotyping using nanopore MinION sequencing. Scientific Reports 2017, 7, Article 41759.
    doi: 10.1038/srep41759google scholar: lookup
  4. Crispo M, Mulet AP, Tesson L, Barrera N, Cuadro F, dos Santos-Neto PC. Efficient generation of myostatin knock-out sheep using CRISPR/Cas9 technology and microinjection into zygotes. PLoS One 2015, 10(8), e0136690.
    doi: 10.1371/journal.pone.0136690google scholar: lookup
  5. Dall'Olio S, Scotti E, Fontanesi L, Tassinari M. Analysis of the 227 bp short interspersed nuclear element (SINE) insertion of the promoter of the myostatin (MSTN) gene in different horse breeds. Veterinaria Italiana 2014, 50(3), 193-197.
    doi: 10.12834/vetit.61.178.3google scholar: lookup
  6. Danecek P, Bonfield JK, Liddle J, Marshall J, Ohan V, Pollard MO. Twelve years of SAMtools and BCFtools. GigaScience 2021, 10(2), 1-4.
    doi: 10.1093/gigascience/giab008google scholar: lookup
  7. De Coster W, D'Hert S, Schultz DT, Cruts M, Van Broeckhoven C. NanoPack: visualizing and processing long-read sequencing data. Bioinformatics 2018, 34(15), 2666-2669.
    doi: 10.1093/bioinformatics/bty149google scholar: lookup
  8. Deamer D, Akeson M, Branton D. Three decades of nanopore sequencing. Nature Biotechnology 2016, 34, 518-524.
    doi: 10.1038/nbt.3423google scholar: lookup
  9. Deiner K, Renshaw MA, Li Y, Olds BP, Lodge DM, Pfrender ME. Long-range PCR allows sequencing of mitochondrial genomes from environmental DNA. Methods in Ecology and Evolution 2017, 8(12), 1888-1898.
    doi: 10.1111/2041-210x.12836google scholar: lookup
  10. Gibson DG, Young L, Chuang RY, Venter JC, Hutchison CA, Smith HO. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nature Methods 2009, 6(5), 343-345.
    doi: 10.1038/nmeth.1318google scholar: lookup
  11. Gim GM, Kwon DH, Eom KH, Moon J, Park JH, Lee WW. Production of MSTN-mutated cattle without exogenous gene integration using CRISPR-Cas9. Biotechnology Journal 2021, 17, 2100198.
    doi: 10.1002/biot.202100198google scholar: lookup
  12. Ginevičienė V, Jakaitienė A, Pranckevičienė E, Milašius K, Utkus A. Variants in the myostatin gene and physical performance phenotype of elite athletes. Genes 2021, 12(5), 757.
    doi: 10.3390/genes12050757google scholar: lookup
  13. Han H, Ma Y, Wang T, Lian L, Tian X, Hu R. One-step generation of myostatin gene knockout sheep via the CRISPR/Cas9 system. Frontiers of Agricultural Science and Engineering 2014, 1(1), 2.
    doi: 10.15302/j-fase-2014007google scholar: lookup
  14. Hill EW, Gu J, Eivers SS, Fonseca RG, McGivney BA, Govindarajan P. A sequence polymorphism in MSTN predicts sprinting ability and racing stamina in thoroughbred horses. PLoS One 2010, 5(1), e8645.
    doi: 10.1371/journal.pone.0008645google scholar: lookup
  15. Hill EW, McGivney BA, Gu J, Whiston R, MacHugh DE. A genome-wide SNP-association study confirms a sequence variant (g.66493737C>T) in the equine myostatin (MSTN) gene as the most powerful predictor of optimum racing distance for thoroughbred racehorses. BMC Genomics 2010, 11(1), 552.
    doi: 10.1186/1471-2164-11-552google scholar: lookup
  16. Hill EW, McGivney BA, Rooney MF, Katz LM, Parnell A, MacHugh DE. The contribution of myostatin (MSTN) and additional modifying genetic loci to race distance aptitude in thoroughbred horses racing in different geographic regions. Equine Veterinary Journal 2019, 51(5), 625-633.
    doi: 10.1111/evj.13058google scholar: lookup
  17. Hwang WY, Fu Y, Reyon D, Maeder ML, Kaini P, Sander JD. Heritable and precise zebrafish genome editing using a CRISPR-Cas system. PLoS One 2013, 8(7), e68708.
    doi: 10.1371/journal.pone.0068708google scholar: lookup
  18. Ikawa M, Tanaka N, Kao WWY, Verma IM. Generation of transgenic mice using lentiviral vectors: a novel preclinical assessment of lectiviral vectors for gene therapy. Molecular Therapy 2003, 8(4), 666-673.
    doi: 10.1016/s1525-0016(03)00240-5google scholar: lookup
  19. Jain M, Koren S, Miga KH, Quick J, Rand AC, Sasani TA. Nanopore sequencing and assembly of a human genome with ultra-long reads. Nature Biotechnology 2018, 36(4), 338-345.
    doi: 10.1038/nbt.4060google scholar: lookup
  20. Jain M, Olsen HE, Paten B, Akeson M. The Oxford nanopore MinION: delivery of nanopore sequencing to the genomics community. Genome Biology 2016, 17(1), 1-11.
    doi: 10.1186/s13059-016-1103-0google scholar: lookup
  21. Janečka JE, Davis BW, Ghosh S, Paria N, das PJ, Orlando L. Horse Y chromosome assembly displays unique evolutionary features and putative stallion fertility genes. Nature Communications 2018, 9(1), 2945.
    doi: 10.1038/s41467-018-05290-6google scholar: lookup
  22. Johnson PL, Dodds KG, Bain WE, Greer GJ, McLean NJ, McLaren RJ. Investigations into the GDF8 g+6723G-A polymorphism in New Zealand Texel sheep. Journal of Animal Science 2009, 87(6), 1856-1864.
    doi: 10.2527/jas.2008-1508google scholar: lookup
  23. Kalbfleisch TS, Rice ES, DePriest MS Jr, Walenz BP, Hestand MS, Vermeesch JR. Improved reference genome for the domestic horse increases assembly contiguity and composition. Communications Biology 2018, 1(1), 197.
    doi: 10.1038/s42003-018-0199-zgoogle scholar: lookup
  24. Kambadur R, Sharma M, Smith TPL, Bass JJ. Mutations in myostatin (GDF8) in double-muscled Belgian Blue and Piedmontese cattle. Genome Research 1997, 7(9), 910-916.
    doi: 10.1101/gr.7.9.910google scholar: lookup
  25. Kosicki M, Tomberg K, Bradley A. Repair of double-strand breaks induced by CRISPR-Cas9 leads to large deletions and complex rearrangements. Nature Biotechnology 2018, 36, 765-771.
    doi: 10.1038/nbt.4192google scholar: lookup
  26. Lee S-J. Genetic analysis of the role of proteolysis in the activation of latent myostatin. PLoS One 2008, 3(2), e1628.
    doi: 10.1371/journal.pone.0001628google scholar: lookup
  27. Lee SJ, McPherron AC. Regulation of myostatin activity and muscle growth. Proceedings of the National Academy of Sciences of the United States of America 2001, 98(16), 9306-9311.
    doi: 10.1073/pnas.151270098google scholar: lookup
  28. Li H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 2018, 34(18), 3094-3100.
    doi: 10.1093/bioinformatics/bty191google scholar: lookup
  29. Li H, Durbin R. Fast and accurate short read alignment with burrows-wheeler transform. Bioinformatics 2009, 25(14), 1754-1760.
    doi: 10.1093/bioinformatics/btp324google scholar: lookup
  30. Liu HY, Zhou L, Zheng MY, Huang J, Wan S, Zhu A. Diagnostic and clinical utility of whole genome sequencing in a cohort of undiagnosed Chinese families with rare diseases. Scientific Reports 2019, 9(1), 1-11.
    doi: 10.1038/s41598-019-55832-1google scholar: lookup
  31. Lord J, McMullan DJ, Eberhardt RY, Rinck G, Hamilton SJ, Quinlan-Jones E. Prenatal exome sequencing analysis in fetal structural anomalies detected by ultrasonography (PAGE): a cohort study. The Lancet 2019, 393(10173), 747-757.
    doi: 10.1016/s0140-6736(18)31940-8google scholar: lookup
  32. Magi A, Giusti B, Tattini L. Characterization of MinION nanopore data for resequencing analyses. Briefings in Bioinformatics 2017, 18(6), 940-953.
    doi: 10.1093/bib/bbw077google scholar: lookup
  33. Martin M, Patterson M, Garg S, O Fischer S, Pisanti N, Klau GW. WhatsHap: fast and accurate read-based phasing. bioRxiv 2016, 085050.
    doi: 10.1101/085050google scholar: lookup
  34. McCabe MJ, Gauthier MEA, Chan CL, Thompson TJ, de Sousa SMC, Puttick C. Development and validation of a targeted gene sequencing panel for application to disparate cancers. Scientific Reports 2019, 9(1), 16.
    doi: 10.1038/s41598-019-52000-3google scholar: lookup
  35. McPherron AC, Lawler AM, Lee SJ. Regulation of skeletal muscle mass in mice by a new TGF-beta superfamily member. Nature 1997, 387(6628), 83-90.
    doi: 10.1038/387083a0google scholar: lookup
  36. Moro LN, Viale DL, Bastón JI, Arnold V, Suvá M, Wiedenmann E. Generation of myostatin edited horse embryos using CRISPR/Cas9 technology and somatic cell nuclear transfer. Scientific Reports 2020, 10(1), 1-10.
    doi: 10.1038/s41598-020-72040-4google scholar: lookup
  37. Mosher DS, Quignon P, Bustamante CD, Sutter NB, Mellersh CS, Parker HG. A mutation in the myostatin gene increases muscle mass and enhances racing performance in heterozygote dogs. PLoS Genetics 2007, 3(5), e79.
    doi: 10.1371/journal.pgen.0030079google scholar: lookup
  38. O'Hara V, Cowan A, Riddell D, Massey C, Martin J, Piercy RJ. A highly prevalent SINE mutation in the myostatin (MSTN) gene promoter is associated with low circulating myostatin concentration in thoroughbred racehorses. Scientific Reports 2021, 11(1), 7916.
    doi: 10.1038/s41598-021-86783-1google scholar: lookup
  39. Omelina ES, Ivankin AV, Letiagina AE, Pindyurin AV. Optimized PCR conditions minimizing the formation of chimeric DNA molecules from MPRA plasmid libraries. BMC Genomics 2019, 20(7), 1-10.
    doi: 10.1186/s12864-019-5847-2google scholar: lookup
  40. Petersen JL, Valberg SJ, Mickelson JR, McCue ME. Haplotype diversity in the equine myostatin gene with focus on variants associated with race distance propensity and muscle fiber type proportions. Animal Genetics 2014, 45(6), 827-835.
    doi: 10.1111/age.12205google scholar: lookup
  41. Pira E, Vacca GM, Dettori ML, Piras G, Moro M, Paschino P. Polymorphisms at myostatin gene (MSTN) and the associations with sport performances in Anglo-Arabian racehorses. Animals 2021, 11(4), 964.
    doi: 10.3390/ani11040964google scholar: lookup
  42. Rad R, Rad L, Wang W, Cadinanos J, Vassiliou G, Rice S. PiggyBac transposon mutagenesis: a tool for cancer gene discovery in mice. Science (New York, N.Y.) 2010, 330(6007), 1104-1107.
    doi: 10.1126/science.1193004google scholar: lookup
  43. Rooney MF, Hill EW, Kelly VP, Porter RK. The “speed gene” effect of myostatin arises in thoroughbred horses due to a promoter proximal SINE insertion. PLoS One 2018, 13(10), e0205664.
    doi: 10.1371/journal.pone.0205664google scholar: lookup
  44. Rooney MF, Neto NGB, Monaghan MG, Hill EW, Porter RK. Conditionally immortalised equine skeletal muscle cell lines for in vitro analysis. Biochemistry and Biophysics Reports 2022, 33, 101391.
    doi: 10.1016/j.bbrep.2022.101391google scholar: lookup
  45. Santagostino M, Khoriauli L, Gamba R, Bonuglia M, Klipstein O, Piras FM. Genome-wide evolutionary and functional analysis of the equine repetitive element 1: an insertion in the myostatin promoter affects gene expression. BMC Genetics 2015, 16(1), 126.
    doi: 10.1186/s12863-015-0281-1google scholar: lookup
  46. Satsangi J, Jewell DP, Welsh K, Bunce M, Bell JI. Effect of heparin on polymerase chain reaction. The Lancet 1994, 343, 1509-1510.
    doi: 10.1016/s0140-6736(94)92622-0google scholar: lookup
  47. Schuelke M, Wagner KR, Stolz LE, Hübner C, Riebel T, Kömen W. Myostatin mutation associated with gross muscle hypertrophy in a child. New England Journal of Medicine 2004, 350(26), 2682-2688.
    doi: 10.1056/nejmoa040933google scholar: lookup
  48. Skarnes WC, Rosen B, West AP, Koutsourakis M, Bushell W, Iyer V. A conditional knockout resource for the genome-wide study of mouse gene function. Nature 2011, 474(7351), 337-342.
    doi: 10.1038/nature10163google scholar: lookup
  49. Smolka M, Paulin LF, Grochowski CM, Mahmoud M, Behera S, Gandhi M. Comprehensive structural variant detection: from mosaic to population-level. bioRxiv .
    doi: 10.1101/2022.04.04.487055google scholar: lookup
  50. Sze MA, Schloss PD. The impact of DNA polymerase and number of rounds of amplification in PCR on 16S rRNA gene sequence data. mSphere 2019, 4(3).
    doi: 10.1128/msphere.00163-19google scholar: lookup
  51. Tait-Burkard C, Doeschl-Wilson A, McGrew MJ, Archibald AL, Sang HM, Houston RD. Livestock 2.0 - genome editing for fitter, healthier, and more productive farmed animals. Genome Biology 2018, 19(1), 204.
    doi: 10.1186/s13059-018-1583-1google scholar: lookup
  52. Thomas M, Langley B, Berry C, Sharma M, Kirk S, Bass J. Myostatin, a negative regulator of muscle growth, functions by inhibiting myoblast proliferation. Journal of Biological Chemistry 2000, 275(51), 40235-40243.
    doi: 10.1074/jbc.m004356200google scholar: lookup
  53. Tozaki T, Hamilton NA. Control of gene doping in human and horse sports. Gene Therapy 2021, 29, 107-112.
    doi: 10.1038/s41434-021-00267-5google scholar: lookup
  54. Tozaki T, Ohnuma A, Kikuchi M, Ishige T, Kakoi H, Hirota KI. Rare and common variant discovery by whole-genome sequencing of 101 thoroughbred racehorses. Scientific Reports 2021, 11(1), 16057.
    doi: 10.1038/s41598-021-95669-1google scholar: lookup
  55. Tozaki T, Ohnuma A, Nakamura K, Hano K, Takasu M, Takahashi Y. Detection of indiscriminate genetic manipulation in thoroughbred racehorses by targeted resequencing for gene-doping control. Genes 2022, 13(9), 1589.
    doi: 10.3390/genes13091589google scholar: lookup
  56. Vaughan-Shaw PG, Walker M, Ooi L, Gilbert N, Farrington SM, Dunlop MG. A simple method to overcome the inhibitory effect of heparin on DNA amplification. Cellular Oncology (Dordrecht) 2015, 38(6), 493-495.
    doi: 10.1007/s13402-015-0250-8google scholar: lookup
  57. Wolfman NM, McPherron AC, Pappano WN, Davies MV, Song K, Tomkinson KN. Activation of latent myostatin by the BMP-1/tolloid family of metalloproteinases. Proceedings of the National Academy of Sciences of the United States of America 2003, 100(26), 15842-15846.
    doi: 10.1073/pnas.2534946100google scholar: lookup
  58. Xu L, Zhao P, Mariano A, Han R. Targeted myostatin gene editing in multiple mammalian species directed by a single pair of TALE nucleases. Molecular Therapy-Nucleic Acids 2013, 2, e112.
    doi: 10.1038/mtna.2013.39google scholar: lookup
  59. Zheng Z, Li S, Su J, Leung AWS, Lam TW, Luo R. Symphonizing pileup and full-alignment for deep learning-based long-read variant calling. Nature Computational Science 2022, 2, 797-803.

Citations

This article has been cited 2 times.
  1. Jafari H, Abebe BK, Cong L, Ahmed Z, Zhaofei W, Sun M, Muhatai G, Chuzhao L, Dang R. Review: Genomic insights into the adaptive traits and stress resistance in modern horses. Stress Biol 2026 Jan 12;6(1):5.
    doi: 10.1007/s44154-025-00274-1pubmed: 41521281google scholar: lookup
  2. Wu D, Ding S, Liu N, Shi Y, Su P, Shi H, Shi Y, Han B, Cheng S, Ren X, Tian F, Chen P, Wu J, Su X, Li R. Codon changes challenge PCR-based gene doping detection. Gene Ther 2025 Dec;32(6):632-640.
    doi: 10.1038/s41434-025-00569-ypubmed: 41057515google scholar: lookup
Subscribe to our newsletter
Join 99,850 horse owners like you who receive our email updates on horse health and nutrition.