Identification and validation of genetic variants predictive of gait in standardbred horses.
Abstract: Several horse breeds have been specifically selected for the ability to exhibit alternative patterns of locomotion, or gaits. A premature stop codon in the gene DMRT3 is permissive for "gaitedness" across breeds. However, this mutation is nearly fixed in both American Standardbred trotters and pacers, which perform a diagonal and lateral gait, respectively, during harness racing. This suggests that modifying alleles must influence the preferred gait at racing speeds in these populations. A genome-wide association analysis for the ability to pace was performed in 542 Standardbred horses (n = 176 pacers, n = 366 trotters) with genotype data imputed to ~74,000 single nucleotide polymorphisms (SNPs). Nineteen SNPs on nine chromosomes (ECA1, 2, 6, 9, 17, 19, 23, 25, 31) reached genome-wide significance (p < 1.44 x 10-6). Variant discovery in regions of interest was carried out via whole-genome sequencing. A set of 303 variants from 22 chromosomes with putative modifying effects on gait was genotyped in 659 Standardbreds (n = 231 pacers, n = 428 trotters) using a high-throughput assay. Random forest classification analysis resulted in an out-of-box error rate of 0.61%. A conditional inference tree algorithm containing seven SNPs predicted status as a pacer or trotter with 99.1% accuracy and subsequently performed with 99.4% accuracy in an independently sampled population of 166 Standardbreds (n = 83 pacers, n = 83 trotters). This highly accurate algorithm could be used by owners/trainers to identify Standardbred horses with the potential to race as pacers or as trotters, according to the genotype identified, prior to initiating training and would enable fine-tuning of breeding programs with designed matings. Additional work is needed to determine both the algorithm's utility in other gaited breeds and whether any of the predictive SNPs play a physiologically functional role in the tendency to pace or tag true functional alleles.
Publication Date: 2019-05-28 PubMed ID: 31136578PubMed Central: PMC6555539DOI: 10.1371/journal.pgen.1008146Google Scholar: Lookup
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- Journal Article
- Research Support
- N.I.H.
- Extramural
- Research Support
- Non-U.S. Gov't
- Research Support
- U.S. Gov't
- Non-P.H.S.
Summary
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This study identifies and validates genetic variants that predict the type of gait in Standardbred horses, which can help trainers determine whether a horse is suited to be a pacer or trotter before training begins.
Objective and Methodology
- The researchers conducted a genomic study on Standardbred horses to identify genetic variations that could predict their ability to perform certain types of gaits. Gaits, in this context, refer to the patterns of movement of the horses. Horses can either be pacers (lateral movement) or trotters (diagonal movement).
- Using a genome-wide association analysis, the team studied genetic details of 542 horses (176 pacers and 366 trotters) to identify genetic predictors of gait. A set of around 74,000 single nucleotide polymorphisms or SNPs (variations in single base pairs in a DNA sequence) were analyzed.
- Thereafter, genomic regions of interest were mapped through whole genome sequencing to find possible modifying effects on gait.
Results and Findings
- Nineteen SNPs on nine different chromosomes were significantly associated with the ability to pace.
- The combination of these genetic variations was then mapped in 659 more Standardbreds using high-throughput genetic screening, resulting in a very low error rate of 0.61%, proving the accuracy of this model’s predictions.
- Further, an algorithm was developed using a random forest classification analysis, containing seven SNPs, that accurately predicted a horse’s gait status as a pacer or trotter with 99.1% accuracy. This algorithm was tested on another sample of 166 Standardbreds and gave an accuracy of 99.4%.
Implications and Future Research
- The implications of this research are significant for horse trainers, owners, and breeders. Using this algorithm, they can determine the potential of a Standardbred horse to race as a pacer or a trotter before initiating any training. This could also allow breeders to fine-tune their breeding programs accordingly.
- Further research is required to test the utility of this algorithm in other breeds and to determine if any of the SNPs identified play a functional role in determining a horse’s gait or if they tag other functional genetic alleles.
Cite This Article
APA
McCoy AM, Beeson SK, Rubin CJ, Andersson L, Caputo P, Lykkjen S, Moore A, Piercy RJ, Mickelson JR, McCue ME.
(2019).
Identification and validation of genetic variants predictive of gait in standardbred horses.
PLoS Genet, 15(5), e1008146.
https://doi.org/10.1371/journal.pgen.1008146 Publication
Researcher Affiliations
- Department of Veterinary Clinical Medicine, University of Illinois, Urbana, Illinois, United States of America.
- Veterinary Population Medicine Department, University of Minnesota, St. Paul, Minnesota, United States of America.
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas, United States of America.
- Paul Caputo, DVM, Pompano Beach, Florida, United States of America.
- Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Oslo, Norway.
- Moore Equine Services, Cambridge, Ontario, Canada.
- Department of Clinical Sciences and Services, Royal Veterinary College, London, United Kingdom.
- Veterinary and Biomedical Sciences Department, University of Minnesota, St. Paul, Minnesota, United States of America.
- Veterinary Population Medicine Department, University of Minnesota, St. Paul, Minnesota, United States of America.
MeSH Terms
- Algorithms
- Alleles
- Animals
- Biomarkers
- Codon, Nonsense / genetics
- Gait / genetics
- Gene Frequency / genetics
- Genetic Variation / genetics
- Genome-Wide Association Study
- Genotype
- Horses / genetics
- Locomotion / genetics
- Mutation / genetics
- Polymorphism, Single Nucleotide / genetics
- Selective Breeding
- Transcription Factors / genetics
Grant Funding
- F30 OD023369 / NIH HHS
- K08 AR055713 / NIAMS NIH HHS
- T32 OD010993 / NIH HHS
Conflict of Interest Statement
I have read the journal\'s policy and the authors of this manuscript have the following competing interests: AMM and MEM are named as inventors on a pending patent application for the predictive model described herein, submitted by the University of Minnesota.
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