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Home / Equine Research Bank / Genet Sel Evol / Genetic analysis of geometric morphometric 3D visuals of Fre...
Genetics, selection, evolution : GSE2023; 55(1); 63; doi: 10.1186/s12711-023-00837-8

Genetic analysis of geometric morphometric 3D visuals of French jumping horses.

Abstract: For centuries, morphology has been the most commonly selected trait in horses. A 3D video recording enabled us to obtain the coordinates of 43 anatomical landmarks of 2089 jumping horses. Generalized Procrustes analysis provided centered and scaled coordinates that were independent of volume, i.e., centroid size. Genetic analysis of these coordinates (mixed model; 17,994 horses in the pedigree) allowed us to estimate a variance-covariance matrix. New phenotypes were then defined: the "summarized shapes". They were obtained by linear combinations of Procrustes coordinates with, as coefficients, the eigenvectors of the genetic variance-covariance matrix. These new phenotypes were used in genome-wide association analyses (GWAS) and multitrait genetic analysis that included judges' scores and competition results of the horses. Results: We defined ten shapes that represented 86% of the variance, with heritabilities ranging from 0.14 to 0.42. Only one of the shapes was found to be genetically correlated with competition success (r = - 0.12, standard error = 0.07). Positive and negative genetic correlations between judges' scores and shapes were found. This means that the breeding objective defined by judges involves improvement of anatomical parts of the body that are negatively correlated with each other. Known single nucleotide polymorphisms (SNPs) on chromosomes 1 and 3 for height at withers were significant for centroid size but not for any of the shapes. As these SNPs were not associated with the shape that distinguished rectangular horses from square horses (with height at withers greater than body length), we hypothesize that these SNPs play a role in the overall development of horses, i.e. in height, width, and length but not in height at withers when standardized to unit centroid size. Several other SNPs were found significant for other shapes. Conclusions: The main application of 3D morphometric analysis is the ability to define the estimated breeding value (EBV) of a sire based on the shape of its potential progeny, which is easier for breeders to visualize in a single synthetic image than a full description based on linear profiling. However, the acceptance of these new phenotypes by breeders and the complex nature of summarized shapes may be challenging. Due to the low genetic correlations of the summarized shapes with jumping performance, the methodology did not allow indirect performance selection criteria to be defined.
© 2023. ’Institut National de Recherche en Agriculture, Alimentation et Environnement (INRAE).
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Publication Date: 2023-09-18 PubMed ID: 37723416PubMed Central: PMC10506242DOI: 10.1186/s12711-023-00837-8Google Scholar: Lookup
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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 the analysis of genetic factors influencing the physical shapes of French jumping horses using 3D imaging, and its impact on performance and breeding choices.

Methodology

  • The researchers used 3D video recording to capture the coordinates of 43 anatomical landmarks on 2089 jumping horses.
  • A technique known as Generalized Procrustes analysis was then used to provide scaled coordinates that were independent of volume, thus neutralizing the effect of size differences.
  • Using a mixed model and a pedigree of 17,994 horses, genetic analysis was performed on these coordinates to estimate a variance-covariance matrix.
  • New phenotypes, known as “summarized shapes”, were defined as linear combinations of Procrustes coordinates with the eigenvectors of the genetic variance-covariance matrix as coefficients.
  • These new phenotypes were used in genome-wide association analyses (GWAS) and a multitrait genetic analysis that included judges’ scores and competition results of the horses.

Results

  • Ten shapes were defined that represented 86% of the variance, with heritabilities ranging from 0.14 to 0.42.
  • Only one of the shapes was found to be genetically correlated with competition success.
  • Positive and negative genetic correlations were found between judges’ scores and shapes, indicating that the breeding goals set by judges involve improvement of body parts that are negatively correlated with each other.
  • Known single nucleotide polymorphisms (SNPs) on chromosomes 1 and 3 associated with height at withers were significant for overall horse development, but not for any of the shapes.
  • Several other significant SNPs were discovered for other shapes.

Conclusions

  • The primary application of 3D morphometric analysis allows breeders to determine the estimated breeding value (EBV) of a sire based on the potential shape of its offspring. This is easier to visualize in a single image rather than a full description based on linear profiling.
  • However, the acceptance of these new phenotypes by breeders might be challenging due to the complexity of summarized shapes.
  • Since the genetic correlations of the summarized shapes with jumping performance are low, the methodology did not allow for defining indirect performance selection criteria.

Cite This Article

APA
Ricard A, Crevier-Denoix N, Pourcelot P, Crichan H, Sabbagh M, Dumont-Saint-Priest B, Danvy S. (2023). Genetic analysis of geometric morphometric 3D visuals of French jumping horses. Genet Sel Evol, 55(1), 63. https://doi.org/10.1186/s12711-023-00837-8

Publication

Genetics, selection, evolution : GSE
ISSN: 1297-9686
NlmUniqueID: 9114088
Country: France
Language: English
Volume: 55
Issue: 1
Pages: 63
PII: 63

Researcher Affiliations

Ricard, Anne
  • Pôle développement, innovation et recherche, Institut français du cheval et de l'équitation, 61310, Exmes-Gouffern en Auge, France. anne.ricard@inrae.fr.
  • Université Paris Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France. anne.ricard@inrae.fr.
Crevier-Denoix, Nathalie
  • INRAE, Ecole Nationale Vétérinaire d'Alfort, Unité 957 BPLC, 94700, Maisons-Alfort, France.
Pourcelot, Philippe
  • INRAE, Ecole Nationale Vétérinaire d'Alfort, Unité 957 BPLC, 94700, Maisons-Alfort, France.
Crichan, Harmony
  • Pôle développement, innovation et recherche, Institut français du cheval et de l'équitation, 61310, Exmes-Gouffern en Auge, France.
Sabbagh, Margot
  • Pôle développement, innovation et recherche, Institut français du cheval et de l'équitation, 61310, Exmes-Gouffern en Auge, France.
Dumont-Saint-Priest, Bernard
  • Pôle développement, innovation et recherche, Institut français du cheval et de l'équitation, 61310, Exmes-Gouffern en Auge, France.
Danvy, Sophie
  • Pôle développement, innovation et recherche, Institut français du cheval et de l'équitation, 61310, Exmes-Gouffern en Auge, France.

MeSH Terms

  • Animals
  • Horses / genetics
  • Genome-Wide Association Study
  • Pedigree
  • Phenotype
  • Polymorphism, Single Nucleotide

Conflict of Interest Statement

The authors declare that they have no competing interests.

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