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

BACKGROUND: 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 vo...

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Autores principales: Ricard, Anne, Crevier-Denoix, Nathalie, Pourcelot, Philippe, Crichan, Harmony, Sabbagh, Margot, Dumont-Saint-Priest, Bernard, Danvy, Sophie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10506242/
https://www.ncbi.nlm.nih.gov/pubmed/37723416
http://dx.doi.org/10.1186/s12711-023-00837-8
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author Ricard, Anne
Crevier-Denoix, Nathalie
Pourcelot, Philippe
Crichan, Harmony
Sabbagh, Margot
Dumont-Saint-Priest, Bernard
Danvy, Sophie
author_facet Ricard, Anne
Crevier-Denoix, Nathalie
Pourcelot, Philippe
Crichan, Harmony
Sabbagh, Margot
Dumont-Saint-Priest, Bernard
Danvy, Sophie
author_sort Ricard, Anne
collection PubMed
description BACKGROUND: 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(g) = − 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12711-023-00837-8.
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spelling pubmed-105062422023-09-19 Genetic analysis of geometric morphometric 3D visuals of French jumping horses Ricard, Anne Crevier-Denoix, Nathalie Pourcelot, Philippe Crichan, Harmony Sabbagh, Margot Dumont-Saint-Priest, Bernard Danvy, Sophie Genet Sel Evol Research Article BACKGROUND: 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(g) = − 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12711-023-00837-8. BioMed Central 2023-09-18 /pmc/articles/PMC10506242/ /pubmed/37723416 http://dx.doi.org/10.1186/s12711-023-00837-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Ricard, Anne
Crevier-Denoix, Nathalie
Pourcelot, Philippe
Crichan, Harmony
Sabbagh, Margot
Dumont-Saint-Priest, Bernard
Danvy, Sophie
Genetic analysis of geometric morphometric 3D visuals of French jumping horses
title Genetic analysis of geometric morphometric 3D visuals of French jumping horses
title_full Genetic analysis of geometric morphometric 3D visuals of French jumping horses
title_fullStr Genetic analysis of geometric morphometric 3D visuals of French jumping horses
title_full_unstemmed Genetic analysis of geometric morphometric 3D visuals of French jumping horses
title_short Genetic analysis of geometric morphometric 3D visuals of French jumping horses
title_sort genetic analysis of geometric morphometric 3d visuals of french jumping horses
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10506242/
https://www.ncbi.nlm.nih.gov/pubmed/37723416
http://dx.doi.org/10.1186/s12711-023-00837-8
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