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Home / Equine Research Bank / Animals (Basel) / Estimates of Genetic Parameters for Shape Space Data in Fran...
Animals : an open access journal from MDPI2022; 12(17); 2186; doi: 10.3390/ani12172186

Estimates of Genetic Parameters for Shape Space Data in Franches-Montagnes Horses.

Abstract: Conformation traits such as joint angles are important selection criteria in equine breeding, but mainly consist of subjective evaluation scores given by breeding judges, showing limited variation. The horse shape space model extracts shape data from 246 landmarks (LM) and objective joint angle measurements from triplets of LM on standardized horse photographs. The heritability was estimated for 10 joint angles (seven were measured twice with different LM placements), and relative warp components of the whole shape, in 608 Franches-Montagnes (FM) horses (480 stallions, 68 mares and 60 geldings born 1940-2018, 3-25 years old). The pedigree data comprised 6986 horses. Genetic variances and covariances were estimated by restricted maximum likelihood model (REML), including the fixed effects birth year, age (linear and quadratic), height at withers (linear and quadratic), as well as postural effects (head, neck, limb position and body alignment), together with a random additive genetic animal component and the residual effect. Estimated heritability varied from 0.08 (stifle joint) to 0.37 (poll). For the shape, the type was most heritable (0.36 to 0.37) and evolved from heavy to light over time. Image-based phenotyping can improve the selection of horses for conformation traits with moderate heritability (e.g., poll, shoulder and fetlock).
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Publication Date: 2022-08-25 PubMed ID: 36077906PubMed Central: PMC9454882DOI: 10.3390/ani12172186Google 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 investigates the heritability of conformation traits such as joint angles in Franches-Montagnes (FM) horses, using a shape space model that enables objective measurement. Analysing data from 608 FM horses, it suggests that these traits have moderate heritability and could therefore be selected for in equine breeding.

Objectives and Methodology

  • The research aimed to derive objective measurements for conformation traits, traditionally assessed subjectively by breeding judges, in FM horses. The focus was on joint angles which are important selection criteria in equine breeding.
  • The study used the horse shape space model for extracting shape data. This model uses 246 landmarks (LMs) on standardized horse photographs to measure joint angles.
  • The pedigree data of 6986 horses was analysed, providing a large dataset for solid analysis. Among these, the key focus was on 608 FM horses, including 480 stallions, 68 mares, and 60 geldings born between 1940 and 2018 and aged between 3-25 years.
  • The researchers used a restricted maximum likelihood model (REML) to estimate genetic variances and covariances. This model included the fixed effects of birth year, age, height at withers, postural effects, along with a random additive genetic animal component and the residual effect.

Key Findings

  • The study found that the heritability of these traits varied between a low of 0.08 (stifle joint) to a high of 0.37 (poll).
  • For the shape traits, the type was revealed to be most heritable, ranging from 0.36 to 0.37.
  • The research noticed an evolution of the most heritable traits, from heavy to light, over time.
  • The team concluded that using image-based phenotyping could improve the selection process for horses with respect to conformation traits with moderate heritability such as the poll, shoulder, and fetlock.

Implications

  • By providing a method to objectively measure key traits, this research could greatly enhance equine breeding practices by enabling breeders to select more effectively for horses with desirable conformation traits.
  • The image-based phenotyping method could also drive improvements in assessment methods, reducing reliance on subjective evaluation by breeding judges.
  • As certain conformation traits showed moderate levels of heritability, breeders could more confidently select these traits knowing that they are likely to be passed on to the next generation.

Cite This Article

APA
Gmel AI, Burren A, Neuditschko M. (2022). Estimates of Genetic Parameters for Shape Space Data in Franches-Montagnes Horses. Animals (Basel), 12(17), 2186. https://doi.org/10.3390/ani12172186

Publication

Animals : an open access journal from MDPI
ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 12
Issue: 17
PII: 2186

Researcher Affiliations

Gmel, Annik Imogen
  • Animal GenoPhenomics, Agroscope, Rte de la Tioleyre 4, 1725 Posieux, Switzerland.
  • Equine Department, Vetsuisse Faculty, University of Zurich, Winterthurerstrasse 260, 8057 Zurich, Switzerland.
Burren, Alexander
  • School of Agricultural, Forest and Food Sciences HAFL, Bern University of Applied Sciences, Länggasse 85, 3052 Zollikofen, Switzerland.
Neuditschko, Markus
  • Animal GenoPhenomics, Agroscope, Rte de la Tioleyre 4, 1725 Posieux, Switzerland.

Grant Funding

  • 625000469 / Swiss Federal Office of Agriculture

Conflict of Interest Statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Citations

This article has been cited 5 times.
  1. Gmel AI, Brem G, Neuditschko M. New genomic insights into the conformation of Lipizzan horses. Sci Rep 2023 Jun 2;13(1):8990.
    doi: 10.1038/s41598-023-36272-4pubmed: 37268682google scholar: lookup
  2. Oliveira D, Halpern B, Martínez-Freiría F, Kaliontzopoulou A. Head Shape Heritability in the Hungarian Meadow Viper Vipera ursinii rakosiensis. Animals (Basel) 2023 Jan 16;13(2).
    doi: 10.3390/ani13020322pubmed: 36670862google scholar: lookup
  3. Gmel AI, Lamas LP, Rosa TV, Stefaniuk-Szmukier M, Klecel W, Martin-Gimenez T, Cruz A, Weishaupt MA, Neuditschko M. Shape and joint angle data for seven European horse breeds and their repeatability. Data Brief 2024 Oct;56:110799.
    doi: 10.1016/j.dib.2024.110799pubmed: 39252769google scholar: lookup
  4. Gmel AI, Mikko S, Ricard A, Velie BD, Gerber V, Hamilton NA, Neuditschko M. Using high-density SNP data to unravel the origin of the Franches-Montagnes horse breed. Genet Sel Evol 2024 Jul 10;56(1):53.
    doi: 10.1186/s12711-024-00922-6pubmed: 38987703google scholar: lookup
  5. Ricard A, Crevier-Denoix N, Pourcelot P, Crichan H, Sabbagh M, Dumont-Saint-Priest B, Danvy S. Genetic analysis of geometric morphometric 3D visuals of French jumping horses. Genet Sel Evol 2023 Sep 18;55(1):63.
    doi: 10.1186/s12711-023-00837-8pubmed: 37723416google scholar: lookup
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