Evidence map›Paper›PMID 37723416›Full record

ArticleGenetics, selection, evolution : GSE2023

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

Anne Ricard, Nathalie Crevier-Denoix, Philippe Pourcelot, Harmony Crichan, Margot Sabbagh, Bernard Dumont-Saint-Priest, Sophie Danvy

Open access · goldAbstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
9.7field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Anne RicardPôle développement, innovation et recherche, Institut français du cheval et de l'équitation, 61310, Exmes-Gouffern en Auge, France. anne.ricard@inrae.fr.ORCID http://orcid.org/0000-0002-2113-5153
Nathalie Crevier-DenoixINRAE, Ecole Nationale Vétérinaire d'Alfort, Unité 957 BPLC, 94700, Maisons-Alfort, France.
Philippe PourcelotINRAE, Ecole Nationale Vétérinaire d'Alfort, Unité 957 BPLC, 94700, Maisons-Alfort, France.
Harmony CrichanPôle développement, innovation et recherche, Institut français du cheval et de l'équitation, 61310, Exmes-Gouffern en Auge, France.
Margot SabbaghPôle développement, innovation et recherche, Institut français du cheval et de l'équitation, 61310, Exmes-Gouffern en Auge, France.
Bernard Dumont-Saint-PriestPôle développement, innovation et recherche, Institut français du cheval et de l'équitation, 61310, Exmes-Gouffern en Auge, France.
Sophie DanvyPôle développement, innovation et recherche, Institut français du cheval et de l'équitation, 61310, Exmes-Gouffern en Auge, France.
Institut Français · FRÉcole Nationale Vétérinaire d'Alfort · FRAgroParisTech · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFor 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.

resultsWe 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

conclusionsThe 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.

Indexed as

Genome-Wide Association StudyPolymorphism, Single NucleotideAnimalsHorsesPedigreePhenotype

Identifiers

PMID37723416
PMCPMC10506242
OpenAlexW4386834782

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.