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Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: Prediction accuracy implications

Bouvet Jean-Marc, Makouanzi Garel, Cros David, Vigneron Philippe. 2016. Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: Prediction accuracy implications. Heredity, 116 : pp. 146-157.

Journal article ; Article de recherche ; Article de revue à facteur d'impact
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Bouvet al 2015 Heredity_modelling_variance_eucalyptus.pdf

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577277.pdf

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Url - jeu de données : https://doi.org/10.5061/dryad.g73t2

Quartile : Q1, Sujet : ECOLOGY / Quartile : Q2, Sujet : GENETICS & HEREDITY / Quartile : Q2, Sujet : EVOLUTIONARY BIOLOGY

Abstract : Hybrids are broadly used in plant breeding and accurate estimation of variance components is crucial for optimizing genetic gain. Genome-wide information may be used to explore models designed to assess the extent of additive and non-additive variance and test their prediction accuracy for the genomic selection. Ten linear mixed models, involving pedigree- and marker- based relationship matrices among parents, were developed to estimate additive (A), dominance (D) and epistatic (AA, AD and DD) effects. Five complementary models, involving the gametic phase to estimate marker-based relationships among hybrid progenies, were developed to assess the same effects. The models were compared using tree height and 3303 single-nucleotide polymorphism markers from 1130 cloned individuals obtained via controlled crosses of 13 Eucalyptus urophylla females with 9 Eucalyptus grandis males. Akaike information criterion (AIC), variance ratios, asymptotic correlation matrices of estimates, goodness-of- fi t, prediction accuracy and mean square error (MSE) were used for the comparisons. The variance components and variance ratios differed according to the model. Models with a parent marker-based relationship matrix performed better than those that were pedigree-based, that is, an absence of singularities, lower AIC, higher goodness-of- fi t and accuracy and smaller MSE. However, AD and DD variances were estimated with high s.es. Using the same criteria, progeny gametic phase-based models performed better in fi tting the observations and predicting genetic values. However, DD variance could not be separated from the dominance variance and null estimates were obtained for AA and AD effects. This study highlighted the advantages of progeny models using genome-wide information.

Mots-clés Agrovoc : Eucalyptus grandis, Eucalyptus urophylla, Génotype, Sélection, Hybride, génomique, Marqueur génétique, Modèle linéaire, Polymorphisme génétique, Modèle mathématique, Méthode statistique, Essai de provenances, Héritabilité génotypique

Mots-clés géographiques Agrovoc : République démocratique du Congo

Classification Agris : F30 - Plant genetics and breeding
U10 - Computer science, mathematics and statistics
K10 - Forestry production

Champ stratégique Cirad : Axe 1 (2014-2018) - Agriculture écologiquement intensive

Auteurs et affiliations

  • Bouvet Jean-Marc, CIRAD-BIOS-UMR AGAP (FRA)
  • Makouanzi Garel, CRDPI (COG)
  • Cros David, CIRAD-BIOS-UMR AGAP (CMR) ORCID: 0000-0002-8601-7991
  • Vigneron Philippe, CIRAD-BIOS-UMR AGAP (COG)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/577277/)

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