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

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.

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Bibliographic Details
Main Authors: Bouvet, Jean-Marc, Makouanzi, Garel, Cros, David, Vigneron, Philippe
Format: article biblioteca
Language:eng
Subjects:F30 - Génétique et amélioration des plantes, U10 - Informatique, mathématiques et statistiques, K10 - Production forestière, Eucalyptus grandis, Eucalyptus urophylla, génotype, sélection, hybride, génomique, marqueur génétique, modèle linéaire, polymorphisme génétique, modèle mathématique, méthode statistique, essai de provenances, héritabilité génotypique, http://aims.fao.org/aos/agrovoc/c_2693, http://aims.fao.org/aos/agrovoc/c_26492, http://aims.fao.org/aos/agrovoc/c_3225, http://aims.fao.org/aos/agrovoc/c_6951, http://aims.fao.org/aos/agrovoc/c_3707, http://aims.fao.org/aos/agrovoc/c_92382, http://aims.fao.org/aos/agrovoc/c_24030, http://aims.fao.org/aos/agrovoc/c_34040, http://aims.fao.org/aos/agrovoc/c_24031, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_7377, http://aims.fao.org/aos/agrovoc/c_36850, http://aims.fao.org/aos/agrovoc/c_1373982832607, http://aims.fao.org/aos/agrovoc/c_8500,
Online Access:http://agritrop.cirad.fr/577277/
http://agritrop.cirad.fr/577277/7/577277.pdf
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spelling dig-cirad-fr-5772772024-01-28T22:51:21Z http://agritrop.cirad.fr/577277/ http://agritrop.cirad.fr/577277/ 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. Heredity, 116 : 146-157.https://doi.org/10.1038/hdy.2015.78 <https://doi.org/10.1038/hdy.2015.78> 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 eng 2016 Heredity F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques K10 - Production forestière Eucalyptus grandis Eucalyptus urophylla génotype sélection hybride génomique marqueur génétique modèle linéaire polymorphisme génétique modèle mathématique méthode statistique essai de provenances héritabilité génotypique http://aims.fao.org/aos/agrovoc/c_2693 http://aims.fao.org/aos/agrovoc/c_26492 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_6951 http://aims.fao.org/aos/agrovoc/c_3707 http://aims.fao.org/aos/agrovoc/c_92382 http://aims.fao.org/aos/agrovoc/c_24030 http://aims.fao.org/aos/agrovoc/c_34040 http://aims.fao.org/aos/agrovoc/c_24031 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_7377 http://aims.fao.org/aos/agrovoc/c_36850 http://aims.fao.org/aos/agrovoc/c_1373982832607 République démocratique du Congo http://aims.fao.org/aos/agrovoc/c_8500 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. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/577277/7/577277.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1038/hdy.2015.78 10.1038/hdy.2015.78 info:eu-repo/semantics/altIdentifier/doi/10.1038/hdy.2015.78 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1038/hdy.2015.78 info:eu-repo/semantics/dataset/purl/https://doi.org/10.5061/dryad.g73t2
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic F30 - Génétique et amélioration des plantes
U10 - Informatique, mathématiques et statistiques
K10 - Production forestière
Eucalyptus grandis
Eucalyptus urophylla
génotype
sélection
hybride
génomique
marqueur génétique
modèle linéaire
polymorphisme génétique
modèle mathématique
méthode statistique
essai de provenances
héritabilité génotypique
http://aims.fao.org/aos/agrovoc/c_2693
http://aims.fao.org/aos/agrovoc/c_26492
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_6951
http://aims.fao.org/aos/agrovoc/c_3707
http://aims.fao.org/aos/agrovoc/c_92382
http://aims.fao.org/aos/agrovoc/c_24030
http://aims.fao.org/aos/agrovoc/c_34040
http://aims.fao.org/aos/agrovoc/c_24031
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_7377
http://aims.fao.org/aos/agrovoc/c_36850
http://aims.fao.org/aos/agrovoc/c_1373982832607
http://aims.fao.org/aos/agrovoc/c_8500
F30 - Génétique et amélioration des plantes
U10 - Informatique, mathématiques et statistiques
K10 - Production forestière
Eucalyptus grandis
Eucalyptus urophylla
génotype
sélection
hybride
génomique
marqueur génétique
modèle linéaire
polymorphisme génétique
modèle mathématique
méthode statistique
essai de provenances
héritabilité génotypique
http://aims.fao.org/aos/agrovoc/c_2693
http://aims.fao.org/aos/agrovoc/c_26492
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_6951
http://aims.fao.org/aos/agrovoc/c_3707
http://aims.fao.org/aos/agrovoc/c_92382
http://aims.fao.org/aos/agrovoc/c_24030
http://aims.fao.org/aos/agrovoc/c_34040
http://aims.fao.org/aos/agrovoc/c_24031
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_7377
http://aims.fao.org/aos/agrovoc/c_36850
http://aims.fao.org/aos/agrovoc/c_1373982832607
http://aims.fao.org/aos/agrovoc/c_8500
spellingShingle F30 - Génétique et amélioration des plantes
U10 - Informatique, mathématiques et statistiques
K10 - Production forestière
Eucalyptus grandis
Eucalyptus urophylla
génotype
sélection
hybride
génomique
marqueur génétique
modèle linéaire
polymorphisme génétique
modèle mathématique
méthode statistique
essai de provenances
héritabilité génotypique
http://aims.fao.org/aos/agrovoc/c_2693
http://aims.fao.org/aos/agrovoc/c_26492
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_6951
http://aims.fao.org/aos/agrovoc/c_3707
http://aims.fao.org/aos/agrovoc/c_92382
http://aims.fao.org/aos/agrovoc/c_24030
http://aims.fao.org/aos/agrovoc/c_34040
http://aims.fao.org/aos/agrovoc/c_24031
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_7377
http://aims.fao.org/aos/agrovoc/c_36850
http://aims.fao.org/aos/agrovoc/c_1373982832607
http://aims.fao.org/aos/agrovoc/c_8500
F30 - Génétique et amélioration des plantes
U10 - Informatique, mathématiques et statistiques
K10 - Production forestière
Eucalyptus grandis
Eucalyptus urophylla
génotype
sélection
hybride
génomique
marqueur génétique
modèle linéaire
polymorphisme génétique
modèle mathématique
méthode statistique
essai de provenances
héritabilité génotypique
http://aims.fao.org/aos/agrovoc/c_2693
http://aims.fao.org/aos/agrovoc/c_26492
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_6951
http://aims.fao.org/aos/agrovoc/c_3707
http://aims.fao.org/aos/agrovoc/c_92382
http://aims.fao.org/aos/agrovoc/c_24030
http://aims.fao.org/aos/agrovoc/c_34040
http://aims.fao.org/aos/agrovoc/c_24031
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_7377
http://aims.fao.org/aos/agrovoc/c_36850
http://aims.fao.org/aos/agrovoc/c_1373982832607
http://aims.fao.org/aos/agrovoc/c_8500
Bouvet, Jean-Marc
Makouanzi, Garel
Cros, David
Vigneron, Philippe
Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: Prediction accuracy implications
description 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.
format article
topic_facet F30 - Génétique et amélioration des plantes
U10 - Informatique, mathématiques et statistiques
K10 - Production forestière
Eucalyptus grandis
Eucalyptus urophylla
génotype
sélection
hybride
génomique
marqueur génétique
modèle linéaire
polymorphisme génétique
modèle mathématique
méthode statistique
essai de provenances
héritabilité génotypique
http://aims.fao.org/aos/agrovoc/c_2693
http://aims.fao.org/aos/agrovoc/c_26492
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_6951
http://aims.fao.org/aos/agrovoc/c_3707
http://aims.fao.org/aos/agrovoc/c_92382
http://aims.fao.org/aos/agrovoc/c_24030
http://aims.fao.org/aos/agrovoc/c_34040
http://aims.fao.org/aos/agrovoc/c_24031
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_7377
http://aims.fao.org/aos/agrovoc/c_36850
http://aims.fao.org/aos/agrovoc/c_1373982832607
http://aims.fao.org/aos/agrovoc/c_8500
author Bouvet, Jean-Marc
Makouanzi, Garel
Cros, David
Vigneron, Philippe
author_facet Bouvet, Jean-Marc
Makouanzi, Garel
Cros, David
Vigneron, Philippe
author_sort Bouvet, Jean-Marc
title Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: Prediction accuracy implications
title_short Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: Prediction accuracy implications
title_full Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: Prediction accuracy implications
title_fullStr Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: Prediction accuracy implications
title_full_unstemmed Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: Prediction accuracy implications
title_sort modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications
url http://agritrop.cirad.fr/577277/
http://agritrop.cirad.fr/577277/7/577277.pdf
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AT crosdavid modelingadditiveandnonadditiveeffectsinahybridpopulationusinggenomewidegenotypingpredictionaccuracyimplications
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