Literature DB >> 25145447

Factor analytic and reduced animal models for the investigation of additive genotype-by-environment interaction in outcrossing plant species with application to a Pinus radiata breeding programme.

Brian R Cullis1, Paul Jefferson, Robin Thompson, Alison B Smith.   

Abstract

KEY MESSAGE: Modelling additive genotype-by-environment interaction is best achieved with the use of factor analytic models. With numerous environments and for outcrossing plant species, computation is facilitated using reduced animal models. The development of efficient plant breeding strategies requires a knowledge of the magnitude and structure of genotype-by-environment interaction. This information can be obtained from appropriate linear mixed model analyses of phenotypic data from multi-environment trials. The use of factor analytic models for genotype-by-environment effects is known to provide a reliable, parsimonious and holistic approach for obtaining estimates of genetic correlations between all pairs of trials. When breeding for outcrossing species the focus is on estimating additive genetic correlations and effects which is achieved by including pedigree information in the analysis. The use of factor analytic models in this setting may be computationally prohibitive when the number of environments is moderate to large. In this paper, we present an approach that uses an approximate reduced animal model to overcome the computational issues associated with factor analytic models for additive genotype-by-environment effects. The approach is illustrated using a Pinus radiata breeding dataset involving 77 trials, located in environments across New Zealand and south eastern Australia, and with pedigree information on 315,581 trees. Using this approach we demonstrate the existence of substantial additive genotype-by-environment interaction for the trait of stem diameter measured at breast height. This finding has potentially significant implications for both breeding and deployment strategies. Although our approach has been developed for forest tree breeding programmes, it is directly applicable for other outcrossing plant species, including sugarcane, maize and numerous horticultural crops.

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Year:  2014        PMID: 25145447     DOI: 10.1007/s00122-014-2373-0

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  7 in total

1.  Analyzing variety by environment data using multiplicative mixed models and adjustments for spatial field trend.

Authors:  A Smith; B Cullis; R Thompson
Journal:  Biometrics       Date:  2001-12       Impact factor: 2.571

2.  Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysis.

Authors:  B R Cullis; A B Smith; C P Beeck; W A Cowling
Journal:  Genome       Date:  2010-11       Impact factor: 2.166

3.  Analysis of yield and oil from a series of canola breeding trials. Part I. Fitting factor analytic mixed models with pedigree information.

Authors:  C P Beeck; W A Cowling; A B Smith; B R Cullis
Journal:  Genome       Date:  2010-11       Impact factor: 2.166

4.  Joint modeling of additive and non-additive genetic line effects in single field trials.

Authors:  Helena Oakey; Arūnas Verbyla; Wayne Pitchford; Brian Cullis; Haydn Kuchel
Journal:  Theor Appl Genet       Date:  2006-08-02       Impact factor: 5.699

5.  Joint modeling of additive and non-additive (genetic line) effects in multi-environment trials.

Authors:  Helena Oakey; Arūnas P Verbyla; Brian R Cullis; Xianming Wei; Wayne S Pitchford
Journal:  Theor Appl Genet       Date:  2007-04-11       Impact factor: 5.699

6.  Variance components for survival of piglets at farrowing using a reduced animal model.

Authors:  Ian M S White; Rainer Roehe; Pieter W Knap; Sue Brotherstone
Journal:  Genet Sel Evol       Date:  2006-06-23       Impact factor: 4.297

7.  Estimation in a multiplicative mixed model involving a genetic relationship matrix.

Authors:  Alison M Kelly; Brian R Cullis; Arthur R Gilmour; John A Eccleston; Robin Thompson
Journal:  Genet Sel Evol       Date:  2009-04-09       Impact factor: 4.297

  7 in total
  12 in total

1.  Genetic-based interactions among tree neighbors: identification of the most influential neighbors, and estimation of correlations among direct and indirect genetic effects for leaf disease and growth in Eucalyptus globulus.

Authors:  J Costa E Silva; B M Potts; A R Gilmour; R J Kerr
Journal:  Heredity (Edinb)       Date:  2017-05-31       Impact factor: 3.821

2.  Improving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials.

Authors:  Kaio Olímpio Das Graças Dias; Salvador Alejandro Gezan; Claudia Teixeira Guimarães; Alireza Nazarian; Luciano da Costa E Silva; Sidney Netto Parentoni; Paulo Evaristo de Oliveira Guimarães; Carina de Oliveira Anoni; José Maria Villela Pádua; Marcos de Oliveira Pinto; Roberto Willians Noda; Carlos Alexandre Gomes Ribeiro; Jurandir Vieira de Magalhães; Antonio Augusto Franco Garcia; João Cândido de Souza; Lauro José Moreira Guimarães; Maria Marta Pastina
Journal:  Heredity (Edinb)       Date:  2018-02-23       Impact factor: 3.821

3.  Genotype by environment interaction for growth and Dothistroma resistance and clonal connectivity between environments in radiata pine in New Zealand and Australia.

Authors:  Yongjun Li; Heidi S Dungey; Mike Carson; Sue Carson
Journal:  PLoS One       Date:  2018-10-12       Impact factor: 3.240

4.  Use of Contemporary Groups in the Construction of Multi-Environment Trial Datasets for Selection in Plant Breeding Programs.

Authors:  Alison Smith; Aanandini Ganesalingam; Christopher Lisle; Gururaj Kadkol; Kristy Hobson; Brian Cullis
Journal:  Front Plant Sci       Date:  2021-02-02       Impact factor: 5.753

5.  Spatial Models With Inter-Tree Competition From Airborne Laser Scanning Improve Estimates of Genetic Variance.

Authors:  David Pont; Heidi S Dungey; Mari Suontama; Grahame T Stovold
Journal:  Front Plant Sci       Date:  2021-01-07       Impact factor: 5.753

6.  Reparametrization-based estimation of genetic parameters in multi-trait animal model using Integrated Nested Laplace Approximation.

Authors:  Boby Mathew; Anna Marie Holand; Petri Koistinen; Jens Léon; Mikko J Sillanpää
Journal:  Theor Appl Genet       Date:  2015-11-18       Impact factor: 5.699

7.  Age trends of genetic parameters, early selection and family by site interactions for growth traits in Larix kaempferi open-pollinated families.

Authors:  Shu Diao; Yimei Hou; Yunhui Xie; Xiaomei Sun
Journal:  BMC Genet       Date:  2016-07-07       Impact factor: 2.797

8.  Effect of trait's expression level on single-step genomic evaluation of resistance to Dothistroma needle blight.

Authors:  Jaroslav Klápště; Heidi S Dungey; Natalie J Graham; Emily J Telfer
Journal:  BMC Plant Biol       Date:  2020-05-11       Impact factor: 4.215

9.  Genomic selection for non-key traits in radiata pine when the documented pedigree is corrected using DNA marker information.

Authors:  Yongjun Li; Jaroslav Klápště; Emily Telfer; Phillip Wilcox; Natalie Graham; Lucy Macdonald; Heidi S Dungey
Journal:  BMC Genomics       Date:  2019-12-27       Impact factor: 3.969

10.  Leveraging breeding programs and genomic data in Norway spruce (Picea abies L. Karst) for GWAS analysis.

Authors:  Zhi-Qiang Chen; Yanjun Zan; Pascal Milesi; Linghua Zhou; Jun Chen; Lili Li; BinBin Cui; Shihui Niu; Johan Westin; Bo Karlsson; Maria Rosario García-Gil; Martin Lascoux; Harry X Wu
Journal:  Genome Biol       Date:  2021-06-13       Impact factor: 13.583

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