Literature DB >> 24247951

Joint analysis of genotypic and environmental effects.

H R Gregorius1, G Namkoong.   

Abstract

A definition of jointly contributing genotypic and environmental effects is introduced, from which a new concept of genotype × environment interactions is derived. Interaction is defined to be the failure of genotypic or environmental response functions to be separable. For separable response functions, the contributions of the genotypic and environmental effects must be related in terms of an operator which can describe their joint actions. A scale-free method of determining the simplest operator is developed in terms of comparative norms of reaction and a characteristic of the operator is given for several operators. With a defined operator, the genetic and environmental contributions can be derived, and biologically interpreted. These methods are applied to published data on Pinus caribaea.

Entities:  

Year:  1986        PMID: 24247951     DOI: 10.1007/BF00288581

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


  5 in total

1.  The statistical sign test.

Authors:  W J DIXON; A M MOOD
Journal:  J Am Stat Assoc       Date:  1946-12       Impact factor: 5.033

2.  A STUDY OF REACTION NORMS IN NATURAL POPULATIONS OF DROSOPHILA PSEUDOOBSCURA.

Authors:  Anand P Gupta; R C Lewontin
Journal:  Evolution       Date:  1982-09       Impact factor: 3.694

3.  The relation between hybrid vigour and genotype-environment interactions.

Authors:  R Knight
Journal:  Theor Appl Genet       Date:  1973-01       Impact factor: 5.699

4.  The genotype x environment-to-phenotype relationship.

Authors:  H R Gregorius
Journal:  Theor Appl Genet       Date:  1977-07       Impact factor: 5.699

5.  Annotation: the analysis of variance and the analysis of causes.

Authors:  R C Lewontin
Journal:  Am J Hum Genet       Date:  1974-05       Impact factor: 11.025

  5 in total
  12 in total

1.  Predictive and postdictive success of statistical analyses of yield trials.

Authors:  H G Gauch; R W Zobel
Journal:  Theor Appl Genet       Date:  1988-07       Impact factor: 5.699

2.  Genetic variation in nutrient response functions.

Authors:  G Namkoong; A Jonsson; G Eriksson
Journal:  Theor Appl Genet       Date:  1992-11       Impact factor: 5.699

3.  Using the shifted multiplicative model to search for "separability" in crop cultivar trials.

Authors:  P L Cornelius; M Seyedsadr; J Crossa
Journal:  Theor Appl Genet       Date:  1992-06       Impact factor: 5.699

4.  Exploring genotype by environment interaction on cassava yield and yield related traits using classical statistical methods.

Authors:  Moshood A Bakare; Siraj Ismail Kayondo; Cynthia I Aghogho; Marnin D Wolfe; Elizabeth Y Parkes; Peter Kulakow; Chiedozie Egesi; Ismail Yusuf Rabbi; Jean-Luc Jannink
Journal:  PLoS One       Date:  2022-07-18       Impact factor: 3.752

5.  A shifted multiplicative model cluster analysis for grouping environments without genotypic rank change.

Authors:  J Crossa; P L Cornelius; M Seyedsadr; P Byrne
Journal:  Theor Appl Genet       Date:  1993-01       Impact factor: 5.699

6.  Relative family performance and variance structure of open-pollinated Douglas-fir seedlings grown in three competitive environments.

Authors:  J B St Clair; W T Adams
Journal:  Theor Appl Genet       Date:  1991-04       Impact factor: 5.699

7.  A reaction norm model for genomic selection using high-dimensional genomic and environmental data.

Authors:  Diego Jarquín; José Crossa; Xavier Lacaze; Philippe Du Cheyron; Joëlle Daucourt; Josiane Lorgeou; François Piraux; Laurent Guerreiro; Paulino Pérez; Mario Calus; Juan Burgueño; Gustavo de los Campos
Journal:  Theor Appl Genet       Date:  2013-12-12       Impact factor: 5.699

8.  FW: An R Package for Finlay-Wilkinson Regression that Incorporates Genomic/Pedigree Information and Covariance Structures Between Environments.

Authors:  Lian Lian; Gustavo de Los Campos
Journal:  G3 (Bethesda)       Date:  2015-12-29       Impact factor: 3.154

9.  Genotype-covariate correlation and interaction disentangled by a whole-genome multivariate reaction norm model.

Authors:  Guiyan Ni; Julius van der Werf; Xuan Zhou; Elina Hyppönen; Naomi R Wray; S Hong Lee
Journal:  Nat Commun       Date:  2019-05-20       Impact factor: 14.919

10.  Increased Proportion of Variance Explained and Prediction Accuracy of Survival of Breast Cancer Patients with Use of Whole-Genome Multiomic Profiles.

Authors:  Ana I Vazquez; Yogasudha Veturi; Michael Behring; Sadeep Shrestha; Matias Kirst; Marcio F R Resende; Gustavo de Los Campos
Journal:  Genetics       Date:  2016-04-29       Impact factor: 4.562

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