Partitioning the forms of genotype-by-environment interaction in the reaction norm analysis of stability

Title
Partitioning the forms of genotype-by-environment interaction in the reaction norm analysis of stability
Publication Date
2023-04-07
Author(s)
Waters, Dominic L
( author )
OrcID: https://orcid.org/0000-0003-4697-1243
Email: dwater21@une.edu.au
UNE Id une-id:dwater21
van der Werf, Julius H J
( author )
OrcID: https://orcid.org/0000-0003-2512-1696
Email: jvanderw@une.edu.au
UNE Id une-id:jvanderw
Robinson, Hannah
Hickey, Lee T
Clark, Sam A
( author )
OrcID: https://orcid.org/0000-0001-8605-1738
Email: sclark37@une.edu.au
UNE Id une-id:sclark37
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
Springer
Place of publication
Germany
DOI
10.1007/s00122-023-04319-9
UNE publication id
une:1959.11/55411
Abstract

The slope of regression in a reaction norm model, where the performance of a genotype is regressed over an environmental covariable, is often used as a measure of stability of genotype performance. This method could be developed further by partitioning variation in the slope of regression into the two sources of genotype-by-environment interaction (G×E) which cause it: scale-type G×E (heterogeneity of variance) and rank-type G×E (heterogeneity of correlation). Because the two types of G×E have very diferent properties, separating their efect would enable a clearer understanding of stability. The aim of this paper was to demonstrate two methods which seek to achieve this in reaction norm models. Reaction norm models were ft to yield data from a multi-environment trial in Barley (Hordeum vulgare), with the adjusted mean yield from each environment used as the environmental covariable. Stability estimated from factor-analytic models, which can disentangle the two types of G×E and estimate stability based on rank-type G×E, was used for comparison. Adjusting the reaction norm slope to account for scale-type G ×E using a genetic regression more than tripled the correlation with factor-analytic estimates of stability (0.24–0.26 to 0.80–0.85), indicating that it removed variation in the reaction norm slope that originated from scale-type G×E. A standardisation procedure had a more modest increase (055–0.59) but could be useful when curvilinear reaction norms are required. Analyses which use reaction norms to explore the stability of genotypes could gain additional insight into the mechanisms of stability by applying the methods outlined in this study.

Link
Citation
Theoretical and Applied Genetics, 136(5), p. 1-14
ISSN
1432-2242
0040-5752
Pubmed ID
37027025
Start page
1
End page
14
Rights
Attribution 4.0 International

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