Abstract
Due to the universal presence of genotype by environment interactions, understanding the pattern of quantitative trait loci (QTL)-by-environment interactions is a prerequisite for effective marker-assisted selection. In this report, we describe a biplot approach for investigating QTL-by-environment patterns. This approach involves two steps. It starts with a two-way table containing effects of individual QTLs in individual environments for the trait under investigation. This table is decomposed into principal components via singular value decomposition, and the first two principal components are plotted for both QTLs and environments to form a biplot. The resulting ‘QQE biplot’ contains information on QTL main effects (Q) and QTL-by-environment interactions (QE). A QQE biplot displays the QTL-by-environment patterns and allows visualization of: (1) the magnitude of the effect of a QTL, (2) the average effect of a QTL and its stability across environments, (3) the effects of a QTL in individual environments, (4) the similarity/dissimilarity among QTLs in effect and response to the environments, (5) the similarity/dissimilarity among environments in modulating QTL effects, (6) any differentiation of mega-environments, and (7) the combination of QTL alleles for maximum/minimum expression of the trait for each environment or mega-environment. A case study is provided using the QTL-by-environment two-way table for barley yield.
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Abbreviations
- AMMI:
-
Additive main effect and multiplicative interaction effect model
- G:
-
genotype main effect
- GE:
-
genotype by environment interaction
- GGE:
-
G + GE
- Q:
-
QTL main effect
- QE:
-
QTL-by-environment interaction
- QQE:
-
Q + QE
- QTL:
-
quantitative trait locus
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Yan, W., Tinker, N.A. A biplot approach for investigating QTL-by-environment patterns. Mol Breeding 15, 31–43 (2005). https://doi.org/10.1007/s11032-004-1706-0
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DOI: https://doi.org/10.1007/s11032-004-1706-0