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    It is not the case that Galton, Fisher, and the biometrical tradition established that additive genetic variance can dominate phenotypic variance even under gene-environment interaction.

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    Reasons For

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    Reason for
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    • 1.Early biometrical estimates relied on assumptions (random mating, no gene-environment correlation) that frequently violated reality, inflating heritability coefficients.
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    • 2.Gene-environment interactions often create nonlinear effects that additive models structurally cannot capture, making 'additive dominance' an artifact of the statistical framework.
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    • 3.Heritability is population-specific and environmentally-dependent; claims about dominance require specifying populations and conditions that classical biometrics often left vague.
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    Reasons Against

    1 perspective
    Reason against
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    • 1.Biometrical methods successfully decomposed variance into additive genetic and environmental components across multiple traits, empirically demonstrating genetic dominance.
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    • 2.Twin studies and adoption studies show high heritability estimates persisting across diverse environments, suggesting additive effects remain substantial despite G×E interactions.
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    • 3.Fisher's ANOVA framework mathematically proved additive genetic variance can remain the largest variance component even when G×E interactions exist.
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