Fig 2

Fig 2

A) Model states and parameter definitions for the set of models considered. U (Unduplicated), C₁ (Converging state 1), C₂ (Converging state 2) and F (Fixed) are duplicated states, while S₁ (Single-copy 1) and S₂ (Single-copy 2) are single-copy states (see Methods). C₁ and S₁ are states where the gene from the less-fractionated parental subgenome will be or are preserved, and C₂ and S₂ the corresponding states for the more-fractionated parental subgenome. The fractionation rate ε (the probability of the loss of a gene from the less fractionated subgenome relative to the more fractionated one) can either be the same for conversions to C₁ and C₂ as it is for S₁ and S₂ (ε₁ = ε₂) or it can differ (see B). The weights of the various arrows give a cartoon impression of the relative frequency of the different events: exact parameter estimates for the WGD-bc^nbnf model are given in Fig 1. B) Testing nested models of WGD resolution. The most basic model (top) has neither biased fractionation nor duplicate fixation nor convergent losses. Adding any of these three processes improves the model fit (second row; blue arrows indicating statistical significance; P<10⁻¹⁰). Adding the remaining two processes also improves the fit in all three cases (WGD-bcf model in the third row; P<10⁻¹⁰). However, there is no evidence that the ε₂ parameter is significantly different from 1.0 (WGD-b²cf does not improve the fit over WGD-bc^nbnf, gray arrow indicating a lack of significant improvement in fit from the more complex model), implying no biased fractionation in the transitions to states C₁ and C₂. Likewise, there is no evidence that the η parameter is significantly different from 1.0 (WGD-bcf does not improve fit over WGD-bcⁿf), meaning that losses from C₁ and C₂ occur at similar rates as do losses from U. Hence, the WGD-bc^nbnf model is best supported by these data and is used for the remaining analyses. Model names: WGD-n: Null model; WGD-b: Biased fractionation model; WGD-f: Fixation model; WGD-c: Convergence model; WGD-bcf: Bias/Convergence/Fixation model; WGD-bcⁿf: Bias/ Convergence (non-biased)/Fixation model; WGD-b²cf: Bias (2 rate)/Convergence/Fixation model; WGD-bc^nbnf: Bias/Convergence (non-biased convergence, neutral convergent loss)/ Fixation model.