Additional file 1 of Gene birth in a model of non-genic adaptation
Creators: name: Mani, Somya
name: Tlusty, Tsvi
Publisher: name: figshare
Year: 2023
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 1: Figures S1-S21, Tables 1-3. Table 1. Estimates of one model time-step in various species. Figure S1. The distribution of relative fitnesses and absolute fitness values found to fix in the detailed simulation is statistically similar to the distribution of relative fitnesses and absolute fitness values of individuals simply picked with a probability proportional to their relative fitness. Figure S2. Comparison of adaptation of loci in the main model versus the multi-locus model. Figure S3. Comparison of adaptation of loci in the main model versus a model where de novo gene evolution occurs in the presence of an independently evolving established gene. Figure S4. Trajectories of population averaged fitness subject to diminishing returns epistasis. Figure S5. Neutrality of mutants with fitness effect $$=0.5 \times 10^{-3}$$ = 0.5 × 10 - 3 in N = 1000 populations. Figure S6. Fraction of positive effect mutations (fitness effect &gt; $$0.5 \times 10^{-3}$$ 0.5 × 10 - 3 ). Figure S7. Adjustments to $$\Delta E$$ Δ E in a run of 1000 time steps for a population of 1000 individuals. Figure S8. Parameters conducive to adaptation in N = 100 vs N = 1000 populations in the high mutation rate regime. Figure S9. Non-conducive DFEs. Table 2. Pearson’s correlation coefficients between DFE parameters (rows) and PC1, PC2 and PC3 N = 1000 populations. Figure S10. Three Principal Components explain DFE conducivity. Figure S11. Trade-off between the shape parameter and frequency and size of beneficial mutations for N = 1000 populations. Figure S12. Trade-off between the shape parameter and frequency and size of beneficial mutations for N = 100 populations in the high mutation rate regime. Figure S13. Time of minimum average fitness effects probability of retention of the locus in N = 100 populations in the high mutation rate regime. Figure S14. Selection is essential for sustained fitness increase in the high mutation rate regime. Table 3. Pearson’s correlation coefficients between DFE parameters (rows) and time of minimum fitness for N = 100 and N = 1000 populations in the high mutation rate regime. Figure S15. Rare, large-effect positive jumps lead to sudden fitness increase in trajectories of adaptation. Figure S16. Scatter plot showing the distribution of minimum average fitness and the time of minimum average fitness for populations which eventually crossed the fitness threshold in the high mutation rate regime. Figure S17. Trajectory of population average fitness in the low mutation rate regime. Figure S18. Effect of locus deletion in N = 1000 populations in the high mutation rate regime. Figure S19. Histograms for correlations between expression level, adaptive value and fitness trajectories for populations where the fitness threshold of 0.1 was crossed. Figure S20. Histogram for correlations between random expression level (E rand ) and fitness trajectories for populations where the fitness threshold of 0.1 was crossed. Figure S21. Scale of $$\Delta A$$ Δ A exponential fits as a function of the model parameter p.