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By design, our analysis has focused on mutations with very large fitness effects.
Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems.
If colony fitness increases due to increased worker-worker interactions, selection on mutations with indirect effects on workers can be substantial.
Incomplete penetrance under all the tested conditions suggests that this phase may use highly redundant pathways, involve novel mechanisms, or depend on mutations with lethal phenotypes.
According to the FGM, events of selection are more likely to be observed on mutations with small phenotypic effects (following a geometric distribution), whereas positive selection on mutations with large effects is most likely to occur during the first steps of adaptation.
Also, it applies across any magnitude of bias, e.g., the dramatic reversals that we imagined previously are merely kinetically disfavored pathways, by virtue of relying on mutations with exceedingly low rates.
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Neighboring nucleotides exert a striking influence on mutation, with the hypermutability of CpG dinucleotides in many genomes being an exemplar.
Sequence neighborhoods have been identified as exerting a strong influence on mutation with the most striking illustration being the elevated mutation rate affecting C within the dinucleotide CpG.
Our data also complement previous studies on the association of mutations with COO.
We thus propose a mechanism for efficient adaptation based on a set of mutations with several features.
This problem has been partially addressed with the development of a new class of disease-specific predictors trained on a subset of mutations with defined phenotypic effect.
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