Mutation bias can shape adaptation in large asexual populations experiencing clonal interference

Abstract

The extended evolutionary synthesis invokes a role for development in shaping adaptive evolution, which in population genetics terms corresponds to mutation-biased adaptation. Critics have claimed that clonal interference makes mutation-biased adaptation rare. We consider the behaviour of two simultaneously adapting traits, one with larger mutation rate U , the other with larger selection coefficient s , using asexual travelling wave models. We find that adaptation is dominated by whichever trait has the faster rate of adaptation v in isolation, with the other trait subject to evolutionary stalling. Reviewing empirical claims for mutation-biased adaptation, we find that not all occur in the ‘origin-fixation’ regime of population genetics where v is only twice as sensitive to s as to U . In some cases, differences in U are at least ten to twelve times larger than differences in s , as needed to cause mutation-biased adaptation even in the ‘multiple mutations’ regime. Surprisingly, when U > s in the ‘diffusive-mutation’ regime, the required sensitivity ratio is also only two, despite pervasive clonal interference. Given two traits with identical v , the benefit of having higher s is surprisingly small, occurring largely when one trait is at the boundary between the origin-fixation and multiple mutations regimes.

Asymmetric Evolvability Leads to Specialization without Trade-Offs

“…These results leverage the findings of Schiffels et al (2011), and later work by Gomez et al (2020) and Venkataram et al (2019), to illustrate that asexual adaptation is not just slower than adaptation with recombination, but differs in other significant aspects. Other models have predicted differences in the nature of adaptation in asexual versus sexual organisms, such as difference in epistasis among fixed mutations (Livnat et al 2008) and, as discussed above, asexuality is linked with extreme generalism in some insects (Gibson 2019).…”

“…In assessing the causes and generality of asymmetric evolvability and the resulting evolution of specialism, I applied the results of Schiffels et al (2011) and Gomez et al (2020) to make two predictions. First, I expected the likelihood of specialization to be sensitive to population-genetic parameters determining evolvability, principally N, , s and L. Second, in asexual populations, increasing N or  will worsen clonal interference and exacerbate the asymmetry between the rates of evolution in the common and rare environments.…”

“…Recent theory focusing on asexual evolution has predicted that adaptation among sites with small selection coefficients can be effectively stalled by interference from rapidly evolving sites with larger effects (Schiffels et al 2011). Extending this model to multiple traits, Gomez et al (2019) showed that clonal interference can produce a false signature of trade-offs where none exist, and Gomez et al (2020) showed that a trait with more frequent or larger beneficial mutations can effectively stall adaptation in a trait with lower evolvability, an effect that Venkataram et al (2019) recently demonstrated experimentally. Here, specialization is seen to evolve when a rare environment becomes unprofitable in comparison to the more common environment, solely because of slow relative improvement in how organisms can exploit the rare environment.…”

“…plots mean fitness in each environment, comparing treatments when each trait evolves alone (no mutation in the other trait) versus when it evolves simultaneously with the other fitness trait. With complete linkage (r = 0) and therefore clonal interference between traits (seeSchiffels et al 2011;Gomez et al 2020),…”

Clonal Interference and Mutation Bias in Small Bacterial Populations in Droplets

“…As large populations suffer less from genetic drift and contain more adaptive variants than small populations, natural selection will likely filter out the small set of most beneficial mutants, even if they are rare, leading to more repeatable evolution through selection bias. By contrast, in small populations adaptation relies more heavily on the chance occurrence of beneficial mutations and, hence, mutation bias has a relatively stronger impact [9,10].…”