Inferring the distributions of fitness effects and proportions of strongly deleterious mutations

Charmouh, Anders P.; Bocedi, Greta; Hartfield, Matthew

doi:10.1093/g3journal/jkad140

Cited by 3 publications

(1 citation statement)

References 66 publications

(108 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ultimately, such predictions and their tests are key to tackling problems such as the emergence of antimicrobial resistance and rapid environmental change that threatens populations [4]. From numerous studies using different approaches to estimate or quantify the DFE [5], we know that it is influenced by several factors such as the genetic background, the environment, the effective population size, and prior history of adaptation [1][2][3]6,7].…”

Section: Introductionmentioning

confidence: 99%

Mutation bias alters the distribution of fitness effects of mutations

Sane,

Parveen,

Agashe

2024

Preprint

View full text Add to dashboard Cite

Mutation bias is an important factor determining the diversity of genetic variants available for selection, and can therefore constrain the genetic paths to adaptation. An additional constraint emerges over the course of evolution. As adaptation proceeds and some beneficial mutations are fixed, new beneficial mutations become rare, limiting further adaptation. Recent theoretical work predicts that these constraints may be alleviated by a change in the direction of mutation bias (i.e., a bias reversal). As populations sample previously underexplored types of mutations, the distribution of fitness effects (DFE) of mutations should shift towards more beneficial mutations. Here, we test this prediction using Escherichia coli, which has a transition mutation bias, with ~55% of single-nucleotide mutations being transitions compared to the unbiased expectation of ~33% transitions. We generated mutant strains with a wide range of mutation biases from 96% transitions to 98% transversions, either reinforcing or reversing the wild type transition bias. Quantifying DFEs of hundreds of single mutations obtained from mutation accumulation experiments for each strain, we find strong support for the theoretical prediction. Strains that oppose the ancestral bias (i.e., with a strong transversion bias) have DFEs with the highest proportion of beneficial mutations, whereas strains that exacerbate the ancestral transition bias have up to 10-fold fewer beneficial mutations. Such dramatic differences in the DFE should drive large variation in the rate and outcome of adaptation. Our results thus strongly suggest an important and generalized evolutionary role for mutation bias shifts.

show abstract

Section: Introductionmentioning

confidence: 99%

Mutation bias alters the distribution of fitness effects of mutations

Sane,

Parveen,

Agashe

2024

Preprint

View full text Add to dashboard Cite

show abstract

Life history and deleterious mutation rate coevolution

Avila,

Lehmann

2023

Journal of Theoretical Biology

View full text Add to dashboard Cite

Life history and deleterious mutation rate coevolution

Avila

Lehmann

2022

Preprint

View full text Add to dashboard Cite

The cost of germline maintenance and repair gives rise to a trade-off between lowering the deleterious mutation rate and investing into life-history functions. Life-history and the mutation rate therefore coevolve, but this joint evolutionary process is not well understood. Here, we develop a mathematical model to analyse the long-term evolution of traits affecting life-history and the deleterious mutation rate. First, we show that under certain biologically feasible conditions, the evolutionary stable life-history and mutation rate can be characterised using the basic reproductive number of the least-loaded class. This is the expected lifetime production of offspring without deleterious mutations born to individuals with no deleterious mutations. Second, we analyse two specific biological scenarios: (i) coevolution between reproductive effort and mutation rate and (ii) coevolution between age-at-maturity and mutation rate. These two scenarios suggest two broad results. First, the trade-off between lowering mutation rate vs investing into life-history functions depends strongly on environmental conditions and baseline mutation rate. Second, the trade-offs between different life-history functions can be strongly affected by mutation rate coevolution and higher baseline mutation rates select for faster life histories: (i) higher investment into fecundity at the expense of survival and (ii) earlier age of maturation at smaller sizes.

show abstract

Inferring the distributions of fitness effects and proportions of strongly deleterious mutations

Cited by 3 publications

References 66 publications

Mutation bias alters the distribution of fitness effects of mutations

Mutation bias alters the distribution of fitness effects of mutations

Life history and deleterious mutation rate coevolution

Life history and deleterious mutation rate coevolution

Contact Info

Product

Resources

About