| Literature DB >> 31462290 |
Daniel Romero-Mujalli1,2, Florian Jeltsch3,4, Ralph Tiedemann5.
Abstract
BACKGROUND: Organisms are expected to respond to changing environmental conditions through local adaptation, range shift or local extinction. The process of local adaptation can occur by genetic changes or phenotypic plasticity, and becomes especially relevant when dispersal abilities or possibilities are somehow constrained. For genetic changes to occur, mutations are the ultimate source of variation and the mutation rate in terms of a mutator locus can be subject to evolutionary change. Recent findings suggest that the evolution of the mutation rate in a sexual species can advance invasion speed and promote adaptation to novel environmental conditions. Following this idea, this work uses an individual-based model approach to investigate if the mutation rate can also evolve in a sexual species experiencing different conditions of directional climate change, under different scenarios of colored stochastic environmental noise, probability of recombination and of beneficial mutations. The color of the noise mimicked investigating the evolutionary dynamics of the mutation rate in different habitats.Entities:
Keywords: Beneficial mutations, sexual species; Directional climate change; Individual-based models; Mutation rate; Mutator locus; Recombination
Mesh:
Year: 2019 PMID: 31462290 PMCID: PMC6714099 DOI: 10.1186/s12862-019-1494-0
Source DB: PubMed Journal: BMC Evol Biol ISSN: 1471-2148 Impact factor: 3.260
Fig. 1The evolution of the mutation rate under scenarios of directional environmental change, probability of recombination pR, and percentage of beneficial mutations bm. Each data point corresponds to the mean mutation rate present in the population at the end of each simulation run (200 generations). The number of data points per box is shown in parenthesis (selection parameter γ = 2.2). A weaker selection regime (γ = 3.2) showed a similar pattern (data not shown). Stable env: stable environment (no directional environmental change)
Fig. 2The evolution of the mutation rate under scenarios of blue (left) and red (right) noise, directional environmental change, probability of recombination pR, and percentage of beneficial mutations bm. Each data point corresponds to the mean mutation rate present in the population at the end of each simulation run (200 generations). Stable env: stable environment (no directional environmental change)
Parameters values and description (values in parentheses were implemented to evaluate the robustness of outcomes)
| Parameter | Value | Description |
|---|---|---|
|
| 1000 | Carrying capacity |
|
| 2.2 (3.2) | Strength of selection |
|
| 1 | Variance of the stochastic environment |
|
| 0 | Initial environmental optimum |
|
| 0, 0.01, 0.02, 0.03, 0.04 | Rate of environmental change |
|
| Evolving trait | Ecological phenotype |
|
| 0.2 | Initial genetic variance present in the population |
|
| Number of loci per evolving trait | 1 |
|
| Evolving trait, range [0; 1] | Mutation rate |
|
| 0.2 | Variance of the distribution of mutations fitness effect size |
|
| 10, 25, 40, 50 | Percentage (%) of beneficial mutations |
|
| 0 (unlinked), (0.5), 1 (complete linkage), | Probability of recombination |
|
| 300 | Time limit per simulation, in generations. The last 200 generations were exposed to the treatment of directional climate change |
Fig. 3Distribution of fitness effects of mutations according to different scenarios of percentage of beneficial mutations bm. Beneficial mutations are shown in light grey color. Variance of the distribution MV = 0.1