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Adapt or perish: Evolutionary rescue in a gradually deteriorating environment
- Source :
- Genetics, Genetics, 2020, 216 (2), pp.573-583. ⟨10.1534/genetics.120.303624⟩, Genetics, Genetics Society of America, 2020, 216 (2), pp.573-583. ⟨10.1534/genetics.120.303624⟩
- Publication Year :
- 2020
- Publisher :
- Cold Spring Harbor Laboratory, 2020.
-
Abstract
- We investigate the evolutionary rescue of a microbial population in a gradually deteriorating environment, through a combination of analytical calculations and stochastic simulations. We consider a population destined for extinction in the absence of mutants, which can only survive if mutants sufficiently adapted to the new environment arise and fix. We show that mutants that appear later during the environment deterioration have a higher probability to fix. The rescue probability of the population increases with a sigmoidal shape when the product of the carrying capacity and of the mutation probability increases. Furthermore, we find that rescue becomes more likely for smaller population sizes and/or mutation probabilities if the environment degradation is slower, which illustrates the key impact of the rapidity of environment degradation on the fate of a population. We also show that our main conclusions are robust across various types of adaptive mutants, including specialist and generalist ones, as well as mutants modeling antimicrobial resistance evolution. We further express the average time of appearance of the mutants that do rescue the population and the average extinction time of those that do not. Our methods can be applied to other situations with continuously variable fitnesses and population sizes, and our analytical predictions are valid in the weak-to-moderate mutation regime.<br />Comment: 36 pages, 18 figures
- Subjects :
- 0106 biological sciences
Population
adaptation
Investigations
Environment
Biology
Generalist and specialist species
010603 evolutionary biology
01 natural sciences
deteriorating environment
03 medical and health sciences
Mutation Rate
0103 physical sciences
Genetics
Carrying capacity
Theory
variable population size
Selection, Genetic
Quantitative Biology - Populations and Evolution
010306 general physics
education
[SDV.MP] Life Sciences [q-bio]/Microbiology and Parasitology
Population and Evolutionary Genetics
030304 developmental biology
Stochastic simulations
Microbial population
0303 health sciences
education.field_of_study
[SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE]
Extinction
Bacteria
Models, Genetic
fungi
Modeling
Adaptation, Physiological
Extinction time
[SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology
Mutation probability
Evolutionary biology
evolutionary rescue
Mutation (genetic algorithm)
[SDV.GEN.GPO] Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE]
Genetic Fitness
Adaptation
variable fitness
Evolutionary rescue
Subjects
Details
- ISSN :
- 00166731
- Database :
- OpenAIRE
- Journal :
- Genetics, Genetics, 2020, 216 (2), pp.573-583. ⟨10.1534/genetics.120.303624⟩, Genetics, Genetics Society of America, 2020, 216 (2), pp.573-583. ⟨10.1534/genetics.120.303624⟩
- Accession number :
- edsair.doi.dedup.....9876e1acf2de302f1a32b08499e912dc
- Full Text :
- https://doi.org/10.1101/2020.05.05.079616