scholarly journals Evolution of specialization in heterogeneous environments: equilibrium between selection, mutation and migration

2018 ◽  
Author(s):  
Sepideh Mirrahimi ◽  
Sylvain Gandon
Keyword(s):  
Asexual Reproduction ◽  
Rna Viruses ◽  
Adaptive Dynamics ◽  
Mutation Rates ◽  
Heterogeneous Environments ◽  
Evolutionary Forces ◽  
Local Selection ◽  
And Migration ◽  
Source Sink ◽  
Evolution Of Specialization

AbstractAdaptation in spatially heterogeneous environments results from the balance between local selection, mutation and migration. We study the interplay among these different evolutionary forces and demography in a classical two habitat scenario with asexual reproduction. We develop a new theoretical approach that fills a gap between the restrictive assumptions of Adaptive Dynamics and Quantitative Genetics. This analysis yields more accurate predictions of the equilibrium phenotypic distribution in different habitats. We examine the evolutionary equilibrium under general conditions where demography and selection may be non-symmetric between the two habitats. In particular we show how migration may increase differentiation in a source-sink scenario. We discuss the implications of these analytic results for the adaptation of organisms with large mutation rates such as RNA viruses.

scholarly journals Evolution of Specialization in Heterogeneous Environments: Equilibrium Between Selection, Mutation and Migration

Genetics ◽  
2019 ◽  
Vol 214 (2) ◽  
pp. 479-491
Author(s):  
Sepideh Mirrahimi ◽  
Sylvain Gandon
Keyword(s):  
Gaussian Approximation ◽  
Adaptive Dynamics ◽  
Mutation Rates ◽  
Heterogeneous Environments ◽  
Evolutionary Forces ◽  
Phenotypic Distribution ◽  
Local Selection ◽  
And Migration ◽  
Source Sink ◽  
Evolution Of Specialization

Adaptation in spatially heterogeneous environments results from the balance between local selection, mutation, and migration. We study the interplay among these different evolutionary forces and demography in a classical two-habitat scenario with asexual reproduction. We develop a new theoretical approach that goes beyond the Adaptive Dynamics framework, and allows us to explore the effect of high mutation rates on the stationary phenotypic distribution. We show that this approach improves the classical Gaussian approximation, and captures accurately the shape of this equilibrium phenotypic distribution in one- and two-population scenarios. We examine the evolutionary equilibrium under general conditions where demography and selection may be nonsymmetric between the two habitats. In particular, we show how migration may increase differentiation in a source–sink scenario. We discuss the implications of these analytic results for the adaptation of organisms with large mutation rates, such as RNA viruses.

scholarly journals A Hamilton–Jacobi approach to characterize the evolutionary equilibria in heterogeneous environments

2017 ◽  
Vol 27 (13) ◽  
pp. 2425-2460 ◽  
Author(s):  
Sepideh Mirrahimi
Keyword(s):  
Evolutionary Biology ◽  
Gaussian Approximation ◽  
Adaptive Dynamics ◽  
Bimodal Distribution ◽  
Heterogeneous Environments ◽  
Structured Population ◽  
And Migration ◽  
Two Peaks ◽  
Jacobi Equations ◽  
General Method

In this work, we characterize the solution of a system of elliptic integro-differential equations describing a phenotypically structured population subject to mutation, selection and migration between two habitats. Assuming that the effects of the mutations are small but nonzero, we show that the population’s phenotypical distribution has at most two peaks and we give explicit conditions under which the population will be monomorphic (unimodal distribution) or dimorphic (bimodal distribution). More importantly, we provide a general method to determine the dominant terms of the population’s distribution in each case. Our work, which is based on Hamilton–Jacobi equations with constraint, goes further than previous works where such tools were used, for different problems from evolutionary biology, to identify the asymptotic solutions, while the mutations vanish, as a sum of Dirac masses. The main elements for the computation of the dominant terms of the population’s distribution are the convergence of the logarithmic transform of the solution to the unique solution of a Hamilton–Jacobi equation and the computation of the correctors. This method allows indeed to go further than the Gaussian approximation commonly used by biologists and makes a connection between the theories of adaptive dynamics and quantitative genetics. Our work being motivated by biological questions, the objective of this paper is to provide the mathematical details which are necessary for our biological results [S. Mirrahimi and S. Gandon, The equilibrium between selection, mutation and migration in spatially heterogeneous environments, in preparation].

scholarly journals Effect of migration and environmental heterogeneity on the maintenance of quantitative variation: a simulation study

2017 ◽  
Author(s):  
Tegan Krista McDonald ◽  
Sam Yeaman
Keyword(s):  
Genetic Variation ◽  
Habitat Fragmentation ◽  
Environmental Heterogeneity ◽  
Mutation Rates ◽  
Stabilizing Selection ◽  
Heterogeneous Environments ◽  
Migration Rates ◽  
Theoretical Predictions ◽  
And Migration ◽  
General Explanation

AbstractThe paradox of high genetic variation observed in traits under stabilizing selection is a longstanding problem in evolutionary theory, as mutation rates are 10-100 times too low to explain observed levels of standing genetic variation under classic models of mutation-selection balance. Here, we use individual-based simulations to explore the effect of various types of environmental heterogeneity on the maintenance of genetic variation (VA) for a quantitative trait under stabilizing selection. We find that VA is maximized at intermediate migration rates in spatially heterogeneous environments, and that the observed patterns are robust to changes in population size. Spatial environmental heterogeneity increased variation by as much as 10-fold over mutation-selection-balance alone, whereas pure temporal environmental heterogeneity increased variance by only 45% at max. Our results show that some combinations of spatial heterogeneity and migration can maintain considerably more variation than mutation-selection balance, potentially reconciling the discrepancy between theoretical predictions and empirical observations. However, given the narrow regions of parameter space required for this effect, this is unlikely to provide a general explanation for the maintenance of variation. Nonetheless, our results suggest that habitat fragmentation may affect the maintenance of VA and thereby reduce the adaptive capacity of populations.

Rates of Spontaneous Mutation

Genetics ◽  
1998 ◽  
Vol 148 (4) ◽  
pp. 1667-1686 ◽  
Author(s):  
John W Drake ◽  
Brian Charlesworth ◽  
Deborah Charlesworth ◽  
James F Crow
Keyword(s):  
Cell Division ◽  
Base Pair ◽  
Rna Viruses ◽  
Spontaneous Mutation ◽  
Mutation Rates ◽  
Base Pairs ◽  
Evolutionary Forces ◽  
Sexual Generation ◽  
Higher Eukaryotes

Abstract Rates of spontaneous mutation per genome as measured in the laboratory are remarkably similar within broad groups of organisms but differ strikingly among groups. Mutation rates in RNA viruses, whose genomes contain ca. 104 bases, are roughly 1 per genome per replication for lytic viruses and roughly 0.1 per genome per replication for retroviruses and a retrotransposon. Mutation rates in microbes with DNA-based chromosomes are close to 1/300 per genome per replication; in this group, therefore, rates per base pair vary inversely and hugely as genome sizes vary from 6 × 103 to 4 × 107 bases or base pairs. Mutation rates in higher eukaryotes are roughly 0.1–100 per genome per sexual generation but are currently indistinguishable from 1/300 per cell division per effective genome (which excludes the fraction of the genome in which most mutations are neutral). It is now possible to specify some of the evolutionary forces that shape these diverse mutation rates.

scholarly journals Viral Mutation Rates

2010 ◽  
Vol 84 (19) ◽  
pp. 9733-9748 ◽  
Author(s):  
Rafael Sanjuán ◽  
Miguel R. Nebot ◽  
Nicola Chirico ◽  
Louis M. Mansky ◽  
Robert Belshaw
Keyword(s):  
Mutation Rate ◽  
Rna Viruses ◽  
Experimental Testing ◽  
Mutation Rates ◽  
Cell Infection ◽  
Nucleotide Substitutions ◽  
Data Set ◽  
Dna Viruses ◽  
Double Stranded Dna ◽  
Viral Mutation

ABSTRACT Accurate estimates of virus mutation rates are important to understand the evolution of the viruses and to combat them. However, methods of estimation are varied and often complex. Here, we critically review over 40 original studies and establish criteria to facilitate comparative analyses. The mutation rates of 23 viruses are presented as substitutions per nucleotide per cell infection (s/n/c) and corrected for selection bias where necessary, using a new statistical method. The resulting rates range from 10−8 to10−6 s/n/c for DNA viruses and from 10−6 to 10−4 s/n/c for RNA viruses. Similar to what has been shown previously for DNA viruses, there appears to be a negative correlation between mutation rate and genome size among RNA viruses, but this result requires further experimental testing. Contrary to some suggestions, the mutation rate of retroviruses is not lower than that of other RNA viruses. We also show that nucleotide substitutions are on average four times more common than insertions/deletions (indels). Finally, we provide estimates of the mutation rate per nucleotide per strand copying, which tends to be lower than that per cell infection because some viruses undergo several rounds of copying per cell, particularly double-stranded DNA viruses. A regularly updated virus mutation rate data set will be available at www.uv.es/rsanjuan/virmut .

scholarly journals Structural and molecular basis of mismatch correction and ribavirin excision from coronavirus RNA

2017 ◽  
Vol 115 (2) ◽  
pp. E162-E171 ◽  
Author(s):  
François Ferron ◽  
Lorenzo Subissi ◽  
Ana Theresa Silveira De Morais ◽  
Nhung Thi Tuyet Le ◽  
Marion Sevajol ◽  
...  
Keyword(s):  
Molecular Basis ◽  
Rna Synthesis ◽  
Rna Viruses ◽  
Mutation Rates ◽  
Bifunctional Enzyme ◽  
Antiviral Compound ◽  
Mismatch Correction ◽  
Limited Efficacy

Coronaviruses (CoVs) stand out among RNA viruses because of their unusually large genomes (∼30 kb) associated with low mutation rates. CoVs code for nsp14, a bifunctional enzyme carrying RNA cap guanine N7-methyltransferase (MTase) and 3′-5′ exoribonuclease (ExoN) activities. ExoN excises nucleotide mismatches at the RNA 3′-end in vitro, and its inactivation in vivo jeopardizes viral genetic stability. Here, we demonstrate for severe acute respiratory syndrome (SARS)-CoV an RNA synthesis and proofreading pathway through association of nsp14 with the low-fidelity nsp12 viral RNA polymerase. Through this pathway, the antiviral compound ribavirin 5′-monophosphate is significantly incorporated but also readily excised from RNA, which may explain its limited efficacy in vivo. The crystal structure at 3.38 Å resolution of SARS-CoV nsp14 in complex with its cofactor nsp10 adds to the uniqueness of CoVs among RNA viruses: The MTase domain presents a new fold that differs sharply from the canonical Rossmann fold.

scholarly journals Adaptive Value of High Mutation Rates of RNA Viruses: Separating Causes from Consequences

2005 ◽  
Vol 79 (18) ◽  
pp. 11555-11558 ◽  
Author(s):  
Santiago F. Elena ◽  
Rafael Sanjuán
Keyword(s):  
Rna Viruses ◽  
Mutation Rates ◽  
Adaptive Value

scholarly journals Why genes overlap in viruses

2010 ◽  
Vol 277 (1701) ◽  
pp. 3809-3817 ◽  
Author(s):  
Nicola Chirico ◽  
Alberto Vianelli ◽  
Robert Belshaw
Keyword(s):  
Rna Viruses ◽  
Harmful Effect ◽  
Negative Relationship ◽  
Mutation Rates ◽  
Virus Species ◽  
Overlapping Genes ◽  
Genome Length ◽  
Dna Viruses ◽  
The Relationship ◽  
Gene Overlap

The genomes of most virus species have overlapping genes—two or more proteins coded for by the same nucleotide sequence. Several explanations have been proposed for the evolution of this phenomenon, and we test these by comparing the amount of gene overlap in all known virus species. We conclude that gene overlap is unlikely to have evolved as a way of compressing the genome in response to the harmful effect of mutation because RNA viruses, despite having generally higher mutation rates, have less gene overlap on average than DNA viruses of comparable genome length. However, we do find a negative relationship between overlap proportion and genome length among viruses with icosahedral capsids, but not among those with other capsid types that we consider easier to enlarge in size. Our interpretation is that a physical constraint on genome length by the capsid has led to gene overlap evolving as a mechanism for producing more proteins from the same genome length. We consider that these patterns cannot be explained by other factors, namely the possible roles of overlap in transcription regulation, generating more divergent proteins and the relationship between gene length and genome length.

scholarly journals Epistatic interactions within the influenza virus polymerase complex mediate mutagen resistance and replication fidelity

2017 ◽  
Author(s):  
Matthew D. Pauly ◽  
Daniel M. Lyons ◽  
Adam S. Lauring
Keyword(s):  
Genetic Diversity ◽  
Drug Resistance ◽  
Influenza Virus ◽  
Mutation Rate ◽  
Rna Viruses ◽  
Nucleoside Analogs ◽  
Mutation Rates ◽  
Epistatic Interactions ◽  
Polymerase Complex ◽  
Lethal Mutagenesis

AbstractLethal mutagenesis is a broad-spectrum antiviral strategy that employs mutagenic nucleoside analogs to exploit the high mutation rate and low mutational tolerance of many RNA viruses. Studies of mutagen-resistant viruses have identified determinants of replicative fidelity and the importance of mutation rate to viral population dynamics. We have previously demonstrated the effective lethal mutagenesis of influenza virus using three nucleoside analogs as well as the virus’s high genetic barrier to mutagen resistance. Here, we investigate the mutagen-resistant phenotypes of mutations that were enriched in drug-treated populations. We find that PB1 T123A has higher replicative fitness than the wild type, PR8, and maintains its level of genome production during 5-fluorouracil treatment. Surprisingly, this mutagen-resistant variant also has an increased baseline rate of C to U and G to A mutations. A second drug-selected mutation, PA T97I, interacts epistatically with PB T123A to mediate high-level mutagen resistance, predominantly by limiting the inhibitory effect of nucleosides on polymerase activity. Consistent with the importance of epistatic interactions in the influenza polymerase, we find that nucleoside analog resistance and replication fidelity are strain dependent. Two previously identified ribavirin-resistance mutations, PB1 V43I and PB1 D27N, do not confer drug resistance in the PR8 background, and the PR8-PB1 V43I polymerase exhibits a normal baseline mutation rate. Our results highlight the genetic complexity of the influenza virus polymerase and demonstrate that increased replicative capacity is a mechanism by which an RNA virus can counter the negative effects of elevated mutation rates.ImportanceRNA viruses exist as genetically diverse populations. This standing genetic diversity gives them the potential to adapt rapidly, evolve resistance to antiviral therapeutics, and evade immune responses. Viral mutants with altered mutation rates or mutational tolerance have provided insights into how genetic diversity arises and how it affects the behavior of RNA viruses. To this end, we identified variants within the polymerase complex of influenza virus that are able tolerate drug-mediated increases in viral mutation rates. We find that drug resistance is highly dependent on interactions among mutations in the polymerase complex. In contrast to other viruses, influenza virus counters the effect of higher mutation rates primarily by maintaining high levels of genome replication. These findings suggest the importance of maintaining large population sizes for viruses with high mutation rates and show that multiple proteins can affect both mutation rate and genome synthesis.

scholarly journals Episodic diversifying selection and intragenomic interactions shape the evolution of DNA and RNA viruses

2019 ◽  
Author(s):  
Stéphane Aris-Brosou ◽  
Louis Parent ◽  
Neke Ibeh
Keyword(s):  
Rna Viruses ◽  
Viral Evolution ◽  
Amino Acid Level ◽  
Mutation Rates ◽  
Correlated Evolution ◽  
Dna Viruses ◽  
Diversifying Selection ◽  
Dna And Rna ◽  
Show Evidence ◽  
Key Aspects

AbstractViruses are known to have some of the highest and most diverse mutation rates found in any biological replicator, topped by single-stranded (ss) RNA viruses, while double-stranded (ds) DNA viruses have rates approaching those of bacteria. As mutation rates are tightly and negatively correlated with genome size, selection is a clear driver of viral evolution. However, the role of intragenomic interactions as drivers of viral evolution is less well documented. To understand how these two processes affect viral evolution, we systematically surveyed ssRNA, ssDNA, dsRNA, and dsDNA viruses, to find which virus type and which functions show evidence for episodic diversifying selection and correlated evolution. We show that while evidence for selection is mostly found in single stranded viruses, and correlated evolution is more prevalent in DNA viruses, the genes that are affected by both processes are involved in key aspects of their life cycle, favoring viral stability over proliferation. We further show that both evolutionary processes are intimately linked at the amino acid level, which suggests that selection alone does not explain the whole evolutionary —and epidemiological— potential of viruses.

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