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Host virus coevolution - demography versus selection

English title Host virus coevolution - demography versus selection
Applicant Feulner Philine
Number 160812
Funding scheme Project funding (Div. I-III)
Research institution Fischökologie und Evolution Eawag
Institution of higher education Swiss Federal Institute of Aquatic Science and Technology - EAWAG
Main discipline Molecular Biology
Start/End 01.01.2016 - 31.12.2018
Approved amount 193'876.00
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Keywords (4)

rapid evolution; coevolutionary dynamics; eco-evolutionary dynamics; genomics of adaptation

Lay Summary (German)

Lead
Die Identifikation von adaptiven Mutationen im Genom ist von größtem Interesse für unser Verständnis der genetischen Grundlagen von adaptiven Merkmalen und des zeitlichen Ablaufs von adaptiven Anpassungsprozessen. Insbesondere die Fragen nach der Häufigkeit von adaptive Änderungen im Genome und den Parametern, die die Rate dieser Änderungen beeinflussen, sind noch offen.
Lay summary

Ziele dieses Projekts sind (1) die Identifizierung von adaptiven Anpassungen im Genome von koevolvierenden Wirt-Virus Populationen und (2) die Untersuchung des Einflusses von Demographie und Selektion auf diese Anpassungen. Dazu nutzen wir Experimente mit Wirts-Viren Modellsystemen, die in vorangegangen Experimenten bereits Koevolution von Resistenzen und Gegenanpassungen innerhalb von wenigen Generationen gezeigt haben. Im Verlauf dieser Experimente zeigte sich, daß sich die koevolutionären Dynamiken weg von einem Wettrüsten (arms race) hin zu fluktuierender Selektion änderten. Diese Änderung trat ein, sobald sich ein Wirt entwickelt hatte, der gegen alle Viren resistent war. Entscheidend für das gegenwärtige Projekt ist, dass die evolutionären Dynamiken an demografischen Veränderungen gekoppelt waren. Während der ersten Phase des Wettrüstens fluktuierten die Populationen von Wirt und Virus in ihrer Populationsgröße, wohingegen sich die Populationen in der zweiten Phase des Experimentes stabilisierten. Genau dieses Zusammenspiel von Koevolution und Populationsdynamiken (öko-evolutionäre Dynamiken) machen das System zu einem idealen Studienobjekt. Innerhalb dieses Projekts werden die adaptiven Anpassungen von Wirt und Virus auf der Genome und Phänotypen Ebene identifiziert und zwischen Replikaten verglichen. Aus den Daten soll unter Anderem die Häufigkeit und Wahrscheinlichkeit der Fixierung einer adaptiven Änderung und die Zeit zur Fixierung von adaptiven Mutationen bestimmt werden. Zusätzlich werden wir in Versuchen den Einfluss von Selektion und Demographie auf die adaptiven Anpassungen untersuchen. Darüber hinaus soll diese Projekt dazu beitragen genetische Daten besser interpretieren zu können, speziell solche Regionen des Genoms zu identifizieren, welche durch lokale Anpassungen geformt wurden, und Methoden für populationsgenomische Analyse zu entwickeln, die robust gegenüber variierenden Populationsgrößen sind. 

 

Direct link to Lay Summary Last update: 20.08.2015

Responsible applicant and co-applicants

Employees

Name Institute

Publications

Publication
The feedback between selection and demography shapes genomic diversity during coevolution
Retel Cas, Kowallik Vienna, Huang Weini, Werner Benjamin, Künzel Sven, Becks Lutz, Feulner Philine G. D. (2019), The feedback between selection and demography shapes genomic diversity during coevolution, in Science Advances, 5(10), eaax0530-eaax0530.
Ecological and Evolutionary Processes Shaping Viral Genetic Diversity
Retel Cas, Märkle Hanna, Becks Lutz, Feulner Philine (2019), Ecological and Evolutionary Processes Shaping Viral Genetic Diversity, in Viruses, 11(3), 220-220.
Population size changes and selection drive patterns of parallel evolution in a host–virus system
Frickel Jens, Feulner Philine G. D., Karakoc Emre, Becks Lutz (2018), Population size changes and selection drive patterns of parallel evolution in a host–virus system, in Nature Communications, 9(1), 1706-1706.

Datasets

Data from: Population size changes and selection drive patterns of parallel evolution in a host-virus system

Author Frickel, J; Feulner, PGD; Karakoc, E; Becks, L
Publication date 18.06.2018
Persistent Identifier (PID) https://doi.org/10.5061/dryad.4gf1qb7
Repository Dryad
Abstract
Predicting the repeatability of evolution remains elusive. Theory and empirical studies suggest that strong selection and large population sizes increase the probability for parallel evolution at the phenotypic and genotypic levels. However, selection and population sizes are not constant, but rather change continuously and directly affect each other even on short time scales. Here, we examine the degree of parallel evolution shaped through eco-evolutionary dynamics in an algal host population coevolving with a virus. We find high degrees of parallelism at the level of population size changes (ecology) and at the phenotypic level between replicated populations. At the genomic level, we find evidence for parallelism, as the same large genomic region was duplicated in all replicated populations, but also substantial novel sequence divergence between replicates. These patterns of genome evolution can be explained by considering population size changes as an important driver of rapid evolution.

NCBI PRJNA450514

Author Frickel, Jens
Publication date 17.04.2018
Persistent Identifier (PID) PRJNA450514
Repository NCBI SRA


NCBI PRJNA548271

Author Retel, Cas
Publication date 11.06.2019
Persistent Identifier (PID) PRJNA548271
Repository NCBI SRA


Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Rapid evolutionary adaptation: Potential and constraints (International meeting of DFG SPP1819) Talk given at a conference Temporal dynamics of molecular evolution in rapidly coevolving host-virus populations 17.10.2018 Kiel, Germany Retel Cas;
II Joint Congress on Evolutionary Biology Talk given at a conference Co-Genomic Signature of Rapid Antagonistic Co-Evolution 19.08.2018 Montpellier, France Feulner Philine;
Aquatic Virus Workshop 2018 Talk given at a conference Temporal genomics of rapid antagonistic coevolution between Chlorovirus and its Chlorella host 17.06.2018 Lincoln, NE, United States of America Retel Cas;
Statistical & Computational Biology Seminar Individual talk The genomic signature of antagonistic coevolution 16.03.2018 Friborg, Switzerland Retel Cas;
Biology18 Talk given at a conference The genomic signature of rapid antagonistic coevolution 14.02.2018 Neuchatel, Switzerland Retel Cas;
ESEB Poster Genomics of EED in antagonistically coevolving populations 20.08.2017 Groningen, Netherlands Retel Cas;
Rapid evolutionary adaptation: Potential and constraints (2nd Annual Meeting) Talk given at a conference Genomics of rapid adaptation in host-virus coevolution 06.03.2017 Potsdam, Germany Retel Cas;
Biology17 Poster Adaptive genetic changes in rapidly coevolving host and virus populations 02.02.2017 Bern, Switzerland Retel Cas;
The genomic basis of eco-evolutionary change Poster Genomics of rapid adaptation in host-virus co-evolution 05.06.2016 Ascona, Switzerland Retel Cas;


Associated projects

Number Title Start Funding scheme
163446 Speciation Genomics of the Swiss Alpine Whitefish Radiation 01.10.2016 Project funding (Div. I-III)
179637 Host virus coevolution - demography versus selection in the face of multiple stressors 01.01.2019 Project funding (Div. I-III)

Abstract

There is a continuing interest to identify beneficial mutations in the genome. This interest is fuelled by the question regarding the genetic basis of adaptive traits and the need to understand the temporal dynamics of adaptive evolution, i.e., how frequent adaptive changes are and what influences the rate of change. In the project proposed here, we aim to (1) identify rapid adaptive genomic changes in coevolving host-virus populations and (2) comprehend how the dynamics of adaptive change vary with changing demographic setting. Previous experiments with chemostat systems showed that host and virus rapidly evolved resistance and counter adaptation. Later in the experiments, the dynamics shifted from arms race dynamics to fluctuating selection, after a generalist host resistant to all virus populations had evolved. The virus population however did not go extinct due to a trade-off between resistance and growth rates. A key observation is that the evolutionary dynamics in this system are coupled to demographic changes: during the initial arms race dynamics, host and virus population sizes cycle, with dramatic population size reductions, while population size are more steady when the evolutionary dynamics are characterized by fluctuating selection. The entanglement of the coevolutionary and population size dynamics (eco-evolutionary dynamics) makes this an excellent system for the proposed work. Following the described dynamics with whole genome sequencing of both (host and virus) populations across different time points will allow us to identify candidate mutations under selection. The experiments are replicated and fitness of the populations and individual clones at different time can be assessed. In addition, mutations can be traced over time estimating the probability and time to fixation of adaptive changes, providing a picture of the dynamics of adaptive change, in both interacting populations. In a second step, we will vary the experimental setup manipulating selection and demography in a full factorial design and evaluating how this alters the dynamics of adaptive change. Hence, we will improve our understanding on the relative role of two important processes selection and demography within eco-evolutionary dynamics. Furthermore, this project will aid to the knowledge on how to reveal the underlying processes from the observed genomic diversity patterns. An issue of major concern in population genomics, which aims to infer genomic regions, influenced by local adaptation from genome-wide polymorphism data. Hence, our results will also inform method development, which is essential as none of the statistical methods so far is robust under non-equilibrium situations, i.e. fluctuations in population sizes. Therefore, results from this experimental work will in the future aid population genomic inferences in other systems with longer generation times.
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