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Type of publication: Journal Article
Type of document: Full Paper

Year: 2017

Authors: Taus, T; Futschik, A; Schlötterer, C

Title: Quantifying Selection with Pool-Seq Time Series Data.

Source: Mol Biol Evol. 2017; 34(11):3023-3034

Authors Vetmeduni Vienna:

Schlötterer Christian
Taus Thomas

Vetmed Research Units
Institute of Population Genetics

Project(s): ERC ADG: The architecture of adaptation

Population Genetics

Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (Ne) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies.© The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Keywords Pubmed: Adaptation, Biologicalgenetics
Adaptation, Physiologicalgenetics
Biological Evolution
Computer Simulation
Evolution, Molecular
Gene Frequencygenetics
Models, Genetic
Polymorphism, Single Nucleotidegenetics
Selection, Genetic
Sequence Analysis, DNAmethodsstatistics & numerical data
Whole Genome Sequencingmethods

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