ArticleGenetics2016
Estimating the Effective Population Size from Temporal Allele Frequency Changes in Experimental Evolution.
Article in Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
- Apparent stabilizing selection explains micro- and macroevolution of Drosophila wings.Nature ecology & evolution · 2026Article
- Interactions Between Inbreeding, Fitness and the Bacterial Microbiome inEvolutionary applications · 2026Article
- Influence of geography, seasonality and experimental selection on Chironomus riparius recombination rates.BMC genomics · 2026Article
- Seasonal fluctuations in fitness result in severe reductions in effective population size.bioRxiv : the preprint server for biology · 2026Article
- Strength of selection potentiates distinct adaptive responses in an evolution experiment with outcrossing yeast.G3 (Bethesda, Md.) · 2026Article
- A recurrent adaptive mutation in the transmembrane 2B protein of an insect picorna-like virus in a nonnative host.Journal of virology · 2026Article
- Substantial deceleration of adaptation of HIV-1 within 1500 generations in an experimental evolution: a genomic perspective.Virus evolution · 2026Article
- Repeatability of evolution and genomic predictions of temperature adaptation in seed beetles.Nature ecology & evolution · 2025Article
- Eco-evolutionary robustness of wild bacterial communities to experimental perturbation.The ISME journal · 2025Article
- Unraveling the Molecular Basis of Stabilizing Selection by Experimental Evolution.Genome biology and evolution · 2023Article
- Haplotype based testing for a better understanding of the selective architecture.BMC bioinformatics · 2023Article
- Selection on the Fly: Short-Term Adaptation to an Altered Sexual Selection Regime in Drosophila pseudoobscura.Genome biology and evolution · 2023Article
- Bait-ER: A Bayesian method to detect targets of selection in Evolve-and-Resequence experiments.Journal of evolutionary biology · 2023Article
- The genomic scale of fluctuating selection in a natural plant population.Evolution letters · 2022Article
- Experimental evolution reveals the synergistic genomic mechanisms of adaptation to ocean warming and acidification in a marine copepod.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Genome-wide signatures of synergistic epistasis during parallel adaptation in a Baltic Sea copepod.Nature communications · 2022Article
- The Transposition Rate Has Little Influence on the Plateauing Level of the P-element.Molecular biology and evolution · 2022Article
- Predicting the genomic resolution of bulk segregant analysis.G3 (Bethesda, Md.) · 2022Article
- Post-insemination selection dominates pre-insemination selection in driving rapid evolution of male competitive ability.PLoS genetics · 2022Article
- Slow Recovery from Inbreeding Depression Generated by the Complex Genetic Architecture of Segregating Deleterious Mutations.Molecular biology and evolution · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The effective population size ([Formula: see text]) is a major factor determining allele frequency changes in natural and experimental populations. Temporal methods provide a powerful and simple approach to estimate short-term [Formula: see text] They use allele frequency shifts between temporal samples to calculate the standardized variance, which is directly related to [Formula: see text] Here we focus on experimental evolution studies that often rely on repeated sequencing of samples in pools (Pool-seq). Pool-seq is cost-effective and often outperforms individual-based sequencing in estimating allele frequencies, but it is associated with atypical sampling properties: Additional to sampling individuals, sequencing DNA in pools leads to a second round of sampling, which increases the variance of allele frequency estimates. We propose a new estimator of [Formula: see text] which relies on allele frequency changes in temporal data and corrects for the variance in both sampling steps. In simulations, we obtain accurate [Formula: see text] estimates, as long as the drift variance is not too small compared to the sampling and sequencing variance. In addition to genome-wide [Formula: see text] estimates, we extend our method using a recursive partitioning approach to estimate [Formula: see text] locally along the chromosome. Since the type I error is controlled, our method permits the identification of genomic regions that differ significantly in their [Formula: see text] estimates. We present an application to Pool-seq data from experimental evolution with Drosophila and provide recommendations for whole-genome data. The estimator is computationally efficient and available as an R package at https://github.com/ThomasTaus/Nest.
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