ArticleMolecular biology and evolution2017
Quantifying Selection with Pool-Seq Time Series Data.
Article in Molecular biology and evolution, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
63 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A cosmopolitan inversion facilitates seasonal adaptation in overwintering Drosophila.Genetics · 2024Pooled it
- Intersecting experimental evolution and CRISPR screens to identify novel toxin resistance loci.eLife · 2026Article
- Enhancing detection of polygenic adaptation: a comparative study of machine learning and statistical approaches using simulated evolve-and-resequence data.BMC genomics · 2026Article
- Haplotype structure: an overlooked key factor shaping the genomic selection response.Genetics · 2026Article
- Beyond fixation: persistent genetic variation under intense selection.Molecular biology and evolution · 2026Article
- Direct estimation of genotype fitness from time series.bioRxiv : the preprint server for biology · 2026Article
- Experimental Evolution Under Biased Sex Ratios: Phenotypic and Genomic Responses in the Bulb Mite, Rhizoglyphus robini.Genome biology and evolution · 2026Article
- Beyond Fixation: Persistent Genetic Variation Under Intense Selection.bioRxiv : the preprint server for biology · 2026Article
- PolyAdapt: Characterizing Polygenic Adaptive Architectures in the Presence of Strong Linkage Disequilibrium.Genome biology and evolution · 2026Article
- Article
- Influence of geography, seasonality and experimental selection on Chironomus riparius recombination rates.BMC genomics · 2026Article
- Strength of selection potentiates distinct adaptive responses in an evolution experiment with outcrossing yeast.G3 (Bethesda, Md.) · 2026Article
- The Genetic Architecture of Venom Resistance: A Novel Approach to Target Identification and Coevolutionary Discovery.Molecular biology and evolution · 2026Article
- Skim-sequencing for genomic selection in wheat: a comparison of marker platforms.The plant genome · 2026Article
- Pollution-Driven Selection in a Non-Biting Midge: Genome-Wide Responses to Bacillus thuringiensis israelensis and Copper.Molecular ecology · 2026Article
- Linkage-aware inference of fitness from short-read time-series genomic data.bioRxiv : the preprint server for biology · 2026Article
- The genetic architecture and spatiotemporal dynamics of adaptation across human-modified landscapes.The New phytologist · 2026Review
- Linkage-aware inference of fitness from short-read time-series genomic data.Virus evolution · 2026Article
- Selection Estimation from Genetic Time-Series Data: Effects of Limited Sampling and Genetic Drift.Molecular biology and evolution · 2025Article
- Genomic parallelism defines repeated evolution of an inducible offense.Science advances · 2025Article
3 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors.
Funding
Abstract
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.