ReviewJournal of molecular evolution2023
Identifying Targets of Selection in Laboratory Evolution Experiments.
Review in Journal of molecular evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Putting BASIL in a BLT: A Bayesian filtering method for estimating the fitness effects of nascent adaptive mutations.PLoS computational biology · 2026Article
- Examining selection dynamics and limitations in multi-round protein selection of high diversity libraries.Protein engineering, design & selection : PEDS · 2026Article
- Weak pervasive incompatibilities and compensatory adaptation drive hybrid genome evolution in yeast.bioRxiv : the preprint server for biology · 2026Article
- Gut microbiota-mediated lipid accumulation as a driver of evolutionary adaptation to blue light toxicity in Drosophila.Communications biology · 2025Article
- Distinguishing mutants that resist drugs via different mechanisms by examining fitness tradeoffs.eLife · 2024Article
- Distinguishing mutants that resist drugs via different mechanisms by examining fitness tradeoffs.bioRxiv : the preprint server for biology · 2024Article
- Best Practices in Microbial Experimental Evolution.Journal of molecular evolution · 2023Article
- Embracing Complexity: Yeast Evolution Experiments Featuring Standing Genetic Variation.Journal of molecular evolution · 2023Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Adaptive evolution navigates a balance between chance and determinism. The stochastic processes of mutation and drift generate phenotypic variation; however, once mutations reach an appreciable frequency in the population, their fate is governed by the deterministic action of selection, enriching for favorable genotypes and purging the less-favorable ones. The net result is that replicate populations will traverse similar-but not identical-pathways to higher fitness. This parallelism in evolutionary outcomes can be leveraged to identify the genes and pathways under selection. However, distinguishing between beneficial and neutral mutations is challenging because many beneficial mutations will be lost due to drift and clonal interference, and many neutral (and even deleterious) mutations will fix by hitchhiking. Here, we review the best practices that our laboratory uses to identify genetic targets of selection from next-generation sequencing data of evolved yeast populations. The general principles for identifying the mutations driving adaptation will apply more broadly.
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