Genetic Draft, Selective Interference, and Population Genetics of Rapid Adaptation
By Richard A. Neher. 2013
165 citations recorded by the source corpus.
To learn about the past from a sample of genomic sequences, one needs to understand how evolutionary processes shape genetic diversity. Most population genetics inferences are based on frameworks assuming that adaptive evolution is rare. But if positive selection operates on many loci simultaneously, as has recently been suggested for many species, including animals such as flies, then a different approach is necessary. In this review, I discuss recent progress in characterizing and understanding evolution in rapidly adapting populations, in which random associations of mutations with genetic backgrounds of different fitness, i.e., genetic draft, dominate over genetic drift. As a result, neutral genetic diversity depends weakly on population size but strongly on the rate of adaptation or more generally the variance in fitness. Coalescent processes with multiple mergers, rather than Kingman's coalescent, are appropriate genealogical models for rapidly adapting populations, with important implications for p...
Subfields: Ecology, Evolution, Behavior and Systematics, Genetics
View Paper: https://www.semanticscholar.org/paper/ed662d881abf5fa2ae02a783ac51477ed792473c
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In Ecology, Evolution, Behavior and Systematics
In Genetics
- Michael Lässig
- Ville Mustonen
- Aleksandra M. Walczak
- Pavel Sagulenko
- Richard A. Neher
- Vadim Puller
- Trevor Bedford
- K. Kistler
Citations in the corpus
- Predicting evolution (2017, methodology): “This type of model has been applied to the evolution of human influenza 13 ; its fitness trade-off between traits also captures aspects of HIV evolution under host immune pressure 17 , of drug resistance evolution 61 , and of cancer evolution 63 .”
- TreeTime: Maximum-likelihood phylodynamic analysis (2017, background): “The likelihood of observing a particular genealogical tree depends on the size of the population, its geographic structure, and fitness variation in the population (Kingman, 1982; Nordborg, 1997; Neher, 2013).”