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Evolution and Selection of Quantitative Traits$
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Bruce Walsh and Michael Lynch

Print publication date: 2018

Print ISBN-13: 9780198830870

Published to Oxford Scholarship Online: September 2018

DOI: 10.1093/oso/9780198830870.001.0001

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Long-term Response: 3. Adaptive Walks

Long-term Response: 3. Adaptive Walks

(p.991) 27 Long-term Response: 3. Adaptive Walks
Evolution and Selection of Quantitative Traits

Bruce Walsh

Michael Lynch

Oxford University Press

One model for long-term evolution is an adaptive walk, a series of fixations of mutations that moves the trait mean toward some optimal value. The foundation for this idea traces back to Fisher's geometric model, which showed that mutations of large effect are favored when a trait is far from its optimal, while smaller effects are favored as it approaches the optimal value. Under fairly general conditions, this results in a roughly exponential distribution of fixed adaptive effects. An alternative to trait-based walks are walks in fitness space, motivated by considering a series of mutations to improve the fitness of a particular sequence. In such settings, extreme value theory also suggests a roughly exponential distribution, now of fitness (instead of trait) effects, for mutations fixed during the walk. Much of this theory offers at least partial experimental testing, and this chapter describes not only the theory, but also some of the empirical work testing the models.

Keywords:   clonal interference, cost of complexity, cost of pleiotropy, extreme-value theory, Fisher's geometric model, Fisher-Kimura-Orr adaptive walks, Fisher–Tippett–Gnedenko theorem, Maynard-Smith-Gillespie-Orr adaptive walks, mutational landscape model, Orr's invariance result. restricted pleiotropy, selectively accessible, sign epistasis, SSWM model, universal pleiotropy

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