The time scale of evolutionary innovation Journal Article

Author(s): Chatterjee, Krishnendu; Pavlogiannis, Andreas; Adlam, Ben; Nowak, Martin A
Article Title: The time scale of evolutionary innovation
Affiliation IST Austria
Abstract: A fundamental question in biology is the following: what is the time scale that is needed for evolutionary innovations? There are many results that characterize single steps in terms of the fixation time of new mutants arising in populations of certain size and structure. But here we ask a different question, which is concerned with the much longer time scale of evolutionary trajectories: how long does it take for a population exploring a fitness landscape to find target sequences that encode new biological functions? Our key variable is the length, (Formula presented.) of the genetic sequence that undergoes adaptation. In computer science there is a crucial distinction between problems that require algorithms which take polynomial or exponential time. The latter are considered to be intractable. Here we develop a theoretical approach that allows us to estimate the time of evolution as function of (Formula presented.) We show that adaptation on many fitness landscapes takes time that is exponential in (Formula presented.) even if there are broad selection gradients and many targets uniformly distributed in sequence space. These negative results lead us to search for specific mechanisms that allow evolution to work on polynomial time scales. We study a regeneration process and show that it enables evolution to work in polynomial time.
Journal Title: PLoS Computational Biology
Volume: 10
Issue 9
ISSN: 1553-7358
Publisher: Public Library of Science  
Date Published: 2014-09-01
Start Page: e1003818
Copyright Statement: CC BY
Sponsor: Austrian Science Fund (FWF) Grant No P23499-N23, FWF NFN Grant No S11407-N23 (RiSE), ERC Start grant (279307: Graph Games), and Microsoft Faculty Fellows award. Support from the John Templeton foundation is gratefully acknowledged.
DOI: 10.1371/journal.pcbi.1003818
Notes: Conceived and designed the experiments: KC AP BA MAN. Analyzed the data: KC AP BA MAN. Wrote the paper: KC AP BA MAN.
Open access: yes (OA journal)