The structure of genotype-phenotype maps makes fitness landscapes navigable.

Autor: Greenbury SF; Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge, UK. sgreenbury@turing.ac.uk.; The Alan Turing Institute, British Library, London, UK. sgreenbury@turing.ac.uk., Louis AA; Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford, UK. ard.louis@physics.ox.ac.uk., Ahnert SE; The Alan Turing Institute, British Library, London, UK. sea31@cam.ac.uk.; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK. sea31@cam.ac.uk.
Jazyk: angličtina
Zdroj: Nature ecology & evolution [Nat Ecol Evol] 2022 Nov; Vol. 6 (11), pp. 1742-1752. Date of Electronic Publication: 2022 Sep 29.
DOI: 10.1038/s41559-022-01867-z
Abstrakt: Fitness landscapes are often described in terms of 'peaks' and 'valleys', indicating an intuitive low-dimensional landscape of the kind encountered in everyday experience. The space of genotypes, however, is extremely high dimensional, which results in counter-intuitive structural properties of genotype-phenotype maps. Here we show that these properties, such as the presence of pervasive neutral networks, make fitness landscapes navigable. For three biologically realistic genotype-phenotype map models-RNA secondary structure, protein tertiary structure and protein complexes-we find that, even under random fitness assignment, fitness maxima can be reached from almost any other phenotype without passing through fitness valleys. This in turn indicates that true fitness valleys are very rare. By considering evolutionary simulations between pairs of real examples of functional RNA sequences, we show that accessible paths are also likely to be used under evolutionary dynamics. Our findings have broad implications for the prediction of natural evolutionary outcomes and for directed evolution.
(© 2022. Crown.)
Databáze: MEDLINE
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