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Published December 2013 | public
Journal Article

In Darwinian evolution, feedback from natural selection leads to biased mutations

Abstract

Natural selection provides feedback through which information about the environment and its recurring challenges is captured, inherited, and accumulated within genomes in the form of variations that contribute to survival. The variation upon which natural selection acts is generally described as "random." Yet evidence has been mounting for decades, from such phenomena as mutation hotspots, horizontal gene transfer, and highly mutable repetitive sequences, that variation is far from the simplifying idealization of random processes as white (uniform in space and time and independent of the environment or context). This paper focuses on what is known about the generation and control of mutational variation, emphasizing that it is not uniform across the genome or in time, not unstructured with respect to survival, and is neither memoryless nor independent of the (also far from white) environment. We suggest that, as opposed to frequentist methods, Bayesian analysis could capture the evolution of nonuniform probabilities of distinct classes of mutation, and argue not only that the locations, styles, and timing of real mutations are not correctly modeled as generated by a white noise random process, but that such a process would be inconsistent with evolutionary theory.

Additional Information

© 2013 New York Academy of Sciences. Article first published online: 13 Sep. 2013. The authors are deeply indebted to David King for his important and insightful comments on an earlier version of this manuscript, and recommend his recent article, which contributes historical background for this discussion. This work was supported in part by the National Science Foundation under Grant No. PHYS-1066293 and the hospitality of the Aspen Center for Physics. J.D. was in part supported by the NSF, AFOSR, and the Institute for Collaborative Biotechnologies through Grant W911NF-09-0001 from the U.S. Army Research Office. The content does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.

Additional details

Created:
August 22, 2023
Modified:
January 13, 2024