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Information theory, evolutionary innovations and evolvability


Wagner, Andreas (2017). Information theory, evolutionary innovations and evolvability. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 372(1735):0416.

Abstract

How difficult is it to ‘discover’ an evolutionary adaptation or innovation? I here suggest that information theory, in combination with high-throughput DNA sequencing, can help answer this question by quantifying a new phenotype's information content. I apply this framework to compute the phenotypic information associated with novel gene regulation and with the ability to use novel carbon sources. The framework can also help quantify how DNA duplications affect evolvability, estimate the complexity of phenotypes and clarify the meaning of ‘progress’ in Darwinian evolution. This article is part of the themed issue ‘Process and pattern in innovations from cells to societies’.

Abstract

How difficult is it to ‘discover’ an evolutionary adaptation or innovation? I here suggest that information theory, in combination with high-throughput DNA sequencing, can help answer this question by quantifying a new phenotype's information content. I apply this framework to compute the phenotypic information associated with novel gene regulation and with the ability to use novel carbon sources. The framework can also help quantify how DNA duplications affect evolvability, estimate the complexity of phenotypes and clarify the meaning of ‘progress’ in Darwinian evolution. This article is part of the themed issue ‘Process and pattern in innovations from cells to societies’.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
Dewey Decimal Classification:570 Life sciences; biology
590 Animals (Zoology)
Language:English
Date:5 December 2017
Deposited On:01 Mar 2018 09:42
Last Modified:07 Apr 2020 07:08
Publisher:Royal Society Publishing
ISSN:0962-8436
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1098/rstb.2016.0416
PubMed ID:29061889
Project Information:
  • : FunderSNSF
  • : Grant ID31003A_146137
  • : Project TitlePhenotypic innovation, robustness, and recombination in genome-scale metabolic networks
  • : FunderH2020
  • : Grant ID739874
  • : Project TitleNoiseRobustEvo - Noise and robustness in the evolution of novel protein phenotypes

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