Literature DB >> 29061889

Information theory, evolutionary innovations and evolvability.

Andreas Wagner1,2,3.   

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'.
© 2017 The Author(s).

Entities:  

Keywords:  evolvability; gene duplication; progress

Mesh:

Year:  2017        PMID: 29061889      PMCID: PMC5665804          DOI: 10.1098/rstb.2016.0416

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  56 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2000-04-25       Impact factor: 11.205

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Authors:  B R Frieden; A Plastino; B H Soffer
Journal:  J Theor Biol       Date:  2001-01-07       Impact factor: 2.691

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Authors:  Jack W Szostak
Journal:  Nature       Date:  2003-06-12       Impact factor: 49.962

Review 4.  Development of floral organ identity: stories from the MADS house.

Authors:  G Theissen
Journal:  Curr Opin Plant Biol       Date:  2001-02       Impact factor: 7.834

Review 5.  The evolutionary significance of cis-regulatory mutations.

Authors:  Gregory A Wray
Journal:  Nat Rev Genet       Date:  2007-03       Impact factor: 53.242

6.  Emerging principles of regulatory evolution.

Authors:  Benjamin Prud'homme; Nicolas Gompel; Sean B Carroll
Journal:  Proc Natl Acad Sci U S A       Date:  2007-05-09       Impact factor: 11.205

7.  Rate and molecular spectrum of spontaneous mutations in the bacterium Escherichia coli as determined by whole-genome sequencing.

Authors:  Heewook Lee; Ellen Popodi; Haixu Tang; Patricia L Foster
Journal:  Proc Natl Acad Sci U S A       Date:  2012-09-18       Impact factor: 11.205

8.  In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data.

Authors:  J S Edwards; R U Ibarra; B O Palsson
Journal:  Nat Biotechnol       Date:  2001-02       Impact factor: 54.908

9.  Analyses of the effects of all ubiquitin point mutants on yeast growth rate.

Authors:  Benjamin P Roscoe; Kelly M Thayer; Konstantin B Zeldovich; David Fushman; Daniel N A Bolon
Journal:  J Mol Biol       Date:  2013-01-30       Impact factor: 5.469

Review 10.  Reconstruction of biochemical networks in microorganisms.

Authors:  Adam M Feist; Markus J Herrgård; Ines Thiele; Jennie L Reed; Bernhard Ø Palsson
Journal:  Nat Rev Microbiol       Date:  2008-12-31       Impact factor: 60.633

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  2 in total

1.  Innovation: an emerging focus from cells to societies.

Authors:  Michael E Hochberg; Pablo A Marquet; Robert Boyd; Andreas Wagner
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-12-05       Impact factor: 6.237

2.  Faraway, so close. The comparative method and the potential of non-model animals in mitochondrial research.

Authors:  Liliana Milani; Fabrizio Ghiselli
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-12-02       Impact factor: 6.237

  2 in total

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