Literature DB >> 17206577

Ecological specialization and adaptive decay in digital organisms.

Elizabeth A Ostrowski1, Charles Ofria, Richard E Lenski.   

Abstract

The transition from generalist to specialist may entail the loss of unused traits or abilities, resulting in narrow niche breadth. Here we examine the process of specialization in digital organisms--self-replicating computer programs that mutate, adapt, and evolve. Digital organisms obtain energy by performing computations with numbers they input from their environment. We examined the evolutionary trajectory of generalist organisms in an ecologically narrow environment, where only a single computation yielded energy. We determined the extent to which improvements in this one function were associated with losses of other functions, leading to organisms that were highly specialized to perform only one or a few functions. Our results show that as organisms evolved improved performance of the selected function, they often lost the ability to perform other computations, and these losses resulted most often from the accumulation of neutral and deleterious mutations. Beneficial mutations, although relatively rare, were disproportionately likely to cause losses of function, indicating that antagonistic pleiotropy contributed significantly to niche breadth reductions in this system. Occasionally, unused functions were not lost and even increased in performance. Here we find that understanding how the functions were integrated into the genome was crucial to predictions of their maintenance.

Mesh:

Year:  2006        PMID: 17206577     DOI: 10.1086/510211

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  14 in total

1.  Evolution of resistance to quorum quenching in digital organisms.

Authors:  Benjamin E Beckmann; David B Knoester; Brian D Connelly; Christopher M Waters; Philip K McKinley
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2.  Evolution of music by public choice.

Authors:  Robert M MacCallum; Matthias Mauch; Austin Burt; Armand M Leroi
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-18       Impact factor: 11.205

3.  The genetic basis of parallel and divergent phenotypic responses in evolving populations of Escherichia coli.

Authors:  Elizabeth A Ostrowski; Robert J Woods; Richard E Lenski
Journal:  Proc Biol Sci       Date:  2008-02-07       Impact factor: 5.349

Review 4.  Understanding specialism when the Jack of all trades can be the master of all.

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Journal:  Proc Biol Sci       Date:  2012-10-24       Impact factor: 5.349

5.  Learning to get along despite struggling to get by.

Authors:  Elizabeth A Ostrowski; Gad Shaulsky
Journal:  Genome Biol       Date:  2009-05-26       Impact factor: 13.583

6.  A comparison of the effects of random and selective mass extinctions on erosion of evolutionary history in communities of digital organisms.

Authors:  Gabriel Yedid; Jason Stredwick; Charles A Ofria; Paul-Michael Agapow
Journal:  PLoS One       Date:  2012-05-31       Impact factor: 3.240

7.  The effects of low-impact mutations in digital organisms.

Authors:  Chase W Nelson; John C Sanford
Journal:  Theor Biol Med Model       Date:  2011-04-18       Impact factor: 2.432

8.  Computability, Gödel's incompleteness theorem, and an inherent limit on the predictability of evolution.

Authors:  Troy Day
Journal:  J R Soc Interface       Date:  2011-08-17       Impact factor: 4.118

9.  Evolutionary origins of invasive populations.

Authors:  Carol Eunmi Lee; Gregory William Gelembiuk
Journal:  Evol Appl       Date:  2008-06-28       Impact factor: 5.183

10.  Consequences of mutation accumulation for growth performance are more likely to be resource-dependent at higher temperatures.

Authors:  Xiao-Lin Chu; Quan-Guo Zhang
Journal:  BMC Ecol Evol       Date:  2021-06-06
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