Literature DB >> 19852618

Inverse-gene-for-gene infection genetics and coevolutionary dynamics.

Andrew Fenton1, Janis Antonovics, Michael A Brockhurst.   

Abstract

The genetic basis of infection in host-parasite interactions has traditionally been considered within the framework of either gene-for-gene (GFG) or matching-allele models. We present an alternative model, termed inverse-gene-for-gene (IGFG), where pathogen infectiousness is determined by parasite recognition of host signals and/or receptors or where there is active host searching by parasites. We show that coevolutionary dynamics under IGFG are both qualitatively and quantitatively different from those of the GFG model, and we suggest that this new approach may be applicable to a range of important host-parasite systems that are not currently catered for by the existing frameworks.

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Year:  2009        PMID: 19852618     DOI: 10.1086/645087

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


  23 in total

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4.  Understanding the evolution of interspecies interactions in microbial communities.

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Review 5.  Host-parasite co-evolution and its genomic signature.

Authors:  Dieter Ebert; Peter D Fields
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6.  Non-adaptive origins of evolutionary innovations increase network complexity in interacting digital organisms.

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7.  Dissecting the genetic architecture of host-pathogen specificity.

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8.  Dispersal network structure and infection mechanism shape diversity in a coevolutionary bacteria-phage system.

Authors:  Michael Sieber; Matthew Robb; Samantha E Forde; Ivana Gudelj
Journal:  ISME J       Date:  2013-10-03       Impact factor: 10.302

9.  Sustained coevolution of phage Lambda and Escherichia coli involves inner- as well as outer-membrane defences and counter-defences.

Authors:  Alita R Burmeister; Rachel M Sullivan; Jenna Gallie; Richard E Lenski
Journal:  Microbiology (Reading)       Date:  2021-05       Impact factor: 2.777

10.  Evolving digital ecological networks.

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Journal:  PLoS Comput Biol       Date:  2013-03-07       Impact factor: 4.475

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