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Specialization for resistance in wild host-pathogen interaction networks

Properties encompassed by host-pathogen interaction networks have potential to give valuable insight into the evolution of specialization and coevolutionary dynamics in host-pathogen interactions. However, network approaches have been rarely utilized in previous studies of host and pathogen phenotyp...

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Autores principales: Barrett, Luke G., Encinas-Viso, Francisco, Burdon, Jeremy J., Thrall, Peter H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585140/
https://www.ncbi.nlm.nih.gov/pubmed/26442074
http://dx.doi.org/10.3389/fpls.2015.00761
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author Barrett, Luke G.
Encinas-Viso, Francisco
Burdon, Jeremy J.
Thrall, Peter H.
author_facet Barrett, Luke G.
Encinas-Viso, Francisco
Burdon, Jeremy J.
Thrall, Peter H.
author_sort Barrett, Luke G.
collection PubMed
description Properties encompassed by host-pathogen interaction networks have potential to give valuable insight into the evolution of specialization and coevolutionary dynamics in host-pathogen interactions. However, network approaches have been rarely utilized in previous studies of host and pathogen phenotypic variation. Here we applied quantitative analyses to eight networks derived from spatially and temporally segregated host (Linum marginale) and pathogen (Melampsora lini) populations. First, we found that resistance strategies are highly variable within and among networks, corresponding to a spectrum of specialist and generalist resistance types being maintained within all networks. At the individual level, specialization was strongly linked to partial resistance, such that partial resistance was effective against a greater number of pathogens compared to full resistance. Second, we found that all networks were significantly nested. There was little support for the hypothesis that temporal evolutionary dynamics may lead to the development of nestedness in host-pathogen infection networks. Rather, the common patterns observed in terms of nestedness suggests a universal driver (or multiple drivers) that may be independent of spatial and temporal structure. Third, we found that resistance networks were significantly modular in two spatial networks, clearly reflecting spatial and ecological structure within one of the networks. We conclude that (1) overall patterns of specialization in the networks we studied mirror evolutionary trade-offs with the strength of resistance; (2) that specific network architecture can emerge under different evolutionary scenarios; and (3) network approaches offer great utility as a tool for probing the evolutionary and ecological genetics of host-pathogen interactions.
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spelling pubmed-45851402015-10-05 Specialization for resistance in wild host-pathogen interaction networks Barrett, Luke G. Encinas-Viso, Francisco Burdon, Jeremy J. Thrall, Peter H. Front Plant Sci Plant Science Properties encompassed by host-pathogen interaction networks have potential to give valuable insight into the evolution of specialization and coevolutionary dynamics in host-pathogen interactions. However, network approaches have been rarely utilized in previous studies of host and pathogen phenotypic variation. Here we applied quantitative analyses to eight networks derived from spatially and temporally segregated host (Linum marginale) and pathogen (Melampsora lini) populations. First, we found that resistance strategies are highly variable within and among networks, corresponding to a spectrum of specialist and generalist resistance types being maintained within all networks. At the individual level, specialization was strongly linked to partial resistance, such that partial resistance was effective against a greater number of pathogens compared to full resistance. Second, we found that all networks were significantly nested. There was little support for the hypothesis that temporal evolutionary dynamics may lead to the development of nestedness in host-pathogen infection networks. Rather, the common patterns observed in terms of nestedness suggests a universal driver (or multiple drivers) that may be independent of spatial and temporal structure. Third, we found that resistance networks were significantly modular in two spatial networks, clearly reflecting spatial and ecological structure within one of the networks. We conclude that (1) overall patterns of specialization in the networks we studied mirror evolutionary trade-offs with the strength of resistance; (2) that specific network architecture can emerge under different evolutionary scenarios; and (3) network approaches offer great utility as a tool for probing the evolutionary and ecological genetics of host-pathogen interactions. Frontiers Media S.A. 2015-09-23 /pmc/articles/PMC4585140/ /pubmed/26442074 http://dx.doi.org/10.3389/fpls.2015.00761 Text en Copyright © 2015 Barrett, Encinas-Viso, Burdon and Thrall. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Barrett, Luke G.
Encinas-Viso, Francisco
Burdon, Jeremy J.
Thrall, Peter H.
Specialization for resistance in wild host-pathogen interaction networks
title Specialization for resistance in wild host-pathogen interaction networks
title_full Specialization for resistance in wild host-pathogen interaction networks
title_fullStr Specialization for resistance in wild host-pathogen interaction networks
title_full_unstemmed Specialization for resistance in wild host-pathogen interaction networks
title_short Specialization for resistance in wild host-pathogen interaction networks
title_sort specialization for resistance in wild host-pathogen interaction networks
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585140/
https://www.ncbi.nlm.nih.gov/pubmed/26442074
http://dx.doi.org/10.3389/fpls.2015.00761
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