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Specialization for resistance in wild host-pathogen interaction networks

Identifieur interne : 000679 ( Pmc/Checkpoint ); précédent : 000678; suivant : 000680

Specialization for resistance in wild host-pathogen interaction networks

Auteurs : Luke G. Barrett [Australie] ; Francisco Encinas-Viso [Australie] ; Jeremy J. Burdon [Australie] ; Peter H. Thrall [Australie]

Source :

RBID : PMC:4585140

Abstract

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.


Url:
DOI: 10.3389/fpls.2015.00761
PubMed: 26442074
PubMed Central: 4585140


Affiliations:


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PMC:4585140

Le document en format XML

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<p>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 (
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<pmc article-type="research-article">
<pmc-dir>properties open_access</pmc-dir>
<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">Front Plant Sci</journal-id>
<journal-id journal-id-type="iso-abbrev">Front Plant Sci</journal-id>
<journal-id journal-id-type="publisher-id">Front. Plant Sci.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Plant Science</journal-title>
</journal-title-group>
<issn pub-type="epub">1664-462X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">26442074</article-id>
<article-id pub-id-type="pmc">4585140</article-id>
<article-id pub-id-type="doi">10.3389/fpls.2015.00761</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Plant Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Specialization for resistance in wild host-pathogen interaction networks</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Barrett</surname>
<given-names>Luke G.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:type="simple" xlink:href="http://loop.frontiersin.org/people/133318/overview"></uri>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Encinas-Viso</surname>
<given-names>Francisco</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:type="simple" xlink:href="http://loop.frontiersin.org/people/243590/overview"></uri>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Burdon</surname>
<given-names>Jeremy J.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Thrall</surname>
<given-names>Peter H.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:type="simple" xlink:href="http://loop.frontiersin.org/people/230842/overview"></uri>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Commonwealth Scientific and Industrial Research Organization Agriculture Flagship</institution>
<country>Canberra, ACT, Australia</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Centre for Australian National Biodiversity Research, Commonwealth Scientific and Industrial Research Organization</institution>
<country>Canberra, ACT, Australia</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Brigitte Mauch-Mani, Université de Neuchâtel, Switzerland</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: David Mackey, Ohio State University, USA; Yvonne Willi, University of Neuchâtel, Switzerland</p>
</fn>
<corresp id="fn001">*Correspondence: Luke G. Barrett, Commonwealth Scientific and Industrial Research Organization Agriculture Flagship, GPO Box 1600, Canberra ACT 2601, Australia
<email xlink:type="simple">luke.barrett@csiro.au</email>
</corresp>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Plant Biotic Interactions, a section of the journal Frontiers in Plant Science</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>23</day>
<month>9</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="collection">
<year>2015</year>
</pub-date>
<volume>6</volume>
<elocation-id>761</elocation-id>
<history>
<date date-type="received">
<day>04</day>
<month>5</month>
<year>2015</year>
</date>
<date date-type="accepted">
<day>04</day>
<month>9</month>
<year>2015</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright © 2015 Barrett, Encinas-Viso, Burdon and Thrall.</copyright-statement>
<copyright-year>2015</copyright-year>
<copyright-holder>Barrett, Encinas-Viso, Burdon and Thrall</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<license-p>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.</license-p>
</license>
</permissions>
<abstract>
<p>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 (
<italic>Linum marginale</italic>
) and pathogen (
<italic>Melampsora lini</italic>
) 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.</p>
</abstract>
<kwd-group>
<kwd>rust</kwd>
<kwd>virulence</kwd>
<kwd>avirulence</kwd>
<kwd>specialist</kwd>
<kwd>generalist</kwd>
<kwd>bipartite</kwd>
<kwd>temporal</kwd>
<kwd>spatial</kwd>
</kwd-group>
<counts>
<fig-count count="5"></fig-count>
<table-count count="6"></table-count>
<equation-count count="2"></equation-count>
<ref-count count="47"></ref-count>
<page-count count="13"></page-count>
<word-count count="10443"></word-count>
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</front>
</pmc>
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<list>
<country>
<li>Australie</li>
</country>
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<name sortKey="Barrett, Luke G" sort="Barrett, Luke G" uniqKey="Barrett L" first="Luke G." last="Barrett">Luke G. Barrett</name>
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<name sortKey="Burdon, Jeremy J" sort="Burdon, Jeremy J" uniqKey="Burdon J" first="Jeremy J." last="Burdon">Jeremy J. Burdon</name>
<name sortKey="Encinas Viso, Francisco" sort="Encinas Viso, Francisco" uniqKey="Encinas Viso F" first="Francisco" last="Encinas-Viso">Francisco Encinas-Viso</name>
<name sortKey="Thrall, Peter H" sort="Thrall, Peter H" uniqKey="Thrall P" first="Peter H." last="Thrall">Peter H. Thrall</name>
</country>
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</record>

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