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Specialization for resistance in wild host-pathogen interaction networks.

Barrett LG, Encinas-Viso F, Burdon JJ, Thrall PH - Front Plant Sci (2015)

Bottom Line: 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.Third, we found that resistance networks were significantly modular in two spatial networks, clearly reflecting spatial and ecological structure within one of the networks.

View Article: PubMed Central - PubMed

Affiliation: Commonwealth Scientific and Industrial Research Organization Agriculture Flagship Canberra, ACT, Australia.

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.

No MeSH data available.


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Frequency distribution of full and partial resistance specificities for individual host lines for all Linum-Melampsora networks (i.e. merged datasets). For example, a value of 0.5 for full resistance means that an individual host displays full resistance to 50% of pathogens to which it was exposed. This figure demonstrates that generalist hosts are more likely to express partial resistance.
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Figure 2: Frequency distribution of full and partial resistance specificities for individual host lines for all Linum-Melampsora networks (i.e. merged datasets). For example, a value of 0.5 for full resistance means that an individual host displays full resistance to 50% of pathogens to which it was exposed. This figure demonstrates that generalist hosts are more likely to express partial resistance.

Mentions: General properties of the host-pathogen networks are shown in Table 2. All networks were highly variable for resistance patterns among individual hosts, both for full and partial resistance types. Considering all resistance types, resistance networks were moderately connected but skewed toward full susceptibility (Table 2). For all eight networks, we observed a continuum of individual strategies with regards to the breadth of resistance (Figures 2–4), ranging from fully susceptible (i.e., no resistance) though to full or partial resistance to the large majority of pathogens in the network. In terms of pathogen infection (i.e., both partially resistant and fully susceptible hosts), individual hosts on average were susceptible to infection from a very high proportion of pathogens in the network (88–100%: Table 2).


Specialization for resistance in wild host-pathogen interaction networks.

Barrett LG, Encinas-Viso F, Burdon JJ, Thrall PH - Front Plant Sci (2015)

Frequency distribution of full and partial resistance specificities for individual host lines for all Linum-Melampsora networks (i.e. merged datasets). For example, a value of 0.5 for full resistance means that an individual host displays full resistance to 50% of pathogens to which it was exposed. This figure demonstrates that generalist hosts are more likely to express partial resistance.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4585140&req=5

Figure 2: Frequency distribution of full and partial resistance specificities for individual host lines for all Linum-Melampsora networks (i.e. merged datasets). For example, a value of 0.5 for full resistance means that an individual host displays full resistance to 50% of pathogens to which it was exposed. This figure demonstrates that generalist hosts are more likely to express partial resistance.
Mentions: General properties of the host-pathogen networks are shown in Table 2. All networks were highly variable for resistance patterns among individual hosts, both for full and partial resistance types. Considering all resistance types, resistance networks were moderately connected but skewed toward full susceptibility (Table 2). For all eight networks, we observed a continuum of individual strategies with regards to the breadth of resistance (Figures 2–4), ranging from fully susceptible (i.e., no resistance) though to full or partial resistance to the large majority of pathogens in the network. In terms of pathogen infection (i.e., both partially resistant and fully susceptible hosts), individual hosts on average were susceptible to infection from a very high proportion of pathogens in the network (88–100%: Table 2).

Bottom Line: 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.Third, we found that resistance networks were significantly modular in two spatial networks, clearly reflecting spatial and ecological structure within one of the networks.

View Article: PubMed Central - PubMed

Affiliation: Commonwealth Scientific and Industrial Research Organization Agriculture Flagship Canberra, ACT, Australia.

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.

No MeSH data available.


Related in: MedlinePlus