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Specialization for resistance in wild host-pathogen interaction networks

Overview of attention for article published in Frontiers in Plant Science, September 2015
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Title
Specialization for resistance in wild host-pathogen interaction networks
Published in
Frontiers in Plant Science, September 2015
DOI 10.3389/fpls.2015.00761
Pubmed ID
Authors

Luke G. Barrett, Francisco Encinas-Viso, Jeremy J. Burdon, Peter H. Thrall

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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 3%
Czechia 1 3%
Argentina 1 3%
Brazil 1 3%
Unknown 28 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 31%
Student > Ph. D. Student 7 22%
Student > Master 3 9%
Lecturer 2 6%
Student > Doctoral Student 2 6%
Other 4 13%
Unknown 4 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 66%
Biochemistry, Genetics and Molecular Biology 4 13%
Environmental Science 1 3%
Engineering 1 3%
Unknown 5 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 September 2015.
All research outputs
#15,983,535
of 25,374,917 outputs
Outputs from Frontiers in Plant Science
#9,387
of 24,598 outputs
Outputs of similar age
#150,972
of 286,059 outputs
Outputs of similar age from Frontiers in Plant Science
#114
of 355 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,598 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 60% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 286,059 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 355 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.