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Diversifying selection in the wheat stem rust fungus acts predominantly on pathogen-associated gene families and reveals candidate effectors

Overview of attention for article published in Frontiers in Plant Science, September 2014
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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Title
Diversifying selection in the wheat stem rust fungus acts predominantly on pathogen-associated gene families and reveals candidate effectors
Published in
Frontiers in Plant Science, September 2014
DOI 10.3389/fpls.2014.00372
Pubmed ID
Authors

Jana Sperschneider, Hua Ying, Peter N. Dodds, Donald M. Gardiner, Narayana M. Upadhyaya, Karam B. Singh, John M. Manners, Jennifer M. Taylor

Abstract

Plant pathogens cause severe losses to crop plants and threaten global food production. One striking example is the wheat stem rust fungus, Puccinia graminis f. sp. tritici, which can rapidly evolve new virulent pathotypes in response to resistant host lines. Like several other filamentous fungal and oomycete plant pathogens, its genome features expanded gene families that have been implicated in host-pathogen interactions, possibly encoding effector proteins that interact directly with target host defense proteins. Previous efforts to understand virulence largely relied on the prediction of secreted, small and cysteine-rich proteins as candidate effectors and thus delivered an overwhelming number of candidates. Here, we implement an alternative analysis strategy that uses the signal of adaptive evolution as a line of evidence for effector function, combined with comparative information and expression data. We demonstrate that in planta up-regulated genes that are rapidly evolving are found almost exclusively in pathogen-associated gene families, affirming the impact of host-pathogen co-evolution on genome structure and the adaptive diversification of specialized gene families. In particular, we predict 42 effector candidates that are conserved only across pathogens, induced during infection and rapidly evolving. One of our top candidates has recently been shown to induce genotype-specific hypersensitive cell death in wheat. This shows that comparative genomics incorporating the evolutionary signal of adaptation is powerful for predicting effector candidates for laboratory verification. Our system can be applied to a wide range of pathogens and will give insight into host-pathogen dynamics, ultimately leading to progress in strategies for disease control.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Netherlands 2 2%
Germany 1 1%
Brazil 1 1%
France 1 1%
Unknown 90 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 26%
Researcher 21 21%
Student > Bachelor 11 11%
Student > Master 10 10%
Professor > Associate Professor 6 6%
Other 15 15%
Unknown 10 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 63 64%
Biochemistry, Genetics and Molecular Biology 17 17%
Economics, Econometrics and Finance 1 1%
Social Sciences 1 1%
Medicine and Dentistry 1 1%
Other 0 0%
Unknown 15 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 17 July 2016.
All research outputs
#5,752,391
of 23,305,591 outputs
Outputs from Frontiers in Plant Science
#2,937
of 21,131 outputs
Outputs of similar age
#54,997
of 238,486 outputs
Outputs of similar age from Frontiers in Plant Science
#22
of 168 outputs
Altmetric has tracked 23,305,591 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 21,131 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 85% 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 238,486 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 168 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.