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Integrated decoys and effector traps: how to catch a plant pathogen

Overview of attention for article published in BMC Biology, February 2016
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Title
Integrated decoys and effector traps: how to catch a plant pathogen
Published in
BMC Biology, February 2016
DOI 10.1186/s12915-016-0235-8
Pubmed ID
Authors

Jeffrey G. Ellis

Abstract

Plant immune receptors involved in disease resistance and crop protection are related to the animal Nod-like receptor (NLR) class, and recognise the virulence effectors of plant pathogens, whereby they arm the plant's defensive response. Although plant NLRs mainly contain three protein domains, about 10 % of these receptors identified by extensive cross-plant species data base searches have now been shown to include novel and highly variable integrated domains, some of which have been shown to detect pathogen effectors by direct interaction. Sarris et al. have identified a large number of integrated domains that can be used to detect effector targets in host plant proteomes and identify unknown pathogen effectors.Please see related Research article: Comparative analysis of plant immune receptor architectures uncovers host proteins likely targeted by pathogens, http://dx.doi.org/10.1186/s12915-016-0228-7 Since the time of writing, a closely related paper has been released: Kroj T, Chanclud E, Michel-Romiti C, Grand X, Morel J-B. Integration of decoy domains derived from protein targets of pathogen effectors into plant immune receptors is widespread. New Phytol. 2016 (ahead of print).

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Mendeley readers

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
United States 1 1%
Denmark 1 1%
Brazil 1 1%
Unknown 90 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 30%
Researcher 17 18%
Student > Master 11 12%
Student > Bachelor 9 10%
Student > Postgraduate 7 7%
Other 15 16%
Unknown 7 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 61 65%
Biochemistry, Genetics and Molecular Biology 16 17%
Environmental Science 2 2%
Unspecified 1 1%
Nursing and Health Professions 1 1%
Other 3 3%
Unknown 10 11%