Title |
Genome analyses of the wheat yellow (stripe) rust pathogen Puccinia striiformis f. sp. triticireveal polymorphic and haustorial expressed secreted proteins as candidate effectors
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Published in |
BMC Genomics, April 2013
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DOI | 10.1186/1471-2164-14-270 |
Pubmed ID | |
Authors |
Dario Cantu, Vanesa Segovia, Daniel MacLean, Rosemary Bayles, Xianming Chen, Sophien Kamoun, Jorge Dubcovsky, Diane GO Saunders, Cristobal Uauy |
Abstract |
Wheat yellow (stripe) rust caused by Puccinia striiformis f. sp. tritici (PST) is one of the most devastating diseases of wheat worldwide. To design effective breeding strategies that maximize the potential for durable disease resistance it is important to understand the molecular basis of PST pathogenicity. In particular, the characterisation of the structure, function and evolutionary dynamics of secreted effector proteins that are detected by host immune receptors can help guide and prioritize breeding efforts. However, to date, our knowledge of the effector repertoire of cereal rust pathogens is limited. |
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Geographical breakdown
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United States | 5 | 21% |
Netherlands | 1 | 4% |
France | 1 | 4% |
Unknown | 10 | 42% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 11 | 46% |
Scientists | 11 | 46% |
Practitioners (doctors, other healthcare professionals) | 1 | 4% |
Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 3 | 1% |
United Kingdom | 3 | 1% |
Mexico | 2 | <1% |
Turkey | 1 | <1% |
Uruguay | 1 | <1% |
Australia | 1 | <1% |
Brazil | 1 | <1% |
Netherlands | 1 | <1% |
France | 1 | <1% |
Other | 3 | 1% |
Unknown | 256 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 73 | 27% |
Researcher | 57 | 21% |
Student > Master | 31 | 11% |
Student > Bachelor | 17 | 6% |
Student > Doctoral Student | 14 | 5% |
Other | 41 | 15% |
Unknown | 40 | 15% |
Readers by discipline | Count | As % |
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Engineering | 4 | 1% |
Computer Science | 3 | 1% |
Business, Management and Accounting | 1 | <1% |
Other | 7 | 3% |
Unknown | 42 | 15% |