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Genome analyses of the sunflower pathogen Plasmopara halstedii provide insights into effector evolution in downy mildews and Phytophthora

Overview of attention for article published in BMC Genomics, October 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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Title
Genome analyses of the sunflower pathogen Plasmopara halstedii provide insights into effector evolution in downy mildews and Phytophthora
Published in
BMC Genomics, October 2015
DOI 10.1186/s12864-015-1904-7
Pubmed ID
Authors

Rahul Sharma, Xiaojuan Xia, Liliana M. Cano, Edouard Evangelisti, Eric Kemen, Howard Judelson, Stan Oome, Christine Sambles, D. Johan van den Hoogen, Miloslav Kitner, Joël Klein, Harold J. G. Meijer, Otmar Spring, Joe Win, Reinhard Zipper, Helge B. Bode, Francine Govers, Sophien Kamoun, Sebastian Schornack, David J. Studholme, Guido Van den Ackerveken, Marco Thines

Abstract

Downy mildews are the most speciose group of oomycetes and affect crops of great economic importance. So far, there is only a single deeply-sequenced downy mildew genome available, from Hyaloperonospora arabidopsidis. Further genomic resources for downy mildews are required to study their evolution, including pathogenicity effector proteins, such as RxLR effectors. Plasmopara halstedii is a devastating pathogen of sunflower and a potential pathosystem model to study downy mildews, as several Avr-genes and R-genes have been predicted and unlike Arabidopsis downy mildew, large quantities of almost contamination-free material can be obtained easily. Here a high-quality draft genome of Plasmopara halstedii is reported and analysed with respect to various aspects, including genome organisation, secondary metabolism, effector proteins and comparative genomics with other sequenced oomycetes. Interestingly, the present analyses revealed further variation of the RxLR motif, suggesting an important role of the conservation of the dEER-motif. Orthology analyses revealed the conservation of 28 RxLR-like core effectors among Phytophthora species. Only six putative RxLR-like effectors were shared by the two sequenced downy mildews, highlighting the fast and largely independent evolution of two of the three major downy mildew lineages. This is seemingly supported by phylogenomic results, in which downy mildews did not appear to be monophyletic. The genome resource will be useful for developing markers for monitoring the pathogen population and might provide the basis for new approaches to fight Phytophthora and downy mildew pathogens by targeting core pathogenicity effectors.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 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 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Czechia 1 <1%
Unknown 113 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 25%
Student > Ph. D. Student 21 18%
Student > Master 13 11%
Student > Bachelor 8 7%
Student > Doctoral Student 6 5%
Other 19 17%
Unknown 19 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 66 57%
Biochemistry, Genetics and Molecular Biology 19 17%
Engineering 4 3%
Computer Science 2 2%
Economics, Econometrics and Finance 1 <1%
Other 2 2%
Unknown 21 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 22 October 2015.
All research outputs
#4,128,194
of 23,498,099 outputs
Outputs from BMC Genomics
#1,643
of 10,787 outputs
Outputs of similar age
#54,183
of 278,940 outputs
Outputs of similar age from BMC Genomics
#46
of 361 outputs
Altmetric has tracked 23,498,099 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,787 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 84% 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 278,940 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 80% of its contemporaries.
We're also able to compare this research output to 361 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.