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Candidate gene based association mapping in Fusarium culmorum for field quantitative pathogenicity and mycotoxin production in wheat

Overview of attention for article published in BMC Genomic Data, May 2017
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Title
Candidate gene based association mapping in Fusarium culmorum for field quantitative pathogenicity and mycotoxin production in wheat
Published in
BMC Genomic Data, May 2017
DOI 10.1186/s12863-017-0511-9
Pubmed ID
Authors

Valheria Castiblanco, Jose J. Marulanda, Tobias Würschum, Thomas Miedaner

Abstract

Quantitative traits are common in nature, but quantitative pathogenicity has received only little attention in phytopathology. In this study, we used 100 Fusarium culmorum isolates collected from natural field environments to assess their variation for two quantitative traits, aggressiveness and deoxynivalenol (DON) production on wheat plants grown in four different field environments (location-year combinations). Seventeen Fusarium graminearum pathogenicity candidate genes were assessed for their effect on the aggressiveness and DON production of F. culmorum under field conditions. For both traits, genotypic variance among isolates was high and significant while the isolate-by-environment interaction was also significant, amounting to approximately half of the genotypic variance. Among the studied candidate genes, the mitogen-activated protein kinase (MAPK) HOG1 was found to be significantly associated with aggressiveness and deoxynivalenol (DON) production, explaining 10.29 and 6.05% of the genotypic variance, respectively. To the best of our knowledge, this is the first report of a protein kinase regulator explaining differences in field aggressiveness and mycotoxin production among individuals from natural populations of a plant pathogen.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 1 3%
Unknown 39 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 25%
Student > Master 6 15%
Researcher 4 10%
Student > Bachelor 3 8%
Student > Postgraduate 3 8%
Other 5 13%
Unknown 9 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 53%
Biochemistry, Genetics and Molecular Biology 5 13%
Unspecified 1 3%
Nursing and Health Professions 1 3%
Materials Science 1 3%
Other 0 0%
Unknown 11 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 07 October 2017.
All research outputs
#20,660,571
of 25,382,440 outputs
Outputs from BMC Genomic Data
#861
of 1,204 outputs
Outputs of similar age
#251,074
of 326,293 outputs
Outputs of similar age from BMC Genomic Data
#15
of 27 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.