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Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution

Overview of attention for article published in Frontiers in Plant Science, February 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

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328 Mendeley
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Title
Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution
Published in
Frontiers in Plant Science, February 2017
DOI 10.3389/fpls.2017.00119
Pubmed ID
Authors

Clémence Plissonneau, Juliana Benevenuto, Norfarhan Mohd-Assaad, Simone Fouché, Fanny E. Hartmann, Daniel Croll

Abstract

Epidemics caused by fungal plant pathogens pose a major threat to agro-ecosystems and impact global food security. High-throughput sequencing enabled major advances in understanding how pathogens cause disease on crops. Hundreds of fungal genomes are now available and analyzing these genomes highlighted the key role of effector genes in disease. Effectors are small secreted proteins that enhance infection by manipulating host metabolism. Fungal genomes carry 100s of putative effector genes, but the lack of homology among effector genes, even for closely related species, challenges evolutionary and functional analyses. Furthermore, effector genes are often found in rapidly evolving chromosome compartments which are difficult to assemble. We review how population and comparative genomics toolsets can be combined to address these challenges. We highlight studies that associated genome-scale polymorphisms with pathogen lifestyles and adaptation to different environments. We show how genome-wide association studies can be used to identify effectors and other pathogenicity-related genes underlying rapid adaptation. We also discuss how the compartmentalization of fungal genomes into core and accessory regions shapes the evolution of effector genes. We argue that an understanding of genome evolution provides important insight into the trajectory of host-pathogen co-evolution.

X Demographics

X Demographics

The data shown below were collected from the profiles of 41 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 328 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 <1%
Sweden 1 <1%
Unknown 325 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 78 24%
Researcher 61 19%
Student > Master 40 12%
Student > Bachelor 39 12%
Student > Doctoral Student 17 5%
Other 31 9%
Unknown 62 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 167 51%
Biochemistry, Genetics and Molecular Biology 63 19%
Computer Science 4 1%
Immunology and Microbiology 4 1%
Environmental Science 4 1%
Other 14 4%
Unknown 72 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 30. 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 18 January 2019.
All research outputs
#1,327,007
of 25,452,734 outputs
Outputs from Frontiers in Plant Science
#398
of 24,695 outputs
Outputs of similar age
#28,033
of 425,402 outputs
Outputs of similar age from Frontiers in Plant Science
#7
of 501 outputs
Altmetric has tracked 25,452,734 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 24,695 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 98% 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 425,402 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 501 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.