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Comparative genome analysis and genome evolution of members of the magnaporthaceae family of fungi

Overview of attention for article published in BMC Genomics, February 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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13 X users

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Title
Comparative genome analysis and genome evolution of members of the magnaporthaceae family of fungi
Published in
BMC Genomics, February 2016
DOI 10.1186/s12864-016-2491-y
Pubmed ID
Authors

Laura H. Okagaki, Joshua K. Sailsbery, Alexander W. Eyre, Ralph A. Dean

Abstract

Magnaporthaceae, a family of ascomycetes, includes three fungi of great economic importance that cause disease in cereal and turf grasses: Magnaporthe oryzae (rice blast), Gaeumannomyces graminis var. tritici (take-all disease), and Magnaporthe poae (summer patch disease). Recently, the sequenced and assembled genomes for these three fungi were reported. Here, the genomes were compared for orthologous genes in order to identified genes that are unique to the Magnaporthaceae family of fungi. In addition, ortholog clustering was used to identify a core proteome for the Magnaporthaceae, which was examined for diversifying and purifying selection and evidence of two-speed genome evolution. A genome-scale comparative study was conducted across 74 fungal genomes to identify clusters of orthologous genes unique to the three Magnaporthaceae species as well as species specific genes. We found 1149 clusters that were unique to the Magnaporthaceae family of fungi with 295 of those containing genes from all three species. Gene clusters involved in metabolic and enzymatic activities were highly represented in the Magnaporthaceae specific clusters. Also highly represented in the Magnaporthaceae specific clusters as well as in the species specific genes were transcriptional regulators. In addition, we examined the relationship between gene evolution and distance to repetitive elements found in the genome. No correlations between diversifying or purifying selection and distance to repetitive elements or an increased rate of evolution in secreted and small secreted proteins were observed. Taken together, these data show that at the genome level, there is no evidence to suggest multi-speed genome evolution or that proximity to repetitive elements play a role in diversification of genes.

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X Demographics

The data shown below were collected from the profiles of 13 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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 1%
Germany 1 1%
Australia 1 1%
Unknown 66 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 23%
Researcher 14 20%
Student > Master 9 13%
Student > Doctoral Student 4 6%
Professor 3 4%
Other 11 16%
Unknown 12 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 55%
Biochemistry, Genetics and Molecular Biology 11 16%
Arts and Humanities 2 3%
Unspecified 1 1%
Veterinary Science and Veterinary Medicine 1 1%
Other 3 4%
Unknown 13 19%
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 09 March 2016.
All research outputs
#4,551,774
of 24,417,958 outputs
Outputs from BMC Genomics
#1,797
of 10,976 outputs
Outputs of similar age
#65,959
of 303,380 outputs
Outputs of similar age from BMC Genomics
#48
of 234 outputs
Altmetric has tracked 24,417,958 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,976 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 83% 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 303,380 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 78% of its contemporaries.
We're also able to compare this research output to 234 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.