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Prediction of Leymus arenarius (L.) antimicrobial peptides based on de novo transcriptome assembly

Overview of attention for article published in Plant Molecular Biology, September 2015
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

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1 X user
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1 Wikipedia page

Citations

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19 Dimensions

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30 Mendeley
Title
Prediction of Leymus arenarius (L.) antimicrobial peptides based on de novo transcriptome assembly
Published in
Plant Molecular Biology, September 2015
DOI 10.1007/s11103-015-0346-6
Pubmed ID
Authors

Anna A. Slavokhotova, Andrey A. Shelenkov, Tatyana I. Odintsova

Abstract

Leymus arenarius is a unique wild growing Poaceae plant exhibiting extreme tolerance to environmental conditions. In this study we for the first time performed whole-transcriptome sequencing of lymegrass seedlings using Illumina platform followed by de novo transcriptome assembly and functional annotation. Our goal was to identify transcripts encoding antimicrobial peptides (AMPs), one of the key components of plant innate immunity. Using the custom software developed for this study that predicted AMPs and classified them into families, we revealed more than 160 putative AMPs in lymegrass seedlings. We classified them into 7 families based on their cysteine motifs and sequence similarity. The families included defensins, thionins, hevein-like peptides, snakins, cyclotide, alfa-hairpinins and LTPs. This is the first communication about the presence of almost all known AMP families in trascriptomic data of a single plant species. Additionally, cysteine-rich peptides that potentially represent novel families of AMPs were revealed. We have confirmed by RT-PCR validation the presence of 30 transcripts encoding selected AMPs in lymegrass seedlings. In summary, the presented method of pAMP prediction developed by us can be applied for relatively fast and simple screening of novel components of plant immunity system and is well suited for whole-transcriptome or genome analysis of uncharacterized plants.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 20%
Researcher 5 17%
Student > Master 4 13%
Student > Doctoral Student 3 10%
Professor 2 7%
Other 6 20%
Unknown 4 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 43%
Biochemistry, Genetics and Molecular Biology 5 17%
Computer Science 2 7%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Immunology and Microbiology 1 3%
Other 3 10%
Unknown 5 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 14 December 2015.
All research outputs
#7,222,780
of 22,828,180 outputs
Outputs from Plant Molecular Biology
#953
of 2,846 outputs
Outputs of similar age
#86,835
of 268,600 outputs
Outputs of similar age from Plant Molecular Biology
#6
of 38 outputs
Altmetric has tracked 22,828,180 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 2,846 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 65% 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 268,600 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.