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Method for the Identification of Taxon-Specific k-mers from Chloroplast Genome: A Case Study on Tomato Plant (Solanum lycopersicum)

Overview of attention for article published in Frontiers in Plant Science, January 2018
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Title
Method for the Identification of Taxon-Specific k-mers from Chloroplast Genome: A Case Study on Tomato Plant (Solanum lycopersicum)
Published in
Frontiers in Plant Science, January 2018
DOI 10.3389/fpls.2018.00006
Pubmed ID
Authors

Kairi Raime, Maido Remm

Abstract

Polymerase chain reaction and different barcoding methods commonly used for plant identification from metagenomics samples are based on the amplification of a limited number of pre-selected barcoding regions. These methods are often inapplicable due to DNA degradation, low amplification success or low species discriminative power of selected genomic regions. Here we introduce a method for the rapid identification of plant taxon-specific k-mers, that is applicable for the fast detection of plant taxa directly from raw sequencing reads without aligning, mapping or assembling the reads. We identified more than 800 Solanum lycopersicum specific k-mers (32 nucleotides in length) from 42 different chloroplast genome regions using the developed method. We demonstrated that identified k-mers are also detectable in whole genome sequencing raw reads from S. lycopersicum. Also, we demonstrated the usability of taxon-specific k-mers in artificial mixtures of sequences from closely related species. Developed method offers a novel strategy for fast identification of taxon-specific genome regions and offers new perspectives for detection of plant taxa directly from sequencing raw reads.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 24%
Student > Bachelor 7 19%
Student > Ph. D. Student 3 8%
Student > Postgraduate 3 8%
Student > Doctoral Student 1 3%
Other 4 11%
Unknown 10 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 32%
Biochemistry, Genetics and Molecular Biology 4 11%
Engineering 3 8%
Medicine and Dentistry 2 5%
Computer Science 1 3%
Other 3 8%
Unknown 12 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 February 2018.
All research outputs
#14,374,036
of 23,020,670 outputs
Outputs from Frontiers in Plant Science
#8,269
of 20,541 outputs
Outputs of similar age
#240,911
of 441,890 outputs
Outputs of similar age from Frontiers in Plant Science
#223
of 448 outputs
Altmetric has tracked 23,020,670 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,541 research outputs from this source. They receive a mean Attention Score of 4.0. This one has gotten more attention than average, scoring higher than 55% 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 441,890 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 448 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.