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De Novo Assembly of Complete Chloroplast Genomes from Non-model Species Based on a K-mer Frequency-Based Selection of Chloroplast Reads from Total DNA Sequences

Overview of attention for article published in Frontiers in Plant Science, August 2017
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Title
De Novo Assembly of Complete Chloroplast Genomes from Non-model Species Based on a K-mer Frequency-Based Selection of Chloroplast Reads from Total DNA Sequences
Published in
Frontiers in Plant Science, August 2017
DOI 10.3389/fpls.2017.01271
Pubmed ID
Authors

Shairul Izan, Danny Esselink, Richard G. F. Visser, Marinus J. M. Smulders, Theo Borm

Abstract

Whole Genome Shotgun (WGS) sequences of plant species often contain an abundance of reads that are derived from the chloroplast genome. Up to now these reads have generally been identified and assembled into chloroplast genomes based on homology to chloroplasts from related species. This re-sequencing approach may select against structural differences between the genomes especially in non-model species for which no close relatives have been sequenced before. The alternative approach is to de novo assemble the chloroplast genome from total genomic DNA sequences. In this study, we used k-mer frequency tables to identify and extract the chloroplast reads from the WGS reads and assemble these using a highly integrated and automated custom pipeline. Our strategy includes steps aimed at optimizing assemblies and filling gaps which are left due to coverage variation in the WGS dataset. We have successfully de novo assembled three complete chloroplast genomes from plant species with a range of nuclear genome sizes to demonstrate the universality of our approach: Solanum lycopersicum (0.9 Gb), Aegilops tauschii (4 Gb) and Paphiopedilum henryanum (25 Gb). We also highlight the need to optimize the choice of k and the amount of data used. This new and cost-effective method for de novo short read assembly will facilitate the study of complete chloroplast genomes with more accurate analyses and inferences, especially in non-model plant genomes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 104 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 14%
Researcher 15 14%
Student > Bachelor 6 6%
Student > Master 6 6%
Student > Postgraduate 5 5%
Other 10 10%
Unknown 47 45%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 24%
Biochemistry, Genetics and Molecular Biology 16 15%
Environmental Science 5 5%
Computer Science 3 3%
Psychology 2 2%
Other 4 4%
Unknown 49 47%
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 10 September 2017.
All research outputs
#18,571,001
of 23,001,641 outputs
Outputs from Frontiers in Plant Science
#13,962
of 20,492 outputs
Outputs of similar age
#243,197
of 317,609 outputs
Outputs of similar age from Frontiers in Plant Science
#402
of 504 outputs
Altmetric has tracked 23,001,641 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,492 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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We're also able to compare this research output to 504 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.