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The application of RNA-seq to the comprehensive analysis of plant mitochondrial transcriptomes

Overview of attention for article published in Molecular Genetics and Genomics, September 2014
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  • High Attention Score compared to outputs of the same age and source (89th percentile)

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1 blog

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49 Mendeley
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Title
The application of RNA-seq to the comprehensive analysis of plant mitochondrial transcriptomes
Published in
Molecular Genetics and Genomics, September 2014
DOI 10.1007/s00438-014-0905-6
Pubmed ID
Authors

James D. Stone, Helena Storchova

Abstract

We review current studies of plant mitochondrial transcriptomes performed by RNA-seq, highlighting methodological challenges unique to plant mitochondria. We propose ways to improve read mapping accuracy and sensitivity such as modifying a reference genome at RNA editing sites, using splicing- and ambiguity-competent aligners, and masking chloroplast- or nucleus-derived sequences. We also outline modified RNA-seq methods permitting more accurate detection and quantification of partially edited sites and the identification of transcription start sites on a genome-wide scale. The application of RNA-seq goes beyond genome-wide determination of transcript levels and RNA maturation events, and emerges as an elegant resource for the comprehensive identification of editing, splicing, and transcription start sites. Thus, improved RNA-seq methods customized for plant mitochondria hold tremendous potential for advancing our understanding of plant mitochondrial evolution and cyto-nuclear interactions in a broad array of plant species.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Uruguay 1 2%
Italy 1 2%
Germany 1 2%
Unknown 45 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 29%
Student > Ph. D. Student 11 22%
Student > Master 7 14%
Student > Doctoral Student 2 4%
Professor 2 4%
Other 8 16%
Unknown 5 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 51%
Biochemistry, Genetics and Molecular Biology 11 22%
Medicine and Dentistry 2 4%
Engineering 2 4%
Nursing and Health Professions 1 2%
Other 3 6%
Unknown 5 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 08 September 2014.
All research outputs
#6,595,315
of 25,373,627 outputs
Outputs from Molecular Genetics and Genomics
#810
of 3,318 outputs
Outputs of similar age
#60,562
of 249,189 outputs
Outputs of similar age from Molecular Genetics and Genomics
#3
of 29 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 3,318 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 75% 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 249,189 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 75% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.