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Assisted transcriptome reconstruction and splicing orthology

Overview of attention for article published in BMC Genomics, November 2016
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Title
Assisted transcriptome reconstruction and splicing orthology
Published in
BMC Genomics, November 2016
DOI 10.1186/s12864-016-3103-6
Pubmed ID
Authors

Samuel Blanquart, Jean-Stéphane Varré, Paul Guertin, Amandine Perrin, Anne Bergeron, Krister M. Swenson

Abstract

Transcriptome reconstruction, defined as the identification of all protein isoforms that may be expressed by a gene, is a notably difficult computational task. With real data, the best methods based on RNA-seq data identify barely 21 % of the expressed transcripts. While waiting for algorithms and sequencing techniques to improve - as has been strongly suggested in the literature - it is important to evaluate assisted transcriptome prediction; this is the question of how alternative transcription in one species performs as a predictor of protein isoforms in another relatively close species. Most evidence-based gene predictors use transcripts from other species to annotate a genome, but the predictive power of procedures that use exclusively transcripts from external species has never been quantified. The cornerstone of such an evaluation is the correct identification of pairs of transcripts with the same splicing patterns, called splicing orthologs. We propose a rigorous procedural definition of splicing orthologs, based on the identification of all ortholog pairs of splicing sites in the nucleotide sequences, and alignments at the protein level. Using our definition, we compared 24 382 human transcripts and 17 909 mouse transcripts from the highly curated CCDS database, and identified 11 122 splicing orthologs. In prediction mode, we show that human transcripts can be used to infer over 62 % of mouse protein isoforms. When restricting the predictions to transcripts known eight years ago, the percentage grows to 74 %. Using CCDS timestamped releases, we also analyze the evolution of the number of splicing orthologs over the last decade. Alternative splicing is now recognized to play a major role in the protein diversity of eukaryotic organisms, but definitions of spliced isoform orthologs are still approximate. Here we propose a definition adapted to the subtle variations of conserved alternative splicing sites, and use it to validate numerous accurate orthologous isoform predictions.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 5%
Unknown 18 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 32%
Student > Master 5 26%
Student > Ph. D. Student 4 21%
Student > Bachelor 2 11%
Professor > Associate Professor 1 5%
Other 0 0%
Unknown 1 5%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 42%
Agricultural and Biological Sciences 6 32%
Computer Science 2 11%
Environmental Science 1 5%
Unknown 2 11%

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 12 February 2017.
All research outputs
#11,238,537
of 17,363,630 outputs
Outputs from BMC Genomics
#5,741
of 9,281 outputs
Outputs of similar age
#174,443
of 296,482 outputs
Outputs of similar age from BMC Genomics
#563
of 875 outputs
Altmetric has tracked 17,363,630 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,281 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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 296,482 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 875 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.