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Long non-coding RNAs display higher natural expression variation than protein-coding genes in healthy humans

Overview of attention for article published in Genome Biology (Online Edition), January 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)

Mentioned by

2 news outlets
1 blog
32 tweeters
1 Facebook page


100 Dimensions

Readers on

238 Mendeley
1 CiteULike
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Long non-coding RNAs display higher natural expression variation than protein-coding genes in healthy humans
Published in
Genome Biology (Online Edition), January 2016
DOI 10.1186/s13059-016-0873-8
Pubmed ID

Aleksandra E. Kornienko, Christoph P. Dotter, Philipp M. Guenzl, Heinz Gisslinger, Bettina Gisslinger, Ciara Cleary, Robert Kralovics, Florian M. Pauler, Denise P. Barlow


Long non-coding RNAs (lncRNAs) are increasingly implicated as gene regulators and may ultimately be more numerous than protein-coding genes in the human genome. Despite large numbers of reported lncRNAs, reference annotations are likely incomplete due to their lower and tighter tissue-specific expression compared to mRNAs. An unexplored factor potentially confounding lncRNA identification is inter-individual expression variability. Here, we characterize lncRNA natural expression variability in human primary granulocytes. We annotate granulocyte lncRNAs and mRNAs in RNA-seq data from 10 healthy individuals, identifying multiple lncRNAs absent from reference annotations, and use this to investigate three known features (higher tissue-specificity, lower expression, and reduced splicing efficiency) of lncRNAs relative to mRNAs. Expression variability was examined in seven individuals sampled three times at 1- or more than 1-month intervals. We show that lncRNAs display significantly more inter-individual expression variability compared to mRNAs. We confirm this finding in two independent human datasets by analyzing multiple tissues from the GTEx project and lymphoblastoid cell lines from the GEUVADIS project. Using the latter dataset we also show that including more human donors into the transcriptome annotation pipeline allows identification of an increasing number of lncRNAs, but minimally affects mRNA gene number. A comprehensive annotation of lncRNAs is known to require an approach that is sensitive to low and tight tissue-specific expression. Here we show that increased inter-individual expression variability is an additional general lncRNA feature to consider when creating a comprehensive annotation of human lncRNAs or proposing their use as prognostic or disease markers.

Twitter Demographics

The data shown below were collected from the profiles of 32 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 238 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
United Kingdom 2 <1%
Mexico 1 <1%
Finland 1 <1%
Chile 1 <1%
Sweden 1 <1%
Belgium 1 <1%
Russia 1 <1%
Spain 1 <1%
Other 2 <1%
Unknown 224 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 21%
Researcher 51 21%
Student > Postgraduate 37 16%
Student > Bachelor 19 8%
Student > Master 19 8%
Other 38 16%
Unknown 23 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 91 38%
Agricultural and Biological Sciences 77 32%
Medicine and Dentistry 13 5%
Computer Science 8 3%
Immunology and Microbiology 4 2%
Other 14 6%
Unknown 31 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 40. 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 23 October 2017.
All research outputs
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Outputs from Genome Biology (Online Edition)
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Outputs of similar age
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Outputs of similar age from Genome Biology (Online Edition)
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Altmetric has tracked 19,426,268 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,836 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.9. This one has done well, scoring higher than 84% of its peers.
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