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Genetic diagnosis of Mendelian disorders via RNA sequencing

Overview of attention for article published in Nature Communications, June 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
18 news outlets
blogs
2 blogs
twitter
52 X users
facebook
3 Facebook pages
wikipedia
1 Wikipedia page

Citations

dimensions_citation
447 Dimensions

Readers on

mendeley
523 Mendeley
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Title
Genetic diagnosis of Mendelian disorders via RNA sequencing
Published in
Nature Communications, June 2017
DOI 10.1038/ncomms15824
Pubmed ID
Authors

Laura S. Kremer, Daniel M. Bader, Christian Mertes, Robert Kopajtich, Garwin Pichler, Arcangela Iuso, Tobias B. Haack, Elisabeth Graf, Thomas Schwarzmayr, Caterina Terrile, Eliška Koňaříková, Birgit Repp, Gabi Kastenmüller, Jerzy Adamski, Peter Lichtner, Christoph Leonhardt, Benoit Funalot, Alice Donati, Valeria Tiranti, Anne Lombes, Claude Jardel, Dieter Gläser, Robert W. Taylor, Daniele Ghezzi, Johannes A. Mayr, Agnes Rötig, Peter Freisinger, Felix Distelmaier, Tim M. Strom, Thomas Meitinger, Julien Gagneur, Holger Prokisch

Abstract

Across a variety of Mendelian disorders, ∼50-75% of patients do not receive a genetic diagnosis by exome sequencing indicating disease-causing variants in non-coding regions. Although genome sequencing in principle reveals all genetic variants, their sizeable number and poorer annotation make prioritization challenging. Here, we demonstrate the power of transcriptome sequencing to molecularly diagnose 10% (5 of 48) of mitochondriopathy patients and identify candidate genes for the remainder. We find a median of one aberrantly expressed gene, five aberrant splicing events and six mono-allelically expressed rare variants in patient-derived fibroblasts and establish disease-causing roles for each kind. Private exons often arise from cryptic splice sites providing an important clue for variant prioritization. One such event is found in the complex I assembly factor TIMMDC1 establishing a novel disease-associated gene. In conclusion, our study expands the diagnostic tools for detecting non-exonic variants and provides examples of intronic loss-of-function variants with pathological relevance.

X Demographics

X Demographics

The data shown below were collected from the profiles of 52 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 523 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 <1%
Finland 1 <1%
United Kingdom 1 <1%
Russia 1 <1%
United States 1 <1%
Unknown 518 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 105 20%
Researcher 94 18%
Student > Master 68 13%
Student > Bachelor 43 8%
Student > Postgraduate 24 5%
Other 78 15%
Unknown 111 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 172 33%
Agricultural and Biological Sciences 83 16%
Medicine and Dentistry 68 13%
Computer Science 19 4%
Neuroscience 15 3%
Other 41 8%
Unknown 125 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 166. 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 January 2023.
All research outputs
#248,345
of 25,837,817 outputs
Outputs from Nature Communications
#3,598
of 58,118 outputs
Outputs of similar age
#5,226
of 334,376 outputs
Outputs of similar age from Nature Communications
#88
of 1,112 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 58,118 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.5. This one has done particularly well, scoring higher than 93% 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 334,376 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 1,112 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.