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
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 12 | 23% |
United Kingdom | 6 | 12% |
Australia | 5 | 10% |
Ireland | 3 | 6% |
Spain | 2 | 4% |
Italy | 2 | 4% |
France | 2 | 4% |
Netherlands | 1 | 2% |
Germany | 1 | 2% |
Other | 6 | 12% |
Unknown | 12 | 23% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 28 | 54% |
Members of the public | 23 | 44% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
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% |