Title |
Deep intronic mutations and human disease
|
---|---|
Published in |
Human Genetics, May 2017
|
DOI | 10.1007/s00439-017-1809-4 |
Pubmed ID | |
Authors |
Rita Vaz-Drago, Noélia Custódio, Maria Carmo-Fonseca |
Abstract |
Next-generation sequencing has revolutionized clinical diagnostic testing. Yet, for a substantial proportion of patients, sequence information restricted to exons and exon-intron boundaries fails to identify the genetic cause of the disease. Here we review evidence from mRNA analysis and entire genomic sequencing indicating that pathogenic mutations can occur deep within the introns of over 75 disease-associated genes. Deleterious DNA variants located more than 100 base pairs away from exon-intron junctions most commonly lead to pseudo-exon inclusion due to activation of non-canonical splice sites or changes in splicing regulatory elements. Additionally, deep intronic mutations can disrupt transcription regulatory motifs and non-coding RNA genes. This review aims to highlight the importance of studying variation in deep intronic sequence as a cause of monogenic disorders as well as hereditary cancer syndromes. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 2 | 20% |
France | 2 | 20% |
Saudi Arabia | 1 | 10% |
Australia | 1 | 10% |
Unknown | 4 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 6 | 60% |
Members of the public | 3 | 30% |
Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 429 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 66 | 15% |
Student > Master | 64 | 15% |
Researcher | 54 | 13% |
Student > Bachelor | 52 | 12% |
Student > Doctoral Student | 25 | 6% |
Other | 56 | 13% |
Unknown | 112 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 150 | 35% |
Medicine and Dentistry | 67 | 16% |
Agricultural and Biological Sciences | 48 | 11% |
Neuroscience | 9 | 2% |
Computer Science | 6 | 1% |
Other | 24 | 6% |
Unknown | 125 | 29% |