Evaluation of copy number variants for genetic hearing loss: a review of current approaches and recent findings
Autor: | Shira Rockowitz, Courtney E. French, A. Eliot Shearer, Margaret A. Kenna, Wafaa Abbasi |
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Rok vydání: | 2021 |
Předmět: |
congenital
hereditary and neonatal diseases and abnormalities endocrine system diseases Hearing loss Computational biology Biology Genome Human genetics Structural variation mental disorders otorhinolaryngologic diseases Genetics medicine Copy-number variation Multiplex ligation-dependent probe amplification medicine.symptom Exome Genetics (clinical) STRC |
Zdroj: | Human Genetics. 141:387-400 |
ISSN: | 1432-1203 0340-6717 |
DOI: | 10.1007/s00439-021-02365-1 |
Popis: | Structural variation includes a change in copy number, orientation, or location of a part of the genome. Copy number variants (CNVs) are a common cause of genetic hearing loss, comprising nearly 20% of diagnosed cases. While large deletions involving the gene STRC are the most common pathogenic CNVs, a significant proportion of known hearing loss genes also contain pathogenic CNVs. In this review, we provide an overview of currently used methods for detection of CNVs in genes known to cause hearing loss including molecular techniques such as multiplex ligation probe amplification (MLPA) and digital droplet polymerase chain reaction (ddPCR), array-CGH and single-nucleotide polymorphism (SNP) arrays, as well as techniques for detection of CNVs using next-generation sequencing data analysis including targeted gene panel, exome, and genome sequencing data. In addition, in this review, we compile published data on pathogenic hearing loss CNVs to provide an up-to-date overview. We show that CNVs have been identified in 29 different non-syndromic hearing loss genes. An understanding of the contribution of CNVs to genetic hearing loss is critical to the current diagnosis of hearing loss and is crucial for future gene therapies. Thus, evaluation for CNVs is required in any modern pipeline for genetic diagnosis of hearing loss. |
Databáze: | OpenAIRE |
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