Title |
Identification of Copy Number Variants Through Whole-Exome Sequencing in Autosomal Recessive Nonsyndromic Hearing Loss
|
---|---|
Published in |
Genetic Testing, July 2014
|
DOI | 10.1089/gtmb.2014.0121 |
Pubmed ID | |
Authors |
Guney Bademci, Oscar Diaz-Horta, Shengru Guo, Duygu Duman, Derek Van Booven, Joseph Foster, Filiz Basak Cengiz, Susan Blanton, Mustafa Tekin |
Abstract |
Genetic variants account for more than half of the cases with congenital or prelingual onset hearing loss. Autosomal recessive nonsyndromic hearing loss (ARNSHL) is the most common subgroup. Whole-exome sequencing (WES) has been shown to be effective detecting deafness-causing single-nucleotide variants (SNVs) and insertion/deletions (INDELs). After analyzing the WES data for causative SNVs or INDELs involving previously reported deafness genes in 78 families with ARNSHL, we searched for copy number variants (CNVs) through two different tools in 24 families that remained unresolved. We detected large homozygous deletions in STRC and OTOA in single families. Thus, causative CNVs in known deafness genes explain 2 out of 78 (2.6%) families in our sample set. We conclude that CNVs can be reliably detected through WES and should be the part of pipelines used to clarify genetic basis of hearing loss. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Mexico | 1 | 2% |
Belgium | 1 | 2% |
Unknown | 39 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 10 | 24% |
Researcher | 9 | 22% |
Student > Ph. D. Student | 5 | 12% |
Student > Bachelor | 4 | 10% |
Professor | 2 | 5% |
Other | 5 | 12% |
Unknown | 6 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 11 | 27% |
Agricultural and Biological Sciences | 8 | 20% |
Medicine and Dentistry | 8 | 20% |
Computer Science | 2 | 5% |
Chemistry | 2 | 5% |
Other | 2 | 5% |
Unknown | 8 | 20% |