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Challenges in Whole Exome Sequencing: An Example from Hereditary Deafness

Overview of attention for article published in PLOS ONE, February 2012
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Title
Challenges in Whole Exome Sequencing: An Example from Hereditary Deafness
Published in
PLOS ONE, February 2012
DOI 10.1371/journal.pone.0032000
Pubmed ID
Authors

Asli Sirmaci, Yvonne J. K. Edwards, Hatice Akay, Mustafa Tekin

Abstract

Whole exome sequencing provides unprecedented opportunities to identify causative DNA variants in rare Mendelian disorders. Finding the responsible mutation via traditional methods in families with hearing loss is difficult due to a high degree of genetic heterogeneity. In this study we combined autozygosity mapping and whole exome sequencing in a family with 3 affected children having nonsyndromic hearing loss born to consanguineous parents. Two novel missense homozygous variants, c.508C>A (p.H170N) in GIPC3 and c.1328C>T (p.T443M) in ZNF57, were identified in the same ∼6 Mb autozygous region on chromosome 19 in affected members of the family. Both variants co-segregated with the phenotype and were absent in 335 ethnicity-matched controls. Biallelic GIPC3 mutations have recently been reported to cause autosomal recessive nonsyndromic sensorineural hearing loss. Thus we conclude that the hearing loss in the family described in this report is caused by a novel missense mutation in GIPC3. Identified variant in GIPC3 had a low read depth, which was initially filtered out during the analysis leaving ZNF57 as the only potential causative gene. This study highlights some of the challenges in the analyses of whole exome data in the bid to establish the true causative variant in Mendelian disease.

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Geographical breakdown

Country Count As %
United Kingdom 2 2%
Malaysia 1 1%
France 1 1%
Sweden 1 1%
Brazil 1 1%
Israel 1 1%
United States 1 1%
Unknown 74 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 24%
Student > Ph. D. Student 14 17%
Student > Master 11 13%
Student > Postgraduate 8 10%
Student > Bachelor 7 9%
Other 16 20%
Unknown 6 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 35%
Biochemistry, Genetics and Molecular Biology 20 24%
Medicine and Dentistry 17 21%
Computer Science 3 4%
Immunology and Microbiology 2 2%
Other 5 6%
Unknown 6 7%