April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
Deciphering the genetic architecture of retinitis pigmentosa through a combination of panel and whole exome sequencing
Author Affiliations & Notes
  • Feng Wang
    Baylor College of Medicine, Houston, TX
  • Li Zhao
    Baylor College of Medicine, Houston, TX
  • Hui Wang
    Baylor College of Medicine, Houston, TX
  • David A Simpson
    Queen’s University Belfast, Belfast, United Kingdom
  • Stephen P Daiger
    The University of Texas HSC at Houston, Houston, TX
  • Silvestri Giuliana
    Queen’s University Belfast, Belfast, United Kingdom
  • Kang Zhang
    University of California San Diego, La Jolla, CA
  • Robert K Koenekoop
    McGill University Health Centre, Montreal, QC, Canada
  • Ruifang Sui
    Peking Union Medical College Hospital, Peking Union Medical College, Beijing, China
  • Rui Chen
    Baylor College of Medicine, Houston, TX
  • Footnotes
    Commercial Relationships Feng Wang, None; Li Zhao, None; Hui Wang, None; David Simpson, None; Stephen Daiger, None; Silvestri Giuliana, Allergan (C), Bayer (C); Kang Zhang, None; Robert Koenekoop, None; Ruifang Sui, None; Rui Chen, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science April 2014, Vol.55, 3269. doi:
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      Feng Wang, Li Zhao, Hui Wang, David A Simpson, Stephen P Daiger, Silvestri Giuliana, Kang Zhang, Robert K Koenekoop, Ruifang Sui, Rui Chen; Deciphering the genetic architecture of retinitis pigmentosa through a combination of panel and whole exome sequencing. Invest. Ophthalmol. Vis. Sci. 2014;55(13):3269.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 
Purpose
 

The molecular basis of retinitis pigmentosa (RP) is a highly heterogeneous. Many novel pathogenic alleles, genotype-phenotype associations, and disease genes remain to be identified. In this study, we aim to dissect the complex genetic architecture of RP by characterizing a large cohort of RP patients.

 
Methods
 

552 RP patients from different ethnicity groups, including Caucasian and Han Chinese, were recruited. Genomic DNA was extracted from patients’ blood or saliva samples, and sequenced using our custom-designed panel, which includes around 200 retinal disease genes. Patients with negative results from our panel sequencing were further analyzed by whole exome sequencing.

 
Results
 

We successfully identified putatively pathogenic variants in known retinal disease genes for 319 RP cases, achieving a solving rate of approximately 58%. Among the 176 solved simplex cases, multiple inheritance patterns were found, including autosomal recessive (73%), autosomal dominant (14%), x-linked (12%) and even digenic (2%). A total of 460 different pathogenic mutations were identified, 365 of which were novel. Interestingly, 58 mutations were recurrent in multiple solved cases, accounting for approximately 30% of total allele instances. USH2A was the most prevalent causative gene in our cohort, which accounts for about 15% of all the solved case. And EYS is significantly more prevalent (~10 fold) in RP patients from Han Chinese than those from Caucasian population. Surprisingly, around 20% of all the solved cases carried mutations in other retinal disease genes which had not been previously associated with RP. For those cases, where available, clinical reassessments were performed resulting in identification of novel genotype-phenotype correlations and clinical refinements. Finally, whole exome sequencing of unsolved cases revealed multiple candidate disease-causing genes which are currently in the process of further validation.

 
Conclusions
 

Sequencing-based comprehensive genetic testing of large patient cohort yield tremendous amount of new findings at multiple levels of the genetic architecture underlying RP. Information gained from this type of study will lay the foundation toward comprehensive and accurate molecular diagnosis of RP, which is critical for developing proper treatment of the disease.

  
Keywords: 696 retinal degenerations: hereditary • 539 genetics • 537 gene screening  
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