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Zhonghua Yan Ke Za Zhi. 2014 Jun;50(6):434-9.

[Using exon combined target region capture sequencing chip to detect the disease-causing genes of retinitis pigmentosa].

[Article in Chinese]

Author information

1
Ningxia Eye Hospital,Ningxia People's Hospital,Ningxia 750001, China.
2
Email: shengxunlun@163.com.

Abstract

OBJECTIVE:

To detect the disease-causing genes of 10 retinitis pigmentosa pedigrees by using exon combined target region capture sequencing chip.

METHODS:

Pedigree investigation study. From October 2010 to December 2013, 10 RP pedigrees were recruited for this study in Ningxia Eye Hospital. All the patients and family members received complete ophthalmic examinations. DNA was abstracted from patients, family members and controls. Using exon combined target region capture sequencing chip to screen the candidate disease-causing mutations. Polymerase chain reaction (PCR) and direct sequencing were used to confirm the disease-causing mutations.

RESULTS:

Seventy patients and 23 normal family members were recruited from 10 pedigrees. Among 10 RP pedigrees, 1 was autosomal dominant pedigrees and 9 were autosomal recessive pedigrees. 7 mutations related to 5 genes of 5 pedigrees were detected. A frameshift mutation on BBS7 gene was detected in No.2 pedigree, the patients of this pedigree combined with central obesity, polydactyly and mental handicap. No.2 pedigree was diagnosed as Bardet-Biedl syndrome finally. A missense mutation was detected in No.7 and No.10 pedigrees respectively. Because the patients suffered deafness meanwhile, the final diagnosis was Usher syndrome. A missense mutation on C3 gene related to age-related macular degeneration was also detected in No. 7 pedigrees. A nonsense mutation and a missense mutation on CRB1 gene were detected in No. 1 pedigree and a splicesite mutation on PROM1 gene was detected in No. 5 pedigree.

CONCLUSIONS:

Retinitis pigmentosa is a kind of genetic eye disease with diversity clinical phenotypes. Rapid and effective genetic diagnosis technology combined with clinical characteristics analysis is helpful to improve the level of clinical diagnosis of RP.

PMID:
25241976
[Indexed for MEDLINE]

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