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International Journal of Ophthalmology logoLink to International Journal of Ophthalmology
. 2015 Dec 18;8(6):1112–1117. doi: 10.3980/j.issn.2222-3959.2015.06.06

A novel CRX mutation by whole-exome sequencing in an autosomal dominant cone-rod dystrophy pedigree

Qin-Kang Lu 1, Na Zhao 1, Ya-Su Lv 2, Wei-Kun Gong 1, Hui-Yun Wang 1, Qi-Hu Tong 1, Xiao-Ming Lai 1, Rong-Rong Liu 2, Ming-Yan Fang 3, Jian-Guo Zhang 3, Zhen-Fang Du 2, Xian-Ning Zhang 2
PMCID: PMC4651873  PMID: 26682157

Abstract

AIM

To identify the disease-causing gene mutation in a Chinese pedigree with autosomal dominant cone-rod dystrophy (adCORD).

METHODS

A southern Chinese adCORD pedigree including 9 affected individuals was studied. Whole-exome sequencing (WES), coupling the Agilent whole-exome capture system to the Illumina HiSeq 2000 DNA sequencing platform was used to search the specific gene mutation in 3 affected family members and 1 unaffected member. After a suggested variant was found through the data analysis, the putative mutation was validated by Sanger DNA sequencing of samples from all available family members.

RESULTS

The results of both WES and Sanger sequencing revealed a novel nonsense mutation c.C766T (p.Q256X) within exon 5 of CRX gene which was pathogenic for adCORD in this family. The mutation could affect photoreceptor-specific gene expression with a dominant-negative effect and resulted in loss of the OTX tail, thus the mutant protein occupies the CRX-binding site in target promoters without establishing an interaction and, consequently, may block transactivation.

CONCLUSION

All modes of Mendelian inheritance in CORD have been observed, and genetic heterogeneity is a hallmark of CORD. Therefore, conventional genetic diagnosis of CORD would be time-consuming and labor-intensive. Our study indicated the robustness and cost-effectiveness of WES in the genetic diagnosis of CORD.

Keywords: cone-rod dystrophy, autosomal dominant cone-rod dystrophy, whole-exome sequencing, Sanger sequencing, CRX gene, mutation

INTRODUCTION

Cone-rod dystrophies (CORDs; prevalence, 1/40 000) are progressive inherited retinal disorders characterized predominantly by cone dysfunction in the early stage and subsequent rod degeneration[1]. The clinical manifestations of CORDs include photophobia, reduced visual acuity, color vision defects, and central scotoma. Nystagmus may present in some cases. Absent or severely impaired cone function on electroretinography (ERG) is the typical sign of CORDs[2]. Impairment of rod function is frequently observed soon after significant cone dysfunction[1]. In extreme cases, these progressive symptoms are accompanied by widespread, advancing retinal pigmentation along with central and peripheral chorioretinal atrophy. At the advanced stage, CORDs can be difficult to differentiate from retinitis pigmentosa based on the clinical signs alone[3],[4].

CORDs are exceptionally heterogeneous, both genetically and phenotypically[3][5]. Not only is the diagnosis of some of these diseases difficult because of overlapping phenotypes, but mutations within a single gene can cause very different phenotypes[3][5]. CORD may be transmitted as an autosomal dominant (adCORD), autosomal recessive (arCORD), or X-linked trait (xlCORD). To date, mutations in at least 26 genes have been reported to be associated with different forms of CORDs. Of these, 10 genes with mutations responsible for adCORD are: AIPL1[6], CRX[7], GUCA1A[8], GUCY2D[9], PITPNM3[10], PROM1[11], PRPH2[12], RIMS1[13], SEMA4A[14], and UNC119[15]. The next 13 for arCORD are: ABCA4, ADAM9, C8ORF37, CACNA2D4, CDHR1, CERKL, CNGB3, CNNM4, KCNV2, PDE6C, RAX2, RDH5, and RPGRIP1[15]. Other mapped loci or chromosomal regions for arCORD are: NF1, 18q21.1-q21.3, 1q12-q24, and 10q26[16]. xlCORD is caused by mutation in an alternative terminal exon 15 (ORF15) of the RPGR gene, which maps to chromosome Xp21.1[17]. Additional forms of xlCORD are Xq27.2-q28 and the CACNA1F gene on chromosome Xp11.23[18].

Whole-exome sequencing (WES) is a direct, reproducible, and robust method for the confirmation of novel pathogenic genes and the genetic diagnosis of both Mendelian and complex diseases[19]. Protein-coding genes constitute only about 1% of the human genome but harbor nearly 85% of the disease-causing mutations at individual Mendelian loci[20]. Therefore, selectively sequencing complete coding regions can serve as a genome-wide scan for pathogenic genes[20]. Moreover, WES may be a better choice for some diseases with overlapping symptoms that might be ambiguously associated with many pathogenic genes, in which event the detection of mutation by Sanger sequencing could be time-consuming and labor-intensive[19],[21].

Here, we used WES, coupling the Agilent whole-exome capture system to the Illumina HiSeq 2000 DNA sequencing platform, to identify a Chinese pedigree with adCORD.

SUBJECTS AND METHODS

Participants and Examinations

A five-generation Chinese family including 9 affected individuals was investigated in this study(Figure 1). Ophthalmic examination and diagnostic testing was based on color vision testing of three color axes using the Hardy-Rand-Rittler tests(HRR), full-field ERG, Goldmann perimetry, optical coherence tomography (OCT) scans and retinal thickness measurements. One hundred unrelated healthy matched controls were included. This study was conducted in conformity with the Declaration of Helsinki and was approved by the Ethics Committee of Zhejiang University. Written informed consent was given by all participants.

Figure 1. Pedigree of the family investigated Arrow indicates the proband (III-12).

Figure 1

Exome Sequencing and the Data Filtering and Analysis Pipeline

Peripheral blood genomic DNA samples from each of 4 members of the family, III-4, III-10, III-12 and IV-7, were prepared for WES (Figure 1). The whole-exome capture array design, library construction, next-generation sequencing, data filtering, and analysis pipeline followed protocols described previously[21].

Linkage Analysis

MERLIN(Multipoint Engine for Rapid Likelihood Inference) software was used to analyze the compiled pedigree structures of the WES dataset[22]. The filter threshold as a minimum LOD score of 6.0 was set for further analysis.

Prediction of Functional Impact

In an effort to assess the functional significance of the gene variations identified in this study, we used Sorting Intolerant from Tolerant(SIFT; http://sift.bii.a-star.edu.sg/) to predict the functional effect of non-synonymous single-nucleotide polymorphisms (SNPs)[23].

Sanger Sequencing

The putative mutations were validated by Sanger DNA sequencing of samples from available family members (Figure 1).

RESULTS

Clinical Examination

The proband (Figure 1, III-12) was a 50-year-old male, who had been diagnosed with progressively reduced visual acuity and mild color vision abnormalities when he was 40 years old. Fundus photographs indicated a 2PD gold-foil-like reflection of the macula, diffuse hypopigmentation. The peripheral retina exhibited bone spicule-like hyperpigmentation with attenuation of the retinal arteries (Figure 2A). OCT revealed retinal thinning in the macular region (Figure 2B). Fundus autofluorescence showed hyperfluorescence in the macula without peripheral choroidal atrophy (Figure 2C). ERG revealed mildly reduced cone responses and normal rod responses. The other affected members exhibited a similar clinical phenotype, and showed a clear autosomal dominant pattern of inheritance. Therefore, a diagnosis of CORD was made based on the published criteria[2],[3],[24],[25].

Figure 2. Ophthalmic examination results of the proband (III-12).

Figure 2

A: Fundus photographs of the proband showed diffuse hypopigmentation and reduced sensitivity in a central scotoma accompanied by maculopathy. The peripheral retina exhibited bone spicule-like hyperpigmentation with attenuation of retinal arteries. B: OCT of the proband revealed retinal thinning in the macular region. C: Fundus autofluorescence of the proband showed hyperfluorescence in the macula without peripheral choroidal atrophy.

Exome Sequencing Identified 4 Candidate Pathogenic Genes

We generated an average of about 4.5 billion bases of sequence per affected individual as paired-end, 90bp reads, and the fraction of effective bases on-target was about 95% with a minimum 20-fold average sequencing depth on-target. At this depth of coverage, >99% of the targeted bases were sufficiently covered to pass our thresholds for variant-calling (Tables 1, 2). We focused on non-synonymous (NS) variants, splice acceptor, and donor site mutations (SS), anticipating that synonymous variants would be far less likely to be pathogenic. Filtering against public SNP databases, the 1000 Genome Project, eight HapMap exomes, the in-house exome database provided by BGI and one normal individual from the family, 26 genes harboring 26 different NS/SS were shared by the three patients (Table 1).

Table 1. Overview of whole-exome sequencing data production.

Exome capture statistics III-12 (Proband) III-10 (Unaffected) III-4 (Affected) IV-7 (Affected)
1Target region (bp) 51339787 51391525 51339787 51391525
Raw reads 133565546 147779980 136823886 140113624
Raw data yield (Mb) 12021 13300 12314 12610
Reads mapped to genome 118841720 129869013 119724061 122370094
2Reads mapped to target region 57175597 66226757 63991407 62336567
Data mapped to target region (Mb) 4440.09 5159.21 4981.38 4850.57
Mean depth of target region (×) 86.48 100.39 97.03 94.38
Coverage of target region (%) 99.73 99.72 99.72 99.69
Average read length (bp) 89.95 89.97 89.94 89.93
Rate of nucleotide mismatch (%) 0.22 0.18 0.22 0.23
Fraction of target covered ≥4× (%) 99.30 99.35 99.32 99.26
Fraction of target covered ≥10× (%) 98.27 98.50 98.45 98.31
Fraction of target covered ≥20× (%) 95.45 96.24 96.10 95.75
3Capture specificity (%) 48.93 52.08 54.32 51.92
4Reads mapped to flanking region 9072073 9020405 9210197 8861715
Mean depth of flanking region (×) 20.97 22.39 22.24 21.54
Coverage of flanking region (%) 98.92 98.67 98.75 98.59
Fraction of flanking covered ≥4× (%) 91.19 89.02 90.10 89.20
Fraction of flanking covered ≥10× (%) 66.13 63.98 65.45 64.00
Fraction of flanking covered ≥20× (%) 39.15 40.16 40.49 39.22
Fraction of unique mapped bases on or near target (%) 56.14 58.73 61.64 58.83
5Duplication rate (%) 6.80 9.41 8.49 8.39
Mean depth of chrX (×) 96.40 58.22 107.72 54.62
Mean depth of chrY (×) - 55.05 - 53.52
GC rate (%) 45.46 45.92 46.14 45.50
Gender test result F M F M

1Target regions refer to the regions that are actually covered by the designed probes; 2Reads mapped to target regions are reads that are within or overlap with the target region; 3Capture specificity is defined as the percentage of uniquely mapped reads aligning to the target region; 4Flanking region refers to regions ±200 bp on both sides of each target region; 5PCR duplicates would have the same start and end for both mates, which rarely occurs by chance. Duplication rate is the fraction of duplicated reads in the raw data.

Table 2. Summary of SNPs for exome capture sample.

Categories III-12 (proband) III-10 (unaffected) III-4 (affected) IV-7 (affected)
1Number of genomic positions for calling SNPs 134975362 135126064 134975362 135126064
2Number of high-confidence genotypes 128995083 128400486 128538834 128338404
Number of high-confidence genotypes in TR 50782259 50828750 50782665 50812238
Total number of SNPs 110292 108907 109560 108350
Nonsense 114 115 122 120
Readthrough 57 50 53 55
Missense 11030 11033 11010 10849
3Splice site 2704 2767 2729 2673
5-UTR 3813 3777 3836 3767
3-UTR 7426 7276 7327 7187
NR_exon 10219 10113 10086 9933
Synonymous-coding 5856 5939 5929 5908
Intron 65755 64506 65128 64450
Intergenic 3318 3331 3340 3408
Homozygous 45692 45421 45114 45639
Heterozygous 64600 63486 64446 62711

1Genomic positions for calling SNPs include capture target regions and their 200-bp flanking regions; 2Consensus genotype with quality score of at least 20; 3Intronic SNPs within 10 bp of an exon/intron boundary.

Functional Significance of Gene Variations

c.C766T(p.Q256X) in CRX was considered to be a definite pathogenic mutation due to the creation of a novel upstream stop-site which truncates the normal protein. The pathogenicity of the other 25 variants was excluded by SIFT(Table 1) and linkage analysis.

Validation of the CRX Germline Mutation

The Sanger DNA sequencing scan of the whole CRX gene was completely consistent with WES. c.C766T (p.Q256X) within exon 5 of CRX was found in the affected family members but absent from the unaffected members and 100 normal controls (Figure 3).

Figure 3. Results of nucleotide sequencing analysis.

Figure 3

A: Sequence analysis of the CRX coding region in an unrelated normal individual was reference homozygote. B: The proband(III-12) showed a heterozygous c.C766T(p.Q256X) mutation. Arrow indicates the position of the mutation.

DISCUSSION

In this study, we used WES to identify a novel nonsense mutation c.C766T (p.Q256X) within exon 5 of CRX in a Chinese adCRD family. WES analyzes the exons and coding regions of thousands of genes simultaneously using next-generation sequencing technique[20]. By sequencing the exome of a patient and comparing it with a normal reference sequence, variations in an individual's DNA sequence can be identified and related to the individual's medical concerns in an effort to discover the cause of the disorder[20]. The overall molecular diagnostic rate is higher than several comparable genetic tests, including chromosome studies(5%-10%) and chromosomal microarray analysis (15%-20%)[26][28]. Recent increases in accuracy have enabled the development of clinical exome sequencing for mutation identification in patients with suspected genetic diseases[29][31]. We anticipate applications for WES that include the discovery of genes and alleles contributing to Mendelian and complex traits, especially for disease like CORDs, which are exceptionally heterogeneous in genotype and phenotype[5],[19],[29],[30].

The CRX gene located on 19q13 contains 5 exons and encodes a protein with 299 amino acid residues; it is expressed in the inner nuclear layer, where it plays a significant role in the differentiation and maintenance of photoreceptor cells by synergistic interaction with other transcription factors such as NRL and RX[7],[31],[32]. CRX molecule possesses a paired-like homeodomain followed by a basic region, a WSP domain, and a C-terminal OTX tail. The OTX tail is important for its transcriptional activation[32],[33]. CRX exerts its activity on dimerization such as with the neural retina leucine zipper via the OTX tail[34],[35]. Therefore, mutations in CRX abolishing the OTX tail (e.g. c.504delA, c.587delCCCC, c.816delCACinsAA, and c.C766T in this study) affect photoreceptor-specific gene expression with a dominant-negative effect because the OTX tail establishes interactions with other transcription factors[3],[7],[36],[37]. Upon loss of the OTX tail, the mutant protein occupies the CRX-binding site in target promoters without establishing an interaction and, consequently, may block transactivation.

To date, more than 31 CRX mutations have been reported [http://www.retina-international.org/files/sci-news/crxmut.htm (update from June 16, 2005)] to underlie 3 different phenotypes: CORD, autosomal dominant retinitis pigmentosa (RP), and autosomal dominant Leber congenital amaurosis (LCA)[3],[5]. The first mutation in CRX was detected in a Greek family with adCORD[7]. Thereafter, a number of mutations in CRX have been identified as being responsible for CORD as well as LCA or RP[24]. However, the severity and progression vary considerably both within and across families[38]. All CRX mutations appear to be completely penetrant and cause disease in heterozygotes. Missense mutations preferentially affect the conserved homeobox(codons 39-98), and all frameshift mutations leave the homeodomain intact but alter the OTX motif encoded by codons 284-295 at the carboxy terminus[3],[5]. So far, there does not appear to be an obvious relationship between the type of dominant mutation (missense vs frameshift) in CRX and the severity of the resulting retinal disease[3],[5].

In conclusion, we have used WES to identify a novel nonsense mutation c.C766T(p.Q256X) of CRX in a Chinese pedigree with adCORD. Although the assessment of disease-associated variation in CORD is still a difficult task for ophthalmologists and geneticists, WES offers a direct and robust diagnostic tool to substantially advance our knowledge, specifically in CORD-associated diseases and in ophthalmic genetics in general.

Acknowledgments

Foundations: Supported by the Zhejiang Provincial Natural Science Foundation of China (No.LY12H12001); the Ningbo Key Foundation of Society Development (No.2014C50091); the Ningbo Natural Science Foundation (No. 2012A610192); the Ningbo Yinzhou District S&T Foundation (No.YK2013-90); the Shenzhen Municipal Government of China (No.GJHZ20130417140916986).

Conflicts of Interest: Lu QK, None; Zhao N, None; Lv YS, None; Gong WK, None; Wang HY, None; Tong QH, None; Lai XM, None; Liu RR, None; Fang MY, None; Zhang JG, None; Du ZF, None; Zhang XN, None.

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