Development and application of a next-generation-sequencing (NGS) approach to detect known and novel gene defects underlying retinal diseases

1750-1172-7-81750-1172 Research Development and application of a next-generation-sequencing (NGS) approach to detect known and novel gene defects underlying retinal diseases AudoIsabelleisabelle.audo@inserm.fr BujakowskaMKingakinga.bujakowska@inserm.fr LéveillardThierrythierry.leveillard@inserm.fr Mohand-SaïdSaddekmohand@quinze-vingts.fr LancelotMarie-Elisemarie-Elise.Lancelot@inserm.fr GermainAuroreaurore.germain@inserm.fr AntonioAlinealine.antonio@inserm.fr MichielsChristellechristelle.michiels@inserm.fr SaraivaJean-Pauljean-paul.saraiva@integragen.com LetexierMélaniemelanie.letexier@integragen.com SahelJosé-Alainj.sahel@gmail.com BhattacharyaSShomishomi.bhattacharya@cabimer.es ZeitzChristinachristina.zeitz@inserm.fr

INSERM, U968, Paris, F-75012, France

CNRS, UMR_7210, Paris, F-75012, France

UPMC Univ Paris 06, UMR_S 968, Department of Genetics, Institut de la Vision, Paris, F-75012, France

Centre Hospitalier National d'Ophtalmologie des Quinze-Vingts, INSERM-DHOS CIC 503, Paris, F-75012, France

UCL-Institute of Ophthalmology, London, UK

IntegraGen SA, Genopole CAMPUS 1 bat G8 FR-91030 EVRY France

Fondation Ophtalmologique Adolphe de Rothschild, Paris, France

Académie des Sciences-Institut de France, 75006 Paris, France

Department of Celular Therapy and Regenerative Medicine, Andalusian Molecular Biology and Regenerative Medicine Centre (CABIMER), Isla de Cartuja, Seville, Spain

Orphanet Journal of Rare Diseases 1750-1172 2012 7 1 8 http://www.ojrd.com/content/7/1/8 10.1186/1750-1172-7-822277662 129201125120122512012 2012Audo et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. NGS retinal disorders diagnostic tool.

Abstract

Background

Inherited retinal disorders are clinically and genetically heterogeneous with more than 150 gene defects accounting for the diversity of disease phenotypes. So far, mutation detection was mainly performed by APEX technology and direct Sanger sequencing of known genes. However, these methods are time consuming, expensive and unable to provide a result if the patient carries a new gene mutation. In addition, multiplicity of phenotypes associated with the same gene defect may be overlooked.

Methods

To overcome these challenges, we designed an exon sequencing array to target 254 known and candidate genes using Agilent capture. Subsequently, 20 DNA samples from 17 different families, including four patients with known mutations were sequenced using Illumina Genome Analyzer IIx next-generation-sequencing (NGS) platform. Different filtering approaches were applied to identify the genetic defect. The most likely disease causing variants were analyzed by Sanger sequencing. Co-segregation and sequencing analysis of control samples validated the pathogenicity of the observed variants.

Results

The phenotype of the patients included retinitis pigmentosa, congenital stationary night blindness, Best disease, early-onset cone dystrophy and Stargardt disease. In three of four control samples with known genotypes NGS detected the expected mutations. Three known and five novel mutations were identified in NR2E3, PRPF3, EYS, PRPF8, CRB1, TRPM1 and CACNA1F. One of the control samples with a known genotype belongs to a family with two clinical phenotypes (Best and CSNB), where a novel mutation was identified for CSNB. In six families the disease associated mutations were not found, indicating that novel gene defects remain to be identified.

Conclusions

In summary, this unbiased and time-efficient NGS approach allowed mutation detection in 75% of control cases and in 57% of test cases. Furthermore, it has the possibility of associating known gene defects with novel phenotypes and mode of inheritance.

Background

Inherited retinal disorders affect approximately 1 in 2000 individuals worldwide 1 . Symptoms and associated phenotypes are variable. In some groups the disease can be mild and stationary such as in congenital stationary night blindness (CSNB) or achromatopsia (ACHM), whereas other disorders are progressive leading to severe visual impairment such as in rod-cone dystrophies, also known as retinitis pigmentosa (RP) or cone and cone-rod dystrophies. The heterogeneity of these diseases is reflected in the number of underlying gene defects. To date more than 150 genes have been implicated in different forms of retinal disorders http://www.sph.uth.tmc.edu/Retnet/home.htm and yet in a significant proportion of patients the disease causing mutation could not be identified, suggesting additional novel genes that remain to be discovered. Furthermore, recent studies have outlined that distinct phenotypes can be related to the dysfunction of the same gene 2 3 4 . Furthermore, there may be additional phenotype-genotype associations that are still not recognized. The state-of-the-art phenotypic characterization including precise family history and functional as well as structural assessment (i.e. routine ophthalmic examination, perimetry, color vision, full field and multifocal electroretinography (ERG), fundus autofluorescence (FAF) imaging and optical coherence tomography (OCT)) allows targeted mutation analysis for some disorders. However, in most cases of inherited retinal diseases, similar phenotypic features can be due to a large number of different gene defects.

Various methods can be used for the identification of the corresponding genetic defect. All these methods have advantages and disadvantages. Sanger sequencing is still the gold-standard in determining the gene defect, but due to the heterogeneity of the disorders it is time consuming and expensive to screen all known genes. Mutation detection by commercially available APEX genotyping microarrays (ASPER Ophthalmics, Estonia) 5 6 allows the detection of only known mutations. In addition, a separate microarray has been designed for each inheritance pattern, which tends to escalate the costs especially in simplex cases, for which inheritance pattern cannot be predetermined. Indirect methods with single nucleotide polymorphism (SNP) microarrays for linkage and homozygosity mapping are also powerful tools, which has proven its reliability in identifying novel and known gene defects 7 8 9 10 11 12 . However, in case of homozygosity mapping the method can only be applied to consanguineous families or inbred populations. To overcome these challenges, we designed a custom sequencing array in collaboration with a company (IntegraGen, Evry, France) to target all exons and part of flanking sequences for 254 known and candidate retinal genes. This array was subsequently applied through NGS to a cohort of 20 patients from 17 families with different inheritance pattern and clinical diagnosis including RP, CSNB, Best disease, early-onset cone dystrophy and Stargardt disease.

Methods

Clinical investigation

The study protocol adhered to the tenets of the Declaration of Helsinki and was approved by the local Ethics Committee (CPP, Ile de France V). Informed written consent was obtained from each study participant. Index patients underwent full ophthalmic examination as described before 13 . Whenever available, blood samples from affected and unaffected family members were collected for co-segregation analysis.

Previous molecular genetic analysis

Total genomic DNA was extracted from peripheral blood leucocytes according to manufacturer's recommendations (Qiagen, Courtaboeuf, France). DNA samples from some patients with a diagnosis of RP were first analyzed and excluded for known mutations by applying commercially available microarray analysis (arRP and adRP ASPER Ophthalmics, Tartu, Estonia). In some cases, pathogenic variants in EYS, C2orf71, RHO, PRPF31, PRPH2 and RP1 were excluded by direct Sanger sequencing of the coding exonic and flanking intronic regions of the respective genes 13 14 15 16 17 . Conditions used to amplify PRPH2 can be provided on request.

Molecular genetic analysis using NGS

A custom-made SureSelect oligonucleotide probe library was designed to capture the exons of 254 genes for different retinal disorders and candidate genes according to Agilent's recommendations (Table 1). These genes include 177 known genes underlying retinal dysfunction (http://www.sph.uth.tmc.edu/retnet/sum-dis.htm, October 2010, Table 1) and 77 candidate genes associated with existing animal models and expression data (Table 2). The eArray web-based probe design tool was used for this purpose https://earray.chem.agilent.com/earray. The following parameters were chosen for probe design: 120 bp length, 3× probe-tiling frequency, 20 bp overlap in restricted regions, which were identified by the implementation of eArray's RepeatMasker program. A total of 27,430 probes, covering 1177 Mb, were designed and synthesized by Agilent Technologies (Santa Clara, CA, USA). Sequence capture, enrichment, and elution were performed according to the manufacturer's instructions (SureSelect, Agilent). Briefly, three μg of each genomic DNA were fragmented by sonication and purified to yield fragments of 150-200 bps. Paired-end adaptor oligonucleotides from Illumina were ligated on repaired DNA fragments, which were then purified and enriched by six PCR cycles. 500 ng of the purified libraries were hybridized to the SureSelect oligo probe capture library for 24 h. After hybridization, washing, and elution, the eluted fraction underwent 14 cycles of PCR-amplification. This was followed by purification and quantification by qPCR to obtain sufficient DNA template for downstream applications. Each eluted-enriched DNA sample was then sequenced on an Illumina GAIIx as paired-end 75 bp reads. Image analysis and base calling was performed using Illumina Real Time Analysis (RTA) Pipeline version 1.10 with default parameters. Sequence reads were aligned to the reference human genome (UCSC hg19) using commercially available software (CASAVA1.7, Illumina) and the ELANDv2 alignment algorithm. Sequence variation annotation was performed using the IntegraGen in-house pipeline, which consisted of gene annotation (RefSeq), detection of known polymorphisms (dbSNP 131, 1000 Genome) followed by mutation characterization (exonic, intronic, silent, nonsense etc.). For each position, the exomic frequencies (homozygous and heterozygous) were determined from all the exomes already sequenced by IntegraGen and the exome results provided by HapMap project.

Table 1

Known retinal disease genes

Number

Gene name

ABCA4

ABCC6

ADAM9

AHI1

AIPL1

ALMS1

ARL6

ARMS2

ATXN7

BBS10

BBS12

BBS2

BBS4

BBS5

BBS7

BBS9

BEST1

C1QTNF5

C2orf71

CA4

CABP4

CACNA1F

CACNA2D4

CC2D2A

CDH23

CDH3

CEP290

CERKL

CFB

CFH

CHM

CLN3

CLRN1

CNGA1

CNGA3

CNGB1

CNGB3

CNNM4

COL11A1

COL2A1

COL9A1

CRB1

CRX

CYP4V2

DFNB31

DMD

DPP3

EFEMP1

ELOVL4

ERCC6

EYS

FAM161A

FBLN5

FSCN2

FZD4

GNAT1

GNAT2

GPR98

GRK1

GRM6

GUCA1A

GUCA1B

GUCY2D

HMCN1

HTRA1

IDH3B

IMPDH1

IMPG2

INPP5E

INVS

IQCB1

JAG1

KCNJ13

KCNV2

KLHL7

LCA5

LRAT

LRP5

MERTK

MFRP

MKKS

MKS1

MTND1

MTND6

MT-AP6

MTND2

MTND5

MTND4

MYO7A

NDP

NPHP1

NPHP3

NPHP4

NR2E3

NRL

NYX

OAT

100

OFD1

101

OPA1

102

OPA3

103

OPN1LW

104

OPN1MW

105

OPN1Sw

106

OTX2

107

PANK2

108

PAX2

109

PCDH15

110

PCDH21

111

PDE6A

112

PDE6B

113

PDE6C

114

PDE6G

115

PDZD7

116

PEX1

117

PEX2

118

PEX7

119

PGK1

120

PHYH

121

PITPNM3

122

PRCD

123

PROM1

124

PRPF3

125

PRPF31

126

PRPF8

127

PRPH2

128

RAX2

129

RB1

130

RBP3

131

RBP4

132

RD3

133

RDH12

134

RDH5

135

RGR

136

RGS9

137

RGS9BP

138

RHO

139

RIMS1

140

RLBP1

141

ROM1

142

RP1

143

RP1L1

144

RP2

145

RP9

146

RPE65

147

RPGR

148

RPGRIP1

149

RPGRIP1L

150

RS1

151

SAG

152

SDCCAG8

153

SEMA4A

154

SLC24A1

155

SNRNP200

156

SPATA7

157

TEAD1

158

TIMM8A

159

TIMP3

160

TLR3

161

TLR4

162

TMEM126A

163

TOPORS

164

TREX1

165

TRIM32

166

TRPM1

167

TSPAN12

168

TTC8

169

TTPA

170

TULP1

171

UNC119

172

USH1C

173

USH1G

174

USH2A

175

VCAN

176

WFS1

177

ZNF513

Table 2

Candidate genes for retinal disorders

Number

Gene name

Reason

References

ADCY1

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

ANKRD33

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

ANXA2

Promotion of choroidal neovascularization

ARL13B

Cilia protein, mutations lead to Joubert Syndrome

BMP7

Regulation of Pax 2 in mouse retina

BSG

Thierry Leveillard personal commmunication

CAMK2D

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

CCDC28B

Modifier for BBS

39 40

CLCN7

Cln7-/- mice severe osteopetrosis and retinal degeneration

COL4A3

Alport syndrome, with eye abnormalities

42 43

COL4A4

Alport syndrome, with eye abnormalities

42 44

COL4A5

Alport syndrome, with eye abnormalities

42 45

CUBN

Personal communication Renata Kozyraki

CYP1B1

glaucoma

DOHH

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

DSCAML1

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

ESRRB

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

FIZ1

Interactor of NRL

GJA9

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

GNAZ

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

GNGT1

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

GPR152

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

HCN1

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

HEATR5A

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

HIST1H1C

Expressed in retina

Expression databases

IMPG1

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

INSL5

diff. Expression rd1 mouse

Chalmel et al., manuscript in preparatiom

KCNB1

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

KCTD7

Expressed in retina

Expression databases

LASS4

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

LRIT2

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom Rd1 mouse

LRP2

Personal communication Renata Kozyraki

MAB21L1

diff. expression Rd1 mouse

Chalmel et al., manuscript in preparatiom

MAP2

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

MAS1

Degeneration of cones due to expression of Mas1

MAST2

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

MPP4

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

MYOC

glaucoma

NDUFA12

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

NEUROD1

BETA2/NeuroD1 -/- mouse: photoreceptor degeneration

NOS2

glaucoma

NXNL1

Rod-derived cone viability factor

NXNL2

Rod-derived cone viability factor 2

OPN1MW2

Cone opsin, medium-wave-sensitive2

OPTN

glaucoma

PFKFB2

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

PIAS3

Rod photoreceptor development

PKD2L1

Diff. expression in human retinal detachment

Delyfer et al. 2011 submitted

PLEKHA1

Age-related macular degeneratiom

PPEF2

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

RAB8A

Interacts with RPGR, role in cilia biogenesis and maintenance

RABGEF1

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

RCVRN

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

RGS20

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

RNF144B

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

RORB

Rod photoreceptor development in mice

RXRG

Retinoic acid receptor, highly expressed in the eye

Expression databases

SGIP1

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

SLC16A8

Altered visual function in ko-mice

SLC17A7

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

STAM2

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

STK35

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

STX3

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

SV2B

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

TBC1D24

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

THRB

Essential for M-cone development in rodents

TMEM216

Cilia protein, mutations lead to Joubert and Meckel syndrome

TMEM67

Cilia protein, mutations lead to Joubert

TRPC1

diff. expression rd1 mouse

diff. expression Rd1 mouse

UHMK1

diff. expression rd1 mouse

diff. expression Rd1 mouse

VSX1

Stimulator for promoter NXNL1

VSX2

Stimulator for promoter NXNL1

WDR17

diff. expression rd1 mouse

diff. expression Rd1 mouse

WDR31

diff. expression Nxnl1-/- mouse

WISP1

diff. expression rd1 mouse

Chalmel et al., manuscript in preparatiom

XIAP

Protects photoreceptors in animal models of RP

ZDHHC2

diff. expression Rd1 mouse

Chalmel et al., manuscript in preparatiom

Investigation of annotated sequencing data

We received the annotated sequencing data in the form of excel tables. On average 946 SNPs and 83 insertions and deletions were identified for each sample (Figure 1). By using the filtering system, we first investigated variants (nonsense and missense mutations, intronic variants located +/- 5 apart from exon), which were absent in dbSNP and NCBI databases http://ncbi.nlm.nih.gov/. In the absence of known gene defects or putative pathogenic variants (see below) in the first step, we selected known genes, which were previously clinically associated including variants present in dbSNP and NCBI databases (Figure 1). Each predicted pathogenic variant was confirmed by Sanger sequencing.

Figure 1

Flow chart of variant analysis

Flow chart of variant analysis. IntegraGen provided the results in form of excel tables. For each sample on average 946 SNPs and 83 inDels were detected, of which 11 represent missense, nonsense or putative splice site mutations, which were absent in dbSNB, NCBI and 1000 genome databases. Of those 1-5 variants were predicted to be pathogenic. In case where none of the variants were predicted to be pathogenic, dbSNB, NCBI and 1000 genome databases were included to detect mutations referenced with an rs-number. Co-segregation analysis was performed in families with putative pathogenic variants.

Assessment of the pathogenicity of variants

Following criteria were applied to evaluate the pathogenic nature of novel variations identified by NGS: 1) stop/frameshift variants were considered as most likely to be disease causing; 2) co-segregation in the family; 3) absence in control samples; 4) for missense mutations amino acid conservation was studied in the UCSC Genome Browser http://genome.ucsc.edu/ across species from all different evolutionary branches. If the amino acid residue did not change it was considered as "highly conserved". If a different change was seen in fewer than five species and not in the primates then it was considered as "moderately conserved" and if a change was present in 5-7, it was considered as "weakly conserved", otherwise the amino acid residue was considered as "not conserved", 5) pathogenicity predictions with bioinformatic tools (Polyphen: Polymorphism Phenotyping, http://genetics.bwh.harvard.edu/pph/ and SIFT: Sorting Intolerant From Tolerant, http://blocks.fhcrc.org/sift/SIFT.html) if at least one of the program predicted the variant to be possibly damaging, it was considered to be pathogenic; 6) presence of the second mutant allele in the case of autosomal recessive inheritance. Mutations were described according to the HGVS website http://www.hgvs.org/mutnomen. In accordance with this nomenclature, nucleotide numbering reflects cDNA numbering with +1 corresponding to the A of the ATG translation initiation codon in the reference sequence. The initiation codon is codon 1. The correct nomenclature for mutation was checked applying Mutalyzer http://www.lovd.nl/mutalyzer/.

Results

The overall sequencing coverage of the captured regions was 98.4% and 90.4% for a 1× and a 10× coverage respectively. The overall sequencing depth was > 120×. The number of reference and variant sequences detected by NGS, reflected the correct zygosity state of the variant; on average if 50% of the sequences represented the variant, then a heterozygous state was called, while if 100% of the sequences represented the variant, then a homozygous or hemizygous state was annotated by IntegraGen.

Validation of the novel genetic testing tool for retinal disorders

To validate the novel genetic testing tool for retinal disorders, we used four DNA samples from families, in which we had previously identified different types of mutations by Sanger sequencing: one 1 bp duplication and one 1 bp deletion in PRPF31 and missense mutations in TRPM1 and BEST1 (Table 3). Three of the four mutations were detectable by NGS, whereas the deletion in PRPF31 was not identified. To validate if this was due to a technical problem of deletion detection in general or low coverage at this position, the sequencing depth was investigated in detail. Indeed the coverage at this position reflected by the mean depth was only ~1-6 for all samples. This indicates that although the coverage in general was very good, specific probes used here need to be redesigned to improve the capture for specific exons.

Table 3

Patients with known mutations used to validate the novel genetic approach for retinal disorders

Index

Phenotype

Gene

Mutation

Allele State

Read reference NGS

Read variant NGS

Mutation detected by NGS

Mean depth

CIC00034, F28

adRP

PRPF31

c.666dup

p.I223YfsX56

het

yes

21.3-22.5

CIC00140, F108

adRP

PRPF31

c.997delG

p.E333SfsX5

het

5.0-5.2

CIC00238, F165

arCSNB

TRPM1

c.1418G > C

p.R473P

homo

yes

36.7

CIC00707, F470

Best and adCSNB see Table 5

BEST1

c.73C > T

p.R25W

het

yes

99.4

Detection of known and novel mutations

Some of the patients from the 14 families with no known gene defect were previously excluded for known mutations using microarray analysis and by Sanger sequencing in the known genes EYS, C2orf71, RHO, PRPF31, PRPH2 and RP1. Other samples were never genetically investigated. In four DNA samples known mutations were detected (Table 4) from three different families with autosomal dominant (ad) or recessive (ar) RP. All mutations co-segregated with the phenotype (Figure 2). In seven samples, novel mutations in known genes were identified. These mutations co-segregated with the phenotype from five different families with adCSNB, x-linked incomplete CSNB, adRP, arRP and x-linked RP (Table 5, Figures 3 and 4). One of the cases from these five families was also used as a control for Best disease carrying a known BEST1 mutation (Table 3). In addition to the Best phenotype, ERG-responses of this patient resembled those of complete CSNB, i.e. showing selective ON-bipolar pathway dysfunction. This phenotype was independent of the Best phenotype (Figure 3). The most likely disease causing mutation detected by NGS was a novel heterozygous TRPM1 mutation (Table 4, Figure 3).

Table 4

Detection of known mutations by using the novel genetic approach for retinal disorders

Index

Phenotype

Pre-screening

Gene

Mutation

Allele State

Read reference NGS

Read variant NGS

Reference

Mutation verified by Sanger and co-segregation

CIC00019, F16

adRP

Linkage, RHO, PRPF31, PRPH2, RP1

PRPF3

c.1481C > T

p.T494M

het

yes

CIC0000893, F574

adRP

RHO, PRPF31, PRPH2, RP1

NR2E3

c.166G > A

p.G56R

het

yes

CIC000128, F100

arRP, consang.

EYS

c.408_423del p.N137VfsX24

homo

179

13 69

yes

CIC0000943, F100

arRP, consang

EYS

c.408_423del p.N137VfsX24

homo

193

13 69

yes

Figure 2

Detection of known mutations by NGS in 254 retinal genes

Detection of known mutations by NGS in 254 retinal genes. The index patient 19 of family 16 with adRP revealed the p.T494M mutations in PRPF3, which co-segregates with the phenotype. Two family members never clinically investigated from the last generation (984 and 1167 carrying a question mark) were reported to be not affected but carried the mutation. They may develop the phenotype at a later stage. In addition variability of the phenotype of this mutation was documented 35. Two patients, 128 and 943 of family 100 with arRP from Jewish origin revealed the known EYS mutation p.N137VfsX24, which was found in all screened affected family members. The index patient 893 of family 574 showed the previously described NR2E3 p.G56R mutation, which co-segregated with the phenotype.

Table 5

Detection of novel mutations by using the novel genetic approach for retinal disorders

Index

Phenotype

Pre-screening

Gene

Mutation

Allele State

Read reference NGS

Read variant NGS

Mutation verified by Sanger and co-segregation

Conservation

Polyphen

Sift

CIC00707,

F470

adCSNB and Best see Table 3

RHO, PDE6B, GNAT1

TRPM1

c.1961A > C

p.H654P

het

yes

moderately conserved

possibly damaging

tolerated

CIC000348, F232

adRP, mild

RHO, PRPF31, PRPH2, RP1, adRP chip

PRPF8

c.6992A > G

p.E2331G

het

yes

moderately conserved

possibly damaging

affect protein function

CIC000346, F232

adRP

PRPF8

c.6992A > G

p.E2331G

het

yes

moderately conserved

possibly damaging

affect protein function

CIC000347, F232

adRP

PRPF8

c.6992A > G

p.E2331G

het

yes

moderately conserved

possibly damaging

affect protein function

CIC04240,

F2025

arRP, consang., detailed clinic in 70

RS1

CRB1

c.2219C > T

p.S740F

homo

194

yes

highly conserved

probably damaging

affect protein function

CIC00199,

F146

adRP or x-linked RP with affected carrier

RHO, PRPF31, PRPH2, RP1, adRP chip

RPGR

c.248-2A > G

splice defect

hetero

yes

conserved

splice site

n.a.

CIC04094,

F1915

icCSNB

CACNA1F

c.973C > T

p.Q325X

hemi

yes

n.a.

Figure 3

Best disease and CSNB co-segregating in one family

Best disease and CSNB co-segregating in one family. a) Sanger and NGS detected in all patients with Best disease a BEST1 mutation. b) NGS detected in all patients with a cCSNB phenotype a novel TRPM1 mutation. c) Fundus colour photographs (above) and fundus autofluorescence (below) of patient 707 showing multiple yellow deposits within the posterior pole which are hyper autofluorescent d) Electro-oculogram of patient 707 showing no slight rise after illumination in keeping with the diagnosis of Best disease e) Full Field Electroretinogram of patient 707 showing ON-bipolar cell pathway dysfunction in keeping with the diagnosis of cCSNB.

Figure 4

Detection of novel mutations using NGS in 254 retinal genes

Detection of novel mutations using NGS in 254 retinal genes. Novel mutations in PRPF8, CRB1, RPGR and CACNA1F co-segregated in affected and asymptomatic carriers with the adRP, arRP, x-linked dominant and X-liked icCSNB phenotypes respectively. Asymptomatic individuals are marked with a question mark.

Unsolved cases

In six of the 14 families with Stargardt disease, adRP, adCD with postreceptoral defects, arRP, early onset arCD with macrocephaly and mental retardation described in affected sister and x-linked cCSNB, the disease associated mutations remain to be elucidated or validated (Table 6, Figure 5).

Table 6

Patients with unsolved genotype and unlikely disease causing mutations

Index

Phenotype

Pre-screening

Gene

Mutation

Allele State

Read reference NGS

Read variant NGS

Mutation verified by Sanger and co-segregation

Comment

CIC03282,

F1388

Stargardt

ABCA4 microarray

ABCA4

c.1268A > G

p.H423R

het

yes

but reported as polymorphism

c.6764G > T

p.S2255I

no additional variants in lower covered exons

het

yes

but reported as polymorphism

CFH

c.3482C > A

p.P1161Q

het

yes

conserved, probably damaging

c.1204C > T

p.H402Y

het

yes

AMD

CIC01269, F761

adRP

RP1L1

c.5959C > T

p.Q1987X

het

145

150

yes, did not co-segregate

pass to whole exome sequencing

CIC01312,

F795

adCD with post-receptoral defects

RHO, PDE6B,

GNAT1 adRP chip

CUBN

c.127C > T

p.R43X

het

139

102

yes, did not co-segregate

pass to whole exome sequencing

CUBN

c.9340G > A

p.G3114S

het

yes, did not co-segregate

GUCY2D

c.1499C > T

p.P500L

het

yes, did not co-segregate

TRPM1

c.3904T > C

p.C1302R

het

102

yes, did not co-segregate

CIC03225,

F1362

arRP consang.

arRP chip

PROM1

c.314A > G

p.Y105C

het

120

115

yes, but no additional mutation

no homo, no compound hets, pass to whole exome sequencing

GUCY2D

c.2917G > A

p.V973L

het

false positive, not found by Sanger

DSCAML1

c.592C > T

p.R198C

het

yes, but no additional mutation

TBC1D24

c.641G > A

p.R214H

het

yes, but no additional mutation

TMEM67

c.1700A > G

p.Y567C

het

yes, but no additional mutation

CIC04757

F2364

Index and affected sister early onset arCD, macro-cephaly and mental retardation in affected sister consang.

IMPG2

c.3439C > T

p.P1147S

homo

140

Polyphen and Sift benign, not conserved

PKD2L1

c.1027C > T

p.R343C

het

c.1202T > G

p.V401G

het

appeared also het in 11 of our samples

appeared also het in affected sister but no other mutation in less covered exons

DFNB31

c.1943C > A p.S648Y

het

yes

affected sister also both variants but both come from father, no other variant in lower covered region.

c.2644C > A

p.R882S

het

yes

EYS

c.7597A > G

p.K2533E

het

151

149

yes

Affected sister does not carry this variant

RPGRIP1

c.2417C > T

p.T806I

het

138

132

not conserved

CIC04152, F1955

male x-linked cCSNB, has affected nephew

NYX

TRPM1

c.470C > T

p.S157F

het

118

130

yes, no other het mutation.

x-linked inheritance and phenotype verification

Index patients and respective gene defect are highlighted in bold. In some cases also family members were used for NGS.

Figure 5

Detection of novel mutation by using NGS in 254 retinal genes

Detection of novel mutation by using NGS in 254 retinal genes. Family 795 reveals autosomal dominant cone dystrophy with post-receptoral defects. Four putative disease causing mutations were investigated on the basis of co-segregation. However, none of them co-segregated in all affected family members with the phenotype and thus are not considered to be disease causing. Individuals marked with a star were clinically investigated, patients with a question mark are asymptomatic and patients with a plus sign show high myopia.

Discussion

By using NGS in 254 known and candidate genes we were able to detect known and novel mutations in 57% of families tested. In order to achieve this goal, we applied a rigorous protocol (Figure 1). To our knowledge, this is the first report using NGS to investigate all inherited retinal disorders at once. In a study restricted to adRP, Bowne and co-workers used a similar approach including 46 known and candidate genes for adRP 18 . All their cases had previously been screened and excluded for most of the known genes underlying adRP. The authors were able to identify known or novel mutations in five out of 21 cases in genes not included in a pre-screening 18 . This added five patients to their adRP cohort with known gene defects, indicating that 64% of their patients show known mutations with new genes still to be discovered in the remaining 36%. The current study provides a more exhaustive tool, since it incorporates screening of 254 genes implicated in various retinal disorders of different inheritance patterns and additional candidate genes for these phenotypes. With this approach a cohort of both pre-screened and unscreened samples, was investigated. The mutation detection rate of 57% is high and was never obtained before by high throughput screening methods. Furthermore, this approach is probably less time consuming and expensive than existing methods such as direct sequencing of all known genes or microarray analysis. Of note however is one of the variants detected with the NGS approach (i.e. p.V973L exchange in GUCY2D), which was not confirmed by direct Sanger sequencing, suggesting the possibility of false positive using the high throughput screening. Verification by direct Sanger sequencing of most likely pathogenic variants is therefore essential to validate NGS data, although the false positive rate is assumed to be low (in our study 1/28 verified sequence variants represented a false positive).

Overall, the study of 20 subjects from 17 families by NGS showed that most of the targeted regions are well covered (more than 98%). However, some of the regions showed a lower coverage (GC-rich regions) or were not captured (repetitive regions). This was for instance the case for two genes underlying cCSNB, (i.e. NYX and GRM6) and the repetitive region of ORF15 of RPGR. For GC-rich regions the capture design could be improved in the future by modifying NGS chemistry, as it was successfully achieved for Sanger sequencing using different additives, which improved the amplification and subsequent sequencing. If repetitive regions like ORF15 of RPGR remain problematic for sequencing by NGS, direct Sanger sequencing of these targets might be the first screening of choice; in particular for disorders caused only by a few gene defects such as CSNB, and xl-RP.

By applying NGS sequencing to our retinal panel, known and novel mutations were detected in different patients. We believe that our diagnostic tool is particularly important for heterogeneous disorders like RP, for which many gene defects with different prevalence have been associated to one phenotype. It also allows the rapid detection of novel mutations in minor genes which are often not screened as a priority by direct Sanger sequencing. This was the case in our study for three individuals from one family with adRP in which NGS detected a novel PRPF8 mutation in both affected and one unaffected family member (Table 4, Figure 4). In this family, the RP phenotype is mild and therefore it is possible that the unaffected member may develop symptoms later in life or alternatively it may be a case of incomplete penetrance as reported for another splicing factor gene, PRPF31 and recently for PRPF8 as well 19 20 21 22 . Interestingly, a novel TRPM1 mutation was identified in a patient with adCSNB, a gene previously only associated with arCSNB 23 24 25 26 . This is the first report of a TRPM1 mutation co-segregating with ad Schubert-Bornschein type complete CSNB. Since the location of this mutation is not different compared to other mutations leading to arCSNB, it is not quite clear how TRPM1 mutations might lead to either ad or arCSNB. Functional investigations are needed to validate the pathogenicity of this variant. Furthermore, this finding suggests that TRPM1 heterozygous mutation carriers from arCSNB families should be investigated by electroretinography to determine whether they display similar retinal dysfunction as in affected members of the presented adCSNB family. Detection of a novel RPGR splice site mutation in family 146 presented a challenge. The actual disease causing change was concealed under a wrongly annotated rs62638633, which had previously been clinically associated to RP by a German group http://www.ncbi.nlm.nih.gov/sites/varvu?gene=6103&rs=62638633, (personal communication, Markus Preising). These observations indicate that the stringent filtering we applied initially can mask those referenced disease causing variants. Bearing this in mind one can still first investigate unknown variants, but should then examine dbSNP for referenced variants either described to be disease causing, having a low minor allele frequency or present in interesting candidate genes. An accurate discrimination of non-pathogenic polymorphisms versus disease causing polymorphism in SNP databases is warranted to resolve this challenge.

In six families from the investigated cohort the disease causing mutations still remain to be identified. In the Stargardt patient with no pathogenic ABCA4 mutations two variants in CFH were detected, one of which (rs1061170) had previously been reported to predispose to age related macular degeneration (AMD) 27 28 29 . The second CFH change is a novel variant, affecting a highly conserved residue, not found in NGS data from the other 19 samples and never associated with a disease. The variants co-segregated in the only available family members, which were the patient's parents. Apart from the association with AMD, CFH mutations have been previously associated with renal diseases, the most common being membranoproliferative glomerulonephritis and hemolytic uremic syndrome, which can be also associated with an eye phenotype 30 31 . No renal dysfunction was present in our patient. To validate if the two variants identified in CFH are indeed disease causing, the DNA samples from other available family members for co-segregation analysis as well as characterization of functional consequences of the novel variant are needed. One patient with complete CSNB had an affected nephew and thus x-linked inheritance was assumed. However, neither Sanger nor NGS detected a mutation in the only known x-linked gene, NYX, causing cCSNB. To exclude recessive inheritance TRPM1 and GRM6 were investigated in detail. Indeed the patient carried a novel heterozygous TRPM1 variant, which affects a highly conserved amino acid and was not identified in the other 19 samples investigated here (Table 6). However, direct Sanger sequencing of lower covered regions did not identify a second mutation in this gene. Similarly no mutations in GRM6 were identified. These findings outline the need for additional family members to determine, through co-segregation, the pathogenicity of the numerous variants identified by NGS. This was also true for two other families with nonsense mutations in CUBN (Fam795) and RP1L1 (Fam761) (Table 6). The nonsense mutation in CUBN, co-segregated with the phenotype in most of the family members (Figure 5). Had we not had access to additional family members, we might have retained this gene defect as the underlying cause for adCD and considered CUBN as a new gene involved in adCD. None of the other putatively pathogenic mutations identified in CUBN, TRPM1 and GUCY2D co-segregated with the phenotype in this family (Table 6, Figure 5). RP1L1 was already a candidate for adRP 32 but was previously associated with occult macular dystrophy 33 . In our study, this variant did not co-segregate with the phenotype in other affected family members (data not shown).

This NGS study ended with six genetically unresolved families, which can be further investigated with whole exome sequencing. Although, no clear information about the actual percentage of missing gene defects underlying each group of inherited retinal disorders exists, previous studies have reported that in many cases the genetic cause still needs to be determined 18 34 . Whole exome sequencing approaches allow the detection of both, novel and known gene defects, but also generate numerous variants and therefore require the inclusion of more than one DNA sample for each family to rapidly exclude non-pathogenic variants. Due to the higher costs of exome sequencing for one sample compared to targeted sequencing, we propose to initially perform targeted sequencing in the index patient and proceed only after exclusion of a known gene defect to whole exome sequencing.

Conclusions

In summary, our diagnostic tool is an unbiased time efficient method, which not only allows detecting known and novel mutations in known genes but also potentially associates known gene defects with novel phenotypes. This genetic testing tool can now be applied to large cohorts of inherited retinal disorders and should rapidly deliver the prevalence of known genes and the percentage of cases with missing genetic defect for underlying forms of retinal disorders.

List of abbreviations

ad: autosomal dominant; ar: autosomal recessive; as: asymptomatic; het: heterozygous; homo: homozygous; hemi: hemizygous; - not noted; consang.: consanguinity was reported; n.a.: not applicable; CSNB: congenital stationary night blindness; RP: retinitis pigmentosa:

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

IA was involved in the study design, participated in the choice of genes, interpreted the NGS data, clinically investigated patients, collected DNA samples, and has been involved in drafting the manuscript. KB participated in the choice of genes, interpreted the NGS data and has been involved in drafting the manuscript. TL was involved in the study design, participated in the choice of genes and has been involved in drafting the manuscript. SM-S clinically investigated patients and collected DNA samples. M-EL confirmed the NGS data by Sanger sequencing, performed control and co-segregation analysis. AG extracted DNA, confirmed the NGS data by Sanger sequencing, and performed control and co-segregation analysis. AA extracted DNA, confirmed the NGS data by Sanger sequencing, and performed control and co-segregation analysis. CM confirmed the NGS data by Sanger sequencing, and performed control and co-segregation analysis. J-PS performed NGS. ML performed the bioinformatic interpretation of NGS. J-AS clinically investigated patients and participated in the study design. SSB participated in the study design and has been involved in drafting the manuscript. CZ has made the study design, participated in the choice of genes, interpreted the NGS data and wrote the manuscript. All authors read and approved the final manuscript.

Acknowledgements

The authors are grateful to the families described in this study, Dominique Santiard-Baron and Christine Chaumeil for their help in DNA collection and to clinical staff. The project was financially supported by GIS-maladies rares (CZ), Agence Nationale de la Recherche (ANR, SSB), Foundation Voir et Entendre and BQR, Foundation Fighting Blindness (IA, FFB Grant # CD-CL-0808-0466-CHNO and the CIC503 recognized as an FFB center, FFB Grant # C-CMM-0907-0428-INSERM04), Ville de Paris and region Ile de France.

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