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Erschienen in: Orphanet Journal of Rare Diseases 1/2012

Open Access 01.12.2012 | Research

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

verfasst von: Isabelle Audo, Kinga M Bujakowska, Thierry Léveillard, Saddek Mohand-Saïd, Marie-Elise Lancelot, Aurore Germain, Aline Antonio, Christelle Michiels, Jean-Paul Saraiva, Mélanie Letexier, José-Alain Sahel, Shomi S Bhattacharya, Christina Zeitz

Erschienen in: Orphanet Journal of Rare Diseases | Ausgabe 1/2012

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.
Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​1750-1172-7-8) contains supplementary material, which is available to authorized users.

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.
Abkürzungen
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:

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 [24]. 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 [712]. 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 [1317]. 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
1
ABCA4
2
ABCC6
3
ADAM9
4
AHI1
5
AIPL1
6
ALMS1
7
ARL6
8
ARMS2
9
ATXN7
10
BBS10
11
BBS12
12
BBS2
13
BBS4
14
BBS5
15
BBS7
16
BBS9
17
BEST1
18
C1QTNF5
19
C2
20
C2orf71
21
C3
22
CA4
23
CABP4
24
CACNA1F
25
CACNA2D4
26
CC2D2A
27
CDH23
28
CDH3
29
CEP290
30
CERKL
31
CFB
32
CFH
33
CHM
34
CLN3
35
CLRN1
36
CNGA1
37
CNGA3
38
CNGB1
39
CNGB3
40
CNNM4
41
COL11A1
42
COL2A1
43
COL9A1
44
CRB1
45
CRX
46
CYP4V2
47
DFNB31
48
DMD
49
DPP3
50
EFEMP1
51
ELOVL4
52
ERCC6
53
EYS
54
FAM161A
55
FBLN5
56
FSCN2
57
FZD4
58
GNAT1
59
GNAT2
60
GPR98
61
GRK1
62
GRM6
63
GUCA1A
64
GUCA1B
65
GUCY2D
66
HMCN1
67
HTRA1
68
IDH3B
69
IMPDH1
70
IMPG2
71
INPP5E
72
INVS
73
IQCB1
74
JAG1
75
KCNJ13
76
KCNV2
77
KLHL7
78
LCA5
79
LRAT
80
LRP5
81
MERTK
82
MFRP
83
MKKS
84
MKS1
85
MTND1
86
MTND6
87
MT-AP6
88
MTND2
89
MTND5
90
MTND4
91
MYO7A
92
NDP
93
NPHP1
94
NPHP3
95
NPHP4
96
NR2E3
97
NRL
98
NYX
99
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
1
ADCY1
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
2
ANKRD33
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
3
ANXA2
Promotion of choroidal neovascularization
[36]
4
ARL13B
Cilia protein, mutations lead to Joubert Syndrome
[37]
5
BMP7
Regulation of Pax 2 in mouse retina
[38]
6
BSG
-
Thierry Leveillard personal commmunication
7
CAMK2D
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
8
CCDC28B
Modifier for BBS
[39, 40]
9
CLCN7
Cln7-/- mice severe osteopetrosis and retinal degeneration
[41]
10
COL4A3
Alport syndrome, with eye abnormalities
[42, 43]
11
COL4A4
Alport syndrome, with eye abnormalities
[42, 44]
12
COL4A5
Alport syndrome, with eye abnormalities
[42, 45]
13
CUBN
-
Personal communication Renata Kozyraki
14
CYP1B1
glaucoma
[46]
15
DOHH
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
16
DSCAML1
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
17
ESRRB
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
18
FIZ1
Interactor of NRL
[47]
19
GJA9
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
20
GNAZ
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
21
GNGT1
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
22
GPR152
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
23
HCN1
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
24
HEATR5A
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
25
HIST1H1C
Expressed in retina
Expression databases
26
IMPG1
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
27
INSL5
diff. Expression rd1 mouse
Chalmel et al., manuscript in preparatiom
28
KCNB1
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
29
KCTD7
Expressed in retina
Expression databases
30
LASS4
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
31
LRIT2
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom Rd1 mouse
32
LRP2
-
Personal communication Renata Kozyraki
33
MAB21L1
diff. expression Rd1 mouse
Chalmel et al., manuscript in preparatiom
34
MAP2
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
35
MAS1
Degeneration of cones due to expression of Mas1
[48]
36
MAST2
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
37
MPP4
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
38
MYOC
glaucoma
[49]
39
NDUFA12
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
40
NEUROD1
BETA2/NeuroD1 -/- mouse: photoreceptor degeneration
[50]
41
NOS2
glaucoma
[51]
42
NXNL1
Rod-derived cone viability factor
[52]
43
NXNL2
Rod-derived cone viability factor 2
[53]
44
OPN1MW2
Cone opsin, medium-wave-sensitive2
[54]
45
OPTN
glaucoma
[55]
46
PFKFB2
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
47
PIAS3
Rod photoreceptor development
[56]
48
PKD2L1
Diff. expression in human retinal detachment
Delyfer et al. 2011 submitted
49
PLEKHA1
Age-related macular degeneratiom
[57]
50
PPEF2
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
51
RAB8A
Interacts with RPGR, role in cilia biogenesis and maintenance
[58]
52
RABGEF1
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
53
RCVRN
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
54
RGS20
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
55
RNF144B
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
56
RORB
Rod photoreceptor development in mice
[59]
57
RXRG
Retinoic acid receptor, highly expressed in the eye
Expression databases
58
SGIP1
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
59
SLC16A8
Altered visual function in ko-mice
[60]
60
SLC17A7
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
61
STAM2
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
62
STK35
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
63
STX3
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
64
SV2B
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
65
TBC1D24
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
66
THRB
Essential for M-cone development in rodents
[61]
67
TMEM216
Cilia protein, mutations lead to Joubert and Meckel syndrome
[62]
68
TMEM67
Cilia protein, mutations lead to Joubert
[63]
69
TRPC1
diff. expression rd1 mouse
diff. expression Rd1 mouse
70
UHMK1
diff. expression rd1 mouse
diff. expression Rd1 mouse
71
VSX1
Stimulator for promoter NXNL1
[64]
72
VSX2
Stimulator for promoter NXNL1
[64]
73
WDR17
diff. expression rd1 mouse
diff. expression Rd1 mouse
74
WDR31
diff. expression Nxnl1-/- mouse
[65]
75
WISP1
diff. expression rd1 mouse
Chalmel et al., manuscript in preparatiom
76
XIAP
Protects photoreceptors in animal models of RP
[66]
77
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.

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: Poly morphism Phen otyping, 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
11
13
yes
21.3-22.5
CIC00140, F108
adRP
PRPF31
c.997delG
p.E333SfsX5
het
-
-
no
5.0-5.2
CIC00238, F165
arCSNB
TRPM1
c.1418G > C
p.R473P
homo
0
38
yes
36.7
CIC00707, F470
Best and adCSNB see Table 5
BEST1
c.73C > T
p.R25W
het
40
38
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
25
22
[67]
yes
CIC0000893, F574
adRP
RHO, PRPF31, PRPH2, RP1
NR2E3
c.166G > A
p.G56R
het
5
3
[68]
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
0
193
[13, 69]
yes
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
39
38
yes
moderately conserved
possibly damaging
tolerated
CIC000348, F232
adRP, mild
RHO, PRPF31, PRPH2, RP1, adRP chip
PRPF8
c.6992A > G
p.E2331G
het
13
10
yes
moderately conserved
possibly damaging
affect protein function
CIC000346, F232
adRP
-
PRPF8
c.6992A > G
p.E2331G
het
5
9
yes
moderately conserved
possibly damaging
affect protein function
CIC000347, F232
as
adRP
-
PRPF8
c.6992A > G
p.E2331G
het
15
17
yes
moderately conserved
possibly damaging
affect protein function
CIC04240,
F2025
arRP, consang., detailed clinic in [70]
RS1
CRB1
c.2219C > T
p.S740F
homo
2
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
30
22
yes
conserved
splice site
n.a.
n.a.
CIC04094,
F1915
icCSNB
-
CACNA1F
c.973C > T
p.Q325X
hemi
0
28
yes
n.a.
n.a.
n.a.

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
77
61
yes
but reported as polymorphism
[71]
    
c.6764G > T
p.S2255I
no additional variants in lower covered exons
het
2
7
yes
but reported as polymorphism
[72]
   
CFH
c.3482C > A
p.P1161Q
het
77
52
yes
conserved, probably damaging
    
c.1204C > T
p.H402Y
het
94
87
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
61
44
yes, did not co-segregate
 
   
GUCY2D
c.1499C > T
p.P500L
het
41
34
yes, did not co-segregate
 
   
TRPM1
c.3904T > C
p.C1302R
het
102
99
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
6
2
false positive, not found by Sanger
 
   
DSCAML1
c.592C > T
p.R198C
het
70
81
yes, but no additional mutation
 
   
TBC1D24
c.641G > A
p.R214H
het
27
12
yes, but no additional mutation
 
   
TMEM67
c.1700A > G
p.Y567C
het
80
58
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
0
140
no
Polyphen and Sift benign, not conserved
   
PKD2L1
c.1027C > T
p.R343C
het
63
68
  
    
c.1202T > G
p.V401G
het
25
19
 
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
7
7
yes
affected sister also both variants but both come from father, no other variant in lower covered region.
    
c.2644C > A
p.R882S
het
27
14
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
no
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.

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 [1922]. Interestingly, a novel TRPM1 mutation was identified in a patient with adCSNB, a gene previously only associated with arCSNB [2326]. 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) [2729]. 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.

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.
This article is published under license to 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.

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.
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Metadaten
Titel
Development and application of a next-generation-sequencing (NGS) approach to detect known and novel gene defects underlying retinal diseases
verfasst von
Isabelle Audo
Kinga M Bujakowska
Thierry Léveillard
Saddek Mohand-Saïd
Marie-Elise Lancelot
Aurore Germain
Aline Antonio
Christelle Michiels
Jean-Paul Saraiva
Mélanie Letexier
José-Alain Sahel
Shomi S Bhattacharya
Christina Zeitz
Publikationsdatum
01.12.2012
Verlag
BioMed Central
Erschienen in
Orphanet Journal of Rare Diseases / Ausgabe 1/2012
Elektronische ISSN: 1750-1172
DOI
https://doi.org/10.1186/1750-1172-7-8

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