Targeted next generation sequencing identifies novel NOTCH3 gene mutations in CADASIL diagnostics patients
Maksemous et al. Human Genomics
Targeted next generation sequencing identifies novel NOTCH3 gene mutations in CADASIL diagnostics patients
Neven Maksemous 0
Robert A. Smith 0
Larisa M. Haupt 0
Lyn R. Griffiths 0
0 Genomics Research Centre, Institute of Health and Biomedical Innovation (IHBI), School of Biomedical Sciences, Queensland University of Technology (QUT) , Q Block, 60 Musk Ave, Kelvin Grove Campus, Brisbane 4059, Queensland , Australia
Background: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a monogenic, hereditary, small vessel disease of the brain causing stroke and vascular dementia in adults. CADASIL has previously been shown to be caused by varying mutations in the NOTCH3 gene. The disorder is often misdiagnosed due to its significant clinical heterogeneic manifestation with familial hemiplegic migraine and several ataxia disorders as well as the location of the currently identified causative mutations. The aim of this study was to develop a new, comprehensive and efficient single assay strategy for complete molecular diagnosis of NOTCH3 mutations through the use of a custom next-generation sequencing (NGS) panel for improved routine clinical molecular diagnostic testing. Results: Our custom NGS panel identified nine genetic variants in NOTCH3 (p.D139V, p.C183R, p.R332C, p.Y465C, p. C597W, p.R607H, p.E813E, p.C977G and p.Y1106C). Six mutations were stereotypical CADASIL mutations leading to an odd number of cysteine residues in one of the 34 NOTCH3 gene epidermal growth factor (EGF)-like repeats, including three new typical cysteine mutations identified in exon 11 (p.C597W; c.1791C>G); exon 18 (p.C977G; c. 2929T>G) and exon 20 (p.Y1106C; c.3317A>G). Interestingly, a novel missense mutation in the CACNA1A gene was also identified in one CADASIL patient. All variants identified (novel and known) were further investigated using in silico bioinformatic analyses and confirmed through Sanger sequencing. Conclusions: NGS provides an improved and effective methodology for the diagnosis of CADASIL. The NGS approach reduced time and cost for comprehensive genetic diagnosis, placing genetic diagnostic testing within reach of more patients.
AmpliSeq Custom Panel; CADASIL; Next-generation sequencing; NOTCH3
The stroke syndrome CADASIL [MIM 125310] (cerebral
autosomal dominant arteriopathy with subcortical infarcts
and leukoencephalopathy) disorder results in neuronal
white matter abnormalities and is characterised by a variety
of symptoms including, vascular degeneration, recurrent
subcortical ischaemic strokes, progressive cognitive decline,
dementia, migraine with aura (22 % of patients) and
premature death . The unique deposition of granular
osmiophilic material (GOM) in systemic and brain vasculature
differentiates CADASIL patients from those suffering
similar hereditary vascular disorders . CADASIL is often
misdiagnosed due to its significant clinically heterogeneic
manifestation with familial hemiplegic migraine and several
ataxia disorders, as these disorders have an autosomal
dominant mode of inheritance and share clinical characteristics
such as hemiplegic migraine, migraine with typical aura
and progressive ataxia [3–6]. Mutations implicated in
CADASIL have been identified on chromosome 19,
specifically within NOTCH3 (MIM 600276), which encodes a
transmembrane receptor primarily expressed in vascular
smooth muscle cells. NOTCH3 located at 19p13 is 33
exons long and spans approximately 7 kb . Currently, at
least 200 mutations resulting in an odd number of cysteine
residues are known to be associated with CADASIL. These
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mutations all occur in exons 2–24 of NOTCH3 that encode
34 epidermal growth factor (EGF)-like repeats in the
extracellular domain of the NOTCH3 protein. The large number
of exons combined with their high GC content makes
comprehensive sequencing of this gene with traditional Sanger
sequencing (SS) expensive and time consuming. With the
advent of next-generation sequencing (NGS), the
sequencing of target genes, regions, exomes or whole genomes,
provides cost-effective, high-throughput screening suitable
for molecular diagnostics enabling detection of a wide array
of mutations with sensitivity and specificity. Here, we have
performed targeted gene sequencing using a custom
fivegene NGS panel , encompassing the coding sequences,
20–100 bp exon/intron boundaries and the 5′ and 3′UTR
regions of NOTCH3 in 44 patients.
NGS-panel sequencing output
The sequencing output data from the Ion Torrent PGM
was analysed using the Ion Torrent platform-specific
software Torrent Suite V3.6 (Thermo Fisher Scientific,
Scoresby, Victoria, Australia). The 44 samples were
sequenced using seven different Ion 316 chips, to generate
an average sequencing of 3,303,300 total reads, 477.4 Mb
total bases sequenced, and 472.2 Mb with 99 % of bases
aligned to the human complete genome (hg19) per Ion 316
chip. For all samples sequenced, the average read depth
across the target region was 560.65×, while the average
percentage of target bases covered at 20× or greater was 96
% and the average uniformity of coverage was 90.64 %.
Sequencing data analysis
Comprehensive screening for NOTCH3 using the
AmpliSeq Custom NGS panel  (Thermo Fisher Scientific,
Scoresby, Victoria, Australia) for targeted gene sequencing
was conducted on 44 patients, previously screened for
standard sequencing exons (3 and 4) and/or (2,11, 18 and
19) by SS and classified as being negative for known
Initial analysis using the IonReporter software
(Thermo Fisher Scientific, Scoresby, Victoria, Australia)
identified 42 variants scattered over NOTCH3 among
the 44 patients. An overview of all variants detected in
our study is shown in Additional file 1: Table S1 online.
Of these, nine particularly notable genetic variants were
identified in 10 patients (22.7 %) out of the 44 subjects:
five novel potential mutations
(NOTCH3:NM_000435:exon4:c.416A>T:p.D139V, exon1 1:c.1791C>G:p.C597W
and c.1820G>A: p.R607H, exon18: c.2929T>G,:
p.C977G; and exon20: c.3317A>G: p.Y1106C); three
previously reported disease-causing missense mutations
(NOTCH3:NM_000435:exon4:c.547T>Cp.C183R , exon
6:c.994C>T, p.R332C [9, 10]; and exon9: c.1394A>G:
p.Y465R ) and one novel synonymous genetic variant
in NOTCH3:NM_000435:exon16:c.2439G>A: p.E813E
[Tables 1 and 2]. Clinical information for all samples
was not available [see Additional file 2: Table S2];
however, the following clinical parameters were attributed
to the relevant samples in our cohort: (i) white matter
abnormalities were seen in patients with E813E, C183R
and R332C mutations; (ii) positive skin biopsy signs
were reported in patients with C977G, Y1106C, Y465C
and C183R and (iii) a family history of dementia and/or
stroke was reported in patients with E813E, C977G,
Y1106C, C183R, R332C and R465C mutations.
Molecular genetic testing using the custom NGS panel
encompassing five genes (NOTCH3, CACNA1A, ATP1A2,
SCN1A and TRESK genes) identified two remarkable
variants in case C-36
(CACNA1A:NM_023035:c.832G>T:p.A278S and SCN1A:NM_006920:c.3924A>T: p.E1308D
[Table 1]). These mutations correspond to highly
conserved amino acid residues according to four in silico
prediction tools (PhyloP of score of >2.0, PolyPhen2 HVar of
score >0.7, and MutationTaster with a damaging effect and
GERP++ score above 5).
In addition to these variants, nine rare single nucleotide
polymorphisms (SNPs) in the NOTCH3 gene with minor
allele frequency (MAF) ≤0.1 % were observed in nine
patients with no other causative mutation found in NOTCH3
[Additional file 1: Table S1 online and Table 3]. One
patient (case C-3) was shown to carry two rare amino acid
changing variants p.S497L and p.A1020P in exons 9 and
19 of NOTCH3, respectively. All nine SNPs were further
assessed by seven in silico prediction programmes with
three of these variants (p.S497L, p.P496L and p.Y220Y)
shown to have a damaging effect by MutationTaster.
All variants detected by NGS and reported in this
study were visually confirmed using Integrative
Genomics Viewer (IGV v2.3) software  and compared with
NCBI reference sequences . In order to verify the
accuracy of potential novel mutations identified by NGS,
SS was performed for all samples with the five
nonsynonymous variants along with the synonymous new
variant showing complete consistency (100 %) between
the two methods [Fig. 1].
Analyses of the potential functional significance of the
six novel NOTCH3 genetic variants identified the
C597W, C977G and Y1106C missense mutations to be
pathogenic by six of the seven genetic prediction
software programmes (PhyloP, SIFT, PolyPhen2,
MutationTaster, AGVGD and PhD-SNP) [Table 1].
Finally, we compared the potential functional
significance of the three known pathogenic missense
mutations (C183R, R332C and Y465C) with the six novel
genomic variants identified using the same seven in
silico software programmes. The C183R and R332C
mutations showed a high potential damaging effect when
analysed by all seven programmes used; in contrast, the
Fig. 1 Sequences (reverse complement) of the six novel genetic variants in NOTCH3 identified by NGS. The figure shows the six heterozygous
exonic point variants: a p.D139V in exon 4, b p.C597W in exon 11, c p.R607H in exon 11, d synonymous variant p.E813E in exon 16, e p.C977G in
exon 18 and f p.Y1106C in exon 20 identified in this study. Only bases non-concordant with consensus sequence are displayed in the target reads
with the integrative genomics viewer IGV . The normal nucleotide and protein sequences are depicted at the bottom and top of the figure
Y465C mutation showed a tolerated or benign effect in
four of the seven in silico programmes [Table 2].
Molecular genetic testing is an essential tool for accurate
CADASIL diagnosis. Several diagnostic approaches have
been used for CADASIL, in particular the use of skin
biopsy to detect unusual NOTCH3 expression. However,
despite the widespread use of biopsy testing, the low
sensitivity of this method in CADASIL diagnosis has
been reported . In addition, previous work by
Markus et al. tested the sensitivity of single strand
conformation polymorphism (SSCP) analysis for
detecting NOTCH3 mutations, with an effective success rate of
80 to 85 % . More recently, He et al. reported that
varying and population-dependant results in the
effectiveness of using the pre-genetic “CADASIL scale”
screening tool which evaluates clinical presentations and
neuroimaging data in an effort to minimise NOTCH3
gene testing [15, 16]. As such, current diagnosis relies
on the screening of all exons by sequencing to identify
mutations in NOTCH3.
We have previously demonstrated the efficiency of our
NGS panel for detecting known and novel mutations in a
cohort of episodic ataxia patients and increasing the rate
of mutation detection by 48 % . We have now utilised
this custom targeted massively parallel NGS panel to
examine the coding sequences, intron/exon boundaries
including 20–100 bases of flanking intronic nucleotides
and the 5′ and 3′UTR regions of NOTCH3 in a cohort of
44 patients with clinically suspicious CADASIL.
Targeted gene sequencing analysis efficiently identified
nine novel genetic variants in NOTCH3, of which five
nonsynonymous mutations (p.D139V, p.C597W, p.R607H,
p.C977G and p.Y1106C) and one synonymous variant
(p.E813E) have not been previously described. In addition,
three missense mutations previously reported as
pathogenic (C183R , R332C [9, 10] and Y465C ) but not
previously identified in our diagnostics cohort were also
detected . In total, six typical CADASIL mutations
involving cysteine alterations were identified in seven
patients (15.9 %) out of 44 subjects, a detection rate higher
than previously reported by Fernandez et al. and Bianchi et
al. [18, 19].
Interestingly, previous studies have revealed
differences in the spectrum of NOTCH3 mutations between
Asian and Italian populations and populations of
Caucasian ethnicity [18, 20, 21]. Our results also showed no
evidence of strong clustering of NOTCH3 mutations in
specific exons. The variants identified in this study occur
in seven different exons (4, 6, 9, 11, 16, 18 and 20)
within the EGF-like repeat regions of the gene. The
patient cohort encompasses different ethnic backgrounds,
reflecting the diversity of the Australian population. This
highlights the potential confounding factor in nations of
multiple ethnic backgrounds, where mutations may
occur at multiple sites making molecular diagnosis
difficult and time consuming if using traditional SS
methodologies. While exonic clustering in ethnic
groups is likely due to founder effects, de novo
mutations resulting in mutations in ethnically homogenous
populations are possible. In this instance, the use of
SS may still miss mutations in a proportion of
patients suggesting that screening of all coding regions
in NOTCH3 is of benefit for the comprehensive
molecular diagnosis of CADASIL.
Six of the missense mutations identified were
stereotypical CADASIL mutations, resulting in a loss or gain
of one of the six cysteine residues (4, 8, 11, 15, 25 and
28) of the EGF-like repeats located in the extracellular
domain of NOTCH3 . Any mutation within the
cysteine residues (a gain or loss) leads to an odd number of
cysteine residues and result in impaired dimerisation of
NOTCH3 or formation of inappropriate disulphide
bonds causing aberrant NOTCH3 signaling [22, 23]. As
such, these three mutations (p.C597W, p.C977G and
p.Y1106C) were considered to be disease-causing and
associated with the pure and typical pathogenetic
mechanisms of CADASIL [4, 24]. The substitution of the
p.C597S has been previously identified in an Arabic
family , while the substitution of p.C977S has been
reported in a Chinese patient  with both mutations
found to be associated with CADASIL pathogenesis.
We also observed two novel amino acid substitutions
(p.D139V and p.R607H) not directly involving cysteine
residues, predicted to be possibly damaging and benign,
respectively. As discussed by Roy et al. , there is
some controversy over the classification non-cysteine
residue altering variants and their significance to
CADASIL. Several NOTCH3 alterations that do not affect
cysteine residues have been reported in families with
CADASIL, which may involve other disruptions to
protein function, though these may result in changes that
effectively change cysteine residue availability [27–32]. It
is worth noting that the predicted score for p.D139V by
the SIFT programme (0.06) was more deleterious than
the known pathogenic mutation p.Y465C, with a score
of 0.08, technically considered to be benign. A SIFT
score from 0 to 0.05 indicates that the amino acid
change has a damaging effect. Further investigation of
this mutation is warranted to determine the effect of
these non-cysteine affecting changes on NOTCH3
function as well as on mediating signal transduction for
vascular development and inducing the pathology of
CADASIL. This provides new insights into the diagnosis
of and pathomechanisms causing CADASIL.
The last novel synonymous variant we identified
(p.E813E) was predicted by the MutationTaster programme
to cause the gain of an RNA splicing donor site. This gain
may result in altered protein function and therefore, despite
being silent, this variant could be a real mutation causing
CADASIL. Direct functional evaluation of NOTCH3 in this
patient is needed to confirm this hypothesis, but such
studies were not able to be performed at this time.
The in silico analysis tools to analyse the detected
variants also revealed some interesting potential
ramifications of the previously identified p.Y465C mutation. In
2003, Razvi et al. described this amino acid substitution
as a mutation causing CADASIL . In contrast,
during our analysis, the computational tools predicted this
amino acid change as tolerated or benign. The PhyloP
score of 0.0272 and SIFT score of 0.08 (damaging score
<0.05) suggest this amino acid is not conserved. The
mutation is a classical CADASIL mutation; however, as
stated by Joutel et al. “mutations can be unambiguously
classified as pathogenic when they lead to an uneven
number of cysteine residues in one of the 34 EGFR
domains constituting the extracellular domain of the
receptor” . This discrepancy between evolutionary
conservation and functional correlation models suggests
caution when using functional prediction software in
assigning a role to missense mutations involving cysteine
residues in NOTCH3. The in vivo effect of amino acid
substitutions should be the final arbiter for precisely
describing their role in causing CADASIL, but as such
tests are laborious to undertake, they are rarely
performed for diagnoses. Careful consideration of the
symptomatic profile may be useful in such cases and in the
future when sufficient mutation data has accumulated
offering clinicians more precision in ascribing the
functional role of mutations in CADASIL.
Interestingly, in this study, patient C-36 demonstrated
compound heterozygosity for two missense mutations in
the CACNA1A and SCN1A genes (not normal target
genes for CADASIL screening) [Table 1]. Mutations
within these two ion channel genes are associated with
various autosomal dominant disorders: hemiplegic
migraine, episodic ataxia type 2, spinocerebellar ataxia
type 6 and epilepsy with previously reported
overlapping symptoms among these disorders [33–35]. It is
worth noting that the p.E1297D mutation in SCN1A
gene was previously reported in an Italian family with
idiopathic childhood epilepsy . The linkage
between CACNA1A and SCN1A gene mutations and
CADASIL has not previously been reported; therefore,
an ongoing study in our lab will investigate the effect
of these two variants/genes on CADASIL disease
In terms of the clinical classification of the detected
genetic variants, the full available evidence needs to be
considered. Typical CADASIL mutations involve the
addition or elimination of a cysteine residue in one of
the 34 NOTCH3 gene epidermal growth factor
(EGF)like repeats, resulting in mismatched disulphide bridging
and altered protein function, a hypothesis which has
been borne out by observational and functional studies
[37, 38]. Under the current American College of Medical
Genetics and Genomics (ACMG) guidelines for variant
classification, functional studies supporting a damaging
effect for a variant on gene function constitute strong
evidence for pathogenicity. Each of the cysteine altering
variants also has multiple moderate and supporting lines
of evidence. These include presence in a
diseaseassociated functional domain; presence at a loci where
another pathogenic mutation is known (as determined
by searching HGMD, LOVD and VEP databases);
absence from controls in population databases (1000
Genomes, dbSNP, ExAC); being the kind of variant
(missense SNV) associated with the disease; presence in
an individual with a clear phenotype; cosegregation with
disease in family members (only for patients C-10 and
C-44) and multiple in silico analyses predicting
pathogenicity. This combination of evidence is sufficient to
characterise them as pathogenic or disease-causing
mutations according to the ACMG guidelines .
For the non-cysteine altering NOTCH3 variants, there
is less information available. Family segregation analysis
and clinical information were not available for patients
C-11 (p.D39V) or C-15 (p. R607H). Despite being novel
amino acid changing variants in loci where
diseasecausing mutations are known to exist and/or functional
domains, there is insufficient strength of evidence to
classify either variant as pathogenic or likely pathogenic.
Additionally, both these patients had complex
phenotypes that do not precisely map to CADASIL, and share
features of episodic ataxia or familial hemiplegic
migraine, indicating a potential overlapping
pathophysiology or comorbidities with these disorders. Thus, these
variants should be classified as variants of uncertain
significance (VOUS) according to the ACMG guidelines.
Patient C-24 with the synonymous variant (p.E318E) had
family history indicative of CADASIL, but no other
supporting evidence, though neither does the variant have
any criteria for being classified as benign. This variant
has also been classified as a VOUS.
Patient C-36, who bears variants in both CACNA1A
and SCN1A also, had no family members available for
further investigation. Neither variant has sufficient
evidence to indicate direct pathogenicity, despite being in
regions of these genes known to harbour disease-causing
mutations. Additionally, their presence in a gene which
causes symptoms overlapping with CADASIL indicates a
possible complex pathophysiology that requires more
research. Hence, these variants have been classified as
Finally, nine rare variants were identified in nine
patients with no other causative mutation in NOTCH3
[Table 3]. Of these, three amino acid changing variants
(p.S497L, p.A1020P and p.H1133Q) were recently
reported by Abramycheva et al.  as normal
polymorphisms in Russian CADASIL patients. However, in this
study, patient C-3 was found to carry non-cysteine
NOTCH3 gene variants (p.S496L and p.A1020P). As yet,
a comparison of the effect of these two non-cysteine
variants on the pathogenic mechanisms of CADASIL or
CADASIL-like phenotype  to a single non-cysteine
variant on disease pathogenesis has not been
We have identified classical CADASIL-causing
mutations as well as a number of amino acid changing
variants that have uncertain causative effects on this disease.
The study of a larger population cohort of cases
including symptomatic detail will likely provide more clinical
and molecular information about their impact as well as
the potential effect of any rare SNPs. Most interestingly,
our results indicate that there may be other CADASIL
gene/genes yet to be identified for inclusion in future
NGS technologies provide an effective method for
CADASIL and related disease diagnosis. Sequencing
large but targeted regions of interest of pooled DNA
from multiple samples is a promising tool for the
discovery of both known and novel variants associated with
disease. Compared with traditional SS, the NGS platform
provides increased accuracy along with reduced time
and assay costs necessary to perform routine genetic
diagnosis of CADASIL in ethnically heterogeneous
populations, putting such testing within reach of more
Materials and methods
Forty-four patients with a suspected clinical diagnosis of
CADASIL were re-screened using the NGS approach.
Patients referred to the Genomics Research Centre
(GRC) diagnostic laboratory for CADASIL molecular
testing through neurologists from Australia and New
Zealand and showed no mutations when using SS in our
standard exon sequencing (3 and 4) at the first stage and
(2, 11, 18 and 19) second stage . Re-sequencing of
the 44 patients was based on the clinical information
had provided (i.e. positive skin biopsy results for
CADASIL or white matter changes in their MRI) indicating
that CADASIL-causing mutations may be present.
Ion AmpliSeq custom panel design
The AmpliSeq design target used in this report
comprised the coding exons, exon/intron junctions and UTR
regions of the NOTCH3 gene. The Ampliseq automated
primer design tool (http://www.ampliseq.com) was used
to design primers covering 92.79 % of the desired target
area (8071 bp) aligned to the reference human genome
(hg 19). The missing regions include a 175 bp region in
exon 1 (position 15311617-15311792 on chromosome
19) and a 407 bp region in exon 24 (position
1528842715288834 on chromosome 19). The remainder of the 33
exons in the NOTCH3 gene were included at 100 %
Genomic DNA was previously purified from peripheral
blood samples using standard extraction conditions
using Qiagen QIAamp DNA Blood Midi Kits as
recommended by the manufacturer. The Qubit dsDNA High
Sensitivity (HS) Assay Kit (Thermo Fisher Scientific,
Scoresby, Victoria, Australia) was used to ensure
accuracy of DNA concentration input (10 ng/μL) to NGS
Library preparation was performed using the Ion
AmpliSeq library kit 2.0 (Thermo Fisher Scientific, Scoresby,
Victoria, Australia) according to the standard protocol (Cat.
no. 4480441, Rev. 4.0). Briefly, for the multiplex PCR
amplification, 10 ng of each genomic DNA sample was amplified
using the optimised modification method generated in our
laboratory allowing each primer pool to be amplified as a
5-μL reaction, rather than a 20-μL reaction (protocol is
available upon request). This was performed using 1 μL of
5× Ion AmpliSeq HiFi Master Mix, 2.5 μL of 2× AmpliSeq
Custom primer pool, 0.5 μL nuclease-free water and 1 μL
(10 ng/μL) of DNA. The reaction mix was heated for 2 min
at 99 °C for enzyme activation, followed by 18 two-step
cycles of 99 °C for 15 s and 60 °C for 4 min, ending with a
holding period at 10 °C.
After cycling, the two 5 μL/reaction pools for each
sample were combined into a single well with a total volume
10 μL. The pooled amplified samples were partially
digested using 1 μL FuPa enzyme per sample at 50 °C for
10 min and 55 °C for 10 min followed by enzyme
inactivation at 60 °C for 20 min. To enable multiple sample
libraries to be loaded per chip, 2 μL of a unique diluted
Barcode Adapter mix including Ion Xpress Barcode
(numbered 1-16) and Ion P1 Adaptor at standard volumes was
ligated to the end of the digested amplicons using 1 μL
DNA ligase for 30 min at 22 °C followed by ligase
inactivation for 10 min at 72 °C. The resulting unamplified
adaptor-ligated libraries were purified using the 22.5 μL
Agencourt AMPure XP system (Beckman Coulter, Brea,
CA, USA) followed by addition of 75 μL freshly prepared
70 % ethanol to each library.
After purification, the amplicon libraries were further
amplified to enrich material for accurate quantification
using 25 μL Platinum PCR SuperMix High Fidelity and
1 μL of library Amplification Primer Mix (Ion AmpliSeq
library kit 2.0, Thermo Fisher Scientific, Scoresby,
Victoria, Australia), at 98 °C for 2 min followed by five
two-step cycles of 98 °C for 15 s and 60 °C for 1 min.
The amplified amplicon libraries were then purified
using 12.5 μL Agencourt AMPure XP Reagent followed
by a second purification step with 30 μL AMPure XP
and 75 μL of freshly prepared 70 % ethanol added to
each library. The concentration and size of amplicons
was then determined using an Agilent BioAnalyzer DNA
High-Sensitivity chip (Agilent Technologies, Santa Clara,
CA, USA), according to manufacturers’ instructions.
After quantification, each library was diluted to a
concentration of ~10 pM prior to template preparation.
Subsequently, libraries (n = 16) were pooled in equimolar
amounts prior to further processing.
Template preparation (emulsion PCR) and sequencing
Emulsion PCR, emulsion breaking and enrichment
(template preparation) were performed using the Ion PGM
OT2 200 Template Kit (Thermo Fisher Scientific, Scoresby,
Victoria, Australia), according to the manufacturers’
instructions (part no. 4480974 Rev. 4.0).
After preparation of the ISPs, sequencing was
performed with an Ion Torrent Personal Genome Machine
(PGM) system using Ion Sequencing 200 Kit V2 and an
Ion 316 Chip (Thermo Fisher Scientific, Scoresby,
Victoria, Australia) according to the manufacturers’
procedures (Cat. no.4482006 Rev.1.0).
The Ion Torrent PGM sequence data was mapped to the
complete human genome (hg19) by the Ion Torrent Suite
software and Torrent Server along with Torrent Mapping
Alignment Program optimised to Ion Torrent data. The
bam format file generated by Torrent Suite was uploaded
and visualised for human examination using Integrative
Genomics Viewer (IGV) 2.3 software . The Ion
Reporter software 4.0 (Thermo Fisher Scientific, Scoresby,
Victoria, Australia) was used to analyse data from Torrent
PGM. The software identifies variants and performs
automated annotation on Ion PGM data. Variants were
classified into simple categories, summarised into a report which
included links to appropriate databases for known variants.
DNA and protein sequences from NGS and SS were
compared with the NCBI reference sequences  and
the UCSC genome browser . All rs ID numbers,
locations, allele frequencies and genotypes for all variants
were determined based on SNPs reported in the dbSNP
database  and further analysed in the 1000 Genomes
data set. To predict the effect of non-synonymous single
nucleotide substitutions on protein structure, function
or phenotype, we used the wANNOVAR programme
[42, 43] which included the use of five functional
prediction software programmes for non-synonymous variants
(PhyloP , SIFT , PolyPhen2 , MutationTaster
 and GERP++ ). In silico prediction programmes
including AGVGD  and PhD-SNP  were also
used to predict causative variants. For synonymous
variants and variants in non-coding regions, the
MutationTaster  software alone was used. All variants
detected were examined for associated information in
the public databases (at a minimum, dbSNP, OMIM,
LOVD, 1000 Genomes and HGMD) and in the
Sanger sequencing (SS)
All detected novel mutations by NGS were further
investigated by SS. Molecular analysis of the NOTCH3 gene was
performed according to a previously described protocol
. Briefly, genomic DNA was extracted using Qiagen
QIAamp DNA Blood Midi kits. DNA was amplified by
PCR to screen the exons containing novel mutations and
was performed with the primers shown in Additional file 3:
Table S3 online. PCR amplification for all exons were
conducted as previously described , and cycling protocols
is available for all exons upon request. PCR products were
purified using Affymetrix ExoSap-IT reagent (ExoSap-IT,
USB Corporation, Staufen, Germany) and directly
sequenced for both sense and antisense strands using Big Dye
Terminator V3.1 (Applied Biosystems, Foster City,
CA, USA) on an ABI 3500 Genetic Analyser (Applied
Biosystems) according to established procedures.
Sequences were analysed with Chromas 2.33 software
(Technelysium, Brisbane, Queensland, Australia).
Additional file 1: Table S1. Variants detected in NOTCH3 gene by NGS
in all 40 patients the transcript RefSeq NM_000435.2. (DOC 75 kb)
Additional file 2: Table S2. Overview of clinical data for patients tested
using the NGS panel with a clinical diagnosis of CADASIL. (DOC 59 kb)
Additional file 3: Table S3. List of primers used for PCR amplification
of exons with novel NOTCH3 mutations and variants detected by NGS.
(DOC 28 kb)
CADASIL: Cerebral autosomal dominant arteriopathy with subcortical infarcts
and leukoencephalopathy; DNA: Deoxyribonucleic acid; EGF: Epidermal
growth factor; GERP: Genomic evolutionary rate profiling; GOM: Granular
osmiophilic material; GRC: The Genomics Research Centre; IGV: Integrative
Genomics Viewer; NATA: National Association of Testing Authorities,
Australia; NCBI: National Centre for Biotechnology Information; NGS:
Nextgeneration sequencing; NOTCH3: Notch, Drosophila, Homolog of, 3;
PCR: Polymerase chain reaction; PGM: Personal Genome Machine;
SNPs: Single nucleotide polymorphisms; UTR: Untranslated region
The authors express their gratitude to all neurologists for referring patients
and supplying clinical data to our NATA accredited diagnostic lab at the
Genomics Research Centre, IHBI, QUT. We thank A/Prof Rod Lea and Dr Miles
Benton for help with bioinformatic analysis, interpretation and advice.
Neven Maksemous was supported by a QUT Postgraduate Scholarship. This
work was supported by an Australian International Science Linkages grant
and by infrastructure purchased with Australian Government EIF Super
Science Funds as part of the Therapeutic Innovation Australia - Queensland
Node project and by the Migraine Research Foundation, NY, USA.
NM performed the experimental, sequence analysis research, data analysis
and drafted the manuscript with input from all authors. LMH contributed to
the interpretation of the data, read, edited and approved the manuscript.
LRG and RAS conceived the project, supervised research and analysis, read,
edited and approved the manuscript.
Ethics approval and consent to participate
Informed consent was obtained by physicians for all patients for genetic
testing prior to delivery of samples to the laboratory, and this study was
approved by the Queensland University of Technology (QUT) Ethics
Committee (Approval Numbers: 1500000879).
1. Chabriat H , et al. Clinical spectrum of CADASIL: a study of 7 families. Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy . Lancet . 1995 ; 346 ( 8980 ): 934 - 9 .
2. Ruchoux MM , et al. Presence of ultrastructural arterial lesions in muscle and skin vessels of patients with CADASIL . Stroke. 1994 ; 25 ( 11 ): 2291 - 2 .
3. Chabriat H , et al. Autosomal dominant migraine with MRI white-matter abnormalities mapping to the CADASIL locus . Neurology . 1995 ; 45 ( 6 ): 1086 - 91 .
4. Joutel A , et al. Notch3 mutations in CADASIL, a hereditary adult-onset condition causing stroke and dementia . Nature . 1996 ; 383 ( 6602 ): 707 - 10 .
5. Thomsen LL , Olesen J , Russell MB . Increased risk of migraine with typical aura in probands with familial hemiplegic migraine and their relatives . Eur J Neurol . 2003 ; 10 ( 4 ): 421 - 7 .
6. Vedeler C , Bindoff L. A family with atypical CADASIL . J Neurol. 2011 ; 258 ( 10 ): 1888 - 9 .
7. Maksemous N , et al. Next-generation sequencing identifies novel CACNA1A gene mutations in episodic ataxia type 2 . Mol Genet Genomic Med . 2016 ; 4 ( 2 ): 211 - 22 .
8. Dichgans M , et al. Small in-frame deletions and missense mutations in CADASIL: 3D models predict misfolding of Notch3 EGF-like repeat domains . Eur J Hum Genet . 2000 ; 8 ( 4 ): 280 - 5 .
9. Oliveri RL , et al. A novel mutation in the Notch3 gene in an Italian family with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy: genetic and magnetic resonance spectroscopic findings . Arch Neurol . 2001 ; 58 ( 9 ): 1418 - 22 .
10. Tang SC , et al. Arg332Cys mutation of NOTCH3 gene in the first known Taiwanese family with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy . J Neurol Sci . 2005 ; 228 ( 2 ): 125 - 8 .
11. Razvi SS , et al. Diagnostic strategies in CADASIL. Neurology . 2003 ; 60 ( 12 ): 2019 - 20 . author reply 2020 .
12. Thorvaldsdottir H , Robinson JT , Mesirov JP . Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration . Brief Bioinform . 2013 ; 14 ( 2 ): 178 - 92 .
13. Pruitt KD , et al. NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy . Nucleic Acids Res . 2012 ; 40(Database issue):D130-5.
14. Markus HS , et al. Diagnostic strategies in CADASIL. Neurology . 2002 ; 59 ( 8 ): 1134 - 8 .
15. Abramycheva N , et al. New mutations in the Notch3 gene in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy (CADASIL) . J Neurol Sci . 2015 ; 349 ( 1-2 ): 196 - 201 .
16. He D , et al. The comparisons of phenotype and genotype between CADASIL and CADASIL-like patients and population-specific evaluation of CADASIL scale in China . J Headache Pain . 2016 ; 17 : 55 .
17. Roy B , et al. Two novel mutations and a previously unreported intronic polymorphism in the NOTCH3 gene . Mutat Res . 2012 ; 732 ( 1-2 ): 3 - 8 .
18. Bianchi S , et al. CADASIL in central Italy: a retrospective clinical and genetic study in 229 patients . J Neurol . 2015 ; 262 ( 1 ): 134 - 41 .
19. Fernandez A , et al. A next-generation sequencing of the NOTCH3 and HTRA1 Genes in CADASIL Patients . J Mol Neurosci . 2015 ; 56 ( 3 ): 613 - 6 .
20. Adib-Samii P , et al. Clinical spectrum of CADASIL and the effect of cardiovascular risk factors on phenotype: study in 200 consecutively recruited individuals . Stroke . 2010 ; 41 ( 4 ): 630 - 4 .
21. Kim YE , et al. Spectrum of NOTCH3 mutations in Korean patients with clinically suspicious cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy . Neurobiol Aging . 2014 ; 35 ( 3 ): 726 e1- 6 .
22. Joutel A , et al. Pathogenic mutations associated with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy differently affect Jagged1 binding and Notch3 activity via the RBP/JK signaling Pathway . Am J Hum Genet . 2004 ; 74 ( 2 ): 338 - 47 .
23. Wang W , et al. Notch3 signaling in vascular smooth muscle cells induces c-FLIP expression via ERK/MAPK activation. Resistance to Fas ligand-induced apoptosis . J Biol Chem . 2002 ; 277 ( 24 ): 21723 - 9 .
24. Joutel A. Loss-of-function mutation in the NOTCH3 gene: simply a polymorphism? Hum Mutat . 2013 ; 34 ( 11 ):v.
25. Bohlega S. Novel mutation of the notch3 gene in arabic family with CADASIL . Neurol Int . 2011 ; 3 ( 2 ): e6 .
26. Lee YC , et al. Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy: two novel mutations in the NOTCH3 gene in Chinese . J Neurol Sci . 2006 ; 246 ( 1-2 ): 111 - 5 .
27. Brass SD , et al. Case records of the Massachusetts General Hospital. Case 12 - 2009 . A 46-year-old man with migraine, aphasia, and hemiparesis and similarly affected family members . N Engl J Med . 2009 ; 360 ( 16 ): 1656 - 65 .
28. Kim Y , et al. Characteristics of CADASIL in Korea: a novel cysteine-sparing Notch3 mutation . Neurology . 2006 ; 66 ( 10 ): 1511 - 6 .
29. Mazzei R , et al. A novel Notch3 gene mutation not involving a cysteine residue in an Italian family with CADASIL . Neurology. 2004 ; 63 ( 3 ): 561 - 4 .
30. Santa Y , et al. Genetic, clinical and pathological studies of CADASIL in Japan: a partial contribution of Notch3 mutations and implications of smooth muscle cell degeneration for the pathogenesis . J Neurol Sci . 2003 ; 212 ( 1-2 ): 79 - 84 .
31. Scheid R , et al. Cysteine-sparing notch3 mutations: cadasil or cadasil variants? Neurology . 2008 ; 71 ( 10 ): 774 - 6 .
32. Uchino M , et al. Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) and CADASIL-like disorders in Japan . Ann N Y Acad Sci . 2002 ; 977 : 273 - 8 .
33. Herman-Bert A , et al. Mapping of spinocerebellar ataxia 13 to chromosome 19q13.3-q13.4 in a family with autosomal dominant cerebellar ataxia and mental retardation . Am J Hum Genet . 2000 ; 67 ( 1 ): 229 - 35 .
34. Ophoff RA , et al. Familial hemiplegic migraine and episodic ataxia type-2 are caused by mutations in the Ca2+ channel gene CACNL1A4 . Cell . 1996 ; 87 ( 3 ): 543 - 52 .
35. Wallace RH , et al. Neuronal sodium-channel alpha1-subunit mutations in generalized epilepsy with febrile seizures plus . Am J Hum Genet . 2001 ; 68 ( 4 ): 859 - 65 .
36. Orrico A , et al. Mutational analysis of the SCN1A, SCN1B and GABRG2 genes in 150 Italian patients with idiopathic childhood epilepsies . Clin Genet . 2009 ; 75 ( 6 ): 579 - 81 .
37. Arboleda-Velasquez JF , et al. CADASIL mutations impair Notch3 glycosylation by Fringe . Hum Mol Genet . 2005 ; 14 ( 12 ): 1631 - 9 .
38. Opherk C , et al. CADASIL mutations enhance spontaneous multimerization of NOTCH3 . Hum Mol Genet . 2009 ; 18 ( 15 ): 2761 - 7 .
39. Richards S , et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology . Genet Med . 2015 ; 17 ( 5 ): 405 - 24 .
40. Dreszer TR , et al. The UCSC Genome Browser database: extensions and updates 2011 . Nucleic Acids Res . 2012 ; 40 (Database issue): D918 - 23 .
41. Sherry ST , et al. dbSNP: the NCBI database of genetic variation . Nucleic Acids Res . 2001 ; 29 ( 1 ): 308 - 11 .
42. Chang X , Wang K. wANNOVAR: annotating genetic variants for personal genomes via the web . J Med Genet . 2012 ; 49 ( 7 ): 433 - 6 .
43. Wang K , Li M , Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data . Nucleic Acids Res . 2010 ; 38 ( 16 ): e164 .
44. Pollard KS , et al. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res . 2010 ; 20 ( 1 ): 110 - 21 .
45. Ng PC , Henikoff S. Predicting deleterious amino acid substitutions . Genome Res . 2001 ; 11 ( 5 ): 863 - 74 .
46. Adzhubei IA , et al. A method and server for predicting damaging missense mutations . Nat Methods . 2010 ; 7 ( 4 ): 248 - 9 .
47. Schwarz JM , et al. MutationTaster evaluates disease-causing potential of sequence alterations . Nat Methods . 2010 ; 7 ( 8 ): 575 - 6 .
48. Davydov EV , et al. Identifying a high fraction of the human genome to be under selective constraint using GERP++ . PLoS Comput Biol . 2010 ; 6 ( 12 ): e1001025 .
49. Tavtigian SV , et al. Comprehensive statistical study of 452 BRCA1 missense substitutions with classification of eight recurrent substitutions as neutral . J Med Genet . 2006 ; 43 ( 4 ): 295 - 305 .
50. Capriotti E , Calabrese R , Casadio R. Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information . Bioinformatics . 2006 ; 22 ( 22 ): 2729 - 34 .