Supplementary Information for
Whole exome sequencing reveals that the majority of schwannomatosis cases remain
unexplained after excluding SMARCB1 and LZTR1 germline variants
Sonja Hutter1, Rosario M. Piro2,3, David E. Reuss4, Volker Hovestadt2, Felix Sahm4, Said Farschtschi5,
Hildegard Kehrer-Sawatzki6, Stephan Wolf7, Peter Lichter2,3,8, Andreas von Deimling4, Martin U.
Schuhmann9, Stefan M. Pfister1,10, David T. W. Jones1,# and Victor F. Mautner5,#
# co-corresponding authors
Correspondence to: D.T.W.J. (david.jones@dkfz.de) and/or V.F.M. (v.mautner@uke.uni-hamburg.de)
1 Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120
Heidelberg, Germany
2 Division of Molecular Genetics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg,
Germany
3 German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
4 Department of Neuropathology, Heidelberg University Hospital, Im Neuenheimer Feld 224, 69120 Heidelberg, Germany
5 Department of Neurology, University Hospital Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany
6 Institute of Human Genetics, University of Ulm, Albert-Einstein-Allee 11, 89081 Ulm,
7 Genomics and Proteomics Core Facility, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120
Heidelberg, Germany
8 Heidelberg Center for Personalized Oncology (DKFZ-HIPO), 69120 Heidelberg, Germany
9 Department of Neurosurgery, University Hospital Tübingen, Hoppe-Seyler-Strasse 3, 72076 Tübingen, Germany
10 Department of Pediatric Oncology, Haematology and Immunology, Heidelberg University Hospital, Im Neuenheimer Feld
224, 69120 Heidelberg, Germany
Table of contents
Materials & Methods .............................................................................................................................. 2
References ............................................................................................................................................. 11
Supplementary Tables
Supplementary Table S1. Sporadic schwannomatosis patient cohort. ................................................................... 4
Supplementary Table S2. Whole exome and low-coverage whole genome sequencing coverage data. ................ 5
Supplementary Table S3. Mutations and copy number alterations identified by next-generation sequencing or
direct sequencing/450K copy number profiles. ....................................................................................................... 6
Supplementary Table S4. Primer sequences used for targeted LZTR1 sequencing. ................................................ 7
Supplementary Table S5 provided as separate Excel file Table S5_somatic SNVs and indels.
Supplementary Figures
Supplementary Figure S1. Genome-wide copy number profile of a representative schwannomatosis tumor with
(SCH1) or without (SCH2) loss of one copy of chr22 as evidenced by lcWGS. ......................................................... 8
Supplementary Figure S2. Representative genome-wide copy number plots derived from 450k array of
additionally screened tumors with (SCH14) or without (SCH17) loss of chr22. ....................................................... 9
Supplementary Figure S3. Unsupervised hierarchical clustering of 12 schwannomatosis tumor DNA-methylation
profiles................................................................................................................................................................... 10
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Hutter et al.
Materials & Methods
Processing of whole genome and exome sequencing data
The raw read data obtained from both low coverage whole genome sequencing (WGS) and whole
exome sequencing (WES) were processed as previously described [3,9,10]. Briefly, reads from pairedend sequencing were mapped to the human reference genome (hg 19; NCBI build 37.1) with BWA
version 0.6.1-r104-tpx [6] and sorted according to chromosomal coordinates using SAMtools version
0.1.17 [7].
Aligned reads from multiple sequencing lanes were merged and duplicate reads were removed using
Picard tools version 1.61 (http://picard.sourceforge.net/). For further analysis, only uniquely aligned
reads (having a mapping quality of at least 1) were considered. Coverage was computed taking into
account only bases of reads with an average base quality of 25 (Phred-scale). For WES, reads were
additionally required to overlap target regions (defined by Agilent SureSelect v4 without UTRs). Mean
WGS coverage was 2.2-fold for tumor samples (range 1.0-3.2) and 1.9-fold for matched blood
samples (range 1.3-2.5). Mean WES on-target coverage was 115-fold for tumors (range 78-137) and
144-fold for matched controls (range 99-190). For more details on the sequencing data, see
Supplementary Table S2.
Sequence data have been deposited at the European Genome-phenome Archive
(EGA, http://www.ebi.ac.uk/ega/) hosted by the EBI, under accession number EGAS00001000767.
Single nucleotide variant (SNV) and indel detection
The detection of SNVs from uniquely aligned WES reads (see above) was performed based on
SAMtools mpileup version 0.1.17 and bcftools version 0.1.19 [7] as previously described [3,9,10].
Briefly, the initial identification of SNV candidates was determined by SAMtools mpileup considering
only reads with high mapping quality and bases with a base quality of at least 13, and applying the
extended base alignment quality (BAQ) model for reduction of false SNV call rate due to
misalignment [5]. The piled-up sequences were then used to perform variant calling with bcftools
complemented by custom filters to reduce the false positive rate (e.g. due to Illumina-specific error
profiles [8]) while allowing to include mutations with low allele frequencies [3].
The identification of small insertions or deletions (indels) was performed in a similar manner with
SAMtools and bcftools with restrictive parameter settings [3] to reduce the known high false positive
rate associated with current indel detection methods for deep sequencing data. In addition, indel
calls in simple repeat or microsatellite regions were excluded because they commonly contain an
excessive fraction of false positives.
Filtering of somatic events and germline mutations
Somatic SNVs and indels were detected by direct comparison of the WES tumor and control samples,
requiring a somatic SNV to be reported in at most 1/30th of the control reads (to allow for a possible
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Hutter et al.
small fraction of circulating tumor DNA in the matching blood sample) and a somatic indel in none of
the control reads.
Both SNVs and indels were annotated with Annovar [12] predictions of their effect on encoded
proteins (non-synonymous, stopgain, splicing, frameshift, etc). For our analysis, we considered only
exonic indels and SNVs in non-coding genes (ncRNA) as well as those in coding genes predicted to be
non-synonymous or nonsense (stopgain) mutations and/or to affect splice sites. A full list of somatic
indels and SNVs is provided in Supplementary Table S5.
Processing of RNA sequencing data
Paired-end strand-specific RNA-seq reads (Illumina HiSeq, 101bp length) were aligned to the
reference genome using TopHat v1.4.1 [11] and Bowtie v.1.0.0 [4] for exon-exon splice junction
detection. A total of 41.012.716 reads could be mapped to known exons (Ensembl 57).
Processing of 450k data
Illumina Human Methylation 450k BeadChip arrays for 12 schwannomatosis patients were generated
and processed as described previously [1]. For unsupervised hierarchical clustering, we selected the
641 most variably methylated probes across the dataset (s.d. >0.25). Samples were clustered using 1Pearson correlation coefficient as the distance measure and average linkage (x-axis). Methylation
probes were reordered by hierarchical clustering using Euclidean distance and average linkage (yaxis).
Sanger sequencing of selected genes
Routine Sanger sequencing of LZTR1, NF2 and SMARCB1 was performed in 15 additional germline
samples. All coding exons for these genes were amplified from genomic DNA using GoTaq DNA
polymerase (Promega) and purified with illustra ExoStar kit (GE Healthcare). The primers used in
LZTR1 sequencing are listed in Supplementary Table S4, whereas NF2 and SMARCB1 were previously
published [2]. PCR products were sequenced with the PCR primers using the BigDye Terminator v3.1
Cycle Sequencing Kit (Life Technologies) and sequence reactions were run on an ABI PRISM 3100
Genetic Analyzer (Life Technologies). All sequences were manually examined.
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Hutter et al.
Supplementary Table S1. Sporadic schwannomatosis patient cohort.
Sample Age (years) Sex First symptom
Age of Onset (years) Location of Tumor
SCH1
SCH2
SCH3
SCH4
SCH5
SCH6
SCH7
SCH8
46
47
48
65
48
19
57
51
F
M
M
M
F
F
M
F
tumor growth
tumor growth
tumor growth
pain
pain
pain
tumor growth/pain
pain
29
41
16
42
50
5
27
39
segmental
spinal*
spinal + peripheral
peripheral
spine + peripheral*
segmental
spinal + peripheral
peripheral + spinal
SCH9
SCH10
SCH11
SCH12
SCH13
SCH14
SCH15
SCH16
SCH17
SCH18
SCH19
SCH20
SCH21
SCH22
SCH23
45
37
80
34
56
40
60
51
55
47
65
40
51
56
54
F
F
M
M
F
F
F
F
M
M
M
M
F
F
m
pain
tumor growth
neurological deficit
pain
tumor growth
pain
tumor growth
neurological deficit
pain
tumor growth
tumor growth
tumor growth
tumor growth
pain
pain
38
24
61
27
43
29
spinal + peripheral*
segmental
cerebral + spinal, peripheral
spine + peripheral*
*No
16
50
37
60
33
29
42
cerebral + spinal + peripheral
segmental
spinal + peripheral
spinal + peripheral
peripheral
spine + peripheral
spine + peripheral*
segmental*
spinal + peripheral
spinal + peripheral
Tumor load Surgeries
5
5
3
6
15
3
27
32
4
2
2
4
5
2
5
3
unknown
10
5
7
4
5
4
4
13
3
15
10
7
5
10
3
1
2
3
1
1
3
4
1
2
12
3
2
2
2
whole-body MRI
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Supplementary Table S2. Whole exome and low-coverage whole genome sequencing coverage
data.
WES
Sample Sample Type Aligned Read Count On-target coverage
SCH1
SCH1
SCH2
SCH2
SCH3
SCH3
SCH4
SCH4
SCH5
SCH5
SCH6
SCH6
SCH7
SCH7
SCH8
SCH8
blood
tumor
blood
tumor
blood
tumor
blood
tumor
blood
tumor
blood
tumor
blood
tumor
blood
tumor
66.548.781
58.523.364
63.081.894
53.436.967
95.889.921
67.826.718
98.732.982
69.283.068
50.933.576
73.398.688
84.264.230
62.322.788
61.968.072
40.508.818
53.242.335
61.343.453
128.93x
103.24x
122.1x
103.6x
164.58x
126.93x
190.12x
133.91x
98.73x
137.3x
162.23x
116.18x
120.15x
78.35x
102.99x
118.62x
lcWGS
coverage
1.68x
2.15x
2.38x
0.99x
2.01x
2.39x
2.48x
2.72x
2.12x
2.18x
3.22x
2.44x
1.42x
3.15x
1.3x
1.79x
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Supplementary Table S3. Mutations and copy number alterations identified by next-generation sequencing or direct sequencing/450K copy number profiles.
Sample
1st Event (E1)
2nd Event (E2)
3rd Event (E3)
Germline LZTR1 mutation
Deletion of 22q
Somatic NF2 mutation
genomic DNA
lcWGS
450k
genomic DNA
protein
SCH1
c.C2247A
p.Y749X
yes
yes
c.C784T
p.R262X
2
SCH2
-
-
no
no
-
-
5
SCH3
-
-
yes
NA
-
-
4
SCH4
-
-
yes
NA
-
-
4
SCH5
-
-
yes
yes
-
-
4
SCH6
c.321-2A
splicing affected
yes
yes
c.1122+1G>C
splicing affected
2
SCH7
-
-
no
NA
-
-
5
SCH8
-
-
no
no
-
-
5
SCH9
-
-
NA
NA
NA
NA
SCH10
-
-
NA
yes
-
-
SCH11
-
-
NA
NA
NA
NA
-
-
NA
yes
c.482_483insGG
p.G161fsX13
7
NA
yes
c.482_483insGG
p.G161fsX13
7
SCH12a§
SCH12b
#
protein
Schwannomatosis
subgroup#
§
4
SCH13
-
-
NA
NA
NA
NA
SCH14
c.1480_1481insAG
p.R494fs
NA
yes
c.351_352del
p.H116fsX
2
SCH15
-
-
NA
NA
c.C1396T
p.R466X
3* or 6*
SCH16
c.347_348insC
p.A116fs
NA
NA
NA
NA
2
SCH17
-
-
NA
no
c.750_771del
p.T251fsX
6
SCH18
-
-
NA
yes
c.203_206del
p.I68fsX
3
SCH19
-
-
NA
yes
NA
NA
3* or 4*
SCH20
-
-
NA
NA
NA
NA
SCH21
-
-
NA
NA
NA
NA
SCH22
c.G1312T
p.E438X
NA
NA
NA
NA
SCH23
-
-
NA
NA
NA
NA
2*
as described in Table 1; NA: not analyzed; * estimated; § two tumors from the same patient showed exactly the same characteristics, indicating somatic mosaicism; -: no mutation identified
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Hutter et al.
Supplementary Table S4. Primer sequences used for targeted LZTR1 sequencing.
Exon
Exon 1
Exon 2
Exon 3
Exon 4
Exon 5
Exon 6
Exon 7
Exon 8
Exon 9
Exon 10
Exon 11
Exon 12
Exon 13/14
Exon 15
Exon 16
Exon 17/18
Exon 19/20
Exon 21
Primer sequence (5‘-3‘)
Forward
Reverse
GCAGGAAAGGGAGCGTTGAG
GCTCTCCTGCTTAGTCCCAT
GACAGGCAGCAGGTCGTTC
AAGAAAGGCAGCACAGGGATG
GACAGGCAGCAGGTCGTTC
CAGTGTCGGGTGGATGTAGC
AGCCATCCCTTCCAGCCAG
AGCAGTCCCATCTCAGCAGT
CAGTGAAGGCCTGCTGTGG
AGAACCCACTCTCAAGGCCA
CCCACCTGTGTCTGTACCCA
ATTTTCAGGGTGGGGTAGCG
GCTGGCTGGGTCTCTGTTC
CCCAGCCCACACTCTTCCAT
GTGGGGTCAGCGCAATCAG
GGCAGCAACATGGGCAGATA
CCCTTCCCTGTCCTTCCCT
GGTGAGAGAAGCAGAGCAGC
CTCTCCCCTGCCCTGAACA
GGACAGTAATGGAGCTGGACA
CACCAATCCCAAGCTCCCTG
GCAGAAGGGCAGGGTGTC
CACCAATCCCAAGCTCCCTG
TGGCACTCAAAATCCACCAGG
GAAGAAAGCAGCCTCGACCC
GGGCTGTAACCTCCTGCTGT
TGGTAGCTGTCTGGAACCCC
GGTGTGACCCCAAGCAAGTA
TTTAGTGCCACCTCAGCCCA
AGAGAACAGAGACCCAGCCA
GGCAGCACCCACCTTTTGG
CGAGGGGCTCACAGTGGT
GCTCCCAATCTCCTACCGCA
GGCAGTTGTGAGGGTCAGGA
GGCTGCTCTGCTTCTCTCAC
CTGCTTCATCATCCGCTCCC
Product size
848 bp
229 bp
383 bp
241 bp
383 bp
327 bp
294 bp
364 bp
397 bp
366 bp
445 bp
384 bp
491 bp
349 bp
363 bp
699 bp
473 bp
493 bp
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Supplementary Figure S1. Genome-wide copy number profile of a representative schwannomatosis tumor with (SCH1) or without (SCH2) loss of one copy of
chr22 as evidenced by lcWGS.
The X axis represents genomic position and the Y axis represents the log2 of the read count in non-overlapping 1 kb windows.
SCH1 copy number profile
SCH2 copy number profile
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Supplementary Figure S2. Representative genome-wide copy number plots derived from 450k
array of additionally screened tumors with (SCH14) or without (SCH17) loss of chr22.
Log2 tumor:normal copy number ratios (against a pool of normal DNA samples) are displayed along
the chromosome map
SCH14
SCH17
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Supplementary Figure S3. Unsupervised hierarchical clustering of 12 schwannomatosis tumor DNAmethylation profiles.
There is no enrichment for the LZTR1mut/LZTR1WT tumor samples or FFPE vs. fresh-frozen tumor
material.
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