Supplementary Methods
1. DNA extraction from seminomas and matched normal tissues
Frozen tissue was submerged in TRIS buffer and homogenized using a Polytron
homogenizer. The sample was then mixed with 10% SDS and Proteinase K to a final
concentration of 0.1 mg/ml, and incubated overnight at 55 degrees C. DNA was purified
with phenol-chloroform extraction and ethanol precipitation.
2. Library preparation and exome sequencing
DNA (3 micrograms per sample) was sheared using a Covaris S1 Ultrasonicator.
Following adapter ligation, libraries were prepared using Illumina Paired-End Genomic
DNA kit. Exome capture was done using Agilent SureSelect Human All Exon Kit v1.
Samples were sequenced on Illumina GA-IIx and/or HiSeq sequencers using 76-bp
paired-end reads. Image analysis and base calling were done using Illumina pipeline
(v1.6) with default settings.
3. Mapping and variant calling
Burrows-Wheeler Aligner (BWA) software (http://bio-bwa.sourceforge.net/) was used
for aligning sequence reads to the human reference genome NCBI build 36.1 (hg18).
PCR duplicates removal was done using SAMTools (http://samtools.sourceforge.net/).
We created realigned BAM files with Genome Analysis ToolKit (GATK) v1.0
(https://www.broadinstitute.org/gatk/).
For detecting single nucleotide variants (SNVs) we used three different callers:
MuTect (http://www.broadinstitute.org/cancer/cga/mutect), GATK v1.0 Unified
Genotyper, and Partek Genomics Suite. For SNVs detected by GATK or Partek, we
subtracted variants detected in the matched normal from variants detected in the
tumor. For further analysis, we restricted our attention to candidate somatic SNVs that
were in the capture target and in exons or canonical splice sites, with a variant depth ≥
4 and depth in the normal sample ≥ 10. To exclude common germline polymorphisms,
the detected variants were checked against dbSNP 138
(http://www.ncbi.nlm.nih.gov/SNP/) and 1000 Genomes
(http://www.1000genomes.org/) databases. However, any variants present in COSMIC
v47 (http://www.sanger.ac.uk/cosmic), a database of somatic mutations in cancers,
were retained. Variants were annotated using several gene-transcript databases
(Consensus CDS, RefSeq, Ensembl and UCSC, downloaded from
http://hgdownload.soe.ucsc.edu/goldenPath/hg18/bigZips/). Amino-acid changes
were determined based on the longest gene transcript. Somatic nonsynonymous singlenucleotide mutations were analyzed using PolyPhen2
(http://genetics.bwh.harvard.edu/pph2/) to predict their impact on the protein
function.
Microindels were detected using GATK IndelGenotyperV2. For further analysis
we only considered microindels that were in-target and in an exon or at a canonical
splice site. Several filters were applied to reduce false positives: we retained
microindels that (1) were not in a simple repeat, (2) had variant depth ≥ 5 with ≥ 1 read
on each strand, (3) had depth in the normal sample ≥ 10, (4) were contained in ≥ 5% of
the reads, (5) had average base quality of all bases inside the microindel and ±5 bases
around the microindel ≥ 25, (6) had average number of mismatches in the reads
containing the microindel ≤ 4, and (7) had average fraction of mismatched bases in
reads containing the microindel ≤ 0.2.
4. Validation of somatic variants
For validation by Sanger sequencing, we used the Primer3 software to design primers
for PCR and sequencing. PCR was carried out with Promega GoTaq Hot Start Colorless
Master Mix according to the manufacturer’s instructions. We designed primers for 135
variants and we were able to obtain 132 PCR products. Purified PCR products were
sequenced in both directions on an ABI 3730xl DNA analyzer using the PCR primers and
the ABI PRISM BigDye Terminator Cycle Sequencing Ready Reaction kit. For validation
by Ion Torrent PGM, primers were designed at the website www.ampliseq.com.
Ampliseq primer design failed for 4 out of the 77 variants we attempted to design
primers for. Libraries were prepared using the Ion AmpliSeq Library Kit 2.0 according
to the manufacturer’s instructions and run on an Ion 314 Chip.
5. SNP microarrays and ASCAT analysis
Genomic DNAs from the eight tumor-normal pairs were hybridized to Affymetrix SNP
Array 6.0 microarrays. The raw SNP array data were first normalized using CRMA-v2
(http://www.aroma-project.org/vignettes/CRMAv2) and TumorBoost (http://aromaproject.org/vignettes/tumorboost-highlevel). Next, the log2R ratio (LRR) and the Ballele frequency (BAF) were computed and the ASCAT v 2.0 software
(http://heim.ifi.uio.no/bioinf/Projects/ASCAT/) was used to determine the proportion
of malignant cells in the tumor sample and the allele-specific chromosome counts (i.e.,
the number of chromosomes bearing each of the two alleles). Copy-number alterations
were identified based on the allele-specific copy-number counts and average ploidy, i.e.
the, average number of chromosome copies at each site across the genome.