Whole exome sequencing is an efficient and sensitive method for detection of germline mutations in patients with phaeochromcytomas and paragangliomas

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1 Clinical Endocrinology (2014) 80, doi: /cen ORIGINAL ARTICLE Whole exome sequencing is an efficient and sensitive method for detection of germline mutations in patients with phaeochromcytomas and paragangliomas Aideen M. McInerney-Leo*, Mhairi S. Marshall*, Brooke Gardiner*, Diana E. Benn,, Janelle McFarlane*, Bruce G. Robinson,, Matthew A. Brown*, Paul J. Leo*, Roderick J. Clifton-Bligh, and Emma L. Duncan*,, *The University of Queensland Diamantina Institute, Translational Research Institute, Princess Alexandra Hospital, Woolloongabba, Brisbane, Royal North Shore Hospital, The Kolling Institute, University of Sydney, Sydney, NSW, Department of Endocrinology, Royal Brisbane and Women s Hospital, Brisbane and UQ Centre for Clinical Research, The University of Queensland, Herston, Qld, Australia Summary Background Genetic testing is recommended when the probability of a disease-associated germline mutation exceeds 10%. Germline mutations are found in approximately 25% of individuals with phaeochromcytoma (PCC) or paraganglioma (PGL); however, genetic heterogeneity for PCC/PGL means many genes may require sequencing. A phenotype-directed iterative approach may limit costs but may also delay diagnosis, and will not detect mutations in genes not previously associated with PCC/PGL. Objective To assess whether whole exome sequencing (WES) was efficient and sensitive for mutation detection in PCC/ PGL. Methods Whole exome sequencing was performed on blinded samples from eleven individuals with PCC/PGL and known mutations. Illumina TruSeq TM (Illumina Inc, San Diego, CA, USA) was used for exome capture of seven samples, and NimbleGen SeqCap EZ v3.0 (Roche NimbleGen Inc, Basel, Switzerland) for five samples (one sample was repeated). Massive parallel sequencing was performed on multiplexed samples. Sequencing data were called using Genome Analysis Toolkit and annotated using ANNOVAR. Data were assessed for coding variants in RET, NF1, VHL, SDHD, SDHB, SDHC, SDHA, SDHAF2, KIF1B, TMEM127, EGLN1 and MAX. Target capture of five exome capture platforms was compared. Results Six of seven mutations were detected using Illumina TruSeq TM exome capture. All five mutations were detected using NimbleGen SeqCap EZ v3.0 platform, including the mutation missed using Illumina TruSeq TM capture. Target capture for exons in known PCC/PGL genes differs substantially between platforms. Exome sequencing was inexpensive (<$A800 per Correspondence: Emma L. Duncan, Department of Endocrinology, Royal Brisbane and Women s Hospital, Butterfield Road, Herston, QLD 4029, Australia. Tel.: ; Fax: ; e.duncan@uq.edu.au sample for reagents) and rapid (results <5 weeks from sample reception). Conclusion Whole exome sequencing is sensitive, rapid and efficient for detection of PCC/PGL germline mutations. However, capture platform selection is critical to maximize sensitivity. (Received 24 July 2013; returned for revision 8 August 2013; finally revised 27 August 2013; accepted 12 September 2013) Introduction Phaeochromcytomas (PCC) and paragangliomas (PGL) are tumours arising from the adrenal medulla or from extra-adrenal sympathetic or parasympathetic paraganglia. 1 PCCs and extra-adrenal sympathetic paragangliomas secrete catecholamines which can cause paroxysmal hypertension associated with headaches, sweating and palpitations. Hypertension may be so extreme that it can cause heart failure, seizures, stroke and/or sudden death. 2 Although these tumours are usually benign, the lifetime risk of malignancy is approximately 5 13% in PCC, 1, % with sympathetic PGL 3,4 and 2 20% in parasympathetic PGLs. 1,5 Germline determinants of PCC/PGL were first identified when PCC/PGL occurred as part of familial syndromes, namely multiple endocrine neoplasia type 2 (MEN2), von Hippel Lindau (VHL) and neurofibromatosis type I (NF1) 6 caused by mutations in RET, 7 VHL 4 and NF1, 8 respectively. When PCC or PGL develop in individuals with other phenotypic features of these syndromes, a mutation in the relevant gene is almost always identified. 5,9 Conversely, PCC/PGL may be the initial presenting feature in VHL or MEN2. Up to one-third of PCC/PGL patients with VHL mutations have no family history or syndromic features at time of gene testing. 5,10 Interpreting the significance of mutations in VHL in these circumstances can be difficult if the mutation has not been reported previously in the Leiden Open Variation Database (LOVD) 11 or the literature. 25

2 26 A. M. McInerney-Leo et al. Other genes associated with PCC-PGL include the four succinate dehydrogenase (SDH) subunits SDHD, 12 SDHC, 13 SDHB 14 and SDHA, 15 each associated with unique paraganglioma syndromic phenotypes (PGL1, PGL3, PGL4 and PGL5, respectively). Mutations in SDHAF2 (previously SDH5), encoding a protein involved in the SDH complex assembly, have been identified in rare families with PGL2. 16 The most recently identified genes associated with PCC/PGL are transmembrane protein 127 (TMEM127), 17 kinesin family member 1B (KIF1B), 18 EGL nine homolog 1 (EGLN1) 19 and MYC-associated factor X (MAX). 20 Of note, the last gene was identified by whole exome sequencing. Historically, germline mutations were thought to occur in 10% of PCC/PGL cases. 21 It is now recognized that this is an underestimate. Germline mutations in a known associated gene were found in 11 24% of individuals with nonsyndromic isolated PCC/PGL and no known family history 5,10,22 and in 38% of those with multifocal tumours (either bilateral or recurrent). 5,10 These studies did not include SDHAF2, SDHA, KIF1B, EGLN1, TMEM127 or MAX; thus, the frequency of germline mutations in apparently sporadic cases may be higher. Genetic testing is useful both for obviously familial and apparently sporadic PCC/PGL. Identification of the causative gene will direct screening for other associated tumours (e.g. renal carcinoma in VHL and PGL1, PGL3 and PGL4; medullary thyroid cancer in MEN2; and gastrointestinal stromal cell tumours in PGL1, PGL3, PGL4 and PGL5) in both the proband and affected family members; early detection of these tumours may result in reduced morbidity and mortality, as has been shown for MEN2. 23 Asymptomatic family members can be monitored clinically for the development of a catecholamine-secreting PCC/PGL; as the first manifestation of PCC/PGL can be sudden death, this may be life-saving. Genetic testing also allows cessation of unnecessary medical monitoring in noncarriers. As causative mutations are identified in >90% of patients with PCC/PGL with a positive family history, whether syndromic features are present or not, there is universal agreement that familial cases should be offered genetic testing. 5,10,24,25 Some argue that genetic testing is warranted regardless of family history. 5,10 While others might agree in principle, the $A cost of screening the four most common genes (SDHB, SDHD, VHL and RET) using conventional Sanger sequencing methods has led to numerous algorithms for a stepwise approach to testing in apparently sporadic cases The development of massive parallel sequencing allows an alternative approach with simultaneous screening of multiple target regions. A very recent publication demonstrated that targeted sequencing for nine of the known PCC/PGL genes (targeting MAX, RET, SDHA, SDHB, SDHC, SDHD, SDHAF2, TMEM127 and VHL) was a sensitive (987%) means of mutation detection in a cohort of 85 patients with known variants. 28 In this study, we have assessed whether whole exome sequencing, using an off-the-shelf exome capture platform rather than designing individual targeted assays, is a sensitive, timeefficient and cost-effective way to offer genetic testing in a population of individuals with established diagnosis of PCC/PGL. We also evaluated the target capture of the currently available exome capture platforms for exons of the known PCC/PGL genes. Materials and methods Clinical samples This cohort consisted of eleven unrelated patients with an established diagnosis of familial PCC or PGL, in whom germline mutations in VHL, RET, SDHB, SDHC or SDHD had been previously identified. Ethics approval was obtained from the University of Queensland (UQ # ) for the use of their DNA as de-identified samples in testing exome sequencing as a diagnostic method. Laboratory and analysis teams were blinded to the previous mutation reports. Whole exome sequencing Whole exome sequencing was performed on genomic DNA from eleven clinical samples. Sequencing libraries were constructed using a modification of the Illumina TruSeqDNA sample preparation kit. Briefly, 16ug of genomic DNA was sheared to an average fragment size of 200 bp using the Covaris E220. Fragments were purified using AMPureXP beads (Beckman Coulter Inc, Brae, CA, USA) to remove small products (<100 bp), yielding 1 ug of material which was end-polished, A-tailed and adapter-ligated according to the manufacturer s protocol. The libraries were subjected to minimal PCR cycling and quantified using the Agilent High Sensitivity DNA assay. Libraries were combined into pools of six for solution phase hybridization using either the Illumina TruSeq TM (Illumina Inc) Exome Enrichment Kit or the Nimble- Gen EzCap Human v3.0 (Roche NimbleGen Inc) Exome Enrichment Kit. Captured libraries were assessed for both quality and yield using the Agilent High Sensitivity DNA assay and KAPA Library Quantification Kit. Massively parallel sequencing was performed with six samples per flow cell lane using the Illumina HiSeq2000 platform and version 3 SBS chemistry to generate 100 bp paired-end reads (2x100PE). The Illumina Data Analysis Pipeline software (CASAVA v1.8.2) was used for demultiplexing and initial base calling. Sequence data were aligned to the current build of the human genome (hg19, released February 2009) using the Novoalign alignment tool (V ); sequence alignment files were converted using SAMtools (v0.1.16) and Picard tools (v1.42). Single nucleotide polymorphisms (SNPs) and insertion/deletions (indels) were called using the Genome Analysis Toolkit (GATK v1.5.11) and annotated using ANNOVAR. Further analysis of sequence data was performed using custom scripts employing R and Bioconductor. Additionally, we selected variants (SNPs and indels) that passed GATK variant score recalibration (incorporating quality parameters of sequencing depth and quality scores at the SNP position, maximal length of the homopolymer run and strand bias). 29 Data were filtered looking for variants in the target genes (RET, NF1, VHL, SDHD, SDHB, SDHC, SDHA, SDHAF2, KIF1B, TMEM127, EGLN1 and MAX).

3 Exome sequencing in phaeochromcytoma/paraganglioma 27 Target capture platforms We assessed the theoretical target capture regions of five current off-the-shelf capture platforms (Agilent SureSelect XT [Agilent Technologies, Santa Clara, CA, USA]; NimbleGen Seq- Cap EZ v3.0; Illumina TruSeq TM ; Illumina Nextera TM [Illumina Inc] Rapid Capture Expanded Exome; and Illumina Nextera TM Rapid Capture Exome) by downloading the target capture regions for RET, NF1, VHL, SDHD, SDHB, SDHC, SDHA, SDHAF2, KIF1B, TMEM127, EGLN1 and MAX regions from the browser extensible data (BED) files from the websites of the manufacturers. A custom R script compared the percentage overlap of the gene exonic coding regions (CDS), defined using the Bioconductor package TxDb.Hsapiens.UCSC.hg19.known- Gene (Bioconductor, Seattle, WA, USA), with the target capture regions of each platform. Capture was defined as the region targeted by each platform; failure to target an exon adequately was defined as targeting of <90% of the CDS. Using data from this study and from other individuals sequenced for benign disorders, we assessed our in-house capture efficiency for capturing known PCC/PGL genes using the Illumina TruSeq TM (n = 174) and NimbleGen SeqCap EZ (n = 15) exome capture platforms, by calculating the percentage coverage (at 109 depth) of the CDS regions of each gene as defined above. Results Clinical details The clinical information for the eleven patients is presented in Table 1. Sequencing Detailed mapping and coverage statistics for all samples sequenced on each platform are presented in Supplementary Tables S1 and S2. Table 1. Clinical data for individuals with phaeochromcytoma or paraganglioma Subject number Age Gender Reason for genetic testing F Predictive (family history of paraganglioma) M Predictive (family history of paraganglioma) M Head and neck paraganglioma M Predictive (family history of paraganglioma) F Predictive (family history of MEN2) M Phaeochromcytoma F Mediastinal paraganglioma F Predictive (family history of paraganglioma) M Metastatic phaeochromcytoma M Head and neck paraganglioma F Predictive (family history of paraganglioma) Mutation analysis Mutation detection is presented in Table 2. In six of the seven samples sequenced using the Illumina TruSeq TM platform, a coding variant was identified in a known PCC/PGL gene. One SNP in VHL was reported with a minor allele frequency <0001 in dbsnp (release 135), where it was identified as pathogenic based on two case reports. 30,31 The remaining five variants had not been reported in NCBI dbsnp (release 135), 1000Genomes, 1000Genomes small indels (called using the DINDEL programme), the SNPs of 46Genomes release by Complete Genomics and other whole exomes from over 1200 control samples run internally using similar capture technology. Four of the five mutations had previously been reported as pathogenic in LOVD. 11 No mutations were detected in one sample (PCC-163) using the Illumina TruSeq TM exome capture platform. Reviewing the BED files of the sequencing data using Integrated Genome Viewer to assess our coverage of the known PCC/PGL genes, the lack of comprehensive capture of SDHC was apparent. We reviewed the target capture from the manufacturer which showed that multiple exons of SDHC were not captured with this platform. Thus, this sample was subsequently recaptured with the NimbleGen SeqCap EZv.3.0 platform and resequenced. In all five samples (including the repeat sample) sequenced using the NimbleGen SeqCap EZ platform, a coding variant was identified in a known PCC/PGL gene (see Table 2). None had been previously reported in the control databases listed above. Three had been previously reported in LOVD. 11 The remaining two mutations have not been previously reported as pathogenic in the literature. The repeat sample had a mutation in an exon of SDHC not targeted by the Illumina TruSeq TM platform. On reconciliation, all mutations were confirmed to be the previously identified mutation for the individual. Comparison of capture platforms Comparison of BED files from five current off-the-shelf capture platforms is presented in Table 3. Exact percentage theoretical target capture for each exon with its genomic location is presented in Supplementary Table 3. With respect to theoretical capture of PCC/PGL genes, only Illumina Nextera TM Rapid Capture Exome targets of all exons in all known PCC/PGL genes. Of note, this platform does not capture nonexonic regions, so mutations in UTRs will not be detected. The performance of other platforms varied considerably in their theoretical capture, with the most striking differences in the capture of the succinate dehydrogenase genes. Agilent SureSelect XT targeted <32% of SDHD, <60% of SDHB and SDHC, and <50% of SDHA. Illumina TruSeq TM and Illumina Nextera TM Rapid Capture Expanded Exome target <17% of SDHC. A visual comparison of capture across all five platforms for SHDA and SDHC can be seen in Supporting Figures S1 and S2. Although the theoretical capture of NF1 was >80% with all platforms, this is a large gene and all of the platforms (except Illumina Nextera TM Rapid Capture Exome) failed to target several exons. As shown in Supplementary Table 3, theoretical

4 28 A. M. McInerney-Leo et al. Table 2. Summary of identified variants for seven samples with exome capture using Illumina TruSeq TM Exome Enrichment Kit v2.0 and five samples captured using Nimblegen SeqCap EZ v3.0. Sample Number of variants identified Number of heterozygous variants in target genes* Number of good quality** variants in target genes Number of good quality coding or splice site variants in target genes Identified mutation Concurs with previously reported mutation Illumina TruSeq Exome Enrichment Kit v2.0 Nimblegen SeqCap EZ v3.0 PCC SDHD exon3 c.296delt p.leu99profsx36 PCC SDHB exon2 c.137g>a p.arg46gln PCC SDHC exon3 c.148c>t p.arg50cys PCC SDHB exon7 c.689g>a p.arg230his PCC RET exon10 c. 1832G>A p.cys611tyr PCC VHL exon2 c.481c>t p.arg161x PCC None No mutation identified using this capture platform PCC-163 (repeat) SDHC exon2 c.49delc p.ala16 fs PCC SDHB exon5 c.494_497 delaagg p.glu165alafsx3 9 PCC VHL exon3 c.492g>c p.gln164his PCC SDHD exon3 c.242c>t p.pro81leu PCC SDHC exon5 c.397c>t p.arg133x *RET, NF1, VHL, SDHD, SDHB, SDHC, SDHA, SDHAF2, KIF1B, TMEM127, EGLN1 and MAX, **Good quality = Passing GATK recalibration score. variant quality

5 Table 3. Target exon capture for known PCC/PGL genes, comparing manufacturer s files, for five capture platforms Exome sequencing in phaeochromcytoma/paraganglioma 29 Gene Number of exons Agilent SureSelect XT All Exon V5 + UTRs Nimblegen SeqCap EZ v3.0 Illumina TruSeq TM Exome Enrichment Kit v2.0 Illumina Nextera TM Rapid Capture Expanded Exome Illumina Nextera TM Rapid Capture Exome RET 21 93% of 5 exons NF % exon 22 of 22 exons VHL 3 92% SDHD 4 32% exon 4 of three exons 94% of 5 exons 948% of 12 exons 99% 94% exons 1,31,59 99% 94% exons 1, 31, 59 96% SDHB 8 97% 99% SDHC 6 60% exon 2 of three exons 92% 33% exons 1,2,4,5,6 33% exons 1,2,4,5,6 SDHA 15 49% exons 11, 12, 14 of ten exons SDHAF2 4 85% KIF1B 50 97% of six exons TMEM % EGLN1 5 87% MAX 5 98% 91% of five exons 93% 95% of nine exons 96% 96% 95% exons 9, 13 95% Did not target exons 9, 13 98% 94% 93% s 80% No capture exon 5 80% No capture exon 5 target capture of exons in PCC/PGL genes with the Illumina platforms is usually all-or-nothing with very few exons with only partial capture. In contrast, even though overall targeted capture for PCC/PGL genes might be very similar, more exons were only partially captured with Agilent SureSelect XT and NimbleGen SeqCap EZ v3.0 platforms. In-house exome sequencing data from unrelated individuals were used to assess the real-world experience of two platforms (NimbleGen SeqCap EZ v3.0 or Illumina TruSeq TM ) at capturing CDS of known PCC/PGL genes at depth of coverage of tenfold. The results are presented in Supplementary Table 4. These results highlight that target capture represents an ideal that may not be attained with real-life experience; thus, within-laboratory and per-experiment assessment of capture is prudent. Costs and efficiency The reagent costs for these experiments (approximately $A850per individual) were low in comparison with current quoted genetic screening costs ($A4100 to screen the four most

6 30 A. M. McInerney-Leo et al. common genes for these conditions 26 ). Analysis time was not considered in the costings of this proof-of-concept study. However, analysis time after our internal bioinformatics processing was <1 h, and overall time (from sample receipt to mutation report back to the author providing the samples (RCB)) was under 5 weeks. Discussion In this study, we have demonstrated that WES accurately diagnosed all mutations in all 11 patients with PCC/PGL in whom mutations had been detected previously by Sanger sequencing. Further, we were able to discriminate between disease-associated mutations and irrelevant variants. However, appropriate choice of capture platform is critical to ensure adequate coverage of all exons of known PCC/PGL genes. We were initially unable to detect a mutation in a known PCC/ PGL gene in one sample (PCC-163) when sequenced after capture using the Illumina TruSeq TM platform. Review of the sequencing data BED files to assess coverage of the known PCC/PGL genes demonstrated the lack of capture of many exons of SDHC. We subsequently reviewed the target capture information provided by the manufacturer which demonstrated that multiple exons of this gene were not targeted by this platform. This prompted repeat sequencing with a different platform that had improved exonic capture of this gene, and the mutation was easily identified. Our cohort contained patients with mutations in SDHB, SDHC, SDHD, RET and VHL. It is possible that mutations in other PCC/PGL genes may not be detected so simply. However, our internal sequencing data demonstrated good capture and adequate depth of coverage of CDS of other PCC/PGL genes where targeted by the capture platform (Supplementary Table 4). We would emphasize the importance of assessing coverage for each sequencing experiment before excluding the presence of a mutation. Our data fit with the results of targeted sequencing recently reported, in which 987% of mutations were detected in 85 patients with a previously identified mutation. 28 However, and of note, in their prospective cohort of an additional 120 samples, a pathogenic mutation was only found in 166%. An obvious disadvantage of targeted sequencing is the lack of potential for new gene discovery. For example, whole exome sequencing in those majority of individuals in this prospective study in whom a mutation in a known gene was not found may lead to identification of a new PCC/PGL gene(s), by analysing the data for mutations in a common gene shared by unrelated probands. Such a strategy has been demonstrated in other diseases. 32 Further, targeted sequencing involves creation of a specific platform for the known genes; updating this as new genes are identified elsewhere requires re-design of the platform and re-running of samples, with cost implications. Although targeted sequencing may currently represent a relatively cost-effective approach with great depth of coverage of targeted exons, the rapidly falling prices of off-the-shelf exome capture will neutralize such a cost advantage within the very near future. 33 The only other published study of the use of massive parallel sequencing in mutation screening in patient with PCC/PGL is a study of WES in tumour samples from three patients with apparently sporadic PCC. 34 Sixteen variants were identified in known PCC/PGL genes overall; two tumours were thought to harbour probable and possible pathogenic unique variants in NF1 and RET, respectively. Although WES is clearly an efficient method of sequencing multiple genes in one step, we have demonstrated the importance of platform choice in detection of PCC/PGL gene mutations. For a clinical diagnostic service, if a mutation is not detected by WES this should prompt screening, using an alternate method, of the exons not captured by the exome capture platform used. Partial capture of an exon would not be sufficient for confident exclusion of a mutation, even if the overall percentage capture of a particular gene were high. Theoretically, only Illumina Nextera TM Rapid Capture Exome targets all CDS in all known PCC/PGL genes; of note, surrounding UTRs are not targeted by this platform. The theoretical capture for Illumina platforms is generally all-or-nothing ; in contrast, both NimbleGen SeqCap EZ v3.0 and Agilent SureSelect XT target several exons in the known PCC/PGL genes with target capture < of CDS (Supplementary Table 3). A platform with many partially targeted exons would require further screening of many exons before a mutation could be confidently excluded. Therefore, before setting up WES screening for any disease, it is critical to assess the comprehensiveness of the exome capture platform for the known gene(s) for the condition. In addition, sequencing technologies themselves differ in performance. 35 We would highlight that it is critical to assess actual capture of target exons per sample and that target capture may not necessarily concur with real-life experience. To illustrate this, we have presented our in-house experience with exomes captured and sequenced from individuals with unrelated disorders (Table S4). These samples were run in separate experiments over a period during which protocols were updated and fine-tuned to maximize performance; thus, we would caution against over-interpretation of the data as showing one platform to be superior to another. Rather, we provide these data to emphasize the importance of per-experiment and perindividual assessment of capture (including depth of coverage) in mutation screening. The differences in target region selection between capture platforms are due to differences in manufacturer design processes. These may include bias towards certain regions of interest (noncoding regions, UTRs, micrornas); avoidance of regions difficult to capture using their proprietary capture methodology (including probe length and optimal probe target melting temperature 36 ); and/or avoidance of capture of regions prone to multimapping during analysis (e.g. pseudogene or repeat regions). Further, bias in sequence capture relates to GC/AT content which not only influences optimal target-probe TM but may also result in preferential amplification during PCR which has been reported to have a negative impact on the capture of specific regions, including high GC-containing first exons. 37

7 Exome sequencing in phaeochromcytoma/paraganglioma 31 The single-step nature of exome sequencing has great potential for reducing the costs of mutation detection. Since its introduction, the costs of massive parallel sequencing have fallen more rapidly than is usual following introduction of new technologies. 33 At the time we started this study, consumable costs were approximately $A1500 for exome sequencing to provide information for all 13 known PCC/PGL genes compared with quoted commercial costs $A4100 for screening the four most common genes for these conditions using Sanger sequencing. 26 Consumable costs for WES are now <$A800 per sample. Furthermore, as the currently known genes do not fully account for all familial cases of PCC/PGL, 5,10,27 exome sequencing may provide an opportunity for novel gene discovery, as was demonstrated by the identification of MAX as a new PCC gene. 20 Although we did not consider analysis time in this proofof-concept study, our internal bioinformatics processing (as described in the methods) meant that the post-processing analysis was fast (less than one hour) with rapid exclusion of poor-quality variants, variants with high population frequency, and platformrelated or sequencing-related artefact. Similarly, assessing persample coverage of known PCC/PGL genes was aided by custom R scripts. This emphasizes the importance of strong bioinformatics expertise in interpreting WES data. The American Society of Clinical Oncology have suggested that it should become the standard of care to offer cancer genetics testing to patients with an a priori risk of carrying a germline mutation of 10%. 38 The risk of a germline mutation in individuals with PCC/PGL easily passes this threshold. The advent of newer, more efficient and timely mutation detection in subjects with PCC/PGL and their families allows the possibility of earlier detection of PCC/PGL in asymptomatic carriers, appropriate screening for other components of syndromic disorders, and reduction of anxiety and elimination of unnecessary screening for noncarriers. WES is a sensitive, time-efficient and cost-effective method of detecting mutations in the known genes for PCC/PGL. However, careful choice of exome capture platform and good bioinformatics support is necessary for maximal sensitivity of mutation detection. Acknowledgements We acknowledge gratefully the technical support of Jessica Harris, Sharon Song and Lisa Anderson at the University of Queensland Diamantina Institute and Anne Louise Richardson at the Kolling Institute; and administrative help of Kim Gardner at University of Queensland Diamantina Institute. Funding This grant was supported by a project grant from the Royal Brisbane and Women s Hospital Foundation. AMM-L is supported by a University of Queensland student fellowship. MAB is supported by a National Health and Medical Research Council Senior Principal Research Fellowship. Support was also received from the Pheo-Para Alliance (RCB, DEB) and the Hillcrest Foundation (DEB). Disclosure Statement The authors have nothing to disclose. Web resources 1000 Genomes: 46Genomes from Complete Genomics: nomics.com/sequence-data/download-data/ Agilent SureSelect: ( index.htm), ANNOVAR: BEAGLE Utilities program Cluster2haps: Bioconductor package TxDb.Hsapiens.UCSC.hg19.known Gene ( tion/html/txdb.hsapiens.ucsc.hg19.knowngene.html) CASAVA CONDEL: Database of Single Nucleotide Polymorphisms (dbsnp). Bethesda (MD): National Center for Biotechnology Information, National Library of Medicine. (dbsnp Build ID: dbsnp137): DINDEL: Exome Variants Analysis and Reporting (EVAR): GATK: Genome_Analysis_Toolkit Illumina TruSeq ( Integrative Genomics Viewer igv/ Leiden open variation database: MutationTaster: Nextera Rapid Capture Exome Targeted Regions Nextera Rapid Capture Expanded Exome Targeted Regions ( NHLBI Exome Sequencing Project: http//:evs.gs.washington. edu/evs NimbleGen SeqCap EZ ( seqcap/ez/v3/index.html) Novoalign alignment tool: Online Mendelian Inheritance in Man (OMIM): omim.org Package hapfabia - Bioconductor: Picard tools (v142): PolyPhen: SAMtools: SIFT: UCSC genome browser: UK10K project: UniProt:

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9 Exome sequencing in phaeochromcytoma/paraganglioma 33 fragility in humans and zebrafish. American Journal of Human Genetics, 90, Aird, D., Ross, M.G., Chen, W.S. et al. (2011) Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries. Genome Biology, 12, R Statement of the American Society of Clinical Oncology. Genetic testing for cancer susceptibility, Adopted on February 20, Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology, (1996) 14: ; discussion Supporting Information Additional Supporting Information may be found in the online version of this article: Fig. S1. Comparison of target capture of five platforms for SDHA. Fig. S2. Comparison of target capture of five platforms for SDHC. Table S1. Summary statistics for seven samples run on Illumina TruSeq TM exome capture platform. Table S2. Summary statistics for five samples run on Nimble- Gen SeqCap EZ v3.0 exome capture platform. Table S3. Individualized target capture for all exons of known genes for PCC/PGL. Table S4. Percentage capture of known PCC/PGL genes at 109 depth per exon using unrelated samples undergoing exome sequencing for benign conditions using Nimblegen Seq- Cap EZ v3.0 or Illumina TruSeq TM exome capture platforms.