Resolving the full spectrum of human genome variation using Linked-Reads.

Large-scale population analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. To date, this diversity has largely been uncovered using short-read whole-genome sequencing. However, these short-read approaches fail to give a complete picture of a genome. They struggle to identify structural events, cannot access repetitive regions, and fail to resolve the human genome into haplotypes. Here, we describe an approach that retains long range information while maintaining the advantages of short reads. Starting from ∼1 ng of high molecular weight DNA, we produce barcoded short-read libraries. Novel informatic approaches allow for the barcoded short reads to be associated with their original long molecules producing a novel data type known as "Linked-Reads". This approach allows for simultaneous detection of small and large variants from a single library. In this manuscript, we show the advantages of Linked-Reads over standard short-read approaches for reference-based analysis. Linked-Reads allow mapping to 38 Mb of sequence not accessible to short reads, adding sequence in 423 difficult-to-sequence genes including disease-relevant genes STRC, SMN1, and SMN2 Both Linked-Read whole-genome and whole-exome sequencing identify complex structural variations, including balanced events and single exon deletions and duplications. Further, Linked-Reads extend the region of high-confidence calls by 68.9 Mb. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

Mutations in Epigenetic Regulation Genes Are a Major Cause of Overgrowth with Intellectual Disability.

To explore the genetic architecture of human overgrowth syndromes and human growth control, we performed experimental and bioinformatic analyses of 710 individuals with overgrowth (height and/or head circumference ≥+2 SD) and intellectual disability (OGID). We identified a causal mutation in 1 of 14 genes in 50% (353/710). This includes HIST1H1E, encoding histone H1.4, which has not been associated with a developmental disorder previously. The pathogenic HIST1H1E mutations are predicted to result in a product that is less effective in neutralizing negatively charged linker DNA because it has a reduced net charge, and in DNA binding and protein-protein interactions because key residues are truncated. Functional network analyses demonstrated that epigenetic regulation is a prominent biological process dysregulated in individuals with OGID. Mutations in six epigenetic regulation genes-NSD1, EZH2, DNMT3A, CHD8, HIST1H1E, and EED-accounted for 44% of individuals (311/710). There was significant overlap between the 14 genes involved in OGID and 611 genes in regions identified in GWASs to be associated with height (p = 6.84 × 10-8), suggesting that a common variation impacting function of genes involved in OGID influences height at a population level. Increased cellular growth is a hallmark of cancer and there was striking overlap between the genes involved in OGID and 260 somatically mutated cancer driver genes (p = 1.75 × 10-14). However, the mutation spectra of genes involved in OGID and cancer differ, suggesting complex genotype-phenotype relationships. These data reveal insights into the genetic control of human growth and demonstrate that exome sequencing in OGID has a high diagnostic yield.

Mosaic PPM1D mutations are associated with predisposition to breast and ovarian cancer.

Improved sequencing technologies offer unprecedented opportunities for investigating the role of rare genetic variation in common disease. However, there are considerable challenges with respect to study design, data analysis and replication. Using pooled next-generation sequencing of 507 genes implicated in the repair of DNA in 1,150 samples, an analytical strategy focused on protein-truncating variants (PTVs) and a large-scale sequencing case-control replication experiment in 13,642 individuals, here we show that rare PTVs in the p53-inducible protein phosphatase PPM1D are associated with predisposition to breast cancer and ovarian cancer. PPM1D PTV mutations were present in 25 out of 7,781 cases versus 1 out of 5,861 controls (P = 1.12 × 10(-5)), including 18 mutations in 6,912 individuals with breast cancer (P = 2.42 × 10(-4)) and 12 mutations in 1,121 individuals with ovarian cancer (P = 3.10 × 10(-9)). Notably, all of the identified PPM1D PTVs were mosaic in lymphocyte DNA and clustered within a 370-base-pair region in the final exon of the gene, carboxy-terminal to the phosphatase catalytic domain. Functional studies demonstrate that the mutations result in enhanced suppression of p53 in response to ionizing radiation exposure, suggesting that the mutant alleles encode hyperactive PPM1D isoforms. Thus, although the mutations cause premature protein truncation, they do not result in the simple loss-of-function effect typically associated with this class of variant, but instead probably have a gain-of-function effect. Our results have implications for the detection and management of breast and ovarian cancer risk. More generally, these data provide new insights into the role of rare and of mosaic genetic variants in common conditions, and the use of sequencing in their identification.

Mutations in the PP2A regulatory subunit B family genes PPP2R5B, PPP2R5C and PPP2R5D cause human overgrowth.

Overgrowth syndromes comprise a group of heterogeneous disorders characterised by excessive growth parameters, often in association with intellectual disability. To identify new causes of human overgrowth, we have been undertaking trio-based exome sequencing studies in overgrowth patients and their unaffected parents. Prioritisation of functionally relevant genes with multiple unique de novo mutations revealed four mutations in protein phosphatase 2A (PP2A) regulatory subunit B family genes protein phosphatase 2, regulatory Subunit B', beta (PPP2R5B); protein phosphatase 2, regulatory Subunit B', gamma (PPP2R5C); and protein phosphatase 2, regulatory Subunit B', delta (PPP2R5D). This observation in 3 related genes in 111 individuals with a similar phenotype is greatly in excess of the expected number, as determined from gene-specific de novo mutation rates (P = 1.43 × 10(-10)). Analysis of exome-sequencing data from a follow-up series of overgrowth probands identified a further pathogenic mutation, bringing the total number of affected individuals to 5. Heterozygotes shared similar phenotypic features including increased height, increased head circumference and intellectual disability. The mutations clustered within a region of nine amino acid residues in the aligned protein sequences (P = 1.6 × 10(-5)). We mapped the mutations onto the crystal structure of the PP2A holoenzyme complex to predict their molecular and functional consequences. These studies suggest that the mutations may affect substrate binding, thus perturbing the ability of PP2A to dephosphorylate particular protein substrates. PP2A is a major negative regulator of v-akt murine thymoma viral oncogene homolog 1 (AKT). Thus, our data further expand the list of genes encoding components of the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)/AKT signalling cascade that are disrupted in human overgrowth conditions.

Predisposition gene identification in common cancers by exome sequencing: insights from familial breast cancer.

The genetic component of breast cancer predisposition remains largely unexplained. Candidate gene case-control resequencing has identified predisposition genes characterised by rare, protein truncating mutations that confer moderate risks of disease. In theory, exome sequencing should yield additional genes of this class. Here, we explore the feasibility and design considerations of this approach. We performed exome sequencing in 50 individuals with familial breast cancer, applying frequency and protein function filters to identify variants most likely to be pathogenic. We identified 867,378 variants that passed the call quality filters of which 1,296 variants passed the frequency and protein truncation filters. The median number of validated, rare, protein truncating variants was 10 in individuals with, and without, mutations in known genes. The functional candidacy of mutated genes was similar in both groups. Without prior knowledge, the known genes would not have been recognisable as breast cancer predisposition genes. Everyone carries multiple rare mutations that are plausibly related to disease. Exome sequencing in common conditions will therefore require intelligent sample and variant prioritisation strategies in large case-control studies to deliver robust genetic evidence of disease association.

Insights into BRCA Cancer Predisposition from Integrated Germline and Somatic Analyses in 7632 Cancers.

BACKGROUND: It is often assumed any cancer in a germline BRCA1 or BRCA2 (collectively termed BRCA) mutation carrier was caused by that mutation. It is also often assumed the occurrence of breast or ovarian cancer in an individual with a variant of uncertain significance (VUS) suggests the VUS is pathogenic. These assumptions have profound management implications for cancer patients and healthy individuals. METHODS: We compared the frequency of BRCA mutations, allele loss, and Signature 3 in 7632 individuals with 28 cancers and 1000 population controls. Because only increased frequency was the focus of the study, all statistical tests were one-sided. RESULTS: Individuals with breast or ovarian cancer had increased germline BRCA pathogenic mutation frequencies compared to controls (P = 1.0x10-10 and P = 1.4x10-34, respectively). There was no increase in other cancer types. Wild-type allele loss and Signature 3 were statistically significantly higher in breast and ovarian cancers with BRCA mutations compared with other cancers with BRCA mutations (P = 5.1x10-10 and P = 3.7x10-9) and cancers without BRCA mutations (P = 2.8x10-53 and P = 1.0x10-134). There was no difference between non-breast and non-ovarian cancers with BRCA mutations and cancers without BRCA mutations. Allele loss and Signature 3 were statistically significantly higher in breast and ovarian cancers in individuals with BRCA pathogenic mutations compared to those with VUS (P = 3.8x10-17 and P = 1.6x10-8) or benign variants (P = 1.2x10-28 and P = 2.2x10-10). There was no difference between individuals with BRCA VUS and those with benign variants. CONCLUSIONS: These data show that non-breast and non-ovarian cancers in individuals with germline BRCA pathogenic mutations are often not causally related to the mutation and that BRCA VUS are highly unlikely to be pathogenic. These results should reduce inappropriate management of germline BRCA information.

Identification of new Wilms tumour predisposition genes: an exome sequencing study.

BACKGROUND: Wilms tumour is the most common childhood renal cancer and is genetically heterogeneous. While several Wilms tumour predisposition genes have been identified, there is strong evidence that further predisposition genes are likely to exist. Our study aim was to identify new predisposition genes for Wilms tumour. METHODS: In this exome sequencing study, we analysed lymphocyte DNA from 890 individuals with Wilms tumour, including 91 affected individuals from 49 familial Wilms tumour pedigrees. We used the protein-truncating variant prioritisation method to prioritise potential disease-associated genes for further assessment. We evaluated new predisposition genes in exome sequencing data that we generated in 334 individuals with 27 other childhood cancers and in exome data from The Cancer Genome Atlas obtained from 7632 individuals with 28 adult cancers. FINDINGS: We identified constitutional cancer-predisposing mutations in 33 individuals with childhood cancer. The three identified genes with the strongest signal in the protein-truncating variant prioritisation analyses were TRIM28, FBXW7, and NYNRIN. 21 of 33 individuals had a mutation in TRIM28; there was a strong parent-of-origin effect, with all ten inherited mutations being maternally transmitted (p=0·00098). We also found a strong association with the rare epithelial subtype of Wilms tumour, with 14 of 16 tumours being epithelial or epithelial predominant. There were no TRIM28 mutations in individuals with other childhood or adult cancers. We identified truncating FBXW7 mutations in four individuals with Wilms tumour and a de-novo non-synonymous FBXW7 mutation in a child with a rhabdoid tumour. Biallelic truncating mutations in NYNRIN were identified in three individuals with Wilms tumour, which is highly unlikely to have occurred by chance (p<0·0001). Finally, we identified two de-novo KDM3B mutations, supporting the role of KDM3B as a childhood cancer predisposition gene. INTERPRETATION: The four new Wilms tumour predisposition genes identified-TRIM28, FBXW7, NYNRIN, and KDM3B-are involved in diverse biological processes and, together with the other 17 known Wilms tumour predisposition genes, account for about 10% of Wilms tumour cases. The overlap between these 21 constitutionally mutated predisposition genes and 20 genes somatically mutated in Wilms tumour is limited, consisting of only four genes. We recommend that all individuals with Wilms tumour should be offered genetic testing and particularly, those with epithelial Wilms tumour should be offered TRIM28 genetic testing. Only a third of the familial Wilms tumour clusters we analysed were attributable to known genes, indicating that further Wilms tumour predisposition factors await discovery. FUNDING: Wellcome Trust.

The ICR639 CPG NGS validation series: A resource to assess analytical sensitivity of cancer predisposition gene testing.

The analytical sensitivity of a next generation sequencing (NGS) test reflects the ability of the test to detect real sequence variation. The evaluation of analytical sensitivity relies on the availability of gold-standard, validated, benchmarking datasets. For NGS analysis the availability of suitable datasets has been limited. Most laboratories undertake small scale evaluations using in-house data, and/or rely on in silico generated datasets to evaluate the performance of NGS variant detection pipelines. Cancer predisposition genes (CPGs), such as BRCA1 and BRCA2, are amongst the most widely tested genes in clinical practice today. Hundreds of providers across the world are now offering CPG testing using NGS methods. Validating and comparing the analytical sensitivity of CPG tests has proved difficult, due to the absence of comprehensive, orthogonally validated, benchmarking datasets of CPG pathogenic variants. To address this we present the ICR639 CPG NGS validation series. This dataset comprises data from 639 individuals. Each individual has sequencing data generated using the TruSight Cancer Panel (TSCP), a targeted NGS assay for the analysis of CPGs, together with orthogonally generated data showing the presence of at least one CPG pathogenic variant per individual. The set consists of 645 pathogenic variants in total. There is strong representation of the most challenging types of variants to detect, with 339 indels, including 16 complex indels and 24 with length greater than five base pairs and 74 exon copy number variations (CNVs) including 23 single exon CNVs. The series includes pathogenic variants in 31 CPGs, including 502 pathogenic variants in BRCA1 or BRCA2, making this an important comprehensive validation dataset for providers of BRCA1 and BRCA2 NGS testing. We have deposited the TSCP FASTQ files of the ICR639 series in the European Genome-phenome Archive (EGA) under accession number EGAD00001004134.

ICR142 Benchmarker: evaluating, optimising and benchmarking variant calling performance using the ICR142 NGS validation series.

Evaluating, optimising and benchmarking of next generation sequencing (NGS) variant calling performance are essential requirements for clinical, commercial and academic NGS pipelines. Such assessments should be performed in a consistent, transparent and reproducible fashion, using independently, orthogonally generated data. Here we present ICR142 Benchmarker, a tool to generate outputs for assessing germline base substitution and indel calling performance using the ICR142 NGS validation series, a dataset of Illumina platform-based exome sequence data from 142 samples together with Sanger sequence data at 704 sites. ICR142 Benchmarker provides summary and detailed information on the sensitivity, specificity and false detection rates of variant callers. ICR142 Benchmarker also automatically generates a single page report highlighting key performance metrics and how performance compares to widely-used open-source tools. We used ICR142 Benchmarker with VCF files outputted by GATK, OpEx and DeepVariant to create a benchmark for variant calling performance. This evaluation revealed pipeline-specific differences and shared challenges in variant calling, for example in detecting indels in short repeating sequence motifs. We next used ICR142 Benchmarker to perform regression testing with DeepVariant versions 0.5.2 and 0.6.1. This showed that v0.6.1 improves variant calling performance, but there was evidence of minor changes in indel calling behaviour that may benefit from attention. The data also allowed us to evaluate filters to optimise DeepVariant calling, and we recommend using 30 as the QUAL threshold for base substitution calls when using DeepVariant v0.6.1. Finally, we used ICR142 Benchmarker with VCF files from two commercial variant calling providers to facilitate optimisation of their in-house pipelines and to provide transparent benchmarking of their performance. ICR142 Benchmarker consistently and transparently analyses variant calling performance based on the ICR142 NGS validation series, using the standard VCF input and outputting informative metrics to enable user understanding of pipeline performance. ICR142 Benchmarker is freely available at https://github.com/RahmanTeamDevelopment/ICR142_Benchmarker/releases.

CoverView: a sequence quality evaluation tool for next generation sequencing data.

Quality assurance and quality control are essential for robust next generation sequencing (NGS). Here we present CoverView, a fast, flexible, user-friendly quality evaluation tool for NGS data. CoverView processes mapped sequencing reads and user-specified regions to report depth of coverage, base and mapping quality metrics with increasing levels of detail from a chromosome-level summary to per-base profiles. CoverView can flag regions that do not fulfil user-specified quality requirements, allowing suboptimal data to be systematically and automatically presented for review. It also provides an interactive graphical user interface (GUI) that can be opened in a web browser and allows intuitive exploration of results. We have integrated CoverView into our accredited clinical cancer predisposition gene testing laboratory that uses the TruSight Cancer Panel (TSCP). CoverView has been invaluable for optimisation and quality control of our testing pipeline, providing transparent, consistent quality metric information and automatic flagging of regions that fall below quality thresholds. We demonstrate this utility with TSCP data from the Genome in a Bottle reference sample, which CoverView analysed in 13 seconds. CoverView uses data routinely generated by NGS pipelines, reads standard input formats, and rapidly creates easy-to-parse output text (.txt) files that are customised by a simple configuration file. CoverView can therefore be easily integrated into any NGS pipeline. CoverView and detailed documentation for its use are freely available at github.com/RahmanTeamDevelopment/CoverView/releases and www.icr.ac.uk/CoverView.

The Quality Sequencing Minimum (QSM): providing comprehensive, consistent, transparent next generation sequencing data quality assurance.

Next generation sequencing (NGS) is routinely used in clinical genetic testing. Quality management of NGS testing is essential to ensure performance is consistently and rigorously evaluated. Three primary metrics are used in NGS quality evaluation: depth of coverage, base quality and mapping quality. To provide consistency and transparency in the utilisation of these metrics we present the Quality Sequencing Minimum (QSM). The QSM defines the minimum quality requirement a laboratory has selected for depth of coverage (C), base quality (B) and mapping quality (M) and can be applied per base, exon, gene or other genomic region, as appropriate. The QSM format is CX_BY(P Y)_MZ(P Z). X is the parameter threshold for C, Y the parameter threshold for B, P Y the percentage of reads that must reach Y, Z the parameter threshold for M, P Z the percentage of reads that must reach Z. The data underlying the QSM is in the BAM file, so a QSM can be easily and automatically calculated in any NGS pipeline. We used the QSM to optimise cancer predisposition gene testing using the TruSight Cancer Panel (TSCP). We set the QSM as C50_B10(85)_M20(95). Test regions falling below the QSM were automatically flagged for review, with 100/1471 test regions QSM-flagged in multiple individuals. Supplementing these regions with 132 additional probes improved performance in 85/100. We also used the QSM to optimise testing of genes with pseudogenes such as PTEN and PMS2. In TSCP data from 960 individuals the median number of regions that passed QSM per sample was 1429 (97%).  Importantly, the QSM can be used at an individual report level to provide succinct, comprehensive quality assurance information about individual test performance. We believe many laboratories would find the QSM useful. Furthermore, widespread adoption of the QSM would facilitate consistent, transparent reporting of genetic test performance by different laboratories.

Correction: Germline mutations in the oncogene EZH2 cause Weaver syndrome and increased human height.

[This corrects the article DOI: 10.18632/oncotarget.385.].

The ICR96 exon CNV validation series: a resource for orthogonal assessment of exon CNV calling in NGS data.

Detection of deletions and duplications of whole exons (exon CNVs) is a key requirement of genetic testing. Accurate detection of this variant type has proved very challenging in targeted next-generation sequencing (NGS) data, particularly if only a single exon is involved. Many different NGS exon CNV calling methods have been developed over the last five years. Such methods are usually evaluated using simulated and/or in-house data due to a lack of publicly-available datasets with orthogonally generated results. This hinders tool comparisons, transparency and reproducibility. To provide a community resource for assessment of exon CNV calling methods in targeted NGS data, we here present the ICR96 exon CNV validation series. The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM or PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs, the most difficult type of exon CNV to detect. The FASTQ files for the ICR96 exon CNV validation series can be accessed through the European-Genome phenome Archive (EGA) under the accession number EGAS00001002428.

Biallelic TRIP13 mutations predispose to Wilms tumor and chromosome missegregation.

Through exome sequencing, we identified six individuals with biallelic loss-of-function mutations in TRIP13. All six developed Wilms tumor. Constitutional mosaic aneuploidies, microcephaly, developmental delay and seizures, which are features of mosaic variegated aneuploidy (MVA) syndrome, were more variably present. Through functional studies, we show that TRIP13-mutant patient cells have no detectable TRIP13 and have substantial impairment of the spindle assembly checkpoint (SAC), leading to a high rate of chromosome missegregation. Accurate segregation, as well as SAC proficiency, is rescued by restoring TRIP13 function. Individuals with biallelic TRIP13 or BUB1B mutations have a high risk of embryonal tumors, and here we show that their cells display severe SAC impairment. MVA due to biallelic CEP57 mutations, or of unknown cause, is not associated with embryonal tumors and cells from these individuals show minimal SAC deficiency. These data provide insights into the complex relationships between aneuploidy and carcinogenesis.

The ICR142 NGS validation series: a resource for orthogonal assessment of NGS analysis.

To provide a useful community resource for orthogonal assessment of NGS analysis software, we present the ICR142 NGS validation series. The dataset includes high-quality exome sequence data from 142 samples together with Sanger sequence data at 704 sites; 416 sites with variants and 288 sites at which variants were called by an NGS analysis tool, but no variant is present in the corresponding Sanger sequence. The dataset includes 293 indel variants and 247 negative indel sites, and thus the ICR142 validation dataset is of particular utility in evaluating indel calling performance. The FASTQ files and Sanger sequence results can be accessed in the European Genome-phenome Archive under the accession number EGAS00001001332.

Accurate clinical detection of exon copy number variants in a targeted NGS panel using DECoN.

Background: Targeted next generation sequencing (NGS) panels are increasingly being used in clinical genomics to increase capacity, throughput and affordability of gene testing. Identifying whole exon deletions or duplications (termed exon copy number variants, 'exon CNVs') in exon-targeted NGS panels has proved challenging, particularly for single exon CNVs.  Methods: We developed a tool for the Detection of Exon Copy Number variants (DECoN), which is optimised for analysis of exon-targeted NGS panels in the clinical setting. We evaluated DECoN performance using 96 samples with independently validated exon CNV data. We performed simulations to evaluate DECoN detection performance of single exon CNVs and to evaluate performance using different coverage levels and sample numbers. Finally, we implemented DECoN in a clinical laboratory that tests BRCA1 and BRCA2 with the TruSight Cancer Panel (TSCP). We used DECoN to analyse 1,919 samples, validating exon CNV detections by multiplex ligation-dependent probe amplification (MLPA).  Results: In the evaluation set, DECoN achieved 100% sensitivity and 99% specificity for BRCA exon CNVs, including identification of 8 single exon CNVs. DECoN also identified 14/15 exon CNVs in 8 other genes. Simulations of all possible BRCA single exon CNVs gave a mean sensitivity of 98% for deletions and 95% for duplications. DECoN performance remained excellent with different levels of coverage and sample numbers; sensitivity and specificity was >98% with the typical NGS run parameters. In the clinical pipeline, DECoN automatically analyses pools of 48 samples at a time, taking 24 minutes per pool, on average. DECoN detected 24 BRCA exon CNVs, of which 23 were confirmed by MLPA, giving a false discovery rate of 4%. Specificity was 99.7%.  Conclusions: DECoN is a fast, accurate, exon CNV detection tool readily implementable in research and clinical NGS pipelines. It has high sensitivity and specificity and acceptable false discovery rate. DECoN is freely available at www.icr.ac.uk/decon.

OpEx - a validated, automated pipeline optimised for clinical exome sequence analysis.

We present an easy-to-use, open-source Optimised Exome analysis tool, OpEx (http://icr.ac.uk/opex) that accurately detects small-scale variation, including indels, to clinical standards. We evaluated OpEx performance with an experimentally validated dataset (the ICR142 NGS validation series), a large 1000 exome dataset (the ICR1000 UK exome series), and a clinical proband-parent trio dataset. The performance of OpEx for high-quality base substitutions and short indels in both small and large datasets is excellent, with overall sensitivity of 95%, specificity of 97% and low false detection rate (FDR) of 3%. Depending on the individual performance requirements the OpEx output allows one to optimise the inevitable trade-offs between sensitivity and specificity. For example, in the clinical setting one could permit a higher FDR and lower specificity to maximise sensitivity. In contexts where experimental validation is not possible, minimising the FDR and improving specificity may be a preferable trade-off for slightly lower sensitivity. OpEx is simple to install and use; the whole pipeline is run from a single command. OpEx is therefore well suited to the increasing research and clinical laboratories undertaking exome sequencing, particularly those without in-house dedicated bioinformatics expertise.

Implementing rapid, robust, cost-effective, patient-centred, routine genetic testing in ovarian cancer patients.

Advances in DNA sequencing have made genetic testing fast and affordable, but limitations of testing processes are impeding realisation of patient benefits. Ovarian cancer exemplifies the potential value of genetic testing and the shortcomings of current pathways to access testing. Approximately 15% of ovarian cancer patients have a germline BRCA1 or BRCA2 mutation which has substantial implications for their personal management and that of their relatives. Unfortunately, in most countries, routine implementation of BRCA testing for ovarian cancer patients has been inconsistent and largely unsuccessful. We developed a rapid, robust, mainstream genetic testing pathway in which testing is undertaken by the trained cancer team with cascade testing to relatives performed by the genetics team. 207 women with ovarian cancer were offered testing through the mainstream pathway. All accepted. 33 (16%) had a BRCA mutation. The result informed management of 79% (121/154) women with active disease. Patient and clinician feedback was very positive. The pathway offers a 4-fold reduction in time and 13-fold reduction in resource requirement compared to the conventional testing pathway. The mainstream genetic testing pathway we present is effective, efficient and patient-centred. It can deliver rapid, robust, large-scale, cost-effective genetic testing of BRCA1 and BRCA2 and may serve as an exemplar for other genes and other diseases.

CSN and CAVA: variant annotation tools for rapid, robust next-generation sequencing analysis in the clinical setting.

BACKGROUND: Next-generation sequencing (NGS) offers unprecedented opportunities to expand clinical genomics. It also presents challenges with respect to integration with data from other sequencing methods and historical data. Provision of consistent, clinically applicable variant annotation of NGS data has proved difficult, particularly of indels, an important variant class in clinical genomics. Annotation in relation to a reference genome sequence, the DNA strand of coding transcripts and potential alternative variant representations has not been well addressed. Here we present tools that address these challenges to provide rapid, standardized, clinically appropriate annotation of NGS data in line with existing clinical standards. METHODS: We developed a clinical sequencing nomenclature (CSN), a fixed variant annotation consistent with the principles of the Human Genome Variation Society (HGVS) guidelines, optimized for automated variant annotation of NGS data. To deliver high-throughput CSN annotation we created CAVA (Clinical Annotation of VAriants), a fast, lightweight tool designed for easy incorporation into NGS pipelines. CAVA allows transcript specification, appropriately accommodates the strand of a gene transcript and flags variants with alternative annotations to facilitate clinical interpretation and comparison with other datasets. We evaluated CAVA in exome data and a clinical BRCA1/BRCA2 gene testing pipeline. RESULTS: CAVA generated CSN calls for 10,313,034 variants in the ExAC database in 13.44 hours, and annotated the ICR1000 exome series in 6.5 hours. Evaluation of 731 different indels from a single individual revealed 92 % had alternative representations in left aligned and right aligned data. Annotation of left aligned data, as performed by many annotation tools, would thus give clinically discrepant annotation for the 339 (46 %) indels in genes transcribed from the forward DNA strand. By contrast, CAVA provides the correct clinical annotation for all indels. CAVA also flagged the 370 indels with alternative representations of a different functional class, which may profoundly influence clinical interpretation. CAVA annotation of 50 BRCA1/BRCA2 gene mutations from a clinical pipeline gave 100 % concordance with Sanger data; only 8/25 BRCA2 mutations were correctly clinically annotated by other tools. CONCLUSIONS: CAVA is a freely available tool that provides rapid, robust, high-throughput clinical annotation of NGS data, using a standardized clinical sequencing nomenclature.