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.

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.

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.

The Tatton-Brown-Rahman Syndrome: A clinical study of 55 individuals with de novo constitutive DNMT3A variants.

Tatton-Brown-Rahman syndrome (TBRS; OMIM 615879), also known as the DNMT3A-overgrowth syndrome, is an overgrowth intellectual disability syndrome first described in 2014 with a report of 13 individuals with constitutive heterozygous DNMT3A variants. Here we have undertaken a detailed clinical study of 55 individuals with de novoDNMT3A variants, including the 13 previously reported individuals. An intellectual disability and overgrowth were reported in >80% of individuals with TBRS and were designated major clinical associations. Additional frequent clinical associations (reported in 20-80% individuals) included an evolving facial appearance with low-set, heavy, horizontal eyebrows and prominent upper central incisors; joint hypermobility (74%); obesity (weight ³2SD, 67%); hypotonia (54%); behavioural/psychiatric issues (most frequently autistic spectrum disorder, 51%); kyphoscoliosis (33%) and afebrile seizures (22%). One individual was diagnosed with acute myeloid leukaemia in teenage years. Based upon the results from this study, we present our current management for individuals with TBRS.

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.

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.

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.

Mutations in the transcriptional repressor REST predispose to Wilms tumor.

Wilms tumor is the most common childhood renal cancer. To identify mutations that predispose to Wilms tumor, we are conducting exome sequencing studies. Here we describe 11 different inactivating mutations in the REST gene (encoding RE1-silencing transcription factor) in four familial Wilms tumor pedigrees and nine non-familial cases. Notably, no similar mutations were identified in the ICR1000 control series (13/558 versus 0/993; P < 0.0001) or in the ExAC series (13/558 versus 0/61,312; P < 0.0001). We identified a second mutational event in two tumors, suggesting that REST may act as a tumor-suppressor gene in Wilms tumor pathogenesis. REST is a zinc-finger transcription factor that functions in cellular differentiation and embryonic development. Notably, ten of 11 mutations clustered within the portion of REST encoding the DNA-binding domain, and functional analyses showed that these mutations compromise REST transcriptional repression. These data establish REST as a Wilms tumor predisposition gene accounting for ∼2% of Wilms tumor.

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.

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.

Whole-exome sequencing reveals the mutational spectrum of testicular germ cell tumours.

Testicular germ cell tumours (TGCTs) are the most common cancer in young men. Here we perform whole-exome sequencing (WES) of 42 TGCTs to comprehensively study the cancer's mutational profile. The mutation rate is uniformly low in all of the tumours (mean 0.5 mutations per Mb) as compared with common cancers, consistent with the embryological origin of TGCT. In addition to expected copy number gain of chromosome 12p and mutation of KIT, we identify recurrent mutations in the tumour suppressor gene CDC27 (11.9%). Copy number analysis reveals recurring amplification of the spermatocyte development gene FSIP2 (15.3%) and a 0.4 Mb region at Xq28 (15.3%). Two treatment-refractory patients are shown to harbour XRCC2 mutations, a gene strongly implicated in defining cisplatin resistance. Our findings provide further insights into genes involved in the development and progression of TGCT.

Multi-stage genome-wide association study identifies new susceptibility locus for testicular germ cell tumour on chromosome 3q25.

Recent genome-wide association studies (GWAS) and subsequent meta-analyses have identified over 25 SNPs at 18 loci, together accounting for >15% of the genetic susceptibility to testicular germ cell tumour (TGCT). To identify further common SNPs associated with TGCT, here we report a three-stage experiment, involving 4098 cases and 18 972 controls. Stage 1 comprised previously published GWAS analysis of 307 291 SNPs in 986 cases and 4946 controls. In Stage 2, we used previously published customised Illumina iSelect genotyping array (iCOGs) data across 694 SNPs in 1064 cases and 10 082 controls. Here, we report new genotyping of eight SNPs showing some evidence of association in combined analysis of Stage 1 and Stage 2 in an additional 2048 cases of TGCT and 3944 controls (Stage 3). Through fixed-effects meta-analysis across three stages, we identified a novel locus at 3q25.31 (rs1510272) demonstrating association with TGCT [per-allele odds ratio (OR) = 1.16, 95% confidence interval (CI) = 1.06-1.27; P = 1.2 × 10(-9)].

The ICR1000 UK exome series: a resource of gene variation in an outbred population.

To enhance knowledge of gene variation in outbred populations, and to provide a dataset with utility in research and clinical genomics, we performed exome sequencing of 1,000 UK individuals from the general population and applied a high-quality analysis pipeline that includes high sensitivity and specificity for indel detection. Each UK individual has, on average, 21,978 gene variants including 160 rare (0.1%) variants not present in any other individual in the series. These data provide a baseline expectation for gene variation in an outbred population. Summary data of all 295,391 variants we detected are included here and the individual exome sequences are available from the European Genome-phenome Archive as the ICR1000 UK exome series. Furthermore, samples and other phenotype and experimental data for these individuals are obtainable through application to the 1958 Birth Cohort committee.

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.

Breast cancer risk and 6q22.33: combined results from Breast Cancer Association Consortium and Consortium of Investigators on Modifiers of BRCA1/2.

Recently, a locus on chromosome 6q22.33 (rs2180341) was reported to be associated with increased breast cancer risk in the Ashkenazi Jewish (AJ) population, and this association was also observed in populations of non-AJ European ancestry. In the present study, we performed a large replication analysis of rs2180341 using data from 31,428 invasive breast cancer cases and 34,700 controls collected from 25 studies in the Breast Cancer Association Consortium (BCAC). In addition, we evaluated whether rs2180341 modifies breast cancer risk in 3,361 BRCA1 and 2,020 BRCA2 carriers from 11 centers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Based on the BCAC data from women of European ancestry, we found evidence for a weak association with breast cancer risk for rs2180341 (per-allele odds ratio (OR) = 1.03, 95% CI 1.00-1.06, p = 0.023). There was evidence for heterogeneity in the ORs among studies (I(2) = 49.3%; p = <0.004). In CIMBA, we observed an inverse association with the minor allele of rs2180341 and breast cancer risk in BRCA1 mutation carriers (per-allele OR = 0.89, 95%CI 0.80-1.00, p = 0.048), indicating a potential protective effect of this allele. These data suggest that that 6q22.33 confers a weak effect on breast cancer risk.

A genome-wide association study identifies susceptibility loci for Wilms tumor.

Wilms tumor is the most common renal malignancy of childhood. To identify common variants that confer susceptibility to Wilms tumor, we conducted a genome-wide association study in 757 individuals with Wilms tumor (cases) and 1,879 controls. We evaluated ten SNPs in regions significantly associated at P < 5 × 10(-5) in two independent replication series from the UK (769 cases and 2,814 controls) and the United States (719 cases and 1,037 controls). We identified clear significant associations at 2p24 (rs3755132, P = 1.03 × 10(-14); rs807624, P = 1.32 × 10(-14)) and 11q14 (rs790356, P = 4.25 × 10(-15)). Both regions contain genes that are plausibly related to Wilms tumorigenesis. We also identified candidate association signals at 5q14, 22q12 and Xp22.

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.