Detecting clinically actionable variants in the 3' exons of PMS2 via a reflex workflow based on equivalent hybrid capture of the gene and its pseudogene

Background

Hereditary cancer screening (HCS) for germline variants in the 3′ exons of PMS2, a mismatch repair gene implicated in Lynch syndrome, is technically challenging due to homology with its pseudogene PMS2CL. Sequences of PMS2 and PMS2CL are so similar that next-generation sequencing (NGS) of short fragments—common practice in multigene HCS panels—may identify the presence of a variant but fail to disambiguate whether its origin is the gene or the pseudogene. Molecular approaches utilizing longer DNA fragments, such as long-range PCR (LR-PCR), can definitively localize variants in PMS2, yet applying such testing to all samples can have logistical and economic drawbacks.

Methods

To address these drawbacks, we propose and characterize a reflex workflow for variant discovery in the 3′ exons of PMS2. We cataloged the natural variation in PMS2 and PMS2CL in 707 samples and designed hybrid-capture probes to enrich the gene and pseudogene with equal efficiency. For PMS2 exon 11, NGS reads were aligned, filtered using gene-specific variants, and subject to standard diploid variant calling. For PMS2 exons 12–15, the NGS reads were permissively aligned to PMS2, and variant calling was performed with the expectation of observing four alleles (i.e., tetraploid calling). In this reflex workflow, short-read NGS identifies potentially reportable variants that are then subject to disambiguation via LR-PCR-based testing.

Results

Applying short-read NGS screening to 299 HCS samples and cell lines demonstrated >99% analytical sensitivity and >99% analytical specificity for single-nucleotide variants (SNVs) and short insertions and deletions (indels), as well as >96% analytical sensitivity and >99% analytical specificity for copy-number variants. Importantly, 92% of samples had resolved genotypes from short-read NGS alone, with the remaining 8% requiring LR-PCR reflex.

Conclusion

Our reflex workflow mitigates the challenges of screening in PMS2 and serves as a guide for clinical laboratories performing multigene HCS. To facilitate future exploration and testing of PMS2 variants, we share the raw and processed LR-PCR data from commercially available cell lines, as well as variant frequencies from a diverse patient cohort.

Electronic supplementary material

The online version of this article (10.1186/s12881-018-0691-9) contains supplementary material, which is available to authorized users.

Validation of an Expanded Carrier Screen that Optimizes Sensitivity via Full-Exon Sequencing and Panel-wide Copy Number Variant Identification

BACKGROUND

By identifying pathogenic variants across hundreds of genes, expanded carrier screening (ECS) enables prospective parents to assess the risk of transmitting an autosomal recessive or X-linked condition. Detection of at-risk couples depends on the number of conditions tested, the prevalence of the respective diseases, and the screen's analytical sensitivity for identifying disease-causing variants. Disease-level analytical sensitivity is often <100% in ECS tests because copy number variants (CNVs) are typically not interrogated because of their technical complexity.

METHODS

We present an analytical validation and preliminary clinical characterization of a 235-gene sequencing-based ECS with full coverage across coding regions, targeted assessment of pathogenic noncoding variants, panel-wide CNV calling, and specialized assays for technically challenging genes. Next-generation sequencing, customized bioinformatics, and expert manual call review were used to identify single-nucleotide variants, short insertions and deletions, and CNVs for all genes except FMR1 and those whose low disease incidence or high technical complexity precluded novel variant identification or interpretation.

RESULTS

Screening of 36859 patients' blood or saliva samples revealed the substantial impact on fetal disease-risk detection attributable to novel CNVs (9.19% of risk) and technically challenging conditions (20.2% of risk), such as congenital adrenal hyperplasia. Of the 7498 couples screened, 335 were identified as at risk for an affected pregnancy, underscoring the clinical importance of the test. Validation of our ECS demonstrated >99% analytical sensitivity and >99% analytical specificity.

CONCLUSIONS

Validated high-fidelity identification of different variant types-especially for diseases with complicated molecular genetics-maximizes at-risk couple detection.

Development and validation of a 36-gene sequencing assay for hereditary cancer risk assessment

The past two decades have brought many important advances in our understanding of the hereditary susceptibility to cancer. Numerous studies have provided convincing evidence that identification of germline mutations associated with hereditary cancer syndromes can lead to reductions in morbidity and mortality through targeted risk management options. Additionally, advances in gene sequencing technology now permit the development of multigene hereditary cancer testing panels. Here, we describe the 2016 revision of the Counsyl Inherited Cancer Screen for detecting single-nucleotide variants (SNVs), short insertions and deletions (indels), and copy number variants (CNVs) in 36 genes associated with an elevated risk for breast, ovarian, colorectal, gastric, endometrial, pancreatic, thyroid, prostate, melanoma, and neuroendocrine cancers. To determine test accuracy and reproducibility, we performed a rigorous analytical validation across 341 samples, including 118 cell lines and 223 patient samples. The screen achieved 100% test sensitivity across different mutation types, with high specificity and 100% concordance with conventional Sanger sequencing and multiplex ligation-dependent probe amplification (MLPA). We also demonstrated the screen's high intra-run and inter-run reproducibility and robust performance on blood and saliva specimens. Furthermore, we showed that pathogenic Alu element insertions can be accurately detected by our test. Overall, the validation in our clinical laboratory demonstrated the analytical performance required for collecting and reporting genetic information related to risk of developing hereditary cancers.

Design and validation of a next generation sequencing assay for hereditary BRCA1 and BRCA2 mutation testing

Hereditary breast and ovarian cancer syndrome, caused by a germline pathogenic variant in the BRCA1 or BRCA2 (BRCA1/2) genes, is characterized by an increased risk for breast, ovarian, pancreatic and other cancers. Identification of those who have a BRCA1/2 mutation is important so that they can take advantage of genetic counseling, screening, and potentially life-saving prevention strategies. We describe the design and analytic validation of the Counsyl Inherited Cancer Screen, a next-generation-sequencing-based test to detect pathogenic variation in the BRCA1 and BRCA2 genes. We demonstrate that the test is capable of detecting single-nucleotide variants (SNVs), short insertions and deletions (indels), and copy-number variants (CNVs, also known as large rearrangements) with zero errors over a 114-sample validation set consisting of samples from cell lines and deidentified patient samples, including 36 samples with BRCA1/2pathogenic germline mutations.

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Recent advances in sequencing technology make it possible to comprehensively catalog genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious, and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (i) initial read mapping; (ii) local realignment around indels; (iii) base quality score recalibration; (iv) SNP discovery and genotyping to find all potential variants; and (v) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We here discuss the application of these tools, instantiated in the Genome Analysis Toolkit, to deep whole-genome, whole-exome capture and multi-sample low-pass (∼4×) 1000 Genomes Project datasets.