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.

Expanded carrier screening (ECS) identifies couples whose future children are at increased risk of Mendelian conditions. Historically, ECS has been performed with limited or no copy number variant (CNV) calling, often restricted to a handful of founder deletions. The lack of broad CNV calling may reduce the detection rate of ECS. We performed panel-wide copy number deletion calling on a large ECS patient cohort to determine its impact on detecting at-risk couples. For >10,000 anonymized patient samples tested on a validated 176-disease ECS panel, we performed CNV deletion calling on 161 autosomal-recessive disease genes and 10 genes associated with X-linked conditions (calls for several conditions such as SMN1, are treated as special cases and excluded from this analysis). Copy number calling was performed using a Hidden Markov Model on next generation sequencing depth data, and CNVs were identified down to single-exon resolution. Positive and low-confidence CNV calls emitted by the bioinformatics pipeline were reviewed manually by certified experts prior to being curated and reported to patients if found to be deleterious. Approximately 2% of patients have at least one pathogenic deletion CNV. Importantly, the collective frequency of novel pathogenic CNVs exceeds the rate with which founder CNVs (in CLN3, CTNS, GALC, HEXA, MCOLN1, and NEB) were identified in our previous 112-gene panel. Most of the observed deletions are not the six founder deletions we called in previous work, indicating that broader use of CNV calling will improve detection rates in ECS. The presented findings support inclusion of CNV deletion calling in clinical ECS panels such that at-risk couples can be identified with maximal sensitivity. Our large and growing CNV dataset will enable statistically powered studies of CNV frequencies by size, gene, and ethnicity.

Table S5. Allele frequencies from 155 GIAB and Polaris LR-PCRs (XLSX 233 kb)

BackgroundNoninvasive prenatal screening (NIPS) of common aneuploidies using cell-free DNA from maternal plasma is part of routine prenatal care and is widely used in both high-risk and low-risk patient populations. High specificity is needed for clinically acceptable positive predictive values. Maternal copy-number variants (mCNVs) have been reported as a source of false-positive aneuploidy results that compromises specificity.MethodsWe surveyed the mCNV landscape in 87,255 patients undergoing NIPS. We evaluated both previously reported and novel algorithmic strategies for mitigating the effects of mCNVs on the screen's specificity. Further, we analyzed the frequency, length, and positional distribution of CNVs in our large dataset to investigate the curation of novel fetal microdeletions, which can be identified by NIPS but are challenging to interpret clinically.ResultsmCNVs are common, with 65% of expecting mothers harboring an autosomal CNV spanning more than 200kb, underscoring the need for robust NIPS analysis strategies. By analyzing empirical and simulated data, we found that general, outlier-robust strategies reduce the rate of mCNV-caused false positives but not as appreciably as algorithms specifically designed to account for mCNVs. We demonstrate that large-scale tabulation of CNVs identified via routine NIPS could be clinically useful: together with the gene density of a putative microdeletion region, we show that the region's relative tolerance to duplications versus deletions may aid the interpretation of microdeletion pathogenicity.ConclusionsOur study thoroughly investigates a common source of NIPS false positives and demonstrates how to bypass its corrupting effects. Our findings offer insight into the interpretation of NIPS results and inform the design of NIPS algorithms suitable for use in screening in the general obstetric population.

Purpose By identifying pathogenic variants across hundreds of genes, expanded carrier screening (ECS) enables prospective parents to assess risk of transmitting an autosomal recessive or X-linked condition. Detection of at-risk couples depends on the number of conditions tested, the diseases’ respective prevalences, and the screen’s sensitivity for identifying disease-causing variants. Here we present an analytical validation of a 235-gene sequencing-based ECS with full coverage across coding regions, targeted assessment of pathogenic noncoding variants, panel-wide copy-number-variant (CNV) calling, and customized assays for technically challenging genes. Methods Next-generation sequencing, a customized bioinformatics pipeline, 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 precludes novel variant identification or interpretation. Variant calls were compared to reference and orthogonal data. Results Validation of our ECS data demonstrated >99% analytical sensitivity and >99% specificity. A preliminary assessment of 15,177 patient samples reveals the substantial impact on fetal disease-risk detection attributable to novel CNV calling (13.9% of risk) and technically challenging conditions (15.5% of risk), such as congenital adrenal hyperplasia. Conclusion Validated, high-fidelity identification of different variant types—especially in diseases with complicated molecular genetics—maximizes at-risk couple detection.

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.

To examine the impact of copy number variants (CNVs) on detection rates in expanded carrier screening (ECS) panels. ECS panels typically include analysis of copy number variation (CNV) for only a small subset of genes and exons, often to the detriment of detection rate. To assess the impact of panel-wide CNV analysis, a preliminary analysis was performed on 56,267 de-identified ECS tests performed by full-exon next-generation sequencing at Counsyl’s laboratory. A 93 gene subset (consisting of severe and profound diseases) of Counsyl’s ECS panel was analyzed to estimate the additional benefit of copy number analysis. The disease risk, i.e., the probability that a hypothetical child from randomly selected parents is affected by disease, was used as a metric for detection rate. No variant curation was performed on the detected CNVs and all detected deletions/duplications were assumed pathogenic. To calculate the disease risk, historical NGS data at Counsyl was used to estimate deleterious allele frequencies (AFs). The AFs were then used to calculate the disease risk with CNV estimates either excluded or included. Without CNV analysis, the disease risk of the 93 gene subpanel was 123 affected children per 100,000. The addition of CNV analysis increased the detection rate by 2.0%, to 125 affected children per 100,000. This change in disease risk is roughly equivalent to calling non-CNV variants via NGS in the 54 least prevalent genes, which contribute 2.0% of the observed disease risk. Panel-wide CNV analysis increases detection rate and provides more value than the addition of low-prevalence genes. CNV calling may be important to further reduce a patient’s residual risks for specific genes due to certain scenarios, e.g., family history of a genetic disease and partner testing of known carriers for recessive diseases. For example, in HBB, CFTR, and ATM, CNVs account for up to 9% of the total detection rate. Further work to assess the clinical impact of the discovered variants is ongoing.

Purpose The recent growth in pan-ethnic expanded carrier screening (ECS) has raised questions about how such panels might be designed and evaluated systematically. Design principles for ECS panels might improve clinical detection of at-risk couples and facilitate objective discussions of panel choice. Methods Guided by medical-society statements, we propose a method for the design of ECS panels that aims to maximize the aggregate and per-disease sensitivity and specificity across a range of Mendelian disorders considered serious by a systematic classification scheme. We evaluated this method retrospectively using results from 474,644 de-identified carrier screens. We then constructed several idealized panels to highlight strengths and limitations of different ECS methodologies. Results Based on modeled fetal risks for “severe” and “profound” diseases, a commercially available ECS panel (Counsyl) is expected to detect 183 affected conceptuses per 100,000 US births. A screen’s sensitivity is greatly impacted by two factors: (i) the methodology used (e.g., full-exon sequencing finds more affected conceptuses than targeted genotyping) and (ii) the detection rate of the screen for diseases with high prevalence and complex molecular genetics (e.g., fragile X syndrome). Conclusion The described approaches enable principled, quantitative evaluation of which diseases and methodologies are appropriate for pan-ethnic expanded carrier screening.

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.

I Supplementary Materials and Methods 2 1 CNV Deletion Calling 2 2 Census Weighting 2 3 Disease Risk Calculation 2 3.1 Additive Approximation to Disease Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 3.2 Example: Autosomal Recessive Disease Risk for one Disease . . . . . . . . . . . . . . . . . . . . . . 3 3.3 Calculating Disease Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 3.4 Designing Optimal Targeted Genotyping Panels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 4 References 4

The PNAS paper “Recurrent rewiring and emergence of RNA regulatory networks” by Wilinski et al. (1) has a number of flaws. The paper incorrectly interprets the data underlying its major, novel claim about target rewiring. The paper also presents models that conflict with previous results and does not consider existing models that do explain all available results. First, the major novel result from Wilinski et al. (1) is that Neurospora crassa Puf4/5 targets are enriched for cytosolic ribosomal protein mRNAs and that these interactions have been conserved since the common ancestor of Saccharomycotina and Pezizomycotina. This result conflicts with published results (2) and … [↵][1]1Email: gjhogan{at}alumni.stanford.edu. [1]: #xref-corresp-1-1

Reprogramming of a gene's expression pattern by acquisition and loss of sequences recognized by specific regulatory RNA binding proteins may be a major mechanism in the evolution of biological regulatory programs. We identified that RNA targets of Puf3 orthologs have been conserved over 100-500 million years of evolution in five eukaryotic lineages. Focusing on Puf proteins and their targets across 80 fungi, we constructed a parsimonious model for their evolutionary history. This model entails extensive and coordinated changes in the Puf targets as well as changes in the number of Puf genes and alterations of RNA binding specificity including that: 1) Binding of Puf3 to more than 200 RNAs whose protein products are predominantly involved in the production and organization of mitochondrial complexes predates the origin of budding yeasts and filamentous fungi and was maintained for 500 million years, throughout the evolution of budding yeast. 2) In filamentous fungi, remarkably, more than 150 of the ancestral Puf3 targets were gained by Puf4, with one lineage maintaining both Puf3 and Puf4 as regulators and a sister lineage losing Puf3 as a regulator of these RNAs. The decrease in gene expression of these mRNAs upon deletion of Puf4 in filamentous fungi (N. crassa) in contrast to the increase upon Puf3 deletion in budding yeast (S. cerevisiae) suggests that the output of the RNA regulatory network is different with Puf4 in filamentous fungi than with Puf3 in budding yeast. 3) The coregulated Puf4 target set in filamentous fungi expanded to include mitochondrial genes involved in the tricarboxylic acid (TCA) cycle and other nuclear-encoded RNAs with mitochondrial function not bound by Puf3 in budding yeast, observations that provide additional evidence for substantial rewiring of post-transcriptional regulation. 4) Puf3 also expanded and diversified its targets in filamentous fungi, gaining interactions with the mRNAs encoding the mitochondrial electron transport chain (ETC) complex I as well as hundreds of other mRNAs with nonmitochondrial functions. The many concerted and conserved changes in the RNA targets of Puf proteins strongly support an extensive role of RNA binding proteins in coordinating gene expression, as originally proposed by Keene. Rewiring of Puf-coordinated mRNA targets and transcriptional control of the same genes occurred at different points in evolution, suggesting that there have been distinct adaptations via RNA binding proteins and transcription factors. The changes in Puf targets and in the Puf proteins indicate an integral involvement of RNA binding proteins and their RNA targets in the adaptation, reprogramming, and function of gene expression.