Measuring coverage and accuracy of whole-exome sequencing in clinical context

A new long-read mitochondrial-genome protocol (PacBio HiFi) for haemosporidian parasites: a tool for population and biodiversity studies

BACKGROUND

Studies on haemosporidian diversity, including origin of human malaria parasites, malaria's zoonotic dynamic, and regional biodiversity patterns, have used target gene approaches. However, current methods have a trade-off between scalability and data quality. Here, a long-read Next-Generation Sequencing protocol using PacBio HiFi is presented. The data processing is supported by a pipeline that uses machine-learning for analysing the reads.

METHODS

A set of primers was designed to target approximately 6 kb, almost the entire length of the haemosporidian mitochondrial genome. Amplicons from different samples were multiplexed in an SMRTbell® library preparation. A pipeline (HmtG-PacBio Pipeline) to process the reads is also provided; it integrates multiple sequence alignments, a machine-learning algorithm that uses modified variational autoencoders, and a clustering method to identify the mitochondrial haplotypes/species in a sample. Although 192 specimens could be studied simultaneously, a pilot experiment with 15 specimens is presented, including in silico experiments where multiple data combinations were tested.

RESULTS

The primers amplified various haemosporidian parasite genomes and yielded high-quality mt genome sequences. This new protocol allowed the detection and characterization of mixed infections and co-infections in the samples. The machine-learning approach converged into reproducible haplotypes with a low error rate, averaging 0.2% per read (minimum of 0.03% and maximum of 0.46%). The minimum recommended coverage per haplotype is 30X based on the detected error rates. The pipeline facilitates inspecting the data, including a local blast against a file of provided mitochondrial sequences that the researcher can customize.

CONCLUSIONS

This is not a diagnostic approach but a high-throughput method to study haemosporidian sequence assemblages and perform genotyping by targeting the mitochondrial genome. Accordingly, the methodology allowed for examining specimens with multiple infections and co-infections of different haemosporidian parasites. The pipeline enables data quality assessment and comparison of the haplotypes obtained to those from previous studies. Although a single locus approach, whole mitochondrial data provide high-quality information to characterize species pools of haemosporidian parasites.

Improving somatic exome sequencing performance by biological replicates

BACKGROUND

Next-generation sequencing (NGS) technologies offer fast and inexpensive identification of DNA sequences. Somatic sequencing is among the primary applications of NGS, where acquired (non-inherited) variants are based on comparing diseased and healthy tissues from the same individual. Somatic mutations in genetic diseases such as cancer are tightly associated with genomic instability. Genomic instability increases heterogenity, complicating sequencing efforts further, a task already challenged by the presence of short reads and repetitions in human DNA. This leads to low concordance among studies and limits reproducibility. This limitation is a significant problem since identified mutations in somatic sequencing are major biomarkers for diagnosis and the primary input of targeted therapies. Benchmarking studies were conducted to assess the error rates and increase reproducibility. Unfortunately, the number of somatic benchmarking sets is very limited due to difficulties in validating true somatic variants. Moreover, most NGS benchmarking studies are based on relatively simpler germline (inherited) sequencing. Recently, a comprehensive somatic sequencing benchmarking set was published by Sequencing Quality Control Phase 2 (SEQC2). We chose this dataset for our experiments because it is a well-validated, cancer-focused dataset that includes many tumor/normal biological replicates. Our study has two primary goals. First goal is to determine how replicate-based consensus approaches can improve the accuracy of somatic variant detection systems. Second goal is to develop highly predictive machine learning (ML) models by employing replicate-based consensus variants as labels during the training phase.

RESULTS

Ensemble approaches that combine alternative algorithms are relatively common; here, as an alternative, we study the performance enhancement potential of biological replicates. We first developed replicate-based consensus approaches that utilize the biological replicates available in this study to improve variant calling performance. Subsequently, we trained ML models using these biological replicates and achieved performance comparable to optimal ML models, those trained using high-confidence variants identified in advance.

CONCLUSIONS

Our replicate-based consensus approach can be used to improve variant calling performance and develop efficient ML models. Given the relative ease of obtaining biological replicates, this strategy allows for the development of efficient ML models tailored to specific datasets or scenarios.

Cardio-cerebrovascular Outcomes in MODY, Type 1 Diabetes, and Type 2 Diabetes: A Prospective Cohort Study

CONTEXT

Cardio-cerebrovascular events are severe complications of diabetes.

OBJECTIVE

We aim to compare the incident risk of cardio-cerebrovascular events in maturity onset diabetes of the young (MODY), type 1 diabetes, and type 2 diabetes.

METHODS

Type 1 diabetes, type 2 diabetes, and MODY were diagnosed by whole exome sequencing. The primary endpoint was the occurrence of the first major adverse cardiovascular event (MACE), including acute myocardial infarction, heart failure, stroke, unstable angina pectoris, and cardio-cerebrovascular-related mortality. Cox proportional hazards models were applied and adjusted to calculate hazard ratios (HRs) and 95% CIs for the incident risk of MACE in type 1 diabetes, type 2 diabetes, MODY, and MODY subgroups compared with people without diabetes (control group).

RESULTS

Type 1 diabetes, type 2 diabetes, and MODY accounted for 2.7%, 68.1%, and 11.4% of 26 198 participants with diabetes from UK Biobank. During a median follow-up of 13 years, 1028 MACEs occurred in the control group, contrasting with 70 events in patients with type 1 diabetes (HR 2.15, 95% CI 1.69-2.74, P < .05), 5020 events in patients with type 2 diabetes (HR 7.02, 95% CI 6.56-7.51, P < .05), and 717 events in MODY (HR 5.79, 95% CI 5.26-6.37, P < .05). The hazard of MACE in HNF1B-MODY was highest among MODY subgroups (HR 11.00, 95% CI 5.47-22.00, P = 1.5 × 10-11).

CONCLUSION

MODY diagnosed by genetic analysis represents higher prevalence than the clinical diagnosis in UK Biobank. The risk of incident cardio-cerebrovascular events in MODY ranks between type 1 diabetes and type 2 diabetes.

FREQ-Seq2: a method for precise high-throughput combinatorial quantification of allele frequencies

The accurate determination of allele frequencies is crucially important across a wide range of problems in genetics, such as developing population genetic models, making inferences from genome-wide association studies, determining genetic risk for diseases, as well as other scientific and medical applications. Furthermore, understanding how allele frequencies change over time in populations is central to ascertaining their evolutionary dynamics. We present a precise, efficient, and economical method (FREQ-Seq2) for quantifying the relative frequencies of different alleles at loci of interest in mixed population samples. Through the creative use of paired barcode sequences, we exponentially increased the throughput of the original FREQ-Seq method from 48 to 2,304 samples. FREQ-Seq2 can be targeted to specific genomic regions of interest, which are amplified using universal barcoded adapters to generate Illumina sequencing libraries. Our enhanced method, available as a kit along with open-source software for analyzing sequenced libraries, enables the detection and removal of errors that are undetectable in the original FREQ-Seq method as well as other conventional methods for allele frequency quantification. Finally, we validated the performance of our sequencing-based approach with a highly multiplexed set of control samples as well as a competitive evolution experiment in Escherichia coli and compare the latter to estimates derived from manual colony counting. Our analyses demonstrate that FREQ-Seq2 is flexible, inexpensive, and produces large amounts of data with low error, low noise, and desirable statistical properties. In summary, FREQ-Seq2 is a powerful method for quantifying allele frequency that provides a versatile approach for profiling mixed populations.

DEVOUR: Deleterious Variants on Uncovered Regions in Whole-Exome Sequencing

The discovery of low-coverage (i.e. uncovered) regions containing clinically significant variants, especially when they are related to the patient's clinical phenotype, is critical for whole-exome sequencing (WES) based clinical diagnosis. Therefore, it is essential to develop tools to identify the existence of clinically important variants in low-coverage regions. Here, we introduce a desktop application, namely DEVOUR (DEleterious Variants On Uncovered Regions), that analyzes read alignments for WES experiments, identifies genomic regions with no or low-coverage (read depth < 5) and then annotates known variants in the low-coverage regions using clinical variant annotation databases. As a proof of concept, DEVOUR was used to analyze a total of 28 samples from a publicly available Hirschsprung disease-related WES project (NCBI Bioproject: https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB19327), revealing the potential existence of 98 disease-associated variants in low-coverage regions. DEVOUR is available from https://github.com/projectDevour/DEVOUR under the MIT license.

Mapinsights: deep exploration of quality issues and error profiles in high-throughput sequence data

High-throughput sequencing (HTS) has revolutionized science by enabling super-fast detection of genomic variants at base-pair resolution. Consequently, it poses the challenging problem of identification of technical artifacts, i.e. hidden non-random error patterns. Understanding the properties of sequencing artifacts holds the key in separating true variants from false positives. Here, we develop Mapinsights, a toolkit that performs quality control (QC) analysis of sequence alignment files, capable of detecting outliers based on sequencing artifacts of HTS data at a deeper resolution compared with existing methods. Mapinsights performs a cluster analysis based on novel and existing QC features derived from the sequence alignment for outlier detection. We applied Mapinsights on community standard open-source datasets and identified various quality issues including technical errors related to sequencing cycles, sequencing chemistry, sequencing libraries and across various orthogonal sequencing platforms. Mapinsights also enables identification of anomalies related to sequencing depth. A logistic regression-based model built on the features of Mapinsights shows high accuracy in detecting 'low-confidence' variant sites. Quantitative estimates and probabilistic arguments provided by Mapinsights can be utilized in identifying errors, bias and outlier samples, and also aid in improving the authenticity of variant calls.

Whole-Exome and Transcriptome Sequencing Expands the Genotype of Majewski Osteodysplastic Primordial Dwarfism Type II

Microcephalic Osteodysplastic Primordial Dwarfism type II (MOPDII) represents the most common form of primordial dwarfism. MOPD clinical features include severe prenatal and postnatal growth retardation, postnatal severe microcephaly, hypotonia, and an increased risk for cerebrovascular disease and insulin resistance. Autosomal recessive biallelic loss-of-function genomic variants in the centrosomal pericentrin (PCNT) gene on chromosome 21q22 cause MOPDII. Over the past decade, exome sequencing (ES) and massive RNA sequencing have been effectively employed for both the discovery of novel disease genes and to expand the genotypes of well-known diseases. In this paper we report the results both the RNA sequencing and ES of three patients affected by MOPDII with the aim of exploring whether differentially expressed genes and previously uncharacterized gene variants, in addition to PCNT pathogenic variants, could be associated with the complex phenotype of this disease. We discovered a downregulation of key factors involved in growth, such as IGF1R, IGF2R, and RAF1, in all three investigated patients. Moreover, ES identified a shortlist of genes associated with deleterious, rare variants in MOPDII patients. Our results suggest that Next Generation Sequencing (NGS) technologies can be successfully applied for the molecular characterization of the complex genotypic background of MOPDII.

Identification of genotype-biochemical phenotype correlations associated with fructose 1,6-bisphosphatase deficiency

Fructose-1,6-bisphosphatase (FBPase) deficiency, caused by an FBP1 mutation, is an autosomal recessive disorder characterized by hypoglycemic lactic acidosis. Due to the rarity of FBPase deficiency, the mechanism by which the mutations cause enzyme activity loss still remains unclear. Here we identify compound heterozygous missense mutations of FBP1, c.491G>A (p.G164D) and c.581T>C (p.F194S), in an adult patient with hypoglycemic lactic acidosis. The G164D and F194S FBP1 mutants exhibit decreased FBP1 protein expression and a loss of FBPase enzyme activity. The biochemical phenotypes of all previously reported FBP1 missense mutations in addition to G164D and F194S are classified into three functional categories. Type 1 mutations are located at pivotal residues in enzyme activity motifs and have no effects on protein expression. Type 2 mutations structurally cluster around the substrate binding pocket and are associated with decreased protein expression due to protein misfolding. Type 3 mutations are likely nonpathogenic. These findings demonstrate a key role of protein misfolding in mediating the pathogenesis of FBPase deficiency, particularly for Type 2 mutations. This study provides important insights that certain patients with Type 2 mutations may respond to chaperone molecules.

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

BACKGROUND

Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques.

RESULTS

We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection.

CONCLUSION

We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques.

Olaparib-Resistant BRCA2MUT Ovarian Cancer Cells with Restored BRCA2 Abrogate Olaparib-Induced DNA Damage and G2/M Arrest Controlled by the ATR/CHK1 Pathway for Survival

The PARP inhibitor (PARPi) olaparib is currently the drug of choice for serous ovarian cancer (OC), especially in patients with homologous recombination (HR) repair deficiency associated with deleterious BRCA1/2 mutations. Unfortunately, OC patients who fail to respond to PARPi or relapse after treatment have limited therapeutic options. To elucidate olaparib resistance and enhance the efficacy of olaparib, intracellular factors exploited by OC cells to achieve decreased sensitivity to PARPi were examined. An olaparib-resistant OC cell line, PEO1-OR, was established from BRCA2MUT PEO1 cells. The anticancer activity and action of olaparib combined with inhibitors of the ATR/CHK1 pathway (ceralasertib as ATRi, MK-8776 as CHK1i) in olaparib-sensitive and -resistant OC cell lines were evaluated. Whole-exome sequencing revealed that PEO1-OR cells acquire resistance through subclonal enrichment of BRCA2 secondary mutations that restore functional full-length protein. Moreover, PEO1-OR cells upregulate HR repair-promoting factors (BRCA1, BRCA2, RAD51) and PARP1. Olaparib-inducible activation of the ATR/CHK1 pathway and G2/M arrest is abrogated in olaparib-resistant cells. Drug sensitivity assays revealed that PEO1-OR cells are less sensitive to ATRi and CHK1i agents. Combined treatment is less effective in olaparib-resistant cells considering inhibition of metabolic activity, colony formation, survival, accumulation of DNA double-strand breaks, and chromosomal aberrations. However, synergistic antitumor activity between compounds is achievable in PEO1-OR cells. Collectively, olaparib-resistant cells display co-existing HR repair-related mechanisms that confer resistance to olaparib, which may be effectively utilized to resensitize them to PARPi via combination therapy. Importantly, the addition of ATR/CHK1 pathway inhibitors to olaparib has the potential to overcome acquired resistance to PARPi.

Genetic and metabolic investigations for neurodevelopmental disorders: position statement of the Canadian College of Medical Geneticists (CCMG)

PURPOSE AND SCOPE

The aim of this position statement is to provide recommendations for clinicians regarding the use of genetic and metabolic investigations for patients with neurodevelopmental disorders (NDDs), specifically, patients with global developmental delay (GDD), intellectual disability (ID) and/or autism spectrum disorder (ASD). This document also provides guidance for primary care and non-genetics specialists caring for these patients while awaiting consultation with a clinical geneticist or metabolic specialist.

METHODS OF STATEMENT DEVELOPMENT

A multidisciplinary group reviewed existing literature and guidelines on the use of genetic and metabolic investigations for the diagnosis of NDDs and synthesised the evidence to make recommendations relevant to the Canadian context. The statement was circulated for comment to the Canadian College of Medical Geneticists (CCMG) membership-at-large and to the Canadian Pediatric Society (Mental Health and Developmental Disabilities Committee); following incorporation of feedback, it was approved by the CCMG Board of Directors on 1 September 2022.

RESULTS AND CONCLUSIONS

Chromosomal microarray is recommended as a first-tier test for patients with GDD, ID or ASD. Fragile X testing should also be done as a first-tier test when there are suggestive clinical features or family history. Metabolic investigations should be done if there are clinical features suggestive of an inherited metabolic disease, while the patient awaits consultation with a metabolic physician. Exome sequencing or a comprehensive gene panel is recommended as a second-tier test for patients with GDD or ID. Genetic testing is not recommended for patients with NDDs in the absence of GDD, ID or ASD, unless accompanied by clinical features suggestive of a syndromic aetiology or inherited metabolic disease.

Benchmarking freely available HLA typing algorithms across varying genes, coverages and typing resolutions

Identifying the specific human leukocyte antigen (HLA) allele combination of an individual is crucial in organ donation, risk assessment of autoimmune and infectious diseases and cancer immunotherapy. However, due to the high genetic polymorphism in this region, HLA typing requires specialized methods. We investigated the performance of five next-generation sequencing (NGS) based HLA typing tools with a non-restricted license namely HLA*LA, Optitype, HISAT-genotype, Kourami and STC-Seq. This evaluation was done for the five HLA loci, HLA-A, -B, -C, -DRB1 and -DQB1 using whole-exome sequencing (WES) samples from 829 individuals. The robustness of the tools to lower depth of coverage (DOC) was evaluated by subsampling and HLA typing 230 WES samples at DOC ranging from 1X to 100X. The HLA typing accuracy was measured across four typing resolutions. Among these, we present two clinically-relevant typing resolutions (P group and pseudo-sequence), which specifically focus on the peptide binding region. On average, across the five HLA loci examined, HLA*LA was found to have the highest typing accuracy. For the individual loci, HLA-A, -B and -C, Optitype's typing accuracy was the highest and HLA*LA had the highest typing accuracy for HLA-DRB1 and -DQB1. The tools' robustness to lower DOC data varied widely and further depended on the specific HLA locus. For all Class I loci, Optitype had a typing accuracy above 95% (according to the modification of the amino acids in the functionally relevant portion of the HLA molecule) at 50X, but increasing the DOC beyond even 100X could still improve the typing accuracy of HISAT-genotype, Kourami, and STC-seq across all five HLA loci as well as HLA*LA's typing accuracy for HLA-DQB1. HLA typing is also used in studies of ancient DNA (aDNA), which is often based on sequencing data with lower quality and DOC. Interestingly, we found that Optitype's typing accuracy is not notably impaired by short read length or by DNA damage, which is typical of aDNA, as long as the DOC is sufficiently high.

Comparison of actionable events detected in cancer genomes by whole-genome sequencing, in silico whole-exome and mutation panels

Background

Next-generation sequencing is used in cancer research to identify somatic and germline mutations, which can predict sensitivity or resistance to therapies, and may be a useful tool to reveal drug repurposing opportunities between tumour types. Multigene panels are used in clinical practice for detecting targetable mutations. However, the value of clinical whole-exome sequencing (WES) and whole-genome sequencing (WGS) for cancer care is less defined, specifically as the majority of variants found using these technologies are of uncertain significance.

Patients and methods

We used the Cancer Genome Interpreter and WGS in 726 tumours spanning 10 cancer types to identify drug repurposing opportunities. We compare the ability of WGS to detect actionable variants, tumour mutation burden (TMB) and microsatellite instability (MSI) by using in silico down-sampled data to mimic WES, a comprehensive sequencing panel and a hotspot mutation panel.

Results

We reveal drug repurposing opportunities as numerous biomarkers are shared across many solid tumour types. Comprehensive panels identify the majority of approved actionable mutations, with WGS detecting more candidate actionable mutations for biomarkers currently in clinical trials. Moreover, estimated values for TMB and MSI vary when calculated from WGS, WES and panel data, and are dependent on whether all mutations or only non-synonymous mutations were used. Our results suggest that TMB and MSI thresholds should not only be tumour-dependent, but also be sequencing platform-dependent.

Conclusions

There is a large opportunity to repurpose cancer drugs, and these data suggest that comprehensive sequencing is an invaluable source of information to guide clinical decisions by facilitating precision medicine and may provide a wealth of information for future studies. Furthermore, the sequencing and analysis approach used to estimate TMB may have clinical implications if a hard threshold is used to indicate which patients may respond to immunotherapy.

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Genome analysis revealed that treatment biomarkers are shared across solid tumours, highlighting repurposing opportunities.

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Comprehensive panels detect most known biomarkers; however, WGS detects more biomarkers for treatments in clinical trials.

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TMB is well correlated between sequencing methods, but absolute values vary and are dependent on mutation types considered.

RNA-SSNV: A Reliable Somatic Single Nucleotide Variant Identification Framework for Bulk RNA-Seq Data

The usage of expressed somatic mutations may have a unique advantage in identifying active cancer driver mutations. However, accurately calling mutations from RNA-seq data is difficult due to confounding factors such as RNA-editing, reverse transcription, and gap alignment. In the present study, we proposed a framework (named RNA-SSNV, https://github.com/pmglab/RNA-SSNV) to call somatic single nucleotide variants (SSNV) from tumor bulk RNA-seq data. Based on a comprehensive multi-filtering strategy and a machine-learning classification model trained with comprehensively curated features, RNA-SSNV achieved the best precision–recall rate (0.880–0.884) in a testing dataset and robustly retained 0.94 AUC for the precision–recall curve in three validation adult-based TCGA (The Cancer Genome Atlas) datasets. We further showed that the somatic mutations called by RNA-SSNV tended to have a higher functional impact and therapeutic power in known driver genes. Furthermore, VAF (variant allele fraction) analysis revealed that subclonal harboring expressed mutations had evolutional selection advantage and RNA had higher detection power to rescue DNA-omitted mutations. In sum, RNA-SSNV will be a useful approach to accurately call expressed somatic mutations for a more insightful analysis of cancer drive genes and carcinogenic mechanisms.

Target-Sequencing of Female Infertility Pathogenic Gene Panel and a Novel TUBB8 Loss-of-Function Mutation

Genetic screening is an important approach for etiology determination and helps to optimize administration protocols in reproductive centers. After the first pathogenic gene of female infertility was reported in 2016, more and more new pathogenic genes were discovered, and we sought to develop an efficient and cost-effective method for genetic screening in patients. In this study, we designed a target-sequencing panel with 22 female infertility-related genes, namely, TUBB8, PATL2, WEE2, and PANX1 and sequenced 68 primary infertility (PI) and recurrent pregnancy loss (RPL) patients. We sequenced 68 samples reaching an average depth of 1559× and detected 3,134 variants. Among them, 62.2% were synonymous single-nucleotide variants (SNVs) and 36.3% were non-synonymous SNVs. The remaining 1.5% are indels (insertions and deletions) and stop-gains. DNAH11 and TUBB8 are the two genes that mutated most frequently. We also found a novel TUBB8 variant (c.898_900del; p.300_300del), proved its loss-of-function mechanism, and profiled the interactome of the wild-type (WT) and mutant TUBB8 proteins. Overall, this target-sequencing method provides an efficient and cost-effective approach for screening in IVF clinics and will support researchers for the discovery of new pathogenic variants.

Clinical and analytical validation of FoundationOne®CDx, a comprehensive genomic profiling assay for solid tumors

FoundationOne^®CDx (F1CDx) is a United States (US) Food and Drug Administration (FDA)-approved companion diagnostic test to identify patients who may benefit from treatment in accordance with the approved therapeutic product labeling for 28 drug therapies. F1CDx utilizes next-generation sequencing (NGS)-based comprehensive genomic profiling (CGP) technology to examine 324 cancer genes in solid tumors. F1CDx reports known and likely pathogenic short variants (SVs), copy number alterations (CNAs), and select rearrangements, as well as complex biomarkers including tumor mutational burden (TMB) and microsatellite instability (MSI), in addition to genomic loss of heterozygosity (gLOH) in ovarian cancer. CGP services can reduce the complexity of biomarker testing, enabling precision medicine to improve treatment decision-making and outcomes for cancer patients, but only if test results are reliable, accurate, and validated clinically and analytically to the highest standard available. The analyses presented herein demonstrate the extensive analytical and clinical validation supporting the F1CDx initial and subsequent FDA approvals to ensure high sensitivity, specificity, and reliability of the data reported. The analytical validation included several in-depth evaluations of F1CDx assay performance including limit of detection (LoD), limit of blank (LoB), precision, and orthogonal concordance for SVs (including base substitutions [SUBs] and insertions/deletions [INDELs]), CNAs (including amplifications and homozygous deletions), genomic rearrangements, and select complex biomarkers. The assay validation of >30,000 test results comprises a considerable and increasing body of evidence that supports the clinical utility of F1CDx to match patients with solid tumors to targeted therapies or immunotherapies based on their tumor’s genomic alterations and biomarkers. F1CDx meets the clinical needs of providers and patients to receive guideline-based biomarker testing, helping them keep pace with a rapidly evolving field of medicine.

Performance characterization of PCR-free whole genome sequencing for clinical diagnosis

To evaluate the performance of polymerase chain reaction (PCR)-free whole genome sequencing (WGS) for clinical diagnosis, and thereby revealing how experimental parameters affect variant detection.Five NA12878 samples were sequenced using MGISEQ-2000. NA12878 samples underwent WGS with differing deoxyribonucleic acid (DNA) input and library preparation protocol (PCR-based vs PCR-free protocols for library preparation). The depth of coverage and genotype quality of each sample were compared. The performance of each sample was measured for sensitivity, coverage of depth and breadth of coverage of disease-related genes, and copy number variants. We also developed a systematic WGS pipeline (PCR-free) for the analysis of 11 clinical cases.In general, NA12878-2 (PCR-free WGS) showed better depth of coverage and genotype quality distribution than NA12878-1 (PCR-based WGS). With a mean depth of ∼40×, the sensitivity of homozygous and heterozygous single nucleotide polymorphisms (SNPs) of NA12878-2 showed higher sensitivity (>99.77% and >99.82%) than NA12878-1, and positive predictive value exceeded 99.98% and 99.07%. The sensitivity and positive predictive value of homozygous and heterozygous indels for NA12878-2 (PCR-free WGS) showed great improvement than NA128878-1. The breadths of coverage for disease-related genes and copy number variants are slightly better for samples with PCR-free library preparation protocol than the sample with PCR-based library preparation protocol. DNA input also influences the performance of variant detection in samples with PCR-free WGS. All the 19 previously confirmed variants in 11 clinical cases were successfully detected by our WGS pipeline (PCR free).Different experimental parameters may affect variant detection for clinical WGS. Clinical scientists should know the range of sensitivity of variants for different methods of WGS, which would be useful when interpreting and delivering clinical reports.

Whole exome sequencing studies in epilepsy: A deep analysis of the published literature

To evaluate the quality of whole-exome sequencing (WES) reporting in the epilepsy literature. We aimed to assess the quality of reporting of WES in epilepsy. We compared studies based on journal type and if outcome reporting biases exist. We used a self-constructed benchmark to quantitatively analyze studies. We included 451 publications. Reporting was heterogeneous with poor reporting of (1) ACMG guideline application 13% and (2) Human Phenotype Ontology (HPO) numbers in 3% of studies, 3) VUS in 19%. Predictors of reporting included journal type and journal impact factor. Date of publication and publication type were not predictors of poor reporting. Pairwise comparisons of genetics versus neurology journals using relative risks yielded significant differences in reporting of ACMG guideline application (RR 1.88, 95% CI 1.04-3.38); HPO numbers (RR 8.62, 95% CI 1.08-63.37) and deposition of findings to ClinVar (RR 2.50, 95% CI 1.03-6.1). Reporting of WES literature is heterogeneous in quality, and poor reporting hinders collaboration and accession of data into large databases like OMIM and OrphaNet. This study highlights reporting bias in this area and, formal structural guidelines like the CONSORT guidelines used in the reporting of clinical trials are needed to address the issue.

Interest of exome sequencing trio-like strategy based on pooled parental DNA for diagnosis and translational research in rare diseases

Background

Exome sequencing (ES) has become the most powerful and cost‐effective molecular tool for deciphering rare diseases with a diagnostic yield approaching 30%–40% in solo‐ES and 50% in trio‐ES. We applied an innovative parental DNA pooling method to reduce the parental sequencing cost while maintaining the diagnostic yield of trio‐ES.

Methods

We pooled six (Agilent‐CRE‐v2–100X) or five parental DNA (TWIST‐HCE–70X) aiming to detect allelic balance around 8–10% for heterozygous status. The strategies were applied as second‐tier (74 individuals after negative solo‐ES) and first‐tier approaches (324 individuals without previous ES).

Results

The allelic balance of parental‐pool variants was around 8.97%. Sanger sequencing uncovered false positives in 1.5% of sporadic variants. In the second‐tier approach, we evaluated than two thirds of the Sanger validations performed after solo‐ES (41/59–69%) would have been saved if the parental‐pool segregations had been available from the start. The parental‐pool strategy identified a causative diagnosis in 18/74 individuals (24%) in the second‐tier and in 116/324 individuals (36%) in the first‐tier approaches, including 19 genes newly associated with human disorders.

Conclusions

Parental‐pooling is an efficient alternative to trio‐ES. It provides rapid segregation and extension to translational research while reducing the cost of parental and Sanger sequencing.

WEScover: selection between clinical whole exome sequencing and gene panel testing

Background

Whole exome sequencing (WES) is widely adopted in clinical and research settings; however, one of the practical concerns is the potential false negatives due to incomplete breadth and depth of coverage for several exons in clinically implicated genes. In some cases, a targeted gene panel testing may be a dependable option to ascertain true negatives for genomic variants in known disease-associated genes. We developed a web-based tool to quickly gauge whether all genes of interest would be reliably covered by WES or whether targeted gene panel testing should be considered instead to minimize false negatives in candidate genes.

Results

WEScover is a novel web application that provides an intuitive user interface for discovering breadth and depth of coverage across population-scale WES datasets, searching either by phenotype, by targeted gene panel(s) or by gene(s). Moreover, the application shows metrics from the Genome Aggregation Database to provide gene-centric view on breadth of coverage.

Conclusions

WEScover allows users to efficiently query genes and phenotypes for the coverage of associated exons by WES and recommends use of panel tests for the genes with potential incomplete coverage by WES.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04178-5.

Technical in-depth comparison of two massive parallel DNA-sequencing methods for formalin-fixed paraffin-embedded tissue from victims of sudden cardiac death

Sudden cardiac death (SCD) is a tragic and traumatic event. SCD is often associated with hereditary genetic disease and in such cases, sequencing of stored formalin fixed paraffin embedded (FFPE) tissue is often crucial in trying to find a causal genetic variant. This study was designed to compare two massive parallel sequencing assays for differences in sensitivity and precision regarding variants related to SCD in FFPE material. From eight cases of SCD where DNA from blood had been sequenced using HaloPlex, corresponding FFPE samples were collected six years later. DNA from FFPE samples were amplified using HaloPlex HS, sequenced on MiSeq, representing the first method, as well as amplified using modified Twist and sequenced on NextSeq, representing the second method. Molecular barcodes were included to distinguish artefacts from true variants. In both approaches, read coverage, uniformity and variant detection were compared using genomic DNA isolated from blood and corresponding FFPE tissue, respectively. In terms of coverage uniformity, Twist performed better than HaloPlex HS for FFPE samples. Despite higher overall coverage, amplicon-based HaloPlex technologies, both for blood and FFPE tissue, suffered from design and/or performance issues resulting in genes lacking complete coverage. Although Twist had considerably lower overall mean coverage, high uniformity resulted in equal or higher fraction of genes covered at ≥ 20X. By comparing variants found in the matched samples in a pre-defined cardiodiagnostic gene panel, HaloPlex HS for FFPE material resulted in high sensitivity, 98.0% (range 96.6-100%), and high precision, 99.9% (range 99.5-100%) for moderately fragmented samples, but suffered from reduced sensitivity (range 74.2-91.1%) in more severely fragmented samples due to lack of coverage. Twist had high sensitivity, 97.8% (range 96.8-98.7%) and high precision, 99.9% (range 99.3-100%) in all analyzed samples, including the severely fragmented samples.

Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders

Background

Due to its reduced cost and incomparable advantages, WGS is likely to lead to changes in clinical diagnosis of rare and undiagnosed diseases. However, the sensitivity and breadth of coverage of clinical WGS as a diagnostic test for genetic disorders has not been fully evaluated.

Methods

Here, the performance of WGS in NA12878, the YH cell line, and the Chinese trios were measured by assessing their sensitivity, PPV, depth and breadth of coverage using MGISEQ-2000. We also compared the performance of WES and WGS using NA12878. The sensitivity and PPV were tested using the family-based trio design for the Chinese trios. We further developed a systematic WGS pipeline for the analysis of 8 clinical cases.

Results

In general, the sensitivity and PPV for SNV/indel detection increased with mean depth and reached a plateau at an ~ 40X mean depth using down-sampling samples of NA12878. With a mean depth of 40X, the sensitivity of homozygous and heterozygous SNPs of NA12878 was > 99.25% and > 99.50%, respectively, and the PPV was 99.97% and 98.96%. Homozygous and heterozygous indels showed lower sensitivity and PPV. The sensitivity and PPV were still not 100% even with a mean depth of ~ 150X. We also observed a substantial variation in the sensitivity of CNV detection across different tools, especially in CNVs with a size less than 1 kb. In general, the breadth of coverage for disease-associated genes and CNVs increased with mean depth. The sensitivity and coverage of WGS (~ 40X) was better than WES (~ 120X). Among the Chinese trios with an ~ 40X mean depth, the sensitivity among offspring was > 99.48% and > 96.36% for SNP and indel detection, and the PPVs were 99.86% and 97.93%. All 12 previously validated variants in the 8 clinical cases were successfully detected using our WGS pipeline.

Conclusions

The current standard of a mean depth of 40X may be sufficient for SNV/indel detection and identification of most CNVs. It would be advisable for clinical scientists to determine the range of sensitivity and PPV for different classes of variants for a particular WGS pipeline, which would be useful when interpreting and delivering clinical reports.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-00948-5.

The Utility of Whole Exome Sequencing in Diagnosing Pediatric Neurological Disorders

Pediatric neurological disorders have a wide spectrum of clinical presentations and can be challenging to diagnose. Whole exome sequencing (WES) is increasingly becoming an integral diagnostic tool in medicine. It is cost-effective and has high diagnostic yield, especially in consanguineous populations. This study aims to review WES results and its value in diagnosing neurological disorders. A retrospective chart review was performed for WES results between the period of January 2018 to November 2019. Whole exome sequencing was requested for children with unexplained neurological signs and symptoms such as epilepsy, developmental delay, visual impairment, spasticity, hypotonia and magnetic resonance imaging (MRI) brain changes. It was conducted for children in a pediatric neurology clinic of a tertiary center at Jeddah, Saudi Arabia. Twenty-six children with undiagnosed neurological conditions were identified and underwent WES diagnosis. Nineteen patients (73.0%) of the cohort were diagnosed with pathogenic variants, likely pathogenic variants or variants of unknown significance (VUS). Consanguinity was positive in 18 families of the cohort (69.0%). Seven patients showed homozygous mutations. Five patients had heterozygous mutations. There were six patients with VUS and six patients had negative WES results. Whole exome sequencing showed a high diagnostic rate in this group of children with variable neurological disorders.

A novel variant in DMXL2 gene is associated with autosomal dominant non-syndromic hearing impairment (DFNA71) in a Cameroonian family

Approximately half of congenital hearing impairment cases are inherited, with non-syndromic hearing impairment (NSHI) being the most frequent clinical entity of genetic hearing impairment cases. A family from Cameroon with NSHI was investigated by performing exome sequencing using DNA samples obtained from three family members, followed by direct Sanger sequencing in additional family members and controls participants. We identified an autosomal dominantly inherited novel missense variant [NM_001174116.2:c.918G>T; p.(Q306H)] in DMXL2 gene (MIM:612186) that co-segregates with mild to profound non-syndromic sensorineural hearing impairment . The p.(Q306H) variant which substitutes a highly conserved glutamine residue is predicted deleterious by various bioinformatics tools and is absent from several genome databases. This variant was also neither found in 121 apparently healthy controls without a family history of hearing impairment , nor 112 sporadic NSHI cases from Cameroon. There is one previous report of a large Han Chinese NSHI family that segregates a missense variant in DMXL2. The present study provides additional evidence that DMXL2 is involved in hearing impairment etiology, and we suggest DMXL2 should be considered in diagnostic hearing impairment panels.

Genetic Testing in Neurodevelopmental Disorders

Neurodevelopmental disorders are the most prevalent chronic medical conditions encountered in pediatric primary care. In addition to identifying appropriate descriptive diagnoses and guiding families to evidence-based treatments and supports, comprehensive care for individuals with neurodevelopmental disorders includes a search for an underlying etiologic diagnosis, primarily through a genetic evaluation. Identification of an underlying genetic etiology can inform prognosis, clarify recurrence risk, shape clinical management, and direct patients and families to condition-specific resources and supports. Here we review the utility of genetic testing in patients with neurodevelopmental disorders and describe the three major testing modalities and their yields - chromosomal microarray, exome sequencing (with/without copy number variant calling), and FMR1 CGG repeat analysis for fragile X syndrome. Given the diagnostic yield of genetic testing and the potential for clinical and personal utility, there is consensus that genetic testing should be offered to all patients with global developmental delay, intellectual disability, and/or autism spectrum disorder. Despite this recommendation, data suggest that a minority of children with autism spectrum disorder and intellectual disability have undergone genetic testing. To address this gap in care, we describe a structured but flexible approach to facilitate integration of genetic testing into clinical practice across pediatric specialties and discuss future considerations for genetic testing in neurodevelopmental disorders to prepare pediatric providers to care for patients with such diagnoses today and tomorrow.

Massively Parallel Sequencing for Rare Genetic Disorders: Potential and Pitfalls

There have been two major eras in the history of gene discovery. The first was the era of linkage analysis, with approximately 1,300 disease-related genes identified by positional cloning by the turn of the millennium. The second era has been powered by two major breakthroughs: the publication of the human genome and the development of massively parallel sequencing (MPS). MPS has greatly accelerated disease gene identification, such that disease genes that would have taken years to map previously can now be determined in a matter of weeks. Additionally, the number of affected families needed to map a causative gene and the size of such families have fallen: de novo mutations, previously intractable by linkage analysis, can be identified through sequencing of the parent-child trio, and genes for recessive disease can be identified through MPS even of a single affected individual. MPS technologies include whole exome sequencing (WES), whole genome sequencing (WGS), and panel sequencing, each with their strengths. While WES has been responsible for most gene discoveries through MPS, WGS is superior in detecting copy number variants, chromosomal rearrangements, and repeat-rich regions. Panels are commonly used for diagnostic purposes as they are extremely cost-effective and generate manageable quantities of data, with no risk of unexpected findings. However, in instances of diagnostic uncertainty, it can be challenging to choose the right panel, and in these circumstances WES has a higher diagnostic yield. MPS has ethical, social, and legal implications, many of which are common to genetic testing generally but amplified due to the magnitude of data (e.g., relationship misattribution, identification of variants of uncertain significance, and genetic discrimination); others are unique to WES and WGS technologies (e.g., incidental or secondary findings). Nonetheless, MPS is rapidly translating into clinical practice as an extremely useful part of the clinical armamentarium.

Maximizing the acquisition of unique reads in noninvasive capture sequencing experiments

Noninvasive samples as a source of DNA are gaining interest in genomic studies of endangered species. However, their complex nature and low endogenous DNA content hamper the recovery of good quality data. Target capture has become a productive method to enrich the endogenous fraction of noninvasive samples, such as faeces, but its sensitivity has not yet been extensively studied. Coping with faecal samples with an endogenous DNA content below 1% is a common problem when prior selection of samples from a large collection is not possible. However, samples classified as unfavourable for target capture sequencing might be the only representatives of unique specific geographical locations, or to answer the question of interest. To explore how library complexity may be increased without repeating DNA extractions and generating new libraries, in this study we captured the exome of 60 chimpanzees (Pan troglodytes) using faecal samples with very low proportions of endogenous content (<1%). Our results indicate that by performing additional hybridizations of the same libraries, the molecular complexity can be maintained to achieve higher coverage. Also, whenever possible, the starting DNA material for capture should be increased. Finally, we specifically calculated the sequencing effort needed to avoid exhausting the library complexity of enriched faecal samples with low endogenous DNA content. This study provides guidelines, schemes and tools for laboratories facing the challenges of working with noninvasive samples containing extremely low amounts of endogenous DNA.

How geneticists think about Differences/Disorders of Sexual Development (DSD): A conversation

A multidisciplinary DSD clinic offers the opportunity for different specialties to learn from each other, as each provides their own perspective and expertise to the management of these complex patients, leading to collaborative care. For the patient, a multi-disciplinary clinic can improve access to care and decrease stress, as patients see all of the specialists on one day. For urologists seeing patients with DSD within a multi-disciplinary DSD clinic as well as independently, understanding what other specialists provide can help facilitate care and referral. Medical genetics is part of a multi-disciplinary DSD clinic. Given the recent advances in genetic diagnostics, many of the offered tests may be less familiar to the pediatric urologist. Therefore, this conversation reviews the clinical presentations and genetic testing options including chromosomal microarray, genetic testing panel, whole exome sequencing, and whole genome sequencing and how these can be helpful in the diagnosis and management of patients with DSD conditions.

Comprehensive genomic diagnosis of inherited retinal and optical nerve disorders reveals hidden syndromes and personalized therapeutic options

PURPOSE

In the era of precision medicine, genomic characterization of blind patients is critical. Here, we evaluate the effects of comprehensive genetic analysis on the etiologic diagnosis of potentially hereditary vision loss and its impact on clinical management.

METHODS

We studied 100 non-syndromic and syndromic Spanish patients with a clinical diagnosis of blindness caused by alterations on the retina, choroid, vitreous and/or optic nerve. We used a next-generation sequencing (NGS) panel (OFTALMOgenics™), developed and validated within this study, including up to 362 genes previously associated with these conditions.

RESULTS

We identified the genetic cause of blindness in 45% of patients (45/100). A total of 28.9% of genetically diagnosed cases (13/45) were syndromic and, of those, in 30.8% (4/13) extraophthalmic features had been overlooked and/or not related to visual impairment before genetic testing, including cases with Mainzer-Saldino, Bardet-Biedl, mucolipidosis and MLCRD syndromes. In two additional cases-syndromic blindness had been proposed before, but not specifically diagnosed, and one patient with Heimler syndrome had been misdiagnosed as an Usher case before testing. 33.3% of the genetically diagnosed patients (15/45) had causative variants in genes targeted by clinical trials exploring the curative potential of gene therapy approaches.

CONCLUSION

Comprehensive genomic testing provided clinically relevant insights in a large proportion of blind patients, identifying potential therapeutic opportunities or previously undiagnosed syndromes in 42.2% of the genetically diagnosed cases (19/45).

Clinical Massively Parallel Sequencing

BACKGROUND

The newest advances in DNA sequencing are based on technologies that perform massively parallel sequencing (MPS). Since 2006, the output from MPS platforms has increased from 20 Mb to >7 Tb. First-generation MPS platforms amplify individual DNA molecules to multiple copies and then interrogate the sequence of those molecules. Second-generation MPS analyzes single unamplified molecules to generate much longer sequence reads but with less output than first-generation MPS and lower first-pass accuracy. With MPS technologies, it is now possible to analyze genomes, exomes, a defined subset of genes, transcriptomes, and even methylation across the genome. These technologies have and will continue to completely transform the clinical practice.

CONTENT

The major first- and second-generation MPS platforms and how they are used in clinical practice are discussed.

SUMMARY

The ability to sequence terabases of DNA per run on an MPS platform will dramatically change how DNA sequencing is used in clinical practice. Currently, MPS of targeted gene panels is the most common use of this technology clinically, but as the cost for genome sequencing inches downward to $100, this may soon become the method of choice (with the caveat that, at least in the near term, clinical-grade genome sequencing with interpretation may cost much more than $100). Other uses of this technology include sequencing of a mixture of bacterial and viral species (metagenomics), as well as the characterization of methylation across the genome.

Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis

For a better interpretation of variants, evidence-based databases, such as ClinVar, compile data on the presumed relationships between variants and phenotypes. In this study, we aimed to analyze the pattern of sequencing depth in variants from whole-exome sequencing data in the 1000 Genomes project phase 3, focusing on the variants present in the ClinVar database that were predicted to affect protein-coding regions. We demonstrate that the distribution of the sequencing depth varies across different sequencing centers (pair-wise comparison, p < 0.001). Most importantly, we found that the distribution pattern of sequencing depth is specific to each facility, making it possible to correctly assign 96.9% of the samples to their sequencing center. Thus, indicating the presence of a systematic bias, related to the methods used in the different facilities, which generates significant variations in breadth and depth in whole-exome sequencing data in clinically relevant regions. Our results show that methodological differences, leading to significant heterogeneity in sequencing depth, may potentially influence the accuracy of genetic diagnosis. Furthermore, our findings highlight how it is still challenging to integrate results from different sequencing centers, which may also have an impact on genomic research.

Molecular genetic diagnostics of hypogonadotropic hypogonadism: from panel design towards result interpretation in clinical practice

Congenital hypogonadotropic hypogonadism (CHH) is a clinically and genetically heterogeneous congenital disease. Symptoms cover a wide spectrum from mild forms to complex phenotypes due to gonadotropin-releasing hormone (GnRH) deficiency. To date, more than 40 genes have been identified as pathogenic cause of CHH. These genes could be grouped into two major categories: genes controlling development and GnRH neuron migration and genes being responsible for neuroendocrine regulation and GnRH neuron function. High-throughput, next-generation sequencing (NGS) allows to analyze numerous gene sequences at the same time. Nowadays, whole exome or whole genome datasets could be investigated in clinical genetic diagnostics due to their favorable cost-benefit. The increasing genetic data generated by NGS reveal novel candidate genes and gene variants with unknown significance (VUSs). To provide clinically valuable genetic results, complex clinical and bioinformatics work are needed. The multifaceted genetics of CHH, the variable mode of inheritance, the incomplete penetrance, variable expressivity and oligogenic characteristics further complicate the interpretation of the genetic variants detected. The objective of this work, apart from reviewing the currently known genes associated with CHH, was to summarize the advantages and disadvantages of the NGS-based platforms and through the authors' own practice to guide through the whole workflow starting from gene panel design, performance analysis and result interpretation. Based on our results, a genetic diagnosis was clearly identified in 21% of cases tested (8/38).

Exploring the Molecular Aetiology of Preeclampsia by Massive Parallel Sequencing of DNA

PURPOSE OF REVIEW

This manuscript aims to review (for the first time) studies describing NGS sequencing of preeclampsia (PE) women's DNA.

RECENT FINDINGS

Describing markers for the early detection of PE is an essential task because, although associated molecular dysfunction begins early on during pregnancy, the disease's clinical signs usually appear late in pregnancy. Although several biochemical biomarkers have been proposed, their use in clinical environments is still limited, thereby encouraging research into PE's genetic origin. Hundreds of genes involved in numerous implantation- and placentation-related biological processes may be coherent candidates for PE aetiology. Next-generation sequencing (NGS) offers new technical possibilities for PE studying, as it enables large genomic regions to be analysed at affordable cost. This technique has facilitated the description of genes contributing to the molecular origin of a significant amount of monogenic and complex diseases. Regarding PE, NGS of DNA has been used in familial and isolated cases, thereby enabling new genes potentially related to the phenotype to be proposed. For a better understanding of NGS, technical aspects, applications and limitations are presented initially. Thereafter, NGS studies of DNA in familial and non-familial cases are described, including pitfalls and positive findings. The information given here should enable scientists and clinicians to analyse and design new studies permitting the identification of novel clinically useful molecular PE markers.

KCNMA1-linked channelopathy

Bailey et al. review a new neurological channelopathy associated with KCNMA1, encoding the BK voltage- and Ca²⁺-activated K⁺ channel.

KCNMA1 encodes the pore-forming α subunit of the “Big K⁺” (BK) large conductance calcium and voltage-activated K⁺ channel. BK channels are widely distributed across tissues, including both excitable and nonexcitable cells. Expression levels are highest in brain and muscle, where BK channels are critical regulators of neuronal excitability and muscle contractility. A global deletion in mouse (KCNMA1^−/−) is viable but exhibits pathophysiology in many organ systems. Yet despite the important roles in animal models, the consequences of dysfunctional BK channels in humans are not well characterized. Here, we summarize 16 rare KCNMA1 mutations identified in 37 patients dating back to 2005, with an array of clinically defined pathological phenotypes collectively referred to as “KCNMA1-linked channelopathy.” These mutations encompass gain-of-function (GOF) and loss-of-function (LOF) alterations in BK channel activity, as well as several variants of unknown significance (VUS). Human KCNMA1 mutations are primarily associated with neurological conditions, including seizures, movement disorders, developmental delay, and intellectual disability. Due to the recent identification of additional patients, the spectrum of symptoms associated with KCNMA1 mutations has expanded but remains primarily defined by brain and muscle dysfunction. Emerging evidence suggests the functional BK channel alterations produced by different KCNMA1 alleles may associate with semi-distinct patient symptoms, such as paroxysmal nonkinesigenic dyskinesia (PNKD) with GOF and ataxia with LOF. However, due to the de novo origins for the majority of KCNMA1 mutations identified to date and the phenotypic variability exhibited by patients, additional evidence is required to establish causality in most cases. The symptomatic picture developing from patients with KCNMA1-linked channelopathy highlights the importance of better understanding the roles BK channels play in regulating cell excitability. Establishing causality between KCNMA1-linked BK channel dysfunction and specific patient symptoms may reveal new treatment approaches with the potential to increase therapeutic efficacy over current standard regimens.

Whole-Exome Sequencing Identifies Somatic Mutations Associated With Mortality in Metastatic Clear Cell Kidney Carcinoma

Clear cell renal cell carcinoma (ccRCC) is among the most aggressive histologic subtypes of kidney cancer, representing about 3% of all human cancers. Patients at stage IV have nearly 60% of mortality in 2–3 years after diagnosis. To date, most ccRCC studies have used DNA microarrays and targeted sequencing of a small set of well-established, commonly altered genes. An exception is the large multi-omics study of The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC), which identified new ccRCC genes based on whole exome-sequencing (WES) data, and molecular prognostic signatures based on transcriptomics, epigenetics and proteomics data. Applying WES to simultaneously interrogate virtually all exons in the human genome for somatic variation, here we analyzed the burden of coding somatic mutations in metastatic ccRCC primary tumors, and its association with patient mortality from cancer, in patients who received VEGF receptor-targeting drugs as the first-line therapy. To this end, we sequenced the exomes of ten tumor–normal pairs of ccRCC patient tissues from primary biopsies at >100× mean depth and called somatic coding variation. Mutation burden analysis prioritized 138 genes linked to patient mortality. A gene set enrichment analysis evidenced strong statistical support for the abundance of genes involved in the development of kidney cancer (p = 2.31 × 10⁻⁹) and carcinoma (p = 1.22 × 10⁻⁵), with 49 genes having direct links with kidney cancer according to the published records. Two of these genes, SIPA1L2 and EIF3A, demonstrated independent associations with mortality in TCGA-KIRC project data. Besides, three mutational signatures were found to be operative in the tumor exomes, one of which (COSMIC signature 12) has not been previously reported in ccRCC. Selection analysis yielded no detectable evidence of overall positive or negative selection, with the exome-wide number of nonsynonymous substitutions per synonymous site reflecting largely neutral tumor evolution. Despite the limited sample size, our results provide evidence for candidate genes where somatic mutation burden is tentatively associated with patient mortality in metastatic ccRCC, offering new potential pharmacological targets and a basis for further validation studies.

Case for genome sequencing in infants and children with rare, undiagnosed or genetic diseases

Up to 350 million people worldwide suffer from a rare disease, and while the individual diseases are rare, in aggregate they represent a substantial challenge to global health systems. The majority of rare disorders are genetic in origin, with children under the age of five disproportionately affected. As these conditions are difficult to identify clinically, genetic and genomic testing have become the backbone of diagnostic testing in this population. In the last 10 years, next-generation sequencing technologies have enabled testing of multiple disease genes simultaneously, ranging from targeted gene panels to exome sequencing (ES) and genome sequencing (GS). GS is quickly becoming a practical first-tier test, as cost decreases and performance improves. A growing number of studies demonstrate that GS can detect an unparalleled range of pathogenic abnormalities in a single laboratory workflow. GS has the potential to deliver unbiased, rapid and accurate molecular diagnoses to patients across diverse clinical indications and complex presentations. In this paper, we discuss clinical indications for testing and historical testing paradigms. Evidence supporting GS as a diagnostic tool is supported by superior genomic coverage, types of pathogenic variants detected, simpler laboratory workflow enabling shorter turnaround times, diagnostic and reanalysis yield, and impact on healthcare.

Comparative analysis of whole-genome sequencing pipelines to minimize false negative findings

Comprehensive and accurate detection of variants from whole-genome sequencing (WGS) is a strong prerequisite for translational genomic medicine; however, low concordance between analytic pipelines is an outstanding challenge. We processed a European and an African WGS samples with 70 analytic pipelines comprising the combination of 7 short-read aligners and 10 variant calling algorithms (VCAs), and observed remarkable differences in the number of variants called by different pipelines (max/min ratio: 1.3~3.4). The similarity between variant call sets was more closely determined by VCAs rather than by short-read aligners. Remarkably, reported minor allele frequency had a substantial effect on concordance between pipelines (concordance rate ratio: 0.11~0.92; Wald tests, P < 0.001), entailing more discordant results for rare and novel variants. We compared the performance of analytic pipelines and pipeline ensembles using gold-standard variant call sets and the catalog of variants from the 1000 Genomes Project. Notably, a single pipeline using BWA-MEM and GATK-HaplotypeCaller performed comparable to the pipeline ensembles for ‘callable’ regions (~97%) of the human reference genome. While a single pipeline is capable of analyzing common variants in most genomic regions, our findings demonstrated the limitations and challenges in analyzing rare or novel variants, especially for non-European genomes.