Detection Of Structural Variants Research Articles

Actionable Structural Variant Detection via RNA-NGS and DNA-NGS in Patients With Advanced Non–Small Cell Lung Cancer

The National Comprehensive Cancer Network (NCCN) guidelines for non-small cell lung cancer suggest that RNA next-generation sequencing (NGS) may improve the detection of fusions and splicing variants compared with DNA-NGS alone. However, there is limited adoption of RNA-NGS in routine oncology clinical care today. To analyze clinical evidence from a diverse cohort of patients with advanced lung adenocarcinoma and compare the detection of NCCN-recommended actionable structural variants (aSVs; fusions and splicing variants) via concurrent DNA and RNA-NGS vs DNA-NGS alone. This multisite, retrospective cohort study examined patients sequenced between February 2021 and October 2023 within the deidentified, Tempus multimodal database, consisting of linked molecular and clinical data. Participants included patients with advanced lung adenocarcinoma and sufficient tissue sample quantities for both RNA-NGS and DNA-NGS testing. Received results from RNA-NGS and DNA-NGS solid-tissue profiling assays. Detection rates of NCCN guideline-based structural variants (ALK, ROS1, RET and NTRK1/2/3 fusions, as well as MET exon 14 skipping splicing alterations) found uniquely by RNA-NGS. In the evaluable cohort of 5570 patients, median (IQR) age was 67.8 (61.3-75.4) years, and 2989 patients (53.7%) were female. The prevalence of actionable structural variants detected by either RNA-NGS or DNA-NGS was 8.8% (n = 491), with 86.7% (n = 426) of these detected by DNA-NGS. Concurrent RNA-NGS and DNA-NGS identified 15.3% more patients harboring aSVs compared with DNA-NGS alone (491 vs 426 patients, respectively), including 14.3% more patients harboring actionable fusions (376 vs 329 patients) and 18.6% more patients harboring MET exon 14 skipping alterations (115 vs 97 patients). There was no significant association between the assay used for aSV detection and aSV-targeted therapeutic adoption or clinical outcome. Emerging structural variants (eSVs) were found to have a combined prevalence to be 0.7%, with only 47.5% of eSVs detected by DNA-NGS. In this cohort study, the detection of structural variants via concurrent RNA-NGS and DNA-NGS was higher across multiple NCCN-guideline recommended biomarkers compared with DNA-NGS alone, suggesting that RNA-NGS should be routinely implemented in the care of patients with advanced NSCLC.

Optical genome mapping of structural variants in Parkinson’s disease-related induced pluripotent stem cells

BackgroundCertain structural variants (SVs) including large-scale genetic copy number variants, as well as copy number-neutral inversions and translocations may not all be resolved by chromosome karyotype studies. The identification of genetic risk factors for Parkinson’s disease (PD) has been primarily focused on the gene-disruptive single nucleotide variants. In contrast, larger SVs, which may significantly influence human phenotypes, have been largely underexplored. Optical genomic mapping (OGM) represents a novel approach that offers greater sensitivity and resolution for detecting SVs. In this study, we used induced pluripotent stem cell (iPSC) lines of patients with PD-linked SNCA and PRKN variants as a proof of concept to (i) show the detection of pathogenic SVs in PD with OGM and (ii) provide a comprehensive screening of genetic abnormalities in iPSCs.ResultsOGM detected SNCA gene triplication and duplication in patient-derived iPSC lines, which were not identified by long-read sequencing. Additionally, various exon deletions were confirmed by OGM in the PRKN gene of iPSCs, of which exon 3–5 and exon 2 deletions were unable to phase with conventional multiplex-ligation-dependent probe amplification. In terms of chromosomal abnormalities in iPSCs, no gene fusions, no aneuploidy but two balanced inter-chromosomal translocations were detected in one line that were absent in the parental fibroblasts and not identified by routine single nucleotide variant karyotyping.ConclusionsIn summary, OGM can detect pathogenic SVs in PD-linked genes as well as reveal genomic abnormalities for iPSCs that were not identified by other techniques, which is supportive for OGM’s future use in gene discovery and iPSC line screening.

Detection of structural variants linked to mutton flavor and odor in two closely related black goat breeds

BackgroundMutton quality is closely related to genetic variants and gene expression alterations during growth and development, resulting in differences in nutritional values, flavor, and odor.ResultsWe first evaluated and compared the composition of crude protein, crude fat, cholesterol, amino acid (AA), and fatty acid (FA) in the longissimus dorsi muscle of Guizhou black goats (GZB, n = 5) and Yunshang black goats (YBG, n = 6). The contents of cholesterol and FA related to odor in GZB were significantly lower than that in YBG, while the concentrations of umami amino acids and intramuscular fat were significantly higher in GZB. Furthermore, structural variants (SVs) in the genomes of GZB (n = 30) and YBG (n = 11) were explored. It was found that some regions in Chr 10/12/18 were densely involved with a large number of SVs in the genomes of GZB and YBG. By setting FST ≥ 0.25, we got 837 stratified SVs, of which 25 SVs (involved in 12 genes, e.g., CORO1A, CLIC6, PCSK2, and TMEM9) were limited in GZB. Functional enrichment analysis of 14 protein-coding genes (e.g., ENPEP, LIPC, ABCA5, and SLC6A15) revealed multiple terms and pathways related with metabolisms of AA, FA, and cholesterol. The SVs (n = 10) obtained by the whole genome resequencing were confirmed in percentages of 36.67 to 86.67% (n = 96) by PCR method. The SVa and SVd polymorphisms indicated a moderate negative correlation with HMGCS1 activity (n = 17).ConclusionThis study is the first to comprehensively reveal potential SVs related to mutton nutritional values, flavor, and odor based on genomic compare between two black goat breeds with closely genetic relationship. The SVs generated in this study provide a data resource for deeper studies to understand the genomic characteristics and possible evolutionary outcomes with better nutritional values, flavor and extremely light odor.

A unified framework to analyze transposable element insertion polymorphisms using graph genomes

Transposable elements are ubiquitous mobile DNA sequences generating insertion polymorphisms, contributing to genomic diversity. We present GraffiTE, a flexible pipeline to analyze polymorphic mobile elements insertions. By integrating state-of-the-art structural variant detection algorithms and graph genomes, GraffiTE identifies polymorphic mobile elements from genomic assemblies or long-read sequencing data, and genotypes these variants using short or long read sets. Benchmarking on simulated and real datasets reports high precision and recall rates. GraffiTE is designed to allow non-expert users to perform comprehensive analyses, including in models with limited transposable element knowledge and is compatible with various sequencing technologies. Here, we demonstrate the versatility of GraffiTE by analyzing human, Drosophila melanogaster, maize, and Cannabis sativa pangenome data. These analyses reveal the landscapes of polymorphic mobile elements and their frequency variations across individuals, strains, and cultivars.

Comprehensive evaluation and guidance of structural variation detection tools in chicken whole genome sequence data

BackgroundStructural variations (SVs) are widespread across genome and have a great impact on evolution, disease, and phenotypic diversity. Despite the development of numerous bioinformatic tools, commonly referred to as SV callers, tailored for detecting SVs using whole genome sequence (WGS) data and employing diverse algorithms, their performance necessitates rigorous evaluation with real data and validated SVs. Moreover, a considerable proportion of these tools have been primarily designed and optimized using human genome data. Consequently, their applicability and performance in Avian species, characterized by smaller genomes and distinct genomic architectures, remain inadequately assessed.ResultsWe performed a comprehensive assessment of the performance of ten widely used SV callers using population-level real genomic data with the validated five common types of SVs. The performance of SV callers varies with the types and sizes of SVs. As compared with other tools, GRIDSS, Lumpy, Wham, and Manta present better detection accuracy. Pindel can detect more small SVs than others. CNVnator and CNVkit can detect more medium and large copy number variations. Given the poor consistency among different SV callers, the combination calling strategy is not recommended. All tools show poor ability in the detection of insertions (especially with size > 150 bp). At least 50× read depth is required to detect more than 80% of the SVs for most tools.ConclusionsThis study highlights the importance and necessity of using real sequencing data, rather than simulated data only, with validated SVs for SV caller evaluation. Some practical guidance and suggestions are provided for SV detection in future researches.

Cas9-targeted-based long-read sequencing for genetic screening of RPE65 locus.

Long-read sequencing (LRS) enables accurate structural variant detection and variant phasing. When a molecular diagnosis is suspected, target enrichment can reduce the cost and duration of sequencing. LRS was conducted in five inherited retinal dystrophy (IRD) patients harboring a monoallelic variant in RPE65 that remained uncharacterized after clinical exome sequencing (CES). CRISPR-Cas9 guide RNA probes were designed to target a 31kb region, including the entire RPE65 locus. The DNA was sequenced on a MinION platform. Short-read ×30 whole-genome sequencing (WGS) was performed for five patients to validate nanopore results. The nanopore sequencing process yielded a median of 271 reads within the targeted region, with a mean depth of 109 and a median read size of 8kb. All variants identified by CES have been detected using this approach, and no additional RPE65 gene causative variants were found. Nanopore variant detection demonstrated performance akin to short-read WGS at similar coverage levels, although exhibiting increased false positive calls at lower coverage. In this study, we explore the advantages of using a targeted approach together with long-read sequencing to identify variants associated with IRD. The results underscore the utility of targeted long reads for characterizing patients affected by rare diseases when first-tier diagnostic tests are non-conclusive.

Novel Genes of the Male Reproductive System: Potential Roles in Male Reproduction and as Non-hormonal Male Contraceptive Targets.

The development of novel non-hormonal male contraceptives represents a pivotal frontier in reproductive health, driven by the need for safe, effective, and reversible contraceptive methods. This comprehensive review explores the genetic underpinnings of male fertility, emphasizing the crucial roles of specific genes and structural variants (SVs) identified through advanced sequencing technologies such as long-read sequencing (LRS). LRS has revolutionized the detection of structural variants and complex genomic regions, offering unprecedented precision and resolution over traditional next-generation sequencing (NGS). Key genetic targets, including those implicated in spermatogenesis and sperm motility, are highlighted, showcasing their potential as non-hormonal contraceptive targets. The review delves into the systematic identification and validation of male reproductive tract-specific genes, utilizing advanced transcriptomics and genomics studies with validation using novel knockout mouse models. We discuss the innovative application of small molecule inhibitors, developed through platforms like DNA-encoded chemistry technology (DEC-Tec), which have shown significant promise in preclinical models. Notable examples include inhibitors targeting serine/threonine kinase 33 (STK33), soluble adenylyl cyclase (sAC), cyclin-dependent kinase 2 (CDK2), and bromodomain testis associated (BRDT), each demonstrating nanomolar affinity and potential for reversible and specific inhibition of male fertility. This review also honors the contributions of Dr. David L. Garbers whose foundational work has paved the way for these advancements. The integration of genomic, proteomic, and chemical biology approaches, supported by interdisciplinary collaboration, is poised to transform male contraceptive development. Future perspectives emphasize the need for continued innovation and rigorous testing to bring these novel contraceptives from the laboratory to clinical application, promising a new era of male reproductive health management.

Performance of somatic structural variant calling in lung cancer using Oxford Nanopore sequencing technology

BackgroundLung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and seven structural variant callers comprised of generic callers (SVIM, Sniffles2, DELLY in generic mode and cuteSV) and somatic callers (Severus, SAVANA, nanomonsv and DELLY in somatic modes).ResultsDifferent combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short-read sequencing. When compared to somatic structural variants detected with short-read sequencing, more events were detected with long-read sequencing. The mean recall of somatic variant events identified by long-read sequencing was higher for the somatic callers (72%) than generic callers (53%). Among the somatic callers when using the minimap2 aligner, SAVANA and Severus achieved the highest recall at 79.5% and 79.25% respectively, followed by nanomonsv with a recall of 72.5%.ConclusionLong-read sequencing can identify somatic structural variants in clincal samples. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

Combining optical genome mapping and RNA-seq for structural variants detection and interpretation in unsolved neurodevelopmental disorders

BackgroundStructural variations (SVs) are key genetic contributors to neurodevelopmental disorders (NDDs). Exome sequencing (ES), the current first-line tool for genetic testing of NDDs, falls short in SVs detection. This diagnostic gap is being actively addressed by new methods such as optical genome mapping (OGM).MethodsThis study evaluated the utility of combining OGM and RNA-seq in the detection and interpretation of SVs in ES-negative NDDs. OGM was performed in 43 patients with NDDs with inconclusive ES results. Candidate SVs were selected based on disease association and pathogenicity evaluation, and further validated or reconstructed by alternative methods, including long-read sequencing for a complex rearrangement event. RNA-Seq was performed on blood samples from patients with candidate SVs to facilitate interpretation of pathogenicity.ResultsOGM detected four candidate SVs, and RNA-seq confirmed the pathogenicity of three SVs in the patient cohort. This combined approach solved three cases—two cases with de novo SVs in genes associated with autosomal dominant NDDs, including a deletion encompassing the promoter and 5′UTR of MBD5 and an intragenic duplication of PAFAH1B1, and a third case possessing an intragenic duplication in trans with a pathogenic single-nucleotide variant of PLA2G6, associated with autosomal recessive NDDs. The expression alteration of the affected genes and the tandem positioning of two intragenic duplications were confirmed by RNA-seq. In the fourth case, OGM detected a complex rearrangement involving chromosomes 2 and 6, much more complex than the de novo t(2:6)(q13;q15) indicated by conventional cytogenetic analysis. Reconstruction showed that 17 segments of 6q15 spanning 9.3 Mb were disarranged and joined 2q11.2, with four breakpoints detected in the 5′ and 3′ non-coding region of the NDD-associated gene SYNCRIP. RNA-seq revealed largely preserved SYNCRIP expression, leaving the pathogenicity of this complex rearrangement event uncertain.ConclusionsSVs in ES-negative NDDs can be identified by OGM, which is particularly useful for SVs in non-coding regions not covered by ES. OGM helps to construct complex SVs and provides information on the location and orientation of duplications, which is crucial for pathogenicity interpretation. The integration of RNA-seq facilitates the interpretation of the functional consequences of SVs at the transcriptional level. These findings demonstrate the utility and feasibility of combining OGM and RNA-seq in ES-negative cases with NDDs.

Constitutional mosaicism of pathogenic variants in SMARCB1 in a subset of patients with sporadic rhabdoid tumors.

Malignant rhabdoid tumors are aggressive malignancies predominantly affecting very young children. The characteristic genetic alteration is biallelic inactivation of SMARCB1. In approximately 30% of patients one SMARCB1 allele is constitutionally altered conferring a particularly unfavourable prognosis. Constitutional mosaicism for pathogenic SMARCB1 mutations has recently been reported in distinct cases of allegedly sporadic rhabdoid tumors. We aimed to systematically investigate the frequency and clinical impact of constitutional mosaicism in patients with sporadic rhabdoid tumors included in the EU-RHAB registry. We selected 29 patients with rhabdoid tumors displaying at least one pathogenic small variant in SMARCB1 in the tumor DNA and absence of a germline mutation. We re-screened blood-derived patient and control DNA for the respective small variant by PCR with unique molecular identifiers and ultra-deep next generation sequencing. Clinical data in patients with and without mosaicism and 174 EU-RHAB controls were compared. Employing an ultra-deep sequencing approach, we detected tumor-associated SMARCB1 variants in blood-derived DNA in 9/29 patients. In 6/29 patients (21%), whose variant allele frequency (VAF) exceeded 2%, constitutional mosaicism was assumed whereas tumor DNA contamination was documented in 1/3 patients with VAF below 1%. No significant differences were observed between 6 mosaic-positive and 20 -negative patients regarding age at diagnosis, presence of metastases, event-free or overall survival. Constitutional mosaicism for pathogenic small SMARCB1 variants is recurrent in patients with allegedly sporadic rhabdoid tumors. The clinical implications of such variants need to be determined in larger, prospective cohorts also including detection of structural variants of SMARCB1.

Abstract A083: Genomic Analysis of Structural Variations in Pancreatic Cancer Using Long-Read Sequencing

Abstract Objective: Structural variations (SVs) constitute the greatest source of genomic alterations leading to the oncogenesis of many cancers, including the deadliest pancreatic cancer (PC). However, SVs in PC remain largely undefined due to technological limitations of the traditional short-read sequencing. This study aims to establish a comprehensive signature of genomic SVs in PC. Methods: PacBio whole genome long-read sequencing was employed to investigate the genomic landscape of SVs in eight tissues from four pancreatic cancer patients. A variety of SVs callers, including pbsv, Sniffles, cuteSV, and svim, were comprehensively adopted to improve the accuracy of SVs detection. Many undefined characteristics of germline and somatic SVs were revealed by comparing with multiple previously published databases. Besides, the impacts of structural variations on 3D chromatin organization were analyzed by integrating multi-omics data including Hi-C, RNA seq and ChIP seq. Results: A total of 26,844 and 27,028 non-redundant SVs were identified in human pancreatic cancer and matched para-cancerous tissues, respectively. Notably, among these SVs, 23.97% were novel and had not been previously reported. Germline SVs were further characterized and found enriched in 25 well-known susceptible genes, such as TP63, PVT1, and ABO. Additionally, we proposed a panel of germline SVs with predicted highest pathogenicity, involving STOX1, DSPP, and WRN. Totally, 616 somatic SVs were identified and presented high burdens in patients with lymph node metastasis. We observed that somatic DELs and INSs were significantly more prevalent in repetitive regions than in non-repetitive regions. Interestingly, DELs showed a decrease in the proportion occurring in simple repeat regions but an increase in the proportion occurring in LINE and SINE regions compared to INSs. Moreover, it was observed that deletions within topologically associated domains were associated with local enhanced interactions and disrupted chromatin loops, which might influence H3K27ac modification of histone contributing to enhancer or silencer hijacking. Conclusion: This study provides insights into the genomic signature of SVs in human pancreatic cancer. These findings might shed new light on the complexity of SVs and their pathogenesis by interplaying with chromatin organization. Citation Format: Yongxing Du, Xiaohao Zheng, Yunjie Duan, Chengfeng Wang. Genomic Analysis of Structural Variations in Pancreatic Cancer Using Long-Read Sequencing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A083.

Impact and characterization of serial structural variations across humans and great apes

Modern sequencing technology enables the systematic detection of complex structural variation (SV) across genomes. However, extensive DNA rearrangements arising through a series of mutations, a phenomenon we refer to as serial SV (sSV), remain underexplored, posing a challenge for SV discovery. Here, we present NAHRwhals (https://github.com/WHops/NAHRwhals), a method to infer repeat-mediated series of SVs in long-read genomic assemblies. Applying NAHRwhals to haplotype-resolved human genomes from 28 individuals reveals 37 sSV loci of various length and complexity. These sSVs explain otherwise cryptic variation in medically relevant regions such as the TPSAB1 gene, 8p23.1, 22q11 and Sotos syndrome regions. Comparisons with great ape assemblies indicate that most human sSVs formed recently, after the human-ape split, and involved non-repeat-mediated processes in addition to non-allelic homologous recombination. NAHRwhals reliably discovers and characterizes sSVs at scale and independent of species, uncovering their genomic abundance and suggesting broader implications for disease.

High Prevalence of Chromosomal Rearrangements and LINE Retrotranspositions Detected in Formalin-Fixed, Paraffin-Embedded Colorectal Cancer Tissue

Structural variants (SVs) caused by chromosomal rearrangements in common fragile sites (CFS) or LINE retrotranspositions are highly prevalent in colorectal cancer (CRC). However, methodology for targeted detection of these SVs is lacking. We here report the use of formalin-fixed paraffin-embedded targeted locus capture (FFPE-TLC) sequencing as a novel technology for targeted detection of tumor-specific SVs. Analysis of 29 FFPE colorectal tumor and 8 matched normal samples revealed tumor-specific SVs in 24 patients (83%) with a median of 2 SVs per patient (range 1-21). 104 SVs were found in the CFS-associated genes MACROD2, PRKN, FHIT and WWOX in 18 patients (62%) and 39 SVs caused by three LINE transposable elements were found in 15 patients (52%). Tumor-specificity of SVs was independently verified by droplet digital PCR of tumor tissue DNA and their applicability as plasma circulating tumor DNA biomarkers was demonstrated. We conclude that FFPE-TLC sequencing enables the detection of tumor-specific SVs caused by chromosomal rearrangements and LINE retrotranspositions in FFPE tissue. Therefore, FFPE-TLC sequencing facilitates the investigation of the biological and clinical impact of SVs using FFPE material from (retrospective) cohorts of cancer patients and has potential clinical applicability to detect SV biomarkers in the routine molecular diagnostics setting.

Detection and analysis of complex structural variation in human genomes across populations and in brains of donors with psychiatric disorders.

Complex structural variations (cxSVs) are often overlooked in genome analyses due to detection challenges. We developed ARC-SV, a probabilistic and machine-learning-based method that enables accurate detection and reconstruction of cxSVs from standard datasets. By applying ARC-SV across 4,262 genomes representing all continental populations, we identified cxSVs as a significant source of natural human genetic variation. Rare cxSVs have a propensity to occur in neural genes and loci that underwent rapid human-specific evolution, including those regulating corticogenesis. By performing single-nucleus multiomics in postmortem brains, we discovered cxSVs associated with differential gene expression and chromatin accessibility across various brain regions and cell types. Additionally, cxSVs detected in brains of psychiatric cases are enriched for linkage with psychiatric GWAS risk alleles detected in the same brains. Furthermore, our analysis revealed significantly decreased brain-region- and cell-type-specific expression of cxSV genes, specifically for psychiatric cases, implicating cxSVs in the molecular etiology of major neuropsychiatric disorders.

Genomic structural variations link multiple genes to bone mineral density in a multi-ethnic cohort study: Louisiana osteoporosis study.

Osteoporosis, characterized by low BMD, is a highly heritable metabolic bone disorder. Although single nucleotide variations (SNVs) have been extensively studied, they explain only a fraction of BMD heritability. Although genomic structural variations (SVs) are large-scale genomic alterations that contribute to genetic diversity in shaping phenotypic variations, the role of SVs in osteoporosis susceptibility remains poorly understood. This study aims to identify and prioritize genes that harbor BMD-related SVs. We performed whole genome sequencing on 4982 subjects from the Louisiana Osteoporosis Study. To obtain high-confidence SVs, the detection of SVs was performed using an ensemble approach. The SVs were tested for association with BMD variation at the hip (HIP), femoral neck (FNK), and lumbar spine (SPN), respectively. Additionally, we conducted co-occurrence analysis using multi-omics approaches to prioritize the identified genes based on their functional importance. Stratification was employed to explore the sex- and ethnicity-specific effects. We identified significant SV-BMD associations: 125 for FNK-BMD, 99 for SPN-BMD, and 83 for HIP-BMD. We observed SVs that were commonly associated with both FNK and HIP BMDs in our combined and stratified analyses. These SVs explain 13.3% to 19.1% of BMD variation. Novel bone-related genes emerged, including LINC02370, ZNF family genes, and ZDHHC family genes. Additionally, FMN2, carrying BMD-related deletions, showed associations with FNK or HIP BMDs, with sex-specific effects. The co-occurrence analysis prioritized an RNA gene LINC00494 and ZNF family genes positively associated with BMDs at different skeletal sites. Two potential causal genes, IBSP and SPP1, for osteoporosis were also identified. Our study uncovers new insights into genetic factors influencing BMD through SV analysis. We highlight BMD-related SVs, revealing a mix of shared and specific genetic influences across skeletal sites and gender or ethnicity. These findings suggest potential roles in osteoporosis pathophysiology, opening avenues for further research and therapeutic targets.

CYP2D6 copy number determination using digital PCR.

CYP2D6 testing is increasingly used to guide drug therapy and thus, reliable methods are needed to test this complex and polymorphic gene locus. A particular challenge arises from the detection and interpretation of structural variants (SVs) including gene deletions, duplications, and hybrids with the CYP2D7 pseudogene. This study validated the Absolute Q™ platform for digital PCR-based CYP2D6 copy number variation (CNV) determination by comparing results to those obtained with a previously established method using the QX200 platform. In addition, protocols for streamlining CYP2D6 CNV testing were established and validated including the "One-pot" single-step restriction enzyme digestion and a multiplex assay simultaneously targeting the CYP2D6 5'UTR, intron 6, and exon 9 regions. Genomic DNA (gDNA) samples from Coriell (n = 13) and from blood, saliva, and liver tissue (n = 17) representing 0-6 copies were tested on the Absolute Q and QX200 platforms. Custom TaqMan™ copy number (CN) assays targeting CYP2D6 the 5'UTR, intron 6, and exon 9 regions and a reference gene assay (TERT or RNaseP) were combined for multiplexing by optical channel. In addition, two digestion methods (One-pot digestion and traditional) were assessed. Inconclusive CN values on the Absolute Q were resolved using an alternate reference gene and/or diluting gDNA. Overall, results between the two platforms and digestions methods were consistent. The "One-pot" digestion method and optically multiplexing up to three CYP2D6 regions yielded consistent result across DNA sample types and diverse SVs, reliably detecting up to 6 gene copies. Rare variation in reference genes were found to interfere with results and interpretation, which were resolved by using a different reference. The Absolute Q produced accurate and reliable CYP2D6 copy number results allowing for a streamlined and economical protocol using One-pot digestion and multiplexing three target regions. Protocols are currently being expanded to other pharmacogenes presenting with SVs/CNVs.

VolcanoSV enables accurate and robust structural variant calling in diploid genomes from single-molecule long read sequencing

Structural variants (SVs) significantly contribute to human genome diversity and play a crucial role in precision medicine. Although advancements in single-molecule long-read sequencing offer a groundbreaking resource for SV detection, identifying SV breakpoints and sequences accurately and robustly remains challenging. We introduce VolcanoSV, an innovative hybrid SV detection pipeline that utilizes both a reference genome and local de novo assembly to generate a phased diploid assembly. VolcanoSV uses phased SNPs and unique k-mer similarity analysis, enabling precise haplotype-resolved SV discovery. VolcanoSV is adept at constructing comprehensive genetic maps encompassing SNPs, small indels, and all types of SVs, making it well-suited for human genomics studies. Our extensive experiments demonstrate that VolcanoSV surpasses state-of-the-art assembly-based tools in the detection of insertion and deletion SVs, exhibiting superior recall, precision, F1 scores, and genotype accuracy across a diverse range of datasets, including low-coverage (10x) datasets. VolcanoSV outperforms assembly-based tools in the identification of complex SVs, including translocations, duplications, and inversions, in both simulated and real cancer data. Moreover, VolcanoSV is robust to various evaluation parameters and accurately identifies breakpoints and SV sequences.

VISTA: an integrated framework for structural variant discovery.

Structural variation (SV) refers to insertions, deletions, inversions, and duplications in human genomes. SVs are present in approximately 1.5% of the human genome. Still, this small subset of genetic variation has been implicated in the pathogenesis of psoriasis, Crohn's disease and other autoimmune disorders, autism spectrum and other neurodevelopmental disorders, and schizophrenia. Since identifying structural variants is an important problem in genetics, several specialized computational techniques have been developed to detect structural variants directly from sequencing data. With advances in whole-genome sequencing (WGS) technologies, a plethora of SV detection methods have been developed. However, dissecting SVs from WGS data remains a challenge, with the majority of SV detection methods prone to a high false-positive rate, and no existing method able to precisely detect a full range of SVs present in a sample. Previous studies have shown that none of the existing SV callers can maintain high accuracy across various SV lengths and genomic coverages. Here, we report an integrated structural variant calling framework, Variant Identification and Structural Variant Analysis (VISTA), that leverages the results of individual callers using a novel and robust filtering and merging algorithm. In contrast to existing consensus-based tools which ignore the length and coverage, VISTA overcomes this limitation by executing various combinations of top-performing callers based on variant length and genomic coverage to generate SV events with high accuracy. We evaluated the performance of VISTA on comprehensive gold-standard datasets across varying organisms and coverage. We benchmarked VISTA using the Genome-in-a-Bottle gold standard SV set, haplotype-resolved de novo assemblies from the Human Pangenome Reference Consortium, along with an in-house polymerase chain reaction (PCR)-validated mouse gold standard set. VISTA maintained the highest F1 score among top consensus-based tools measured using a comprehensive gold standard across both mouse and human genomes. VISTA also has an optimized mode, where the calls can be optimized for precision or recall. VISTA-optimized can attain 100% precision and the highest sensitivity among other variant callers. In conclusion, VISTA represents a significant advancement in structural variant calling, offering a robust and accurate framework that outperforms existing consensus-based tools and sets a new standard for SV detection in genomic research.

Comprehensive assessment of long-read sequencing platforms and calling algorithms for detection of copy number variation.

Copy number variations (CNVs) play pivotal roles in disease susceptibility and have been intensively investigated in human disease studies. Long-read sequencing technologies offer opportunities for comprehensive structural variation (SV) detection, and numerous methodologies have been developed recently. Consequently, there is a pressing need to assess these methods and aid researchers in selecting appropriate techniques for CNV detection using long-read sequencing. Hence, we conducted an evaluation of eight CNV calling methods across 22 datasets from nine publicly available samples and 15 simulated datasets, covering multiple sequencing platforms. The overall performance of CNV callers varied substantially and was influenced by the input dataset type, sequencing depth, and CNV type, among others. Specifically, the PacBio CCS sequencing platform outperformed PacBio CLR and Nanopore platforms regarding CNV detection recall rates. A sequencing depth of 10x demonstrated the capability to identify 85% of the CNVs detected in a 50x dataset. Moreover, deletions were more generally detectable than duplications. Among the eight benchmarked methods, cuteSV, Delly, pbsv, and Sniffles2 demonstrated superior accuracy, while SVIM exhibited high recall rates.

Long-read sequencing and optical genome mapping identify causative gene disruptions in noncoding sequence in two patients with neurologic disease and known chromosome abnormalities.

Despite advances in next generation sequencing (NGS), genetic diagnoses remain elusive for many patients with neurologic syndromes. Long-read sequencing (LRS) and optical genome mapping (OGM) technologies improve upon existing capabilities in the detection and interpretation of structural variation in repetitive DNA, on a single haplotype, while also providing enhanced breakpoint resolution. We performed LRS and OGM on two patients with known chromosomal rearrangements and inconclusive Sanger or NGS. The first patient, who had epilepsy and developmental delay, had a complex translocation between two chromosomes that included insertion and inversion events. The second patient, who had a movement disorder, had an inversion on a single chromosome disrupted by multiple smaller inversions and insertions. Sequence level resolution of the rearrangements identified pathogenic breaks in noncoding sequence in or near known disease-causing genes with relevant neurologic phenotypes (MBD5, NKX2-1). These specific variants have not been reported previously, but expected molecular consequences are consistent with previously reported cases. As the use of LRS and OGM technologies for clinical testing increases and data analyses become more standardized, these methods along with multiomic data to validate noncoding variation effects will improve diagnostic yield and increase the proportion of probands with detectable pathogenic variants for known genes implicated in neurogenetic disease.