Detection Of Structural Variants Research Articles

How structural variants shape avian phenotypes: Lessons from model systems.

Despite receiving significant recent attention, the relevance of structural variation (SV) in driving phenotypic diversity remains understudied, although recent advances in long-read sequencing, bioinformatics and pangenomic approaches have enhanced SV detection. We review the role of SVs in shaping phenotypes in avian model systems, and identify some general patterns in SV type, length and their associated traits. We found that most of the avian SVs so far identified are short indels in chickens, which are frequently associated with changes in body weight and plumage colouration. Overall, we found that relatively short SVs are more frequently detected, likely due to a combination of their prevalence compared to large SVs, and a detection bias, stemming primarily from the widespread use of short-read sequencing and associated analytical methods. SVs most commonly involve non-coding regions, especially introns, and when patterns of inheritance were reported, SVs associated primarily with dominant discrete traits. We summarise several examples of phenotypic convergence across different species, mediated by different SVs in the same or different genes and different types of changes in the same gene that can lead to various phenotypes. Complex rearrangements and supergenes, which can simultaneously affect and link several genes, tend to have pleiotropic phenotypic effects. Additionally, SVs commonly co-occur with single-nucleotide polymorphisms, highlighting the need to consider all types of genetic changes to understand the basis of phenotypic traits. We end by summarising expectations for when long-read technologies become commonly implemented in non-model birds, likely leading to an increase in SV discovery and characterisation. The growing interest in this subject suggests an increase in our understanding of the phenotypic effects of SVs in upcoming years.

Comparative evaluation of SNVs, indels, and structural variations detected with short- and long-read sequencing data

Short- and long-read sequencing technologies are routinely used to detect DNA variants, including SNVs, indels, and structural variations (SVs). However, the differences in the quality and quantity of variants detected between short- and long-read data are not fully understood. In this study, we comprehensively evaluated the variant calling performance of short- and long-read-based SNV, indel, and SV detection algorithms (6 for SNVs, 12 for indels, and 13 for SVs) using a novel evaluation framework incorporating manual visual inspection. The results showed that indel-insertion calls greater than 10 bp were poorly detected by short-read-based detection algorithms compared to long-read-based algorithms; however, the recall and precision of SNV and indel-deletion detection were similar between short- and long-read data. The recall of SV detection with short-read-based algorithms was significantly lower in repetitive regions, especially for small- to intermediate-sized SVs, than that detected with long-read-based algorithms. In contrast, the recall and precision of SV detection in nonrepetitive regions were similar between short- and long-read data. These findings suggest the need for refined strategies, such as incorporating multiple variant detection algorithms, to generate a more complete set of variants using short-read data.

Resequencing the complete SNCA locus in Indian patients with Parkinson’s disease

The genetic loci implicated in familial Parkinson’s disease (PD) have limited generalizability to the Indian PD population. We tested mutations and the frequency of known mutations in the SNCA gene in a PD cohort from India. We selected 298 PD cases and 301 age-matched controls for targeted resequencing (before QC), along with 363 PD genomes of Indian ancestry and 1029 publicly available whole genomes from India as healthy controls (IndiGenomes), to determine the frequency of monogenic SNCA mutations. The raw sequence reads were analyzed using an in-house analysis pipeline, allowing the detection of small variants and structural variants using Manta. The in-depth analysis of the SNCA locus did not identify missense or structural variants, including previously identified SNCA mutations, in the Indian population. The familial forms of SNCA gene variants do not play a major role in the Indian PD population and this warrants further research in the under-represented population.

Updates on Genetic Hearing Loss: From Diagnosis to Targeted Therapies.

Sensorineural hearing loss (SNHL) is the most common sensory disorder, with a high Mendelian genetic contribution. Considering the genotypic and phenotypic heterogeneity of SNHL, the advent of next-generation sequencing technologies has revolutionized knowledge on its genomic architecture. Nonetheless, the conventional application of panel and exome sequencing in real-world practice is being challenged by the emerging need to explore the diagnostic capability of whole-genome sequencing, which enables the detection of both noncoding and structural variations. Small molecules and gene therapies represent good examples of how breakthroughs in genetic understanding can be translated into targeted therapies for SNHL. For example, targeted small molecules have been used to ameliorate autoinflammatory hearing loss caused by gain-of-function variants of NLRP3 and inner ear proteinopathy with OSBPL2 variants underlying dysfunctional autophagy. Strikingly, the successful outcomes of the first-in-human trial of OTOF gene therapy highlighted its potential in the treatment of various forms of genetic hearing loss. clustered regularly interspaced short palindromic repeats (CRISPR)-based technologies are currently being developed for site-specific genome editing to treat human genetic disorders. These advancements have led to an era of genotype- and mechanism-based precision medicine in SNHL practice.

Abstract LB287: VariLink: A rapid, high-resolution proximity ligation method for the detection of structural variants and chromatin topology features in cancer

Abstract Despite numerous technological advances, including the widespread adoption of next-generation sequencing, many clinically relevant cancer driver mutations go undetected. The reason for this gap in understanding is two-fold: 1) Structural variants (SVs) are particularly challenging to detect using shotgun or long read-based approaches, particularly in heterogenous samples; and 2) It is increasingly accepted that epigenetic dysregulation may be a driver of disease state through mechanisms such as enhancer hijacking or changes to 3D genome organization. To address this gap in understanding, we developed VariLink: a dual-purpose proximity ligation library protocol that yields high-quality, high-resolution, unbiased Hi-C libraries capable of sensitive detection of structural variants and chromatin topological features from a single data set. Importantly, the VariLink protocol can be performed in under 8 hours—less than half of the time required for conventional Hi-C protocols. In the current study, we demonstrate the performance of VariLink for the detection of variants within the primary sequence (such as SVs, SNVs/Indels, and CNVs) in addition to high-resolution reporting of 3D chromatin conformation. We performed benchmarking analyses for both genetic variant detection and chromatin topology in two well-characterized lymphoblast cell lines (GM12878 and K562). We demonstrate the capability of VariLink data to detect interchromosomal translocations with 10-fold higher sensitivity over shotgun. Furthermore, using hybridization capture to detect the BCR-ABL1 fusion in K562 cells, we show that fewer than 100k read pairs is sufficient to detect this fusion with high confidence in VariLink libraries. We find that the shotgun-like, uniform coverage of VariLink data also enables detection of SNVs/Indels with improved sensitivity and precision over conventional Hi-C methods. Importantly, we demonstrate that VariLink libraries maintain topological features consistent with biologically relevant topologically-associated domains (TADs) and chromatin loops, providing insight into novel epigenetic cancer drivers. VariLink enables higher-resolution assessments of chromatin topology over conventional multi-RE-based Hi-C approaches, as demonstrated by 50% more TADs and loops called at 5-kb resolution. Taken together, our data demonstrate that VariLink is a next-generation Hi-C method that enables sensitive detection of clinically relevant structural variants and high-resolution chromatin topology in a single, rapid workflow. Citation Format: Jonathan Torchia, Mital Bhakta, Cory Padilla, Meredith L. Carpenter, Philip Uren, Lisa Munding. VariLink: A rapid, high-resolution proximity ligation method for the detection of structural variants and chromatin topology features in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB287.

Abstract 325: Validation of Aventa FusionPlus: An LDT NGS assay for comprehensive cancer genomic profiling

Abstract Next-generation sequencing (NGS) assays play a pivotal role in illuminating the genomic landscape of cancer by providing insights into gene regulation and biomarker detection for the purpose of guiding therapeutic decisions to advance personalized medicine. We validated the Aventa FusionPlus Test, a Laboratory-Developed Test (LDT) that integrates HiC technology to enhance detection of actionable gene fusions and rearrangements in solid tumors, including those that are missed by current standard of care tests. This is a DNA-based test that is robust to DNA degradation in FFPE specimens, in contrast with RNA-seq and long-read technologies. The test utilizes the Element Biosciences AVITI sequencing platform to achieve high quality sequencing data at low cost per sample. The Aventa FusionPlus test enables gene-level detection of structural variants near or within 361 medically actionable or diagnostically relevant cancer genes. The 3D structure and long-range linkages captured by the test amplify the signal counts for each rearrangement. The test integrates the Arima-HiC+ FFPE sample prep and the Arima Library Prep Kit workflow. After dewaxing and rehydrating the FFPE tissue, the chromatinized DNA is fragmented and the fragmented ends are filled in with a biotinylated nucleotide. Next, spatially proximal fragmented ends of DNA are ligated, capturing the 3D structure of the genome. The proximally-ligated DNA is then purified and further fragmented, and the biotinylated ligation fragments are enriched. DNA libraries are prepared from these enriched fragments and sequenced in “paired-end” mode. Genes involved in genomic rearrangements were detected using the Arima-SV pipeline along with manual curation. The test achieved robust detection of structural variants, with accuracy of 98.8% relative to reference methods. FFPE tumor specimens from 10 different tissue types and a wide range of tumor content (20%-100%) were included. No correlation between tumor cellularity and sensitivity was observed, suggesting that samples with as low as 20% tumor cellularity can be tested. When comparing to RNA-based and other targeted reference methods, we found additional fusions nearby oncogenes missed by these reference methods. As an example, in a breast cancer case, a fusion of genomic regions neighboring BRAF and MYC oncogenes on chromosomes 7 and 8 respectively, was missed by the reference method but was successfully detected by the Aventa FusionPlus test. The Aventa FusionPlus test is a highly sensitive, specific, and accurate method for comprehensive cancer genomic profiling. The enhanced understanding of gene fusions and rearrangements positions the test as a valuable tool for clinical decision-making in oncology. Citation Format: Shadi Melnyk, Jon Belton, Sofia Nomikou, Katelyn Powell, Daniel Heiney, Roy Khalife, Damien Jones, Anthony Schmitt, Catherine Wilson, Melissa Won, Anthony Magliocco, Chris Roberts. Validation of Aventa FusionPlus: An LDT NGS assay for comprehensive cancer genomic profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 325.

Abstract 4895: Optical genome mapping analysis across multiple solid tumor types in Bionano VIATM software

Abstract Solid tumors can show highly complex somatic structural and copy number variants (CNVs) of multiple classes. These variants can reveal mechanisms behind carcinogenesis, including the amplification of oncogenes, deletion or inactivation of tumor suppressor genes, and fusions to create new oncogenes. High degrees of heterogeneity within solid tumors can complicate analysis. Optical Genome Mapping (OGM) is a comprehensive technology which combines the resolution of molecular-level data with the scale of cytogenomic analysis. ≈5-15mg sections of freshly frozen tumor are homogenized in buffer to release ultra-high molecular weight DNA. Long fragments are then labeled at a regular 6mer, then linearized and imaged with native long-range structure (≥150kbp) preserved. In silico molecules are assembled into maps and aligned to a reference genome to detect structural variants with sensitivity to ≥5% allele fraction. Bionano VIATM software provides tools for visualization and interpretation of structural variants detected with OGM. VIA also provides CNV calling and detection of Absence of Heterozygosity (AOH) and allelic imbalance using SNP-FASST3, a segmentation algorithm for detecting mosaic events in OGM and other types of data. VIA calculates a B-Allele frequency (BAF) distribution from OGM data and adds a genome-wide BAF track to the applications suite, enabling calling of allelic imbalance events such as AOH. Visualized together, the overlay of structural variant information on copy number data provides context for chromosome fusions underlying copy number change. Additionally, balanced fusions are revealed consistently in cases where the impact is copy neutral. To demonstrate the utility of integrative analysis of structural, copy number, and allelic imbalance variants in solid tumor datasets, we processed a pilot set of six diverse solid tumors through Bionano software. Brain, breast, kidney, lung, ovarian, and prostate tumor data which had undergone previous analysis in Bionano Solve 3.7 were freshly analyzed in Solve 3.8 and VIA 7.0. In the lung tumor dataset there are clear allelic imbalance segments spanning most of chromosome 4 with no concomitant copy number change. In VIA, these segments can be merged on examination, converted to AOH calls, and further specified to reflect mosaic copy neutral loss of heterozygosity (CN-LOH). In the complex kidney tumor dataset, it is difficult to resolve ploidy state based on copy number data alone. This ambiguity is resolvable with VIA, by leveraging the copy number and BAF-based allelic imbalance distributions and recentering probes to a manually defined diploid region. The comprehensive OGM data approach facilitated by VIA can streamline analysis in challenging solid tumor datasets. Structural variant visualization, CNV detection and AOH detection are available in VIA 7.0. Citation Format: Samer I. Al-Saffar, Benjamin Clifford, Aliz Raksi, Alex Hastie, Neil Miller, Alka Chaubey. Optical genome mapping analysis across multiple solid tumor types in Bionano VIATM software [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4895.

Abstract 7407: Melanoma clonal subline analysis reveals genetic factors driving intra-tumor heterogeneity

Abstract Melanoma is the most invasive skin cancer caused by the malignant melanocytes. The use of immune checkpoint blockade (ICB) improved the survival rate in advanced melanoma. Yet, the response rate to ICB varies across patients due to the highly heterogeneous nature of melanoma. Recent studies reported genomic and epigenetic factors contributing to the therapeutic response. Identifying these factors involved in clonal evolution in melanoma is a key to better understanding the tumor progression and divergence in the therapy response. To study melanoma heterogeneity, we generated twenty-four clonal sublines, each derived from a single cell isolated from a parental cell line derived from the M4 mouse melanoma model. DNA prepared from each subline and a spleen from a healthy mouse were subjected to long-read sequencing. Importantly, long-read sequencing allows direct detection of methylation states, small variants, and structural variants in the same run. The results thus provide excellent means to study genetic and epigenetic factors in clonal evolution. Each of these sublines was also implanted in distinct mice for survival and tumor growth analysis and further functional evaluation. We developed Severus, a structural variation (SV) caller for long reads, which works with single (germline), paired (tumor-normal), and multiple samples (e.g., multi-site or time series). Severus takes advantage of improved phasing in long-read sequencing, attributes somatic variants to germline haplotype, and builds a haplotype-specific breakpoint graph that is used to cluster multi-break rearrangements and represent the derived chromosomal structure. We benchmarked Severus using multiplatform validated COLO829 truthset and CHM1/CHM13 haploid genomes, and Severus outperformed all other methods in terms of recall and precision. The structural variation (SV) analysis using Severus with all the sublines showed enrichment of possibly clonal SVs in chr4, chr11, and mainly in chr13. Further investigation revealed SVs in chr13 were not distributed across the chromosome but clustered in certain regions. Analysis of somatic SNVs in chr13 corroborates the localized hypermutation profile, which indicates a possible kataegis. Interestingly, a loss of the chr13 copy affected by kataegis in one of the sublines coincides with a better survival rate, as compared to other sublines, in an allograft melanoma mouse model, which further supports the association between the kataegis and tumor progression. We also identified other clonal and subclonal events, including the homozygous deletion of Cdkn2a in most of the sublines, associated with their aggressiveness in vivo. Our analysis allowed us to identify clonal and subclonal genetic and epigenetic factors involved in tumor progression and evolution in a melanoma model, which can potentially translate to human disease. Citation Format: Ayse Keskus, Anton Goretsky, Yuelin Liu, Xiwen Cui, Tanveer Ahmad, Eva Perez Guijarro, Asher Bryant, Erin Malloy, Salem Malikic, Glenn Merlino, Chi-Ping Day, Cenk Sahinalp, Mikhail Kolmogorov. Melanoma clonal subline analysis reveals genetic factors driving intra-tumor heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7407.

Abstract 2337: Accelerated optical genome mapping analysis with Stratys Compute and Guided Assembly

Abstract Background Optical genome maps (OGM) from Bionano enable the detection of genomic structural and copy number variants that cannot be detected by next-generation sequencing (NGS) technologies and are often missed by conventional cytogenetic techniques. Bionano has developed bioinformatics pipelines for calling structural and copy number variants including the Bionano Solve de novo assembly pipeline for constitutional analysis and the Rare Variant Analysis (RVA) pipeline for low-allele-fraction cancer applications. Both pipelines are computationally intensive and currently take 5-10 hours on the latest generation of the Bionano Saphyr® Compute which is deployed as a four-node compute cluster and requires significant IT resources. Methods To increase throughput and simplify the deployment of the compute resources needed to support the Stratys™ optical genome mapping instrument, Bionano has developed Stratys™ Compute. Stratys Compute improves both compute and analytical performance by adapting compute-intensive stages in the Solve pipeline to run on GPUs and by developing the Guided Assembly pipeline. Stratys Compute is powered by state-of-the-art NVIDIA RTX 6000 Ada generation cards and CUDA-optimized refinement, alignment, and structural variation detection kernels to accelerate OGM analysis. Stratys Compute is a standalone workstation placed adjacent to Stratys instrument. This will minimize the IT footprint and bypass the integration with the customer site’s data center. We have incorporated these optimizations into the new Guided Assembly pipeline, which aims to combine the low-allele fraction detection capability of the RVA pipeline with the whole genome coverage and ability to detect smaller structural variants enabled by the de novo assembly pipeline. The Guided Assembly pipeline uses the reference genome as an initial seed followed by extension, refinement, and structural variant calling. This new analysis method has been evaluated through comparison to previous results from both existing pipelines and standard benchmarking datasets used to estimate structural variant calling performance and is deployed on Stratys Compute for both constitutional and low allele-fraction applications. Results Guided Assembly has been adapted to run on GPU hardware in a simplified compute tower that can be deployed to a lab along with the Stratys instrument without the need for a dedicated server room. We found concordance between the guided assembly results and our previous de novo and RVA pipeline results. We also found increased sensitivity at low allele fractions for detecting insertion variants smaller than 5 kb and larger than 200 kb while finding equivalent performance for other variant types with the updated methods. The accelerated Guided Assembly for constitutional and low-allele-fraction applications will be available to early access customers in Q4 2023 with full commercial release in Q2 2024. Citation Format: Damla Senol Cali, Thomas Anantharaman, Martin Muggli, Samer Al-Saffar, Charles Schoonover, Neil Miller. Accelerated optical genome mapping analysis with Stratys Compute and Guided Assembly [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2337.

Abstract 2338: Benchmarking long- and short-read somatic structural variation callers using a multi-technology panel of six tumor/normal cell lines

Abstract Better structural variation (SV) detection could improve cancer diagnosis, treatment and prevention. Yet many cancer genomics studies have only reliably detected single nucleotide variants and small indels due to technological limitations of short-read sequencing. While structural variants can be inferred from discordant short read pairs, as much as 70% of SVs remain undetected because of the mappability difficulties. This is especially true for SVs in regions where GC content is greater than 45% or regions which harbor tandem repeats and segmental duplications. Advances in long-read sequencing enabled direct observation of SVs with recall and precision over 95% across a larger portion of the genome. To harness this technology, we developed Severus - a long-read SV caller that provides phased detection of both simple germline SVs as well as complex rearrangements commonly found in cancer genomes. Such rearrangements are built into a breakpoint graph to reconstruct derived tumor chromosome structure. To benchmark Severus and other long-read SV calling methods, we sequenced six tumor/normal cell line pairs using Nanopore, HiFi, short-read and Hi-C sequencing technologies. We combined the calls from multiple tools and technologies to generate benchmarking sets of somatic SV for each tumor cell line, and evaluated short- and long-read tools against this benchmark set. Current tools for SV merging and comparison (such as truvari) were primarily designed for long indels, rather than breakends that are more common in somatic SVs. Another challenge is that different tools may represent the same variants differently in a VCF output. To enable robust somatic SV outputs comparison, we developed a tool called Minda that translates an input VCF entries into a unified representation, and then compares the calls in either pairwise or multi-tool mode. As expected, in our benchmarking of cell six tumor cell line pairs, short-read methods had substantially lower recall and precision, compared to long-read methods. Among the long-read methods, Severus consistently had substantially better recall and precision, compared to Sniffles2, nanomonsv and SAVANA. An analysis of publicly available long-read sequencing of a melanoma cell line (for which curated benchmark SV set is available) produced consistent results. Citation Format: Ayse Keskus, Asher Bryant, Tanveer Ahmad, Ataberk Donmez, Isabel Rodriguez, Nicole Rossi, Yi Xie, Byunggil Yoo, Rose Milano, Hong Lou, Jimin Park, Joshua Gardner, Brandy McNulty, Karen Miga, Mike Dean, Midhat Farooqi, Benedict Paten, Mikhail Kolmogorov. Benchmarking long- and short-read somatic structural variation callers using a multi-technology panel of six tumor/normal cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2338.

Abstract 3492: Comprehensive analysis of hematological malignancies with optical genome mapping and Bionano VIA™Software

Abstract The current standard for analysis of samples with suspected hematological cancer is karyotyping, fluorescence in situ hybridization (FISH), and/or chromosomal microarray (CMA). However, these methods have several limitations for the detection of structural variants (SVs) or copy number variants (CNV) that are smaller than 5 Mbp (karyotyping). Additionally, they are limited in their ability to detect low allele fraction (LAF) events and cannot detect the absence of heterozygosity (AOH) or the loss of heterozygosity (AOH/LOH - FISH and karyotyping). Optical genome mapping (OGM) from Bionano can enable accurate detection of SV and CNV events of sizes down to 5 kbp, with high sensitivity to detect LAF events down to 5% variant allele fraction. Bionano’s VIA™ software provides visualization and analysis support for OGM SV events including an improved Circos plot and ideogram for whole genome review. VIA incorporates CNV calling from OGM data using the SNP-FASST3 algorithm which also allows for accurate copy number calling at allele fractions as low as 10%. CNV detection performance was evaluated using 280 CNV events ranging in size from 175 kbp to 8 Mbp on the 22 autosomal chromosomes. Sensitivity and PPV were calculated for each size range separately. Using SNP-FASST3, VIA also adds the ability to detect AOH/LOH events from OGM data. By analyzing locations where known SNPs disrupt the specific nucleotide sequence motif used by the DLE-1 labeling enzyme, a B-allele frequency can be calculated and enable AOH/LOH detection at low allelic fractions. AOH/LOH performance using SNP-FASST3 was evaluated using a cohort of constitutional and cancer samples analyzed with orthogonal methods as well as with simulated events. Sensitivity for 20-25 Mbp AOH events was 92% with PPV greater than 90% at 25% aberrant cell fraction. The VIA 7.0 release also includes the ability to create a customizable decision tree using supplied reference annotation files for CNV, AOH and SV event pre-classification. VIA resources include a panel of target variants derived from various medical societies for clinical analysis guidelines specific to Acute Myeloid Leukemia (AML), Myelodysplastic Syndrome (MDS) and an aggregation of all hematological malignancy guidelines (pan-heme). These methods, combined with tools for expert review and reclassification of variants, allow users to conduct whole genome interpretation and report results. These new features in VIA provide a streamlined workflow for analyzing heterogeneous hematological cancer samples and demonstrate the analytical performance of updated approaches for detection of CNV and AOH/LOH regions at low allele fractions using optical genome mapping alone. Citation Format: Jacob Wisotsky, Aliz Raski, Westley Sherman, Megan Roytman, Samer Al-Saffar, Jen Hauenstein, Andy Wing Chun Pang, Viren Wasnikar, Neil Miller. Comprehensive analysis of hematological malignancies with optical genome mapping and Bionano VIA™Software [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3492.

Abstract 336: Genome integrity assessment by optical genome mapping for cell manufacturing/bioprocessing applications

Abstract Cells and cell lines are used for multiple applications such as bioprocessing, therapy, and research. To ensure quality of cells and downstream applications, appropriate quality control (QC) methods are critical. Historically, karyotyping has been employed, but it is limited by its very low resolution and tedious laboratory workflow. Other methods such as PCR and targeted sequencing can characterize only small genomic variants at specific loci. Whole genome sequencing can detect small variants genome-wide but has limited sensitivity in detecting structural variants (SVs). Optical genome mapping (OGM) is a novel genome analysis technique that can fill many of the gaps in current capabilities for assessing genome integrity. To find clonal variants, 400 Gbp of data is collected from the parental/control and test samples. For both samples, a de novo assembly is constructed, and homozygous or heterozygous SVs are assessed. Subsequently, the dual variant annotation pipeline identifies unique SVs in the test sample compared to the parental sample. To discover subclonal SVs down to 5% variant allele fraction (VAF), the workflow leverages the generation of 1.5 Tbp of data, requiring a simple adjustment to longer data collection time. Comparison of test sample to parental sample enables easy determination of acquired variants. Finally, generation of ~5 Tbp of data, requiring 2-3 flowcells to be run, enables the detection of SVs at ultra-low VAF down to ~1%. In this study, several dilutions and simulations were performed to examine OGM’s limit of detection. Targeting a coverage of 5 Tbp and analysis using the somatic SV-analysis workflow revealed that OGM has the sensitivity to detect deletions >50kbp, insertions >20kbp, duplications >100 kbp, and translocations at ~1% VAF. We have applied the clonal and somatic workflows to verify genomes’ integrity after cell immortalization, induced pluripotency, transgene-integration, and gene-editing. The data using the robust and sensitive workflows demonstrate that the OGM platform is a cost-effective solution for cell manufacturing/bioprocessing QC applications. Citation Format: Alex Hastie, Andy W. Pang, Alka Chaubey. Genome integrity assessment by optical genome mapping for cell manufacturing/bioprocessing applications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 336.

Abstract 1763: Long-read sequencing of pediatric leukemia identifies clinically relevant genomic rearrangements

Abstract Clinical detection of genomic rearrangements currently depends on a range of complementary and overlapping methods including fluorescence in situ hybridization (FISH), karyotyping, and DNA and/or RNA sequencing. This requirement for multiple tests results in higher total costs, extended analysis time, and increased usage of sometimes limited tumor material. In our laboratory, we apply long high-fidelity reads to human samples using PacBio circular consensus sequencing (HiFi-GS) of 12-18kb DNA fragments, which offers better structural variant detection relative to short-read sequencing. Here, we assess the ability of HiFi-GS to detect clinically relevant genomic rearrangements (CRGRs) in pediatric leukemia. We selected 11 pediatric leukemia cases with corresponding normal (remission) samples, including 7 cases of B-cell acute lymphoblastic leukemia (B-ALL) and 4 cases of acute myeloid leukemia (AML); 5 of these 11 leukemia cases had known CRGRs as below. The remaining 6 leukemia cases had also undergone clinical genetic profiling via karyotyping, FISH, microarray, and sequencing yet a clinical grade genomic driver was not identified. DNA from each sample was sequenced on a Revio instrument (PacBio, Menlo Park, CA) to a target depth of 30x. The PacBio Human Whole Genome Sequencing (WGS) workflow was used to process HiFi reads for haplotagged alignment and phasing, followed by somatic structural variant calling using Severus. Subsequent analysis focused on the presence of break ends in known cancer-relevant genes. We found that HiFi-GS detected the known CRGRs in all 5 cases with prior findings, providing precise break ends and clarifying sometimes unclear cytogenetic observations (such as exact partner genes), in these cases. These included detection of an ETV6-RUNX1 fusion, NUP98-NSD1 fusion, KMT2A-AFF1 fusion, KMT2A-AFDN fusion, and RUNX1-RUNX1T1 fusion. HiFi sequencing also detected CRGRs in 2 of the 6 “undiagnosed cases”; namely, one case of ZNF384-TCF3 fusion and one case of KMT2A-MLLT10 fusion. The former can be cytogenetically cryptic, while the latter can often be missed due to its potentially complex nature. Our results demonstrate that HiFi-GS can reliably detect CRGRs, bringing us closer to the promise of a single comprehensive genetic test for cancer characterization. Additional work examining other somatic structural and copy number variants (i.e., inversions, deletions, and duplications) in these cases, as well as oncogenic sequence variants, is ongoing. Citation Format: Byunggil Yoo, Ayse Keskus, Chengpeng Bi, Lisa Lansdon, Tanveer Ahmad, Irina Pushel, Adam Walter, Margaret Gibson, Erin Guest, Tomi Pastinen, Mikhail Kolmogorov, Midhat S. Farooqi. Long-read sequencing of pediatric leukemia identifies clinically relevant genomic rearrangements [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1763.

Abstract 6257: Genome wide, high-throughput, high-resolution structural variation detection at low variant allele fraction for oncology samples

Abstract Structural variation detection remains an elusive undertaking. For decades, G-banded karyotyping has remained the standard practice for nearly all hematological malignancy samples. Cancers are diseases of the genome and structural variants (SVs) are a hallmark of nearly all cancers, are often drivers of oncogenicity, and can sometimes be targeted for treatment, as highlighted by the discovery of the Philadelphia chromosome and later the development of targeted kinase inhibitors. One of the most important limitations of karyotyping, its requirement for cells to divide in culture, has prevented its application for most solid tumors and therefore, there is considerably less understanding of the impact of SVs in solid tumors. Optical genome mapping is a technique that is revolutionizing cytogenomics and unlocking the understanding of SVs in the genome at a level never seen before. It not only can detect nearly all variants that a karyotype can, but it can provide 10,000x higher resolution and does not require cell culture. Because of this, it is being adopted for oncology studies across hematological malignancies and solid tumors. This study demonstrates the performance of a new high throughput Stratys instrument for generation of optical genome map data at extraordinarily high coverage depth. With this instrument, 12 samples can be loaded at once, each loaded onto its own cartridge and the instrument can collect 400x genome coverage for each of these samples in 24 hours. The instrument has random access to the cartridges so that completed samples can be swapped out to facilitate optimal instrument run efficiency. To date, this system has been demonstrated to run 60 samples in a week, each at 400x coverage. Data from the instrument can be processed by Bionano Access™ and VIA™ software to call SVs, copy number variants (CNVs), regions of loss of heterozygosity (LOH), on a genome wide basis, and to classify those variants automatically according to guidelines such as the National Comprehensive Cancer Network (NCCN), World Health Organization (WHO), and National Health Services (NHS, United Kingdom). This new high throughput system with advanced bioinformatic data analysis has the potential to further transform structural variation analysis in cancer research. Citation Format: Alex R. Hastie, Pat Lynch. Genome wide, high-throughput, high-resolution structural variation detection at low variant allele fraction for oncology samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6257.

Abstract 5665: Native nanopore sequencing of multiple tumor sites reveals genetic and epigenetic intra-tumor heterogeneity in canine osteosarcoma

Abstract Osteosarcoma (OS) is an aggressive bone malignancy affecting children and young adults. Implementation and optimization of neoadjuvant chemotherapy led to significant improvements in outcome, but patients with recurrence or metastases at diagnosis continue to have poor prognosis. Whole genome sequencing (WGS) revealed that a hallmark of OS is a highly rearranged genome with complex copy number aberrations rather than point mutations. A better understanding of the key genomic and epigenetic factors driving clonal evolution may provide insights into the tumor progression and the therapy response. Canine OS recapitulates the majority of the hallmark genetic and molecular factors of human OS and is recognized as an informative model. A significant difference is that initial surgery in canine OS allows us to explore tumor evolution unperturbed by treatment, providing invaluable resources to study the genetic and molecular landscape of tumor evolution. Here, we present the first study to date in which we performed bulk WGS of multiple tumor sites and distal normal tissue in two dogs using nanopore long-read sequencing to analyze the genetic and epigenetic evolution of OS. In both subjects, somatic structural variation detection using Severus revealed chromothripsis-like rearrangements in chr11, leading to the deletion of Cdkn2a, a known cell cycle regulator and tumor suppressor. Interestingly, in one of the subjects, the majority of the SVs (n = 131) shared across all the samples were localized on chr5, coinciding with perturbed copy number profiles and bi-allelic frequency of the SNVs, with all mutations identified using complementary bioinformatics analysis of the same native nanopore reads. The multi-site sample analysis identified subclonal structural alterations in TP53 and ATRX genes. With phased nanopore reads, we observed subject-specific copy-neutral loss-of-heterozygosity events and long identical-by-descent blocks. Haplotype-specific copy-number analysis of tumors showed different aneuploidy patterns in both subjects, highlighted clonal compositions of samples from distinct sites, and identified regions of copy-number heterogeneity. Furthermore, phased nanopore reads also revealed haplotype-specific 5mC and 5hmC methylation differences across tumor samples, where samples from different sites of the same tumor demonstrate distinct methylation patterns that overlap DLG2, RUNX2, KDR, and other genes known as mutational hotspots in canine/human OS. Overall, we showcase how a single sequencing assay allows for a joint analysis of genetic and epigenetic tumor alterations, thus providing a richer understanding of the drivers of somatic evolution and their association with the molecular landscape in the canine OS. These findings can be translated into human disease and shed light on tumor progression and therapy response. Citation Format: Ayse Keskus, Sergey Aganezov, Tanveer Ahmad, Xiaoguang Dai, Robert Walker, John Beaulaurier, Scott Hickey, Sissel Juul, Amy Kathleen LeBlanc, Paul S. Meltzer, Mikhail Kolmogorov. Native nanopore sequencing of multiple tumor sites reveals genetic and epigenetic intra-tumor heterogeneity in canine osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5665.

Tradeoffs in alignment and assembly-based methods for structural variant detection with long-read sequencing data

Long-read sequencing offers long contiguous DNA fragments, facilitating diploid genome assembly and structural variant (SV) detection. Efficient and robust algorithms for SV identification are crucial with increasing data availability. Alignment-based methods, favored for their computational efficiency and lower coverage requirements, are prominent. Alternative approaches, relying solely on available reads for de novo genome assembly and employing assembly-based tools for SV detection via comparison to a reference genome, demand significantly more computational resources. However, the lack of comprehensive benchmarking constrains our comprehension and hampers further algorithm development. Here we systematically compare 14 read alignment-based SV calling methods (including 4 deep learning-based methods and 1 hybrid method), and 4 assembly-based SV calling methods, alongside 4 upstream aligners and 7 assemblers. Assembly-based tools excel in detecting large SVs, especially insertions, and exhibit robustness to evaluation parameter changes and coverage fluctuations. Conversely, alignment-based tools demonstrate superior genotyping accuracy at low sequencing coverage (5-10×) and excel in detecting complex SVs, like translocations, inversions, and duplications. Our evaluation provides performance insights, highlighting the absence of a universally superior tool. We furnish guidelines across 31 criteria combinations, aiding users in selecting the most suitable tools for diverse scenarios and offering directions for further method development.

Benchmarking long-read aligners and SV callers for structural variation detection in Oxford nanopore sequencing data

Structural variants (SVs) are one of the significant types of DNA mutations and are typically defined as larger-than-50-bp genomic alterations that include insertions, deletions, duplications, inversions, and translocations. These modifications can profoundly impact the phenotypic characteristics and contribute to disorders like cancer, response to treatment, and infections. Four long-read aligners and five SV callers have been evaluated using three Oxford Nanopore NGS human genome datasets in terms of precision, recall, and F1-score statistical metrics, depth of coverage, and speed of analysis. The best SV caller regarding recall, precision, and F1-score when matched with different aligners at different coverage levels tend to vary depending on the dataset and the specific SV types being analyzed. However, based on our findings, Sniffles and CuteSV tend to perform well across different aligners and coverage levels, followed by SVIM, PBSV, and SVDSS in the last place. The CuteSV caller has the highest average F1-score (82.51%) and recall (78.50%), and Sniffles has the highest average precision value (94.33%). Minimap2 as an aligner and Sniffles as an SV caller act as a strong base for the pipeline of SV calling because of their high speed and reasonable accomplishment. PBSV has a lower average F1-score, precision, and recall and may generate more false positives and overlook some actual SVs. Our results are valuable in the comprehensive evaluation of popular SV callers and aligners as they provide insight into the performance of several long-read aligners and SV callers and serve as a reference for researchers in selecting the most suitable tools for SV detection.

Application of optical genome mapping technology for the detection of chromosomal structural variations

To assess the value of optical genome mapping (OGM) for the detection of chromosomal structural abnormalities including ring chromosomes, balanced translocations, and insertional translocations. Clinical data of four patients who underwent pre-implantation genetic testing concurrently with OGM and chromosomal microarray analysis at the Center of Reproductive Medicine of the Sixth Affiliated Hospital of Sun Yat-sen University from January to October 2022 due to chromosomal structural abnormalities were selected as the study subjects. Some of the results were verified by multi-color fluorescence in situ hybridization. The OGM has successfully detected a balanced translocation and fine mapped the breakpoints in a patient. Among two patients with insertional translocations, OGM has provided more refined breakpoint locations than karyotyping analysis in a patient who had chromosome 3 inserted into chromosome 6 and determined the direction of the inserted fragment. However, OGM has failed to detect the chromosomal abnormality in a patient with chromosome 8 inserted into the Y chromosome. It has also failed to detect circular signals in a patient with ring chromosome mosaicism. OGM has successfully detected chromosomal structural variations in the four patients and provided assistance for their diagnosis.

Integrating Optical Genome Mapping and Whole Genome Sequencing in Somatic Structural Variant Detection.

Structural variants drive tumorigenesis by disrupting normal gene function through insertions, inversions, translocations, and copy number changes, including deletions and duplications. Detecting structural variants is crucial for revealing their roles in tumor development, clinical outcomes, and personalized therapy. Presently, most studies rely on short-read data from next-generation sequencing that aligns back to a reference genome to determine if and, if so, where a structural variant occurs. However, structural variant discovery by short-read sequencing is challenging, primarily because of the difficulty in mapping regions of repetitive sequences. Optical genome mapping (OGM) is a recent technology used for imaging and assembling long DNA strands to detect structural variations. To capture the structural variant landscape more thoroughly in the human genome, we developed an integrated pipeline that combines Bionano OGM and Illumina whole-genome sequencing and applied it to samples from 29 pediatric B-ALL patients. The addition of OGM allowed us to identify 511 deletions, 506 insertions, 93 duplications/gains, and 145 translocations that were otherwise missed in the short-read data. Moreover, we identified several novel gene fusions, the expression of which was confirmed by RNA sequencing. Our results highlight the benefit of integrating OGM and short-read detection methods to obtain a comprehensive analysis of genetic variation that can aid in clinical diagnosis, provide new therapeutic targets, and improve personalized medicine in cancers driven by structural variation.

Optical Genome Mapping as a Potential Routine Clinical Diagnostic Method.

Chromosome analysis (CA) and chromosomal microarray analysis (CMA) have been successfully used to diagnose genetic disorders. However, many conditions remain undiagnosed due to limitations in resolution (CA) and detection of only unbalanced events (CMA). Optical genome mapping (OGM) has the potential to address these limitations by capturing both structural variants (SVs) resulting in copy number changes and balanced rearrangements with high resolution. In this study, we investigated OGM's concordance using 87 SVs previously identified by CA, CMA, or Southern blot. Overall, OGM was 98% concordant with only three discordant cases: (1) uncalled translocation with one breakpoint in a centromere; (2) uncalled duplication with breakpoints in the pseudoautosomal region 1; and (3) uncalled mosaic triplication originating from a marker chromosome. OGM provided diagnosis for three previously unsolved cases: (1) disruption of the SON gene due to a balanced reciprocal translocation; (2) disruption of the NBEA gene due to an inverted insertion; (3) disruption of the TSC2 gene due to a mosaic deletion. We show that OGM is a valid method for the detection of many types of SVs in a single assay and is highly concordant with legacy cytogenomic methods; however, it has limited SV detection capabilities in centromeric and pseudoautosomal regions.