Low Sequencing Research Articles

Abstract 3551: Continued analysis of extensive data towards Genome in a Bottle benchmarks for a new tumor normal pair

Abstract Here, we detail in-progress genome-scale measurements from a variety of technologies of the first tumor normal benchmark from the Genome in a Bottle (GIAB) consortium. We created the first broadly-consented tumor cell line from a pancreatic ductal adenocarcinoma with matched normal pancreatic and duodenal tissue. Data is being collected from a large homogeneous batch of the tumor cell line and paired normal tissues. As we receive data we make it publicly available on the NCBI hosted GIAB FTP site, https://ftp.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/. When complete, this dataset will include WGS measurements from Illumina, ONT, Hi-C, Bionano, single cell WGS, PacBio HiFi and Onso, and Element. Analysis and development of a variant calling benchmark using this data is ongoing in collaboration with an open working group of the GIAB consortium. Initial Hi-C and optical mapping data from the tumor cell line indicates substantial aneuploidy from translocations that cause large deletions. We found roughly 17 large inversions and translocations and 16 chromosomes with extensive loss of heterozygosity due to missing >30% of one copy, in addition to a few smaller duplications. Low coverage single cell sequencing that provides ploidy estimates across chromosomes showed that most of the large deletions appear in all or nearly all cells with some variation in a few cells. These observations are consistent with bulk WGS analyses from two batches of cells. Additionally, many of the observed large deletions correspond to deletions seen in the population of TCGA chromosomal Loss of Heterogeneity samples. Examining somatic SNVs in non-repetitive regions, we find that close to 60% occur in almost all cells in diploid regions, 30% occur in almost all cells in haploid regions, and 5% in only some cells in diploid and haploid regions, respectively. We take these results to indicate the cell line is relatively homogeneous and stable with most CNVs being deletions. As such, we plan to explore using long reads, ultralong reads, and Hi-C data to generate a near-complete genome assembly of the dominant tumor clone as well as a complete diploid assembly of the normal. With this personalized genome assembly, we will explore aligning tumor and normal reads to each haplotype of the normal to characterize somatic variants, including variants in minor clones. Building on the methods GIAB and T2T have developed to polish diploid assemblies of GIAB’s normal genomes and mosaic variant characterization, we will develop benchmarks for somatic variants against the normal assembly as well as standard references. Citation Format: Justin Wagner, Jennifer McDaniel, Gail L. Rosen, Nathan D. Olson, Vaidehi Patel, Chunlin Xiao, Andrew Liss, Justin Zook. Continued analysis of extensive data towards Genome in a Bottle benchmarks for a new tumor normal pair [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 3551.

Abstract 967: Clinical applicability of targeted panel sequencing in liquid biopsies for disease diagnosis and monitoring of patients with pediatric solid tumors

Abstract Liquid biopsy assays based on sequence analysis of cell-free DNA (cfDNA) have the potential to transform patient care. We recently validated a liquid biopsy platform, LBSeq4Kids, for patients with retinoblastoma, brain tumors and solid tumors using low pass whole genome sequencing (LP-WGS) of cfDNA from aqueous humor (AH), cerebrospinal fluid (CSF), and plasma (PL) to detect Copy Number Alterations (CNAs) in circulating tumor DNA (ctDNA). Herein, we present phase 2, a high-depth comprehensive Next-Generation Sequencing (NGS) panel using cfDNA that allows us to detect SNV’s, indels and gene fusions in clinically relevant genes for pediatric solid and brain tumors. Seventy-four cfDNA specimens have been analyzed to date, using plasma from 43 patients with solid tumors, CSF from 25 patients with brain tumors and AH from six patients with ocular tumors including retinoblastoma. cfDNA was extracted at diagnosis, during therapy, at remission and/or relapse. Sequencing libraries were constructed with the xGen Prism DNA Library Prep Kit using 5ng of cfDNA. For the detection of recurrent mutations and fusions we designed a custom panel using a hybridization-based capture method (Twist Bioscience) that included full coverage of the exons of 136 genes harboring recurrent mutations and selected introns for five genes with recurrent rearrangement breakpoints including BRAF, EWSR1, SYT, FOXO1 and NTRK1. Hybridized libraries were paired-end sequenced (Illumina NextSeq 500) at an average 1000x collapsed coverage. Mutations identified in cfDNA were compared with those in the primary or metastatic tumors profiled with our OncoKids® NGS panel. A total of 35/43 (81%) plasma specimens were positive for either an SNV, deletion or fusion with the most common events being a somatic missense variant in TP53 (13/35, 37%) or translocation involving EWSR1 (9/35, 26%). A total of 16/25 (64%) CSF specimens were positive for SNVs and fusions, most often involving KIAA1549::BRAF (7/25, 28%) in low grade gliomas. A germline variant in RB1 was detectable in two AH specimens from the left and right eye of a patient with bilateral retinoblastoma while plasma from a patient with metastatic retinoblastoma demonstrated clinically relevant variants in RB1 and DICER1. Serial cfDNA profiling revealed a clinically reported TP53 c.746G>C missense variant in the plasma of a patient with osteosarcoma at multiple timepoints through the disease course, with evidence for relapse prior to standard imaging. These data suggest that clinical implementation of a second version of LBSeq4Kids that combines CNA and mutation analysis allows for diagnosis, residual disease detection and risk stratification for pediatric patients with diverse tumor types, regardless of histologic grade, with a variety of pediatric solid and brain tumors. Citation Format: Eirini Christodoulou, Venkata Yellapantula, Katrina O'Halloran, Liya Xu, Jesse L. Berry, Fariba Navid, Dejerianne Ostrow, Jaclyn A. Biegel. Clinical applicability of targeted panel sequencing in liquid biopsies for disease diagnosis and monitoring of patients with pediatric solid tumors [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 967.

Abstract 322: Ultraplex genome and exome sequencing of rare single cells

Abstract Single-cell genome analysis enables researchers to gain novel insights into tumor heterogeneity. Conducting single-cell genomic analysis using next-generation sequencing (NGS) methods has traditionally been challenging since the amount of genomic DNA present in a single cell is limited. PCR-based amplification methods normally have high error rates, low coverage uniformity, and extensive allelic drop-outs making interpretation of SNVs and CNVs challenging.Here we introduce a new whole-genome amplification method which utilizes an optimized isothermal DNA amplification reaction with a Hi-fidelity, error correcting polymerase and downstream library preparation protocol to allow pooling of amplified DNA. The key DNA amplification steps use multiple displacement amplification (MDA) technology to amplify gDNA directly from single cells, nuclei or previously isolated genomic DNA. During the MDA reaction, sample-barcodes are incorporated into the newly synthetized DNA, allowing the amplified DNA to be pooled and processed in to one ultraplex library. This method saves library preparation time, reduces DNA library costs and limits plastic consumable usage.Our current workflow allows 24 samples to be multiplexed in one library and 24 libraries to be produced for a total of 576 samples per sequencing flow cell. This method can be used to investigate chromosomal instability with low pass sequencing or SNV and CNV analysis following whole genome, exome-capture workflows. Citation Format: Ioanna Andreou, Samuel Rulli, Katja Heitz, Silke Huebner, Christin Meerschiff, Eric Lader. Ultraplex genome and exome sequencing of rare single cells [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 322.

Abstract 4643: A novel epigenomic profiling assay reveals disease biology and therapeutic targets in gastro-esophageal cancer from 1 ml of plasma

Abstract INTRODUCTION: Gastro-esophageal adenocarcinoma (GEA) is an aggressive and heterogeneous disease with a poor prognosis. Targeted therapies have failed largely due to challenges associated with biopsy collection, tumor antigen heterogeneity, and accurately distinguishing transcriptionally distinct esophageal, GE junction or gastric tumor types. We developed a novel, multimodal liquid biopsy assay that profiles genome-wide transcriptional activation. Here, we deploy this assay to define clinically relevant insights in a cohort of GEA patients. METHODS: 1 ml of plasma from whole blood samples was used to assess genome-wide enhancer, promoter and DNA methylation loci in 11 GEA patients (Stage III: 1, Stage IV: 10) and 7 healthy volunteers. 6 patients were confirmed as HER2+ based on standard tissue IHC/ISH methods. ctDNA estimation was performed using the ichorCNA algorithm on low pass whole genome sequencing data. A multimodal HER2 classifier developed previously using genome-wide features including HER2 was used to predict HER2 status of the GEA samples. RESULTS: Epigenomic profiling and comparison of GEA and healthy volunteer plasma samples revealed distinct genome-wide transcriptional activation patterns associated with gastroesophageal adenocarcinoma, including (i) the characteristic upregulation of HER2, FGFR2 and VEGF (ii) SOX2, KLF4, GATA6 transcription factor circuitry, and (iii) DNA methylation at the CHFR and MGMT promoters. We then explored if epigenomic profiling of liquid biopsies could infer the activation status of antibody-drug conjugate (ADC) targets currently under investigation in GEA cancers. Simultaneous examination of multiple target genes including HER2, HER3, TROP2, CLDN18, CEACAM5 and MET demonstrated patient-specific differences and dynamic range in transcriptional activation of a subset of these target genes. Finally, we investigated if HER2 status could be assigned accurately and quantitatively from a liquid biopsy using the multimodal HER2 classifier. HER2 positivity by IHC was predicted accurately in 8/11 samples corresponding to an area under the ROC curve (AUC) greater than 0.85. Discordance between plasma and tissue HER2 calls could be partially attributed to variability associated with tumor site/section used for tissue collection, IHC staining, and time between biopsy collection and blood draw. CONCLUSIONS: We demonstrate the feasibility of comprehensive epigenomic profiling from low input volume of 1ml of plasma to provide a snapshot of the tumor’s transcriptional state to derive clinically actionable insights. The HER2 classifier overcomes several of the challenges with IHC profiling by providing a uniform and quantitative measurement of HER2 activation. This non-invasive assay provides an accurate reflection of tumor transcriptional biology that can inform optimal patient selection strategies. Citation Format: Jonathan Beagan, Aparna Gorthi, Anthony D'Ippolito, Travis Clark, Michael Coyne, Tyrone Tamakloe, Amy Donahue, Baovy Tran, Hyun-Hwan Jeong, Kristian Cibulskis, Hathairat Sawaengsri, Corrie A. Painter, Juliann Chmielecki, J Carl Barrett, Mosammat Faria Afreen, Aditya Pandey, Ilexa Ashley Schechter, Martin S. Taylor, Matthew R. Strickland, Matthew Eaton, Samuel J. Klempner. A novel epigenomic profiling assay reveals disease biology and therapeutic targets in gastro-esophageal cancer from 1 ml of plasma [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 4643.

Abstract 972: Non-invasive detection of homologous recombination deficiency in metastatic prostate cancer patients

Abstract Background: The recent endorsement of poly ADP ribose polymerase inhibitors (PARPi) has been a breakthrough in managing prostate cancer (PCa) with homologous recombination deficiency (HRD). However, due to its propensity to metastasize to the bone, HRD assessment in tissue biopsy poses a challenge in advanced PCa. Circulating tumor DNA (ctDNA) as a tumor surrogate may be a promising substitute for pinpointing patients who may benefit from PARPi treatment. Methods: To test whether causes and consequences of HRD can be detected non-invasively in plasma, we pre-selected 139 plasma samples from PCa patients based on aneuploidy screening (mFAST-SeqS). We then applied targeted sequencing using a QIAseq panel including homologous recombination repair (HRR)-related genes as well as genes involved in cell cycle regulation (TP53, RB1, PTEN). Putative, pathogenic germline variants were sequencing in constitutional DNA using Sanger sequencing. Moreover, we performed low pass whole genome sequencing to determine the levels of genomic instability using the shallow HRD (sHRD) algorithm. Results: In our cohort, at least one pathogenic mutation was detected in 68/139 (48.9%) of the patients, of which the majority consisted of alterations in PTEN, TP53 or RB1 (44/139, 31.7%). Pathogenic BRCA1/2 mutations were detected in 13/139 patients (9.4%), the majority of which originated from the germline. In 8/139 patients (5.6%) a pathogenic variant in other HRR genes could be observed and in 3/139 patients (2.2%) CKD12 mutations were detected. As expected, samples with pathogenic HRR mutations and elevated tumor fraction, presented high sHRD scores (<20) in plasma DNA. In contrast, the majority of high ctDNA samples with mutations in PTEN, TP53 or RB1 had sHRD score below the cut-off of 20. However, the detection of genomic instability was clearly depending on tumor fractions. Conclusion: Our study indicates that a non-invasive assessment of root causes and subsequent effects of the HRD phenotype in prostate cancer is feasible, and that mutations in HRR correlate with a high genomic instability. However, to detect and quantify genomic instability in plasma, elevated ctDNA levels are required. Based on in-house data from mFAST-SeqS aneuploidy screening of over 900 plasma samples from advanced prostate cancer, approximately 30% of cfDNA samples would have sufficiently high ctDNA fractions for a combined assessment of causes and consequences of HRD, which might be most informative to direct PARPi treatment in PCa. Citation Format: Georgios Vlachos, Tina Moser, Anna Eberhard, Lisa Glaswitch, Jasmin Blatterer, Emil Bauernhofer, Nina Monsberger, Karl Kashofer, Jochen Geigl, Thomas Bauernhofer, Ellen Heitzer. Non-invasive detection of homologous recombination deficiency in metastatic prostate cancer patients [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 972.

Abstract 980: Plasma tumor fraction is an independent prognostic marker of response to front line chemotherapy in high-grade serous epithelial ovarian cancer: The MITO-16a/MANGO-OV2a/clinical trial experience

Abstract Background. Although 80% of high grade serous ovarian cancer (HGSOC) patients are initially responsive to platinum (Pt)-based chemotherapy, the majority of them experience relapse with a progressive Pt-resistant disease. One of the most challenging issue that hampers the possibility to effectively treat relapsed disease is the lack of biological information about tumor recurrence. To date, the Pt-free interval (PFI), an empirical measure of the time lagging between the end of front-line chemotherapy and relapse, is the only and widely accepted parameter to predict patient outcome and sensitivity to Pt second-line chemotherapy. We have previously demonstrated that analysis of circulating tumor DNA (ctDNA) by low pass whole genome sequencing (sWGS) is a suitable tool to predict patient outcome and to intercept early signs of relapsed disease (Paracchini et al. PMID:33323403). In the present study, we quantified the percentage of tumor fraction (TF) in plasma of patients enrolled within the frame of a phase III clinical trial (MITO-16A/MaNGO-OV2A-EUDRACT number: NCT01706120) to demonstrate, at baseline, the prognostic value of untargeted ctDNA analysis. Methods. 172 eligible patients enrolled with the frame of the MITO-16A/MaNGO-OV2A clinical trial, for whom plasma sample was collected at chemotherapy before chemotherapy, were selected for the study. For each plasma sample, circulating-free DNA (cfDNA) was purified and whole genome libraries (HyperPlus, Roche) sequenced (mean coverage 0.5X). ichorCN algorithm was used to infer the percentage of TF, as previously published (Paracchini et al. PMID:33323403). Results. In 168 out of 172 plasma samples analyzed, the TF was detectable and it ranged from 2.4% to 47%. Cox-model univariate analysis with patients’ overall survival (OS) and Progression-Free Survival (PFS), indicates association of TF levels with both OS and PFS (p<0.001). The prognostic relevance of TF was also confirmed in multivariate analysis, where, considering CA-125, residual tumor, stage of disease, histology and age as co-variables, TF maintained its statistical significance in PFS (HR = 2.1, CI 95%, p-value < 0.003). Conclusion. Retrospective analysis of baseline plasma samples collected within the frame of the MITO-16A/MaNGO-OV2A clinical trial, demonstrated that the percentage of TF is an independent prognostic marker of relapse. This finding confirms the importance of liquid biopsy analysis based on untargeted sWGS tool as an innovative approach to predict response to front line therapy and patient’s outcome Citation Format: Sergio Marchini, Lara Paracchini, Laura Arenare, Giovanni Scambia, Carmela Pisano, Riccardo Zadro, Laura Mannarino, Annamaria Ferrero, Paolo Chiodini, Daniela Califano, Sandro Pignata, Maurizio D'Incalci. Plasma tumor fraction is an independent prognostic marker of response to front line chemotherapy in high-grade serous epithelial ovarian cancer: The MITO-16a/MANGO-OV2a/clinical trial experience [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 980.

Abstract 405: Translocation detection in cancer using low-pass pore-c sequencing

Abstract Complex chromosomal rearrangements, including translocations, play a critical role in oncogenesis and are often identified as recurrent genetic aberrations in hematologic malignancies and solid tumors[1]. Translocation detection by karyotyping of an individual’s metaphase chromosomes remains challenging for detection of balanced rearrangements, which have no gain or loss of genetic material. Rearrangement detection using whole-genome sequencing is a viable alternative, but it relies on breakpoint-spanning reads and requires high sequencing depth (30-60x) with long reads to achieve high sensitivity, especially in repetitive regions of the genome[2]. Here, we describe a workflow for translocation detection at low sequencing depth with Oxford Nanopore’s long read chromatin conformation capture technique, Pore-C[3]. Importantly, for translocation calling, Pore-C does not rely on breakpoint-spanning reads but rather the high intrachromosomal interaction frequency of genomic regions around the breakpoint, thus largely lowering sequencing depth requirements and reducing mapping issues in low complexity regions. We prepared, barcoded, and sequenced Pore-C libraries of 3 cancer cell lines including lung cancer (A549), Acute Monocytic Leukemia (THP-1), melanoma (COLO 829) and its matching normal (COLO 829 BL) on a single Q20+ MinION flow cell (FLO-MIN114). Genome-wide contact maps of low-pass data (<1.5 Gbps per sample) were compared against higher depth (>30 Gbps per sample) Hi-C maps [4], revealing that low-pass Pore-C successfully captured large-scale genomic rearrangement. For example, chromosomal pairs chr8-chr11 and chr15-chr19 in A549, chr9-chr11 and chr1-chr20 in THP1, and chr7-chr15 in Colo829 were detected at <0.5X depth of sequencing coverage. These translocation events were further validated by breakpoint analysis using adaptive sampling, where targeted regions were previously confirmed by independent studies[4],[5]. Low-pass Pore-C detects translocations in an unbiased manner and does not require prior knowledge of the translocation structure. Combined with its simple sample-preparation workflow and the capability to provide genome-wide copy-number information in a single experiment, it can serve as a cost-effective and comprehensive tool for cancer genomic studies. [1] Chromosomal translocations in human cancer, Nature, 372, 143 (1994) [2] Hi-C as a tool for precise detection and characterisation of chromosomal rearrangements and copy number variation in human tumors, Genome Biology, 18, 125 (2017) [3] Identifying synergistic high-order 3D chromatin conformations from genome-scale nanopore concatemer sequencing, Nature Biotechnology, 40, 1488(2022) [4] Chromosomal translocations detection in cancer cells using chromosomal conformation capture data, Genes (Basel), 13, 7 (2022) [5] A multi-platform reference for somatic structural variation detection, Cell Genomics, 2, 6 (2022) Citation Format: Scott Hickey, Xiaoguang Dai, Sergey Aganezov, John Beaulaurier, Eoghan Harrington, Sissel Juul. Translocation detection in cancer using low-pass pore-c sequencing [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 405.

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.

Mapping crossover events of mouse meiotic recombination by restriction fragment ligation-based Refresh-seq

Single-cell whole-genome sequencing methods have undergone great improvements over the past decade. However, allele dropout, which means the inability to detect both alleles simultaneously in an individual diploid cell, largely restricts the application of these methods particularly for medical applications. Here, we develop a new single-cell whole-genome sequencing method based on third-generation sequencing (TGS) platform named Refresh-seq (restriction fragment ligation-based genome amplification and TGS). It is based on restriction endonuclease cutting and ligation strategy in which two alleles in an individual cell can be cut into equal fragments and tend to be amplified simultaneously. As a new single-cell long-read genome sequencing method, Refresh-seq features much lower allele dropout rate compared with SMOOTH-seq. Furthermore, we apply Refresh-seq to 688 sperm cells and 272 female haploid cells (secondary polar bodies and parthenogenetic oocytes) from F1 hybrid mice. We acquire high-resolution genetic map of mouse meiosis recombination at low sequencing depth and reveal the sexual dimorphism in meiotic crossovers. We also phase the structure variations (deletions and insertions) in sperm cells and female haploid cells with high precision. Refresh-seq shows great performance in screening aneuploid sperm cells and oocytes due to the low allele dropout rate and has great potential for medical applications such as preimplantation genetic diagnosis.

Abstract A062: Untargeted analysis of plasma tumor fraction is an independent prognostic marker of response to front line chemotherapy in high-grade serous epithelial ovarian cancer: the MITO-16A/MANGO-OV2A clinical trial experience

Abstract Background: Although 80% of high grade serous ovarian cancer (HGSOC) patients are initially responsive to platinum (Pt)-based chemotherapy, the majority of them experience relapse with a progressive Pt-resistant disease. One of the most challenging issues that hampers the possibility to effectively treat relapsed disease is the lack of biological information about tumor recurrence. To date, the Pt-free interval (PFI), an empirical measure of the time lagging between the end of front-line chemotherapy and relapse, is the only and widely accepted parameter to predict patient outcome and sensitivity to Pt second-line chemotherapy. We have previously demonstrated that analysis of circulating tumor DNA (ctDNA) by low pass whole genome sequencing (sWGS) is a suitable tool to predict patient outcome and to intercept early signs of relapsed disease (Paracchini et al. PMID:33323403). In the present study, we quantified the percentage of tumor fraction (TF) in plasma of patients enrolled within the frame of a phase III clinical trial (MITO-16A/MaNGO-OV2A-EUDRACT number: NCT01706120) to demonstrate, at baseline, the prognostic value of untargeted ctDNA analysis. Methods: 172 eligible patients enrolled with the frame of the MITO-16A/MaNGO-OV2A clinical trial, for whom plasma sample was collected at baseline before chemotherapy, were selected for the study. For each plasma sample, circulating-free DNA (cfDNA) was purified and whole genome libraries (HyperPlus, Roche) sequenced (mean coverage 0.5X). ichorCN algorithm was used to infer the percentage of TF, as previously published (Paracchini et al. PMID:33323403). Results: In 168 out of 172 plasma samples analyzed, the TF was detectable, and it ranged from 2.4% to 47%. Cox-model univariate analysis with patients’ overall survival (OS) and Progression-Free Survival (PFS), indicate association of TF levels with both OS and PFS (p<0.001). The prognostic relevance of TF was also confirmed in multivariate analysis, where, considering CA-125, residual tumor, stage of disease, histology and age as co-variables, TF maintained its statistical significance in PFS (HR = 2.1, CI 95%, p-value < 0.003). Conclusion: Retrospective analysis of baseline plasma samples collected within the frame of the MITO-16A/MaNGO-OVtrialnical trial, demonstrated that the percentage of TF is an independent prognostic marker of relapse. This finding confirms the importance of liquid biopsy analysis based on untargeted sWGS tool as an innovative approach to predict response to front line therapy and patient’s outcome. Citation Format: Sergio Marchini, Lara Paracchini, Laura Arenare, Giovanni Scambia, Carmela Pisano, Riccardo Zadro, Laura Mannarino, Annamaria Ferrero, Paolo Chiodini, Daniela Califano, Piergiacomo Di Gennaro, Sandro Pignata, Maurizio D'Incalci. Untargeted analysis of plasma tumor fraction is an independent prognostic marker of response to front line chemotherapy in high-grade serous epithelial ovarian cancer: the MITO-16A/MANGO-OV2A clinical trial experience [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A062.

Digital RNA sequencing using unique molecular identifiers enables ultrasensitive RNA mutation analysis

Mutation analysis is typically performed at the DNA level since most technical approaches are developed for DNA analysis. However, some applications, like transcriptional mutagenesis, RNA editing and gene expression analysis, require RNA analysis. Here, we combine reverse transcription and digital DNA sequencing to enable low error digital RNA sequencing. We evaluate yield, reproducibility, dynamic range and error correction rate for seven different reverse transcription conditions using multiplexed assays. The yield, reproducibility and error rate vary substantially between the specific conditions, where the yield differs 9.9-fold between the best and worst performing condition. Next, we show that error rates similar to DNA sequencing can be achieved for RNA using appropriate reverse transcription conditions, enabling detection of mutant allele frequencies <0.1% at RNA level. We also detect mutations at both DNA and RNA levels in tumor tissue using a breast cancer panel. Finally, we demonstrate that digital RNA sequencing can be applied to liquid biopsies, analyzing cell-free gene transcripts. In conclusion, we demonstrate that digital RNA sequencing is suitable for ultrasensitive RNA mutation analysis, enabling several basic research and clinical applications.

Construction of relatedness matrices in autopolyploid populations using low-depth high-throughput sequencing data

Key messageAn improved estimator of genomic relatedness using low-depth high-throughput sequencing data for autopolyploids is developed. Its outputs strongly correlate with SNP array-based estimates and are available in the package GUSrelate.High-throughput sequencing (HTS) methods have reduced sequencing costs and resources compared to array-based tools, facilitating the investigation of many non-model polyploid species. One important quantity that can be computed from HTS data is the genetic relatedness between all individuals in a population. However, HTS data are often messy, with multiple sources of errors (i.e. sequencing errors or missing parental alleles) which, if not accounted for, can lead to bias in genomic relatedness estimates. We derive a new estimator for constructing a genomic relationship matrix (GRM) from HTS data for autopolyploid species that accounts for errors associated with low sequencing depths, implemented in the R package GUSrelate. Simulations revealed that GUSrelate performed similarly to existing GRM methods at high depth but reduced bias in self-relatedness estimates when the sequencing depth was low. Using a panel consisting of 351 tetraploid potato genotypes, we found that GUSrelate produced GRMs from genotyping-by-sequencing (GBS) data that were highly correlated with a GRM computed from SNP array data, and less biased than existing methods when benchmarking against the array-based GRM estimates. GUSrelate provides researchers with a tool to reliably construct GRMs from low-depth HTS data.

Anchored-fusion enables targeted fusion search in bulk and single-cell RNA sequencing data

Here, we present Anchored-fusion, a highly sensitive fusion gene detection tool. It anchors a gene of interest, which often involves driver fusion events, and recovers non-unique matches of short-read sequences that are typically filtered out by conventional algorithms. In addition, Anchored-fusion contains a module based on a deep learning hierarchical structure that incorporates self-distillation learning (hierarchical view learning and distillation [HVLD]), which effectively filters out false positive chimeric fragments generated during sequencing while maintaining true fusion genes. Anchored-fusion enables highly sensitive detection of fusion genes, thus allowing for application in cases with low sequencing depths. We benchmark Anchored-fusion under various conditions and found it outperformed other tools in detecting fusion events in simulated data, bulk RNA sequencing (bRNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Our results demonstrate that Anchored-fusion can be a useful tool for fusion detection tasks in clinically relevant RNA-seq data and can be applied to investigate intratumor heterogeneity in scRNA-seq data.

Improved metagenome assemblies through selective enrichment of bacterial genomic DNA from eukaryotic host genomic DNA using ATAC-seq.

Genomics can be used to study the complex relationships between hosts and their microbiota. Many bacteria cannot be cultured in the laboratory, making it difficult to obtain adequate amounts of bacterial DNA and to limit host DNA contamination for the construction of metagenome-assembled genomes (MAGs). For example, Wolbachia is a genus of exclusively obligate intracellular bacteria that live in a wide range of arthropods and some nematodes. While Wolbachia endosymbionts are frequently described as facultative reproductive parasites in arthropods, the bacteria are obligate mutualistic endosymbionts of filarial worms. Here, we achieve 50-fold enrichment of bacterial sequences using ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) with Brugia malayi nematodes, containing Wolbachia (wBm). ATAC-seq uses the Tn5 transposase to cut and attach Illumina sequencing adapters to accessible DNA lacking histones, typically thought to be open chromatin. Bacterial and mitochondrial DNA in the lysates are also cut preferentially since they lack histones, leading to the enrichment of these sequences. The benefits of this include minimal tissue input (<1 mg of tissue), a quick protocol (<4 h), low sequencing costs, less bias, correct assembly of lateral gene transfers and no prior sequence knowledge required. We assembled the wBm genome with as few as 1 million Illumina short paired-end reads with >97% coverage of the published genome, compared to only 12% coverage with the standard gDNA libraries. We found significant bacterial sequence enrichment that facilitated genome assembly in previously published ATAC-seq data sets from human cells infected with Mycobacterium tuberculosis and C. elegans contaminated with their food source, the OP50 strain of E. coli. These results demonstrate the feasibility and benefits of using ATAC-seq to easily obtain bacterial genomes to aid in symbiosis, infectious disease, and microbiome research.

Development of novel SSR markers and validation by assessing the genetic diversity of endangered Deccan mahseer, Tor khudree.

The Deccan mahseer, Tor khudree (Sykes, 1839) is a potential game and food fish species belonging to the family cyprinidae and is categorized as endangered. Its distribution is restricted to southern part of India, specifically to Peninsular Rivers. This study is first to assess the genetic diversity and differentiation in Tor khudree by developing novel simple sequence repeat (SSR) markers. Low depth next generation sequencing followed by sequence analysis in MISA software identified 187,649 SSRs. The novel fourteen validated SSR loci were used for population genetic analysis. All of the SSR loci were highly informative with mean PIC > 0.5. High mean allelic richness (9.29) observed heterozygosity (0.98) and expected heterozygosity (0.79) were observed across the loci. However, genetic differentiation was low but significant (0.052). Negative FIS values were observed in both locus-wise and populations indicating the presence of high heterozygosity. Intrapopulation variation was found to be high (96.29%). The population structure revealed two genetic stocks. The results from the present study including the highly polymorphic markers developed would be a useful resource for further research on population genetics and conservation genetics of the species.

Correlation of urinary comprehensive genomic profile with risk of recurrence of BCG-unresponsive non-muscle invasive bladder cancer treated with atezolizumab in SWOG S1605.

529 Background: Radical cystectomy is recommended for patients with BCG-unresponsive (BU) non-muscle invasive bladder cancer (NMIBC) due to high risk of progression. Improved methods for assessing these risks would greatly facilitate the potential for bladder preservation. Here, we tested the capacity of the urinary comprehensive genomic profile (uCGP) to predict event-free survival (EFS) in patients with BU-NMIBC treated with atezolizumab in the single arm phase 2 trial SWOG S1605. Methods: Urine was collected from patients with BU NMIBC (CIS, Ta, T1) treated with at least one dose of intravenous atezolizumab at baseline and before the 5th cycle of therapy (3 months). The uCGP was assessed using UroAmp (Convergent Genomics). Risk scores for recurrence at baseline and at 3 months were calculated by a prespecified machine learning algorithm incorporating alterations in 60 genes and low pass whole genome sequencing, and categorized as high versus low. Molecular response was classified based on change in uCGP between the two time points. Risk scores and molecular response were submitted to SWOG for clinical correlation with EFS using a Cox model, adjusting for CIS status. Time to event was calculated from date of study entry (baseline risk) or from the 2nd collection time (3-month risk) to first high grade (HG) recurrence or persistent CIS at 3 months. Death unrelated to bladder cancer and patients last known to be alive without HG recurrence were censored at date of last visit. Results: Samples were provided at baseline in 89 patients and before the 5th cycle in 77; 68 had both samples available for paired analysis. The risk score at baseline was classified as high in 69% of samples (73% for CIS ±Ta/T1 and 62% for Ta/T1). At 12 and 18 months the EFS probabilities were 26% and 23% for high-risk and 67% and 51% for low-risk patients, respectively, with a HR of 2.82 (95% CI: 1.58, 5.03; p&lt;0.001). The risk score at the 3-month timepoint was classified as high in 81% of samples, and the EFS probabilities at 12 and 18 months after urine collection were 26% and 22% for high-risk and 80% and 72% for low-risk patients, respectively, with a HR of 3.39 (95% CI: 1.41, 8.13; p&lt;0.006). Molecular response to treatment was classified as complete (CR) in 8%, partial (PR) in 14%, stable (SD) in 25% and progression (PD) in 46%, with 7% having no detectable genomic abnormalities at both time points. Clinical recurrence was observed by 18 months in 0/6 patients with CR, 7/9 (78%) with PR, 11/14 (79%) with SD and 25/33 (76%) with PD by genomic profile. Conclusions: This study suggests that uCGP at baseline and after 4 cycles of treatment can identify genomic patterns associated with an increased risk of HG persistence, recurrence or progression in BU NMIBC treated with immune checkpoint inhibition. Future studies will determine if this can be used to guide early treatment intensification.

Utility of long-read sequencing for All of Us

The All of Us (AoU) initiative aims to sequence the genomes of over one million Americans from diverse ethnic backgrounds to improve personalized medical care. In a recent technical pilot, we compare the performance of traditional short-read sequencing with long-read sequencing in a small cohort of samples from the HapMap project and two AoU control samples representing eight datasets. Our analysis reveals substantial differences in the ability of these technologies to accurately sequence complex medically relevant genes, particularly in terms of gene coverage and pathogenic variant identification. We also consider the advantages and challenges of using low coverage sequencing to increase sample numbers in large cohort analysis. Our results show that HiFi reads produce the most accurate results for both small and large variants. Further, we present a cloud-based pipeline to optimize SNV, indel and SV calling at scale for long-reads analysis. These results lead to widespread improvements across AoU.

PMAT: an efficient plant mitogenome assembly toolkit using low-coverage HiFi sequencing data.

Complete mitochondrial genomes (mitogenomes) of plants are valuable resources for nucleocytoplasmic interactions, plant evolution, and plant cytoplasmic male sterile line breeding. However, the complete assembly of plant mitogenomes is challenging due to frequent recombination events and horizontal gene transfers. Previous studies have adopted Illumina, PacBio, and Nanopore sequencing data to assemble plant mitogenomes, but the poor assembly completeness, low sequencing accuracy, and high cost limit the sampling capacity. Here, we present an efficient assembly toolkit (PMAT) for de novo assembly of plant mitogenomes using low-coverage HiFi sequencing data. PMAT has been applied to the de novo assembly of 13 broadly representative plant mitogenomes, outperforming existing organelle genome assemblers in terms of assembly accuracy and completeness. By evaluating the assembly of plant mitogenomes from different sequencing data, it was confirmed that PMAT only requires 1× HiFi sequencing data to obtain a complete plant mitogenome. The source code for PMAT is available at https://github.com/bichangwei/PMAT. The developed PMAT toolkit will indeed accelerate the understanding of evolutionary variation and breeding application of plant mitogenomes.

A cautionary tale of low-pass sequencing and imputation with respect to haplotype accuracy

BackgroundLow-pass whole-genome sequencing and imputation offer significant cost savings, enabling substantial increases in sample size and statistical power. This approach is particularly promising in livestock breeding, providing an affordable means of screening individuals for deleterious alleles or calculating genomic breeding values. Consequently, it may also be of value in companion animal genomics to support pedigree breeding. We sought to evaluate in dogs the impact of low coverage sequencing and reference-guided imputation on genotype concordance and association analyses.ResultsDNA isolated from saliva of 30 Labrador retrievers was sequenced at low (0.9X and 3.8X) and high (43.5X) coverage, and down-sampled from 43.5X to 9.6X and 17.4X. Genotype imputation was performed using a diverse reference panel (1021 dogs), and two subsets of the former panel (256 dogs each) where one had an excess of Labrador retrievers relative to other breeds. We observed little difference in imputed genotype concordance between reference panels. Association analyses for a locus acting as a disease proxy were performed using single-marker (GEMMA) and haplotype-based (XP-EHH) tests. GEMMA results were highly correlated (r ≥ 0.97) between 43.5X and ≥ 3.8X depths of coverage, while for 0.9X the correlation was lower (r ≤ 0.8). XP-EHH results were less well correlated, with r ranging from 0.58 (0.9X) to 0.88 (17.4X). Across a random sample of 10,000 genomic regions averaging 17 kb in size, we observed a median of three haplotypes per dog across the sequencing depths, with 5% of the regions returning more than eight haplotypes. Inspection of one such region revealed genotype and phasing inconsistencies across sequencing depths.ConclusionsWe demonstrate that saliva-derived canine DNA is suitable for whole-genome sequencing, highlighting the feasibility of client-based sampling. Low-pass sequencing and imputation require caution as incorrect allele assignments result when the subject possesses alleles that are absent in the reference panel. Larger panels have the capacity for greater allelic diversity, which should reduce the potential for imputation error. Although low-pass sequencing can accurately impute allele dosage, we highlight issues with phasing accuracy that impact haplotype-based analyses. Consequently, if accurately phased genotypes are required for analyses, we advocate sequencing at high depth (> 20X).

Selecting autotetraploids from a facultatively apomictic tree of the nonapomictic ‘Licheng’ sweet orange (Citrus sinensis) variety

Tetraploid plays major roles in the polyploid breeding and production of citrus plants. Autotetraploids of nonapomictic citrus varieties are desirable in citrus polyploid breeding due to their high frequencies of hybrid polyploid production, certain genotypes and some predictable phenotypes. However, it is difficult to obtain autotetraploids of nonapomictic citrus varieties. In the present study, the nonapomictic sweet orange variety ‘Licheng’, which is native to China, was used as the main material. A ‘Licheng’ tree, LCOYC-04, that produced polyembryonic seeds at a frequency of 34.96±2.88 % was selected. Plants that grew from self-pollinated polyembryonic seeds of LCOYC-04 were investigated by flow cytometry. Four tetraploids were selected from 550 plants and identified according to chromosome observation. Exonic single-nucleotide polymorphism (SNP) locus genotyping based on genome resequencing showed that 22.18 %-70.49 % of heterozygous loci in the genome of LCOYC-04 were homozygous in the genomes of plants grown from self-pollinated monoembryonic seeds. The proportions of homozygous loci were 2.07 %-2.45 % in the 4 selected tetraploids. These values were close to those in 7 asexual ‘Licheng’ relatives (1.97 %-2.71 %). Therefore, the 4 tetraploids were confirmed to be autotetraploids of LCOYC-04. Genome sequencing revealed a region of low sequencing depth (approximately 855 kb) on chromosome 4 of all ‘Licheng’ trees. The CitRWP gene, which is responsible for the occurrence of nucellar embryos in citrus plants, was located in the low sequencing depth region. It was confirmed by quantitative PCR that one of two allelic CitRWP gene was defective in genome of ‘Licheng’. The current study indicates that it is possible to induce nonapomictic citrus to mutate into facultatively apomictic citrus through chromosome segment deletion, and provides a reference for excavating autotetraploids which produce polyembryonic and monoembryonic seeds.