Sequencing Depth Research Articles

Abstract 4926: Advancements in somatic variant calling from UG100 whole genome and whole exome sequencing data

Abstract Somatic variant calling involves the identification of genomic alterations that occur in somatic cells, requiring deep coverage to enable high sensitivity for low-frequency variants. Characterizing somatic variants across the entire genome therefore benefits from novel cost-efficient sequencing platforms, such as UG100. Here, we present optimization of variant calling tools for short and structural variants on WGS and WES data from UG100. For calling short variants, we optimized DeepVariant (DV) for somatic calling using data from matched tumor-normal sample pairs, improving both variant calling accuracy and pipeline running time (up to 10-fold). We defined the task of somatic variant calling as deciding if the pileup image containing reads from the tumor and normal samples represents a true somatic variant (vs a germline variant or artifact). The challenge of robust variant calling using deep learning models is exacerbated in somatic calling, where sequencing depth and coverage variability are typically high. Our optimized DV overcomes these challenges by several data sampling strategies. First, allele-frequency preserving down-sampling reduces randomness of read sub-sampling in high coverage regions. Second, alternative allele prioritization samples alt-allele supporting reads first allowing to call variants at very high coverage loci without sacrificing sensitivity and computational efficiency. Finally, a Panel-of-Normals based on targeted WES data provides an additional improvement of precision for this assay type. We used these strategies to train two models, one for tumor characterization using WGS (T/N coverage: 40x-150x/40x-100x), and one for deep WES (T/N coverage: >500x/>120x). We called variants on simulated tumors using the WGS model. For VAF>10% the model showed SNV recall >98% and indel recall >95% with false-positive rate of 0.2/Mb. For VAF range of 5-10%, indel recall was 67% and SNV recall was 86%. To demonstrate the utility of our somatic variant calling, we applied the models to call somatic variants from well characterized cancer cell lines: COLO829, HCC1395 and HCC1143. Results showed F1>90% for variants with VAF>10%. The WES model was used to reliably call variants at VAF>5% on simulated tumors with average SNV recall of 99% with precision >99% and indel recall >86% with precision >94%. To analyze structural and copy-number variations, we optimized the assembly engine of GRIDSS to enable fast calling of structural variations and demonstrate that Control-FREEC can be used to call copy number variants. SV calling on COLO829/COLO829BL achieved sensitivity >95%. In conclusion, our research highlights the utility of UG100 within the field of oncology, demonstrating its capacity for comprehensive and precise somatic variant detection, both on WGS and WES data. Citation Format: Doron Shem-Tov, Maya Levy, Gil Hornung, Ilya Soifer, Hila Benjamin, Ariel Jaimovich, Adam Blattler, William Brandler, Robert Sugar, Isaac Kinde, Omer Barad, Doron Lipson. Advancements in somatic variant calling from UG100 whole genome and whole exome sequencing data [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 4926.

Abstract 2522: Predictive value of tumor mutational burden (TMB) in patients with metastatic microsatellite-stable (MSS) colorectal cancer (CRC) given first-line oxaliplatin-based chemotherapy and immune checkpoint blockade (ICB)

Abstract Purpose: Most CRC patients harbor primarily non-immunogenic MSS tumor. The randomized METIMMOX trial (NCT03388190) examined if patients with previously untreated, unresectable abdominal metastases from MSS-CRC may achieve therapeutic efficacy from short-course oxaliplatin-based chemotherapy (FLOX) and sequential ICB (nivolumab) repeatedly. Half of study patients assigned to this experimental treatment had significantly extended progression-free survival (PFS) while the other half had shortened PFS, compared to the control-group patients given standard FLOX chemotherapy with median PFS 9.3 months. Here we explored if somatic mutations (mut) unveiled by next-generation sequencing might provide insights into responsiveness to the METIMMOX regimen. Procedures: Patients had MSS-CRC with infradiaphragmatic metastases deemed unresectable and were eligible for first-line oxaliplatin-based therapy. They were randomly assigned to the control group of FLOX (oxaliplatin, 5-fluorouracil, folinic acid) Q2W or the experimental group of alternating 2 cycles each of FLOX Q2W and nivolumab Q2W, with prespecified break periods. Radiologic response assessment was done every 8 weeks with PFS as the primary endpoint. Diagnostic tumor biopsies and baseline metastasis biopsies were sequenced with the TruSight Oncology 500 assay. TMB was calculated using only coding, non-synonymous single-nucleotide variants and insertions/deletions with variant allele frequency ≥5% and sequencing depth ≥50 ×, applying the effective panel size as the megabases (Mb) denominator. Results: Sequencing data were acquired from 20 experimental-group patients with median PFS 7.9 months (minimum 2.0, maximum 41.6). Median TMB was 5.1 mut/Mb (minimum 0.8, maximum 11.8), concordant in patient-paired primary tumor and metastasis specimens. The TMB was associated with treatment outcome; the higher TMB, the better PFS with hazard ratio 0.83 (95% confidence interval (CI) 0.70-0.98; p = 0.026, Cox regression) for a PFS event with increasing TMB. TMB cut-off as low as 5.0 mut/Mb distinguished between patient groups (p = 0.007, log-rank test) with median PFS 34.9 months (95% CI 10.6-59.2; TMB>5, n = 10) and median PFS 4.6 months (95% CI 2.7-6.5; TMB≤5, n = 10). In the TMB>5 group, 8/10 were KRAS- or BRAF-mutant cases. In the TMB≤5 group, 9/10 metastasis specimens were RAS/BRAF-wildtype cases. Conclusions: TMB >5 mut/Mb was associated with tumor KRAS or BRAF driver mutation and remarkably long PFS in first-line treatment of patients with abdominal metastases from MSS-CRC with alternating short-course oxaliplatin-based chemotherapy and ICB. Citation Format: Anne Hansen Ree, Paula A. Bousquet, Hilde L. Nilsen, Torben Lüders, Shixiong Wang, Tina Visnovska, Diana L. Bordin, Eirik Høye, Hanne M. Hamre, Christian Kersten, Eva Hofsli, Marianne G. Guren, Halfdan Sorbye, Kjersti Flatmark, Sebastian Meltzer. Predictive value of tumor mutational burden (TMB) in patients with metastatic microsatellite-stable (MSS) colorectal cancer (CRC) given first-line oxaliplatin-based chemotherapy and immune checkpoint blockade (ICB) [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 2522.

Abstract 3677: Hybrid capture based sequencing from urinary cell free DNA from colorectal cancer patients

Abstract Background: The study of body fluids other than blood is gaining increasing attention in the field of liquid biopsy. Since urine offers a truly non-invasive sampling method, it is a particularly interesting specimen. Evidence suggests that urine cell-free DNA (ucfDNA) harbors information about renal and bladder cancer. However, not much is known about ucfDNA in colorectal cancer (CRC) patients. Therefore, we aimed to test the feasibility of a hybrid capture based NGS approach with and without preanalytical stabilization of urine samples. Methods: Urine samples were collected from 20 patients with metastatic CRC (mCRC), aliquoted and stored with or without a stabilizing agents (PAXgene Urine Liquid Biopsy Set and Streck urine Preserve) at room temperature. Urine cfDNA was isolated at the day of donation and after 3 days. Matched blood samples were additionally collected in PAXgene Blood ccfDNA Tubes (PreAnalytiX). cfDNA from blood and urine was isolated using the QIAsymphony platform (QIAGEN). cfDNA samples were analyzed using the AVENIO ctDNA Analysis Kit (Roche), a hybrid-capture based approach enriching for 17 clinically relevant genes. Results: While all stabilized ucfDNA yielded high quality libraries, library preparation failed in 66.7% of unstabilized urine samples, demonstrating that without stabilization ucfDNA rapidly degrades after urine donation. In native samples, in which sequencing data could be obtained, sequencing depth was significantly decreased compared to stabilized samples. For stabilized samples, sequence analysis revealed full concordance between urine and plasma for putative germline variants. However, when using less than 50ng of input material of ucfDNA, a low signal-to-noise ratio with a high number of false positive low level variants was observed. We therefore adjusted the limit of detection for ucfDNA to 0.5%, at which CRC-related mutations were detected in ucfDNA in one patient. Although these variants, were not observed in plasma cfDNA, they could be detected in all stabilized urine samples, which hints to true variants. Conclusion: Our data demonstrate that a hybrid-capture based analysis approach is feasible for ucfDNA form CRC patients and that urine may provide complementary information about a patient's tumor that may be missed in plasma. Yet, due to degradation and lower concentrations, immediate stabilization of urine after donation is required. Moreover, the limit of detection needs to be adjusted if low amounts of input DNA is available only. Citation Format: Anna Eberhard, Tina Moser, Leandra Ziegler, Georgios Vlachos, Isaac Lazzeri, Martina Loibner, Armin Gerger, Ellen Heitzer. Hybrid capture based sequencing from urinary cell free DNA from colorectal 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 3677.

Abstract 3701: Urine-based liquid biopsy test for the detection of residual bladder cancer in radical cystectomy patients

Abstract The gold standard therapy for muscle-invasive bladder cancer (MIBC) is neoadjuvant chemotherapy followed by radical cystectomy (RC) and urinary diversion. Some patients may have their disease completely eradicated by chemotherapy as ~35% of patients achieve a pathologic complete response (pCR) when evaluated from RC specimens. RC with urinary diversion is a life-altering operation with high complication rates and therefore determining who are complete responders would improve quality of life and could decrease costs and still achieve a high cure rate via RC avoidance. Unfortunately, current methods cannot accurately identify complete responders. Our lab has developed a urine-based liquid biopsy test in which DNA isolated from urine and germline is isolated and subjected to panel exome sequencing for enumeration of somatic variants. This occurs under the premise that tumor DNA identified (as mutant alleles) is a marker of residual disease while the absence of tumor DNA (meaning the absence of mutant alleles) can indicate a pCR. A 55 gene panel was designed to be used for exonic sequencing of urinary DNA (uDNA) to identify mutations indicative of bladder cancer or therapeutic targets. We have shown that most mutations in tumor tissue are detectable as mutations in urine (Mu). We also showed that the presence or absence of residual Mu after completion of chemotherapy strongly associates with residual disease or pCR at the time of RC, respectively. Therefore, this test could be used after neoadjuvant therapy to better identify patients for RC avoidance. To optimize this test, we are currently evaluating pre-analytical factors affecting the yield, purity, and integrity of uDNA and the quality of sequencing data using prospectively collected samples from patients with MIBC. We are also testing commercial and novel preservatives to identify one that maintains cell-free DNA integrity, yield, and mutation detection accuracy to enable temporary ambient temperature storage without compromising mutation detection, permitting shipping/centralized testing. Lastly, we are comparing two library preparation approaches: classical hybrid capture-based (Agilent SureSelect XTHS) and amplicon+hybrid capture-based (Agilent HaloPlexHS) to determine which performs the best for identifying the variants in a sample. Our results showed that both sequencing depth and the quality bases mapped was higher when utilizing the SureSelect XTHS kit as compared to HaloPlexHS using approximately the same number of reads. This improvement may also increase the power to detect rare alleles. Studies described herein will enable liquid biopsy tests to accurately identify patients with pCR after neoadjuvant therapy and might safely avoid radical cystectomy. Citation Format: Rhea Arya, Henkel Valentine, Uttam Satyal, Raju Chelluri, Mengmeng Li, Philip Abbosh. Urine-based liquid biopsy test for the detection of residual bladder cancer in radical cystectomy 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 3701.

Abstract 3479: Evaluation of subclonal deconvolution pipelines using reference cell-lines and patient plasma samples

Abstract Background: Intratumor heterogeneity plays a pivotal role in treatment resistance, emphasizing the need for a comprehensive understanding of tumor clonal architecture. While various methods exist for extracting this information from bulk tumor sequencing data, few studies have evaluated the entire workflow, from sample processing to subclone calls. Methods: To address this gap, we utilized cell lines with known copy number changes and somatic mutations, constructing 12 ground truth sample sets with varying cellular proportions and tumor purities. These cell lines underwent NGS pipeline using PredicineWES+ with increased sequencing depth across ~600 cancer-related genes. Subclonal analysis workflows, including FACETS, PyClone, and ECLIPSE, were implemented to to assess variant assignment and cellular fractions. The subclone analysis was extended to 91 plasma samples from cancer patients. Results: Our findings indicate that subclonal decomposition effectively segregates mutations from distinct cell lines. Notably, analyzing multiple samples with different proportions of the same subclones outperformed deconvolution from single mixture samples. In plasma samples from cancer patients, nearly one-third exhibited subclonal clinically actionable variants. Conclusions: The established subclonal deconvolution pipeline enhances biomarker analysis from assays utilizing WES with boosted sequencing depth for selected genes. Citation Format: Xiaoxi Dong, Yong Huang, Tom Zhang, Shidong Jia, Pan Du. Evaluation of subclonal deconvolution pipelines using reference cell-lines and patient plasma 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 3479.

Abstract 6085: Leveraging targeted epigenetic and genetic detection for cost-effective cancer classification

Abstract The combinatorial power of genetics and epigenetics is vital to understanding biology in healthy and cancerous states. Utilizing a recent novel approach, we enable the simultaneous identification of modified cytosine and the canonical bases A, C, T & G in an enzymatic single-workflow solution. Generating this information across the whole genome provides a much-improved understanding of genetic and epigenetic changes, but can require a large amount of sequencing, particularly when exploring at depth. Enrichment protocols such as target enrichment enable deep interrogation of target areas whilst maintaining cost effectiveness. Target enrichment panels enable the selective isolation of sequences of interest through target hybridization. Using commercially available panels combined with the novel enzymatic single-workflow solution we show uniform performance across a range of input amounts with reduced sequencing requirements. Samples used were cell free DNA (cfDNA) from patient samples with either Stage I or IV Colorectal Cancer and reportedly healthy controls and were targeted using pan-cancer and methylome panels. Widespread differences such as hypermethylation are clearly observed in late-stage cancer vs early-stage or healthy controls demonstrating utility of the approach for applications such as liquid biopsy. Refining genetic and epigenetic investigations to a narrower region of interest can improve detection of low prevalence disease associated biomarkers at significant sequencing depth and lower sequencing costs. Citation Format: Robert Crawford, Ben Krajacich, Ermira Lleshi, Aurel Negrea, Lisabet Andreasen, Jens Fullgrabe, Jack Monahan, David Morley, Fabio Puddu, Donna McDade Walker, Semyon Kruglyak, Páidí Creed. Leveraging targeted epigenetic and genetic detection for cost-effective cancer classification [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 6085.

Abstract 1764: Long read sequencing allows comprehensive molecular profiling of complex karyotype acute myeloid leukemia (CKAML) with 5q deletions

Abstract Background Acute myeloid leukemia with complex karyotype (CKAML) does frequently show del(5q), deletion of chromosome 5q. Previous work in MDS and AML showed that CKAML form clusters distinguishing del(5q) cases with commonly retained regions (CRRs) in the telomeric (≥5q34) and centromeric (≤5q14.2) ends from cases with loss of the telomeric and/or centromeric regions. Interestingly, del(5q) patients with CRRs were shown to have less genomic lesions and were associated with a better prognosis than other 5q-deleted CKAML cases. Aim: Combining the advantages of two different long read sequencing technologies, Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), we aimed to more comprehensively characterize the molecular landscape of CKAML with del(5q). Our integrative workflow enabled an in-depth characterization of copy number variations (CNV), genomic rearrangements, transcriptomic and epigenomic changes. Methods: Low coverage whole genome sequencing (WGS) using ONT was performed on 209 patients with CKAML to identify del(5q) cases for further in-depth analysis. For 10 selected cases with known CRR status, genomic deep sequencing using PacBio Revio and ONT PromethION was performed, as well as PacBio Revio MAS-seq for fusion transcript detection. Results: A mean sequencing depth of 3-fold (range 0.4-17.3-fold) was obtained by low coverage WGS of the 209 CKAML cases. With a resolution of 0.1 Mbp n=134 del(5q) cases were identified in our CKAML cohort (64%) and commonly deleted regions on 5q could be resolved at 5q21.2 to 5q23.3 and 5q33.3 to 5q35 (Fisher test, FDR Benjamini-Hochberg, p<10−30). These regions separated del(5q) in n=52 cases showing CRR retention and n=82 showing partially no CRR, (either the centromeric or telomeric regions, n=74, or of both regions, n=8 involved). Subsequent co-occurrence analysis provided evidence of an association between the loss of telomeric 5q region with a 3p12-25 deletion. In-depth analysis (30-50 fold) of ten distinct del(5q) cases by PacBio and ONT revealed additional insights into the complex clonal composition of del(5q) cases. For example, one case showed two distinct subclones with 5q14.2-5q35.1 deletion and with translocation t(3;5)(p14;q14) respectively. Moreover, we could demonstrate that 5q-aberrations are far more complex than initially thought showing, e.g. inverted terminal duplications that resulted in fusion transcripts involving PDE4D and leading to its deregulated expression. Conclusion: Using our long read deep sequencing approach we could further delineate the structural complexity of del(5q) CKAML. While gene expression profiling, methylation analysis and correlation of findings with clinical outcome are ongoing and will be presented at the meeting, our results help to further pinpoint the biology underlying del(5q) and to further refine this heterogeneous CKAML subgroup. Citation Format: Felix Schick, Ekaterina Slonova, Eric Straeng, Sarah Huet, Maurizio Raso, Marlon Tilgner, Frederik Damm, Pierre Sujobert, Olga Blau, Lars Bullinger, Anna Dolnik. Long read sequencing allows comprehensive molecular profiling of complex karyotype acute myeloid leukemia (CKAML) with 5q deletions [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 1764.

Abstract 321: Optimized RNA Seq library preparation for fusion calling from FFPE samples

Abstract Gene fusions due to chromosomal rearrangement, duplication, or deletion can be important drivers of cancer. Detection of gene fusions plays a valuable role in selecting targeted therapies. A widely used method for detecting fusion transcripts is targeted RNA sequencing, which focuses sequencing reads on known fusions but does not allow for the detection of novel fusions. Whole transcriptome analysis (WTA), where the entire transcriptome is interrogated, offers an opportunity to detect both known and novel fusions. Herein we examine the effect of sample quality, input mass, increased reverse transcriptase (RT) and insert size on fusion calling. Libraries are prepared using the Watchmaker RNA Library Preparation Kit with or without Polaris Depletion and, for target enrichment, the Twist Exome 2.0 panel prior to paired end 2 × 150 Illumina sequencing. First, control samples, specifically Seraseq Fusion RNA v4 high quality and FFPE samples, are used to determine if any of the parameters interrogated increase the number of breakpoint spanning reads both in a WTA and targeted sequencing context. Once established, the optimized workflow is applied to real FFPE samples. Targeted sequencing results in a higher number of breakpoint spanning reads, compared to WTA, when controlling for sequencing depth, resulting in a higher number of reads supporting each fusion call. Longer insert sizes, achieved by modified SPRI ratios, maintain library complexity and may enhance fusion calling. Taken together, these data demonstrate an optimized protocol for fusion calling from FFPE and demonstrate the utility of both WTA and targeted sequencing for fusion detection. Citation Format: Giulia Corbet, Josh Haimes, Travis Sanders, Martin Ranik, Thomas Harrison, Eduard Casas, Kailee Reed, Doug Wendel, Kristina Giorda, Ariele Hanek, Jen Pavlica, Brian Kudlow. Optimized RNA Seq library preparation for fusion calling from FFPE 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 321.

Abstract 320: Development and automation of a streamlined targeted enrichment method for cancer mutation detection

Abstract Next Generation Sequencing (NGS) of DNA is a powerful tool for the detection of genetic variations, including single nucleotide polymorphisms, copy number variation, and small insertions/deletions. Target enrichment technologies enhance DNA sequencing by enabling users to analyze specific regions of interest only, which helps to effectively increase sequencing depth and sample throughput while minimizing cost. However, many targeted DNA library construction workflows are not optimal for routine genetic testing needs due to inconsistent, lengthy workflow. This poses significant challenge to application like cancer mutation profiling that requires detection sensitivity down to 1% or below due to heterogeneous nature of tumor tissue. In addition, high throughput testing with minimal hands on time is desirable with the rapid advance of precision medicine. Magnetic bead separations are commonly used between the individual reactions of targeted DNA library preparation workflows for cleanup and size selection. These bead clean up reactions are not only labor-intensive and tedious procedures but can also greatly contribute to sample-to sample variation especially when employing automated library preparation procedures. With the sophisticated QIAseq Targeted DNA Pro, we developed a novel streamlined targeted DNA workflow that greatly reduces handling variation by replacing the majority of bead clean up steps with enzymatic reactions, which now can be finished in as little as six hours. In combination with the newly developed QIAseq Normalizer kit, the protocol has been successfully implemented on the Hamilton NGS Star liquid handling platform resulting in up to 96 highly uniform, complex and ready-to-sequence libraries that can be effortless generated in one run. This complete automated solution saves researcher up to four hours of hands-on time. When using commercial reference samples, cancer mutations down to 1% were consistently detected with this automated workflow. The presented data demonstrate that this integrated and streamlined workflow does not only provide an automation friendly workflow but also allows to reliably identify low frequent cancer mutations. The applications presented here are for research use only. Not for use in diagnostic procedures. Citation Format: Zhong Wu, Michelle Baird, Cornelia Mechlen, Peter Hahn, Jonathan M. Shaffer. Development and automation of a streamlined targeted enrichment method for cancer mutation detection [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 320.

Abstract 2808: Levels of isobutyric acid from gut butyrate-producing taxa are associated to Delta-24-RGDOX efficacy against malignant glioma

Abstract Glioblastoma (GBM) is the most aggressive malignant primary brain tumor worldwide. Current standard-of-care treatments allow for a median survival of 12 to 18 months. GBM has a poor survival prognosis, observing less than 6% of patients surviving 5 years post-diagnosis. Among recent treatment advancements, the oncolytic adenovirus Delta-24-RGDOX armed with the T-cell activator OX40L is promising. Studies have unveiled a relationship between the gut microbiome and high levels of short-chain fatty acids (SCFA), such as isobutyric and propionic acid, to immunotherapy response. Changes in the gut microbiome and metabolome associated to viroimmunotherapy efficacy remain unclear. Here, we assessed the gut microbial changes in addition to isobutyric and propionic acid levels regarding viroimmunotherapy efficacy. Immunocompetent C57BL/6 mice were intracranially implanted GL261-5 GBM cells and received intratumoral injections of PBS (control) or Delta-24-RGDOX. A naïve group with no tumor nor treatment was also included. Fecal pellets were collected at three different time points: (1) before tumor implantation, (2) before treatment, and (3) 14 days after the first dose of treatment. Genomic DNA was isolated with the QIAGEN DNeasy Powersoil Pro Kit from fecal pellets (n=75), followed by sequencing with the Illumina platform of the 16S ribosomal RNA V4 region. Quality assessment of the sequences was executed in QIITA. Bacterial community analysis with a sequencing depth of 1,470 reads, while using the taxonomic database SILVA, was followed downstream with QIIME2 and R. Metabolic profiling of SCFA of the fecal pellets was performed through Gas Chromatography. Results showed significant differences in bacterial community structure of viroimmunotherapy-treated mice with survival of >100 days compared to controls (ANOSIM p-value=0.006). Alpha diversity metrics showed significant differences in richness between the naive and tumor-implanted mice of the PBS (KW p-value=0.049) and Delta-24-RGDOX (KW p-value=0.019) groups, highlighting that tumor presence alters the gut microbiota. Additionally, viroimmunotherapy-treated mice with survival of >100 days had a significant increase of Lactobacillus and the butyrate-producing bacterias Erysipelatoclostridium and Ruminococcaceae. Also, we found significantly higher levels of isobutyric acid and lower levels of propionic acid in viroimmunotherapy-treated mice with survival of >100 days (p-value<0.05). These findings suggest that butyrate-producing bacteria coupled with higher levels of isobutyric acid may be important in the efficacy of Delta-24-RGDOX. This highlights the microbial and metabolic changes associated with oncolytic viral therapy efficacy. Sponsored by an award within The University of Puerto Rico/UT MD Anderson Cancer Center Partnership for Excellence in Cancer Research Grant (2U54CA096297-17). Citation Format: Natalie M. Meléndez-Vázquez, Xuejun Fan, Juan Fueyo, Candelaria Gomez-Manzano, Filipa Godoy-Vitorino. Levels of isobutyric acid from gut butyrate-producing taxa are associated to Delta-24-RGDOX efficacy against malignant glioma [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 2808.

Abstract 7022: Whole genome and reduced representation enzymatic methyl-seq enable cost effective methylomes

Abstract DNA methylation is an epigenetic regulator of gene expression with important functions in development and diseases such as cancer. Traditionally, sodium bisulfite conversion was used to distinguish 5-methylcytosines (5mC) and 5-hydroxymethylcytosines (5hmC) from cytosines. However, this method damages DNA and introduces significant sequencing bias. NEBNext® Enzymatic Methyl-seq (EM-seq™) is an enzymatic conversion approach that minimizes DNA damage therefore enabling longer insert sizes, lower duplication rates and a more accurate quantification of methylation in DNA samples with inputs ranging from 10 ng to 200 ng. An improved enzymatic conversion method, EM-seq v2, has a more streamlined workflow and an expanded DNA input range of 100 pg to 200 ng. Libraries made using NA12878 genomic DNA show improved yields, consistent global methylation and an even GC bias representation. The increased library yields subsequently reduces sequencing duplications and costs. Sequencing costs are an important consideration when performing whole genome methylome analysis as this often needs high sequencing depth to attain meaningful coverage to accurately call methylation. Reduced representation libraries, a commonly used method to investigate DNA methylation, relies on enrichment of CpGs within libraries digested using MspI. These CpGs are commonly found in regulatory regions. Although lacking comprehensive CpG coverage, for many researchers this method provides enough cost effective CpG methylation coverage for their studies. Reduced Representation EM-seq libraries (RREM-seq) and Reduced Representation Bisulfite libraries (RRBS) were made using 200 ng to 100 pg of NA12878 DNA. EM-seq adaptors were ligated to MspI digested DNA followed by conversion using either EM-seq v2 or sodium bisulfite. Libraries were PCR amplified and sequenced on an Illumina NovaSeq platform. RREM-seq resulted in higher yields and reproducible results regardless of input amounts compared to RRBS libraries. RREM-seq libraries also identified a higher number of CpGs with even coverage facilitating accurate methylation calling. RREM-seq libraries have superior sequencing metrics resulting in robust methylation profiling. Focusing on a subset of the genome generates higher coverage DNA methylation data at a lower DNA sequencing cost. Citation Format: Vaishnavi Panchapakesa, Chaithanya Ponnaluri, Daniel Evanich, Ariel Erijman, Bradley Langhorst, Louise Williams. Whole genome and reduced representation enzymatic methyl-seq enable cost effective methylomes [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 7022.

Abstract 337: Balanced-strand sequencing for highly efficient duplex variant calling in circulating tumor DNA

Abstract Several approaches for the detection of circulating tumor DNA (ctDNA) are anchored in the accurate identification of cancer-specific single nucleotide variants (SNVs) in plasma. Such approaches are limited in ultra-low tumor fraction (TF) contexts, such as early cancer detection or the identification of postoperative minimal residual disease, where ctDNA SNVs are difficult to distinguish against background sequencing error. ctDNA detection in these critical low TF contexts is further limited by the sparse amount of cell free DNA (cfDNA) in plasma (Zviran et al., 2020). To reduce single-stranded artifact and base calling errors, duplex sequencing can be used to jointly analyze corresponding Watson and Crick strands to detect true, double-stranded variants. Recent work has demonstrated that duplex sequencing can decrease error rates to 10−7 (Hoang et al., 2016) and can be deployed in the whole-genome sequencing (WGS) setting (Cheng et al., 2023). A significant limitation for existing duplex techniques is the need to analytically pair matching DNA strands through exhaustive sequencing, resulting in inefficient use of scarce input material, particularly in plasma cfDNA. These techniques typically capture 1-5% of sequenced molecules, restricting duplex coverage depth. We present balanced-strand sequencing, a PCR-free approach that leverages the hydrogen bonds of complementary DNA to carry matched native strands directly into sequencing, enabling massively scalable duplex sequencing. The approach relies on Ultima Genomics sequencing, where DNA denaturation is not required prior to clonal amplification. In balanced strand sequencing, double-stranded DNA is partitioned and clonally amplified on sequencing beads through emulsion-PCR. Each double-stranded DNA molecule contributes to a single sequencing read, allowing for a linear increase in duplex recovery with increasing sequencing depth. The approach does not require redundant sequencing and therefore maximizes unique molecule throughput. We applied balanced strand sequencing to cfDNA, input as low as 5 ng, and achieved 7-35x whole-genome duplex coverage, roughly 20-fold higher than our prior duplex WGS. We further developed a machine-learning guided single read mutation calling framework, which when combined with duplex error suppression, reduced error rates to 10−7 and enabled accurate ctDNA detection at concentrations <10−5. Use of our analysis framework in APOBEC-mutant bladder cancer plasma samples allowed us to identify APOBEC signatures in plasma and platinum exposure signatures indicative of prior chemotherapy treatment. Altogether, balanced strand sequencing radically enhanced duplex efficiency and has broad applications across cancer. In cfDNA applications, balanced strand sequencing enhances error-correction in tumor-informed ctDNA detection and paves the way for non-tumor informed WGS ctDNA detection. Citation Format: Adam Widman, Alexandre P. Cheng, Aaron Sossin, Srinivas Rajagopalan, Majd Al Assaad, Sunil Deochand, Zoe Steinsnyder, Dina Manaa, Melissa Marton, Catherine Reeves, Itai Rusinek, Eti Meiri, Omer Barad, Zohar Shipony, Shlomit Gilad, Ariel Jaimovich, Michael Sigouros, Jyothi Manohar, Abigail King, David Wilkes, John Otilano, Olivier Elemento, Bishoy M. Faltas, Juan M. Mosquera, Dan A. Landau. Balanced-strand sequencing for highly efficient duplex variant calling in circulating tumor DNA [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 337.

Abstract 2443: Improved detection of low frequency mutations in ovarian and endometrial cancers by utilizing a highly accurate sequencing platform

Abstract Ovarian and endometrial cancers come within the top-4 for incident cancers as well as deaths in North American women. Cure rates have not improved in 30 years as high-grade subtypes continue to be diagnosed in Stage III/IV. Attempts at early diagnosis have failed because high-grade cancer cells exfoliate and metastasize while the primary cancer is small and undetectable by existing tests based on imaging and blood-based tumor markers. DOvEEgene (Detecting Ovarian and Endometrial cancers Early using genomics) is a genomic uterine pap test developed by a McGill team to screen and detect these cancers while they are confined to the gynecologic organs and curable by surgery. The test identifies pathogenic somatic mutations in uterine brush samples. Here we tested the Onso system, a highly accurate sequencing technology from PacBio in order to potentially increase sensitivity while driving down sequencing costs by reducing required sequencing depth vs the current NGS standard. A highly sensitive, error-correcting capture technology (DOvEEgene-SureSelectHS) utilizing duplex error correction sequencing interrogated the exons of 23 genes involved in the development of sporadic and hereditary ovarian and endometrial cancers. We applied a combination of germline gene panel testing on saliva samples with deep duplex sequencing to detect somatic mutations at <0.1% VAF, interrogation of microsatellite loci for instability, and low coverage WGS for copy number analysis of uterine brush samples. We sequenced 20 duplex Illumina sequencing libraries produced using the DovEE assay at PE 100bp mode and compared Onso data in non- duplex sequencing mode as well as duplex sequencing mode to the original Illumina duplex sequencing method. Here, we present this comparison and highlight the benefits of high accuracy sequencing for the detection of very low frequency (<0.1%) somatic mutations. We observed improved mismatch rates for Onso data compared to Illumina, even after duplex error correction was applied. In addition, we found that more individuals are called as displaying microsatellite instablity from the Onso data, which may be due to improved sequencing performance in repetitive regions for Onso. Finally, we observed fewer potential false positive variant calls in the Onso data, highlighting the value of improved sequencing accuracy for rare variant detection. Citation Format: Timothée Revil, Nairi Pezeshkian, Lucy Gilbert, Alexandra Sockell, Jiannis Ragoussis. Improved detection of low frequency mutations in ovarian and endometrial cancers by utilizing a highly accurate sequencing platform [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 2443.

Abstract 6101: PLASMUT: An R Package for estimating the probability of tumor-specific mutations in cell-free DNA

Abstract Noninvasive approaches for detection of tumor-specific mutations in cell-free DNA (cfDNA) have the potential to track a patient’s response to treatment, enabling effective and timely decisions on therapy. However, mutations in cfDNA arising from clonal hematopoeisis (CH) are common and tumor biopsies for definitive identification of the origin of these mutations are not always available. Sequencing of matched cells from buffy coat and the absence of mutations in these cells has been used to rule-out white blood cell (WBC) mutations, but uneven sequencing depths between matched cfDNA and buffy coat and the fraction of mutant alleles are generally ignored by rule-based tests. A probabilistic approach that quantifies the evidence of tumor-derived mutations in cfDNA is needed. We developed a Bayesian framework to estimate the probability that a mutation identified in cfDNA is tumor specific. Our approach requires the number of reads with a mutant allele in plasma (yp) and WBCs (yw) and the corresponding number of total distinct reads at these locations. The posterior odds that a mutation is tumor-derived (S) versus CH or germline (H) is given by the ratio of the probabilities of observing the distinct reads given each model times the prior odds. Estimation of the Bayes factor is obtained by integrating over the unobserved mutant allele fractions in plasma and WBCs using Monte Carlo importance sampling. We applied this approach to 52 patients with initially unresectable colorectal cancer (CRC) liver metastases in the CAIRO5 clinical trial (NCT02162563), using ultra-deep targeted sequencing of cfDNA from plasma and matched WBCs. Among the CAIRO5 patients analyzed, we identified 95 mutations with moderate evidence of tumor-derived cfDNA mutations (Bayes factor > 10) and 19 mutations that were CH-derived (Bayes factor < 0.1). For a subset of 47 cfDNA mutations with no corresponding mutation identified by WBC sequencing, the evidence of tumor origin was highly variable (Bayes factor range: 0.03 to 5.6). While the standard rule-based approach identifies all of these mutations as tumor-derived, none of these mutations reach a moderate evidence cutpoint (all Bayes factors < 6). As a false positive would lead to identification of cfDNA mutations that do not track tumor burden, requiring even higher levels of evidence (Bayes factor > 99) for the selection of cfDNA mutations could be warranted, and still identifies one or more cfDNA mutations in 43 of the patients. This approach is implemented in the R package PLASMUT available from Bioconductor (doi:10.18129/B9.bioc.plasmut). We developed an approach that quantifies the evidence between two competing models for the origin of mutations in cfDNA. A cutpoint for determination of the probability of tumor-derived cfDNA mutations can be tailored to the disease application, balancing the potential benefits of noninvasive testing with the harms of false positives and negatives. Citation Format: Adith S. Arun, Jamie E. Medina, Stephen Cristiano, Daniel C. Bruhm, Remond J. Fijneman, Gerrit A. Meijer, Alessandro Leal, Victor E. Velculescu, Robert B. Scharpf. PLASMUT: An R Package for estimating the probability of tumor-specific mutations in cell-free DNA [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 6101.

Abstract 7008: NEBNext® E5hmC-seqTM: Direct detection of 5-hydroxymethylcytosine at single base resolution

Abstract DNA methylation is a critical epigenetic regulator of gene expression during development and in diseases such as cancer. The modified cytosines, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), can be detected by sequencing libraries generated using existing methods: NEBNext® EM-seq™ or bisulfite sequencing. However, these methods cannot differentiate between 5mC and 5hmC. Interest in the role of 5hmC in regulating gene expression and as a cancer biomarker has increased, resulting in the need for robust methods for the identification of specific 5hmC sites. Methods currently exist to enable discrimination of 5mC and 5hmC (for example, oxBS-seq and TAB-seq), however these are based on modifications of bisulfite sequencing, and suffer from reduced data quality due to fragmentation and loss of DNA. Here we describe an enzymatic method that enables specific detection of 5hmC, termed NEBNext® Enzymatic 5hmC-seq (E5hmC-seqTM). E5hmC-seq libraries were generated for 0.1 ng to 200 ng DNA isolated from human brain and E14 mouse embryonic stem cells. Libraries were prepared using NEBNext® Ultra IITM reagents followed by two enzymatic steps to detect 5hmC. In the first step, 5hmCs are glucosylated, which protects them from subsequent deamination by APOBEC. In contrast, cytosines and 5mCs are deaminated resulting in their conversion to uracil and thymine, respectively. This conversion allows discrimination of 5hmC from cytosine and 5mC. Finally, libraries were PCR amplified using NEBNext® Q5U® and sequenced on the Illumina platform. The E5hmC-seq libraries have similar characteristics to EM-seq libraries, including expected insert sizes due to intact DNA molecules, low duplication rates and minimal GC bias. Moreover, E5hmC-seq libraries were well-correlated between inputs and replicates at higher sequencing depths. Fully hydroxymethylated T4147 phage DNA was used as an internal control, with 98-99% of cytosines identified as 5hmC. 5mC and 5hmC levels were also profiled during E14 cell differentiation for a period of 10 days. Interestingly, 5hmC levels decreased whereas 5mC levels increased particularly during the first five days of differentiation. LC-MS/MS quantification of this same DNA mirrored the changes observed by sequencing. E5hmC-seq libraries provide accurate measurements of 5hmC across a wide input range with expected insert sizes and minimal GC bias. Additionally, subtracting E5hmC-seq data from EM-seq data, which detects both 5mC and 5hmC, enables the precise location of individual 5mC and 5hmC sites. The ability to discriminate between 5mC and 5hmC will allow key insights to be made into the role of cytosine modifications in development and cancer. Citation Format: Garrett M. Cammarata, Daniel J. Evanich, V. K. Chaithanya Ponnaluri, Vaishnavi Panchapakesa, Ariel Erijman, Matt A. Campbell, Nan Dai, Bradley W. Langhorst, Louise Williams. NEBNext® E5hmC-seqTM: Direct detection of 5-hydroxymethylcytosine at single base resolution [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 7008.

Abstract 4869: Efficient study design for the discovery of a gene expression signature predicting metastasis in cutaneous squamous cell carcinoma

Abstract Background: The StepIdent study aims to develop a gene signature predicting metastasis in patients with cutaneous squamous cell carcinoma (cSCC) to improve risk stratification, thus enabling personalized decisions about follow-up schedules and treatment options. Here we describe the unique characteristics, challenges, and best practices for an efficient design of a discovery cohort for a rare outcome (metastasis prevalence: 2-5%); for retrieving, curating, and linking the clinical and pathological data through nationwide databases; and for measuring gene expression through sequencing of archived Formalin-Fixed Paraffin-Embedded (FFPE) primary tumor samples. Methods: Following a predefined protocol, we identified a nested-case control cohort (NCC) of 305 cases and 305 controls from a nationwide cohort of 19,120 patients with a first cSCC in the Netherlands from 2007 to 2009, followed up until 2020. We chose an NCC design since it is an efficient study design in a rare outcome setting (weighting is needed to accommodate the under-sampling of the controls). Patients were identified from the Dutch National Cancer Registry (NCR) and the clinical information was retrieved from the NCR which is linked to the nationwide registry of histo- and cytopathology (PALGA). Tumor blocks were requested from PALGA, and pathological characteristics were assessed by dermatopathologists. We matched controls to cases, based on a risk score estimated by a clinicopathological model. Gene expression was measured using the Illumina RNA Prep with Enrichment kit combined with the whole exome panel and paired-end sequenced on the NextSeq 550. Results: Tissue slides for 541 samples were retrieved for sequencing. 151 samples were excluded after pathology review or due to low pre-library concentration. The final cohort includes 195 case-control pairs (n=390). The median sequencing depth was 43M (Q1-Q3: 35-52M); the median Q30 was 85% (Q1-Q3: 83-87%); the median GC content was 51% (Q1-Q3: 50-52%); a median of 1.8% of base pairs (Q1-Q3: 1.4-2.1%) was trimmed prior to the mapping/alignment; a median of 69% (Q1-Q3: 65-74%) of reads were aligned as protein-coding and a median of 7% (Q1-Q3: 6-10%) as rRNA; a median of 95% (Q1-Q3: 93-96%) of reads were aligned by STAR. Two samples were excluded based on quality control. Conclusion: We described an efficient design and implementation of a nationwide discovery study in cSCC, involving the retrieval of clinicopathological data, the collection of FFPE materials, and the execution of omics measurements. This study presents the largest cohort to date, incorporating omics measurements of primary cSCC samples, combined with simultaneous access to well-curated clinical and pathological information and follow-up data. Our findings can provide guidance for similar studies involving a rare clinical endpoint, where an efficient study design is a necessity. Citation Format: Barbara Rentroia-Pacheco, Lara Pozza, Yan Ting Chen, Daphne Huigh, Celeste J. Eggermont, Olivia FM Steijlen, Sheril Alex, Jvalini Dwarkasing, Domenico Bellomo, Harmen JG van de Werken, Antien L. Mooyaart, Marlies Wakkee, Loes M. Hollestein. Efficient study design for the discovery of a gene expression signature predicting metastasis in cutaneous squamous cell carcinoma [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 4869.

Abstract 318: Demystifying tumor heterogeneity with a fully automated, high-throughput single-cell DNA-Seq (scDNA-seq) workflow

Abstract Objective: Genetic heterogeneity is a key factor underlying tumor drug resistance and metastatic potential. Understanding this heterogeneity is therefore vital to improving both prognosis and treatment. Next-generation sequencing is a valuable tool for analyzing the genetic makeup of tumors. However, bulk sequencing methods lack the sensitivity to fully resolve tumor heterogeneity. While single cell methods provide a powerful approach to dissect such heterogeneity, to date, these methods have been limited in their throughput. To address this bottleneck, we have developed a fully automated workflow for generating scDNA-seq libraries based on PicoPLEX® whole genome amplification (WGA) technology. This high-throughput method, which has been optimized on our ICELL8® cx Single-Cell System, enables the generation of WGA libraries for >1,000 single cells within one day. Methods: We first sought to demonstrate the ability of this new high-throughput method to generate WGA libraries of comparable quality to the standard PicoPLEX workflow in terms of genome coverage, GC bias, and other typical quality metrics. We additionally assessed copy number variant (CNV) detection sensitivity using two cell lines with well-characterized small segmental CNVs: GM22601 (~25Mb deletion on chromosome 4) and GM05067 (~45Mb gain on chromosome 9). We also analyzed a lymphoblastoid line (K562) that carries a range of chromosomal aneuploidies. A total of 1,288 single-cell WGA libraries were generated and sequenced to a depth of 250K paired-end reads per cell. Data analysis was done using the Ginkgo CNV pipeline with an average bin size of 500 kb. As a final proof of principal, we also generated single cell data using tumor and adjacent normal tissue from two clear cell renal cell carcinoma (ccRCC) samples. Results: Libraries generated using our high-throughput workflow had a high mapping rate, with 94.1% of the reads being uniquely mapped. Additionally, the libraries were comparable to those generated with the standard PicoPLEX workflow in terms of coverage uniformity, GC bias and other metrics. Moreover, the segmental aneuploidies in both GM22601 and GM05067 were reliably detected in >90% of cells at a read depth as low as 250,000 reads per cell. Analysis of the ccRCC samples revealed subclonal heterogeneity with various CNVs common to ccRCC, including deletion of chr. 3p, amplification of chr. 5q, and duplication of chr. 2. Conclusion: By adapting PicoPLEX technology to high throughput using the ICELL8 cx Single-Cell System, we have obtained single-cell WGA libraries from up to 1,200 cells at once and enabled the reliable detection of CNVs and tumor subclones at a shallow sequencing depth. In addition, by leveraging the automated nanoliter-dispensing capabilities of ICELL8 cx system this method provides a significant reduction in reagent use and labor compared to plate-based methods. Citation Format: Xuan Li, Raymond Mendoza, Samantha Leong, Hima Anbunathan, Mike Covington, Mohammad Fallahi, Bryan Bell, Shuwen Chen, Yue Yun, Andrew Farmer. Demystifying tumor heterogeneity with a fully automated, high-throughput single-cell DNA-Seq (scDNA-seq) workflow [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 318.

Comparative study on chromatin loop callers using Hi-C data reveals their effectiveness

BackgroundChromosome is one of the most fundamental part of cell biology where DNA holds the hierarchical information. DNA compacts its size by forming loops, and these regions house various protein particles, including CTCF, SMC3, H3 histone. Numerous sequencing methods, such as Hi-C, ChIP-seq, and Micro-C, have been developed to investigate these properties. Utilizing these data, scientists have developed a variety of loop prediction techniques that have greatly improved their methods for characterizing loop prediction and related aspects.ResultsIn this study, we categorized 22 loop calling methods and conducted a comprehensive study of 11 of them. Additionally, we have provided detailed insights into the methodologies underlying these algorithms for loop detection, categorizing them into five distinct groups based on their fundamental approaches. Furthermore, we have included critical information such as resolution, input and output formats, and parameters. For this analysis, we utilized the GM12878 Hi-C datasets at 5 KB, 10 KB, 100 KB and 250 KB resolutions. Our evaluation criteria encompassed various factors, including memory usages, running time, sequencing depth, and recovery of protein-specific sites such as CTCF, H3K27ac, and RNAPII.ConclusionThis analysis offers insights into the loop detection processes of each method, along with the strengths and weaknesses of each, enabling readers to effectively choose suitable methods for their datasets. We evaluate the capabilities of these tools and introduce a novel Biological, Consistency, and Computational robustness score (BCCscore\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$BCC_{score}$$\\end{document}) to measure their overall robustness ensuring a comprehensive evaluation of their performance.

A comprehensive evaluation of the potential of three next-generation short-read-based plant pan-genome construction strategies for the identification of novel non-reference sequence.

Pan-genome studies are important for understanding plant evolution and guiding the breeding of crops by containing all genomic diversity of a certain species. Three short-read-based strategies for plant pan-genome construction include iterative individual, iteration pooling, and map-to-pan. Their performance is very different under various conditions, while comprehensive evaluations have yet to be conducted nowadays. Here, we evaluate the performance of these three pan-genome construction strategies for plants under different sequencing depths and sample sizes. Also, we indicate the influence of length and repeat content percentage of novel sequences on three pan-genome construction strategies. Besides, we compare the computational resource consumption among the three strategies. Our findings indicate that map-to-pan has the greatest recall but the lowest precision. In contrast, both two iterative strategies have superior precision but lower recall. Factors of sample numbers, novel sequence length, and the percentage of novel sequences' repeat content adversely affect the performance of all three strategies. Increased sequencing depth improves map-to-pan's performance, while not affecting the other two iterative strategies. For computational resource consumption, map-to-pan demands considerably more than the other two iterative strategies. Overall, the iterative strategy, especially the iterative pooling strategy, is optimal when the sequencing depth is less than 20X. Map-to-pan is preferable when the sequencing depth exceeds 20X despite its higher computational resource consumption.

The impact of FASTQ and alignment read order on structural variant calling from long-read sequencing data.

Structural variant (SV) calling from DNA sequencing data has been challenging due to several factors, including the ambiguity of short-read alignments, multiple complex SVs in the same genomic region, and the lack of "truth" datasets for benchmarking. Additionally, caller choice, parameter settings, and alignment method are known to affect SV calling. However, the impact of FASTQ read order on SV calling has not been explored for long-read data. Here, we used PacBio DNA sequencing data from 15 Caenorhabditis elegans strains and four Arabidopsis thaliana ecotypes to evaluate the sensitivity of different SV callers on FASTQ read order. Comparisons of variant call format files generated from the original and permutated FASTQ files demonstrated that the order of input data affected the SVs predicted by each caller. In particular, pbsv was highly sensitive to the order of the input data, especially at the highest depths where over 70% of the SV calls generated from pairs of differently ordered FASTQ files were in disagreement. These demonstrate that read order sensitivity is a complex, multifactorial process, as the differences observed both within and between species varied considerably according to the specific combination of aligner, SV caller, and sequencing depth. In addition to the SV callers being sensitive to the input data order, the SAMtools alignment sorting algorithm was identified as a source of variability following read order randomization. The results of this study highlight the sensitivity of SV calling on the order of reads encoded in FASTQ files, which has not been recognized in long-read approaches. These findings have implications for the replication of SV studies and the development of consistent SV calling protocols. Our study suggests that researchers should pay attention to the input order sensitivity of read alignment sorting methods when analyzing long-read sequencing data for SV calling, as mitigating a source of variability could facilitate future replication work. These results also raise important questions surrounding the relationship between SV caller read order sensitivity and tool performance. Therefore, tool developers should also consider input order sensitivity as a potential source of variability during the development and benchmarking of new and improved methods for SV calling.