No abstract

RNA-seq is a powerful tool to detect tissue-specific gene expression, splicing, and genetic variations associated with disease states. However, current RNA-seq approaches have limitations due to poor signal from low-abundant transcripts. Furthermore, tissue-derived RNA samples are often highly degraded, thereby limiting gene detection and suffering from potential sequencing artifacts. Here we show that target capture of sequencing libraries tagged with unique molecular identifiers (UMIs) using the xGen™ Prism DNA library prep kit, optimized for low-input and degraded samples, can overcome these obstacles. Directional and UMI-tagged RNA-seq libraries were constructed with RNA extracted from a FFPE RNA Fusion Reference Standard and captured with different designs of the xGen Pan-Cancer Panel spiked with probes for fusion genes. The first design strategy used IDT's stocked Pan Cancer V1.5 panel targeted to gDNA coordinates. The second design involved extracting all associated RefSeq NM transcripts associated with the gene list. Probes were designed to each transcript and duplicate probes were removed based on exact sequence match. The third strategy leveraged a multi-strain design, which created probes from fasta inputs, but removed probes with 90% or greater homology. Normalized expression was highly correlated (> 85%) between captured and uncaptured samples regardless of rRNA depletion prior to library prep. Captured samples had a greater depth of coverage with over 90% on target bases. In addition, our panel design strategies identified low frequency fusions with deep sequencing regardless of rRNA depletion prior to library prep. The multi-strain design was more effective in reducing redundant capture probes compared the other design strategies. Enhanced coverage and PCR de-duplication with UMIs allowed us to reproducibly measure expression over a wide range of RNA inputs (5-500 ng). We show that target capture of RNA-seq libraries reliably maintains expression information present in uncaptured libraries while increasing coverage for poorly expressed genes and low frequency fusions. In addition, the target captured libraries without rRNA depletion prior to library prep have comparable on-target rate and target coverage with rRNA-depleted, target captured libraries. The addition of UMIs to differentiate between PCR duplicates and unique starting molecules also makes it possible to reliably analyze even highly amplified libraries. (For research use only). Citation Format: Tzu-Chun Chen, Katelyn Larkin, Shale Dames, Hsiao-Yun Huang, Kevin Lai, Jessica Sheu, Timothy Barnes, Katia Star, Manqing Hong, Bosun Min, Ryan Demeter, Ashley Dvorak, Ushati Das Chakravarty, Patrick Lau, Steven Henck. High conversion library preparation with optimal hybridization capture panel design strategy in RNA-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 327.

Diagnostic tools based on next generation sequencing are fundamentally transforming clinical oncology. However, there is a lack of adequate library preparation strategies for highly degraded, clinically relevant samples, such as cell-free DNA (cfDNA) and FFPE DNA. Furthermore, clinical samples are often available in limited quantity, making the detection of pathologic variants particularly challenging. Due to the extreme heterogeneity of these sample types, targeted sequencing is often used to achieve deep coverage of genomic loci and enable detection of low-frequency variants. Commercially available protocols for library preparation require stringent size-selection to remove adapter-dimers, which reduces library complexity. Achieving high specificity can be challenging because low-frequency artifacts arise from a variety of sources, including DNA extraction, library construction, PCR, hybrid selection, and sequencing. These artifacts can be identified by “duplex sequencing”, where strand-specific unique molecular identifiers (UMIs) are used to confirm the presence of an alteration on both strands of an input molecule. However, duplex sequencing typically delivers low conversion rates with degraded samples due to poor ligation efficiency and template loss during size-selection. We present a novel library construction chemistry that eliminates adapter dimers and utilizes duplexed UMIs to increase sensitivity. The method employs a two-step ligation procedure that does not require size-selection or adjustment of AMPure bead ratios during cleanup. We achieve maximal library conversion using a unique, mutant DNA ligase and proprietary sequencing adapters that increase ligation efficiency and suppress chimera formation. We demonstrate performance using three sample types: sheared genomic DNA, cfDNA, and FFPE DNA, across a wide input range (1-1000 ng). To mimic performance with degraded DNA, we created libraries from mixtures of NA12878 and NA24385 cell line DNA sheared to 150 bp with inputs of 1-25 ng and mutant allele fractions (MAFs) down to 0.25%. Libraries were enriched using a 75 kb panel of xGen Lockdown Probes, followed by ultra-deep sequencing and variant calling. When compared to commercially available methods, our approach yielded a 50-100% increase in library complexity with significantly improved sensitivity to <1% variants. We also obtained 100% specificity using duplexed UMI correction, which removed all false-positive calls. To highlight clinical utility, we extended our study to cfDNA samples with inputs of 5-25 ng and MAFs down to 1%, and FFPE DNA samples with inputs of 25-100 ng and MAFs down to 1%. Citation Format: Ushati Das Chakravarty, Zac Zwirko, Yu Zheng, Madelyn Light, Kevin Lai, Keith Bryan, Scott Rose, Yun Bao, Mirna Jarosz, Caifu Chen. Detection of low-frequency variants from highly degraded DNA samples using a novel library preparation method [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 430.

DNA methylation patterns are epigenetic modifications with direct implications in gene expression and chromatin structure regulation. Altered DNA methylation has been reported in various human cancers. The methylation profile of cell-free DNA (cfDNA) from plasma can be exploited to detect and diagnose tissue pathologies and is therefore of great diagnostic interest. Due to limitations of existing NGS library preparations, we present a new workflow, that integrates Unique Molecular Identifier (UMI) based error correction and optimizes library preparation and target enrichment. This workflow incorporates an engineered mutant ligase and proprietary methylated adapters that together prevent chimeras, suppress dimer-formation, and maximize conversion. Our library preparation provides >80% unique mapping efficiency and high conversion efficiency which creates superior sensitivity and specificity for detecting epigenetic signatures from a wide range of inputs (1-250 ng) and samples, including genomic DNA, FFPE DNA and cfDNA. This workflow is suitable for both genome-wide and targeted methylation sequencing. We implemented the target methyl-seq workflow to distinguish between fully methylation and hemimethylation on only one strand of the DNA by ligating in-line UMIs prior to target enrichment, followed by bisulfite conversion and PCR. Using a custom panel for targeted methylation sequencing, we detected >60% of CpG methylation in normal human samples and >95% of CpG methylation in in vitro methylated HCT116 samples. Employing ultra-deep sequencing to an average target depth of 10,000X followed by double-stranded consensus building analysis enables accurate low frequency methylation and hemimethylation detection. The studies presented here offer tools to advance epigenetics research. Citation Format: Hsiao-Yun Huang, Ushati Das Chakravarty, Kevin Lai, Timothy Barnes, Tzu-Chun Chen, Jessica Sheu, Ramses Lopez, Karissa Scott, Lynette Lewis, Anastasia Potts. Identification of symmetric methylation and hemimethylation patterns with optimal panel design, library preparation, and error correction [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 142.

Demonstrate performance of a complete automation and reagent workflow for analysis of cfDNA from bodily fluids. The efficient extraction of cfDNA from bodily fluids is a unique challenge due to the very low concentrations of nucleic acid. The extraction process along with library preparation is a laborious workflow, where human variability can lead to increased variability in the downstream analysis. Integrated DNA Technology (IDT) and Beckman Coulter (BC) have teamed up to provide a complete automation and reagent workflow for analysis of low frequency variants in cfDNA. The Apostle MiniMax™ High Efficiency Isolation Kit from BC provides complex, utilized magnetic nanoparticles to effectively capture cfDNA. IDT's library prep kit utilizes novel chemistry to maximize conversion, suppress adapter-dimer formation, reduce chimera rates, and facilitate double strand consensus analysis to call ultra-low frequency variants. Finally, IDT's xGen™ hybrid capture products maintain high library diversity and on-target rates to enable low frequency variant calling regardless of panel size. The Biomek i5 and i7 Hybrid workstations bring out the best performance from these reagents. The Biomek NGS workstations protocol is written with a modular design with safe stop points, making it customizable for each lab. The automated protocol uses Beckman's Demonstrated Method Interface tools which include: Biomek Method Launcher to run the method without going into Biomek software, Method Options Selector to choose the run parameters with a user friendly interface, Guided labware Setup to set the deck with labware based on the run parameters, DeckOptix Final Check software to help reduce deck setup errors. We demonstrate the performance of this complete workflow with a range of plasma inputs (4-8 mL). Using control samples with known variant frequencies, the workflow yields high library complexity, 100% positive predictive value, and reliable detection of <0.5% mutant allele frequency variants. With real cfDNA, the workflow demonstrates both high cfDNA and sequencing library yields along with high library complexity. The combination of these reagents on the Biomek workstations provides a robust and reproducible solution for the analysis of cfDNA. Citation Format: Nicole Roseman, Shilpa Parakh, Hsiao-Yun Huang, Kevin Lai, Timothy Barnes, Lyn Lewis, Ushati Das Chakravarty, Anastasia Potts, Alisa Jackson, Amy Yoder, Jessica Sheu, Tzu-Chun Chen. Improved conversion in extraction, library construction, and capture improve sensitivity for variants in liquid biopsy samples [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5863.