Abstract
BackgroundTarget enrichment is a critical component of targeted deep next-generation sequencing for the cost-effective and sensitive detection of mutations, which is predominantly performed by either hybrid selection or PCR. Despite the advantages of efficient enrichment, PCR-based methods preclude the identification of PCR duplicates and their subsequent removal. Recently, this limitation was overcome by assigning a unique molecular identifier(UMI) to each template molecule. Currently, several commercial library construction kits based on PCR enrichment are available for UMIs, but there have been no systematic studies to compare their performances. In this study, we evaluated and compared the performances of five commercial library kits from four vendors: the Archer® Reveal ctDNA™ 28 Kit, NEBNext Direct® Cancer HotSpot Panel, Nugen Ovation® Custom Target Enrichment System, Qiagen Human Comprehensive Cancer Panel(HCCP), and Qiagen Human Actionable Solid Tumor Panel(HASTP).ResultsWe evaluated and compared the performances of the five kits using 50 ng of genomic DNA for the library construction in terms of the library complexity, coverage uniformity, and errors in the UMIs. While the duplicate rates for all kits were dramatically decreased by identifying unique molecules with UMIs, the Qiagen HASTP achieved the highest library complexity based on the depth of unique coverage indicating superb library construction efficiency. Regarding the coverage uniformity, the kits from Nugen and NEB performed the best followed by the kits from Qiagen. We also analyzed the UMIs, including errors, which allowed us to adjust the depth of unique coverage and the length required for sufficient complexity. Based on these comparisons, we selected the Qiagen HASTP for further performance evaluations. The targeted deep sequencing method based on PCR target enrichment combined with UMI tagging sensitively detected mutations present at a frequency as low as 1% using 6.25 ng of human genomic DNA as the starting material.ConclusionThis study is the first systematic evaluation of commercial library construction kits for PCR-based targeted deep sequencing utilizing UMIs. Because the kits displayed significant variability in different quality metrics, our study offers a practical guideline for researchers to choose appropriate options for PCR-based targeted sequencing and useful benchmark data for evaluating new kits.
Highlights
Target enrichment is a critical component of targeted deep next-generation sequencing for the costeffective and sensitive detection of mutations, which is predominantly performed by either hybrid selection or PCR
We examined the mean depth by increasing the size of the target regions from 50 to 250 base pairs adjacent to the 3′ end of each primer, as the mean depth of unique coverage can vary depending on how large the regions defined as target regions were
When we examined the distribution of the read depth of each kit using data sets adjusted to 5000× by in silico down-sampling, the depth distributions from the Nugen, NEB, and Qiagen Human Comprehensive Cancer Panel (HCCP) kits were more uniform compared to the other kits (Additional file 5)
Summary
Target enrichment is a critical component of targeted deep next-generation sequencing for the costeffective and sensitive detection of mutations, which is predominantly performed by either hybrid selection or PCR. Despite the advantages of efficient enrichment, PCR-based methods preclude the identification of PCR duplicates and their subsequent removal This limitation was overcome by assigning a unique molecular identifier(UMI) to each template molecule. While the detection of low variant allele fractions (VAFs) requires the sequencing of a sufficient number of molecules, low quantity and quality of DNA extracted from clinical tissue samples often pose obstacles. The detection of low VAF variants in cfDNA samples is challenging because high complexity sequencing libraries must be generated using a limited amount of input DNA. In this regard, it is critical to construct sequencing libraries with a high recovery rate of cfDNA molecules
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