Characterization of background noise in capture-based targeted sequencing data

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Abstract

Background: Targeted deep sequencing is increasingly used to detect low-allelic fraction variants; it is therefore essential that errors that constitute baseline noise and impose a practical limit on detection are characterized. In the present study, we systematically evaluate the extent to which errors are incurred during specific steps of the capture-based targeted sequencing process. Results: We removed most sequencing artifacts by filtering out low-quality bases and then analyze the remaining background noise. By recognizing that plasma DNA is naturally fragmented to be of a size comparable to that of mono-nucleosomal DNA, we were able to identify and characterize errors that are specifically associated with acoustic shearing. Two-thirds of C:G>A:T errors and one quarter of C:G>G:C errors were attributed to the oxidation of guanine during acoustic shearing, and this was further validated by comparative experiments conducted under different shearing conditions. The acoustic shearing step also causes A>G and A>T substitutions localized to the end bases of sheared DNA fragments, indicating a probable association of these errors with DNA breakage. Finally, the hybrid selection step contributes to one-third of the remaining C:G>A:T and one-fifth of the C>T errors. Conclusions: The results of this study provide a comprehensive summary of various errors incurred during targeted deep sequencing, and their underlying causes. This information will be invaluable to drive technical improvements in this sequencing method, and may increase the future usage of targeted deep sequencing methods for low-allelic fraction variant detection.

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Park, G., Park, J. K., Shin, S. H., Jeon, H. J., Kim, N. K. D., Kim, Y. J., … Park, D. (2017). Characterization of background noise in capture-based targeted sequencing data. Genome Biology, 18(1). https://doi.org/10.1186/s13059-017-1275-2

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