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Selective multiplexed enrichment for the detection and quantitation of low-fraction DNA variants via low-depth sequencing

Nature Biomedical Engineering volume 5, pages 690–701 (2021)Cite this article

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Abstract

DNA sequence variants with allele fractions below 1% are difficult to detect and quantify by sequencing owing to intrinsic errors in sequencing-by-synthesis methods. Although molecular-identifier barcodes can detect mutations with a variant-allele frequency (VAF) as low as 0.1% using next-generation sequencing (NGS), sequencing depths of over 25,000× are required, thus hampering the detection of mutations at high sensitivity in patient samples and in most samples used in research. Here we show that low-frequency DNA variants can be detected via low-depth multiplexed NGS after their amplification, by a median of 300-fold, using polymerase chain reaction and rationally designed ‘blocker’ oligonucleotides that bind to the variants. Using an 80-plex NGS panel and a sequencing depth of 250×, we detected single nucleotide polymorphisms with a VAF of 0.019% and contamination in human cell lines at a VAF as low as 0.07%. With a 16-plex NGS panel covering 145 mutations across 9 genes involved in melanoma, we detected low-VAF mutations (0.2–5%) in 7 out of the 19 samples of freshly frozen tumour biopsies, suggesting that tumour heterogeneity could be notably higher than previously recognized.

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Fig. 1: Allele enrichment with mBDA enables the detection of rare variants using low-depth sequencing.
Fig. 2: Quantitation of variant VAFs based on observed VRF values from mBDA libraries.
Fig. 3: Detection and quantitation of variants with a low VAF using mBDA NGS.
Fig. 4: Determination of contaminant identity based on mBDA NGS data.
Fig. 5: Detection of cell-line contamination using mBDA with qPCR.
Fig. 6: Validation of mBDA panels on clinical samples.

Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. All requests for raw and analysed data will be reviewed by the Legal Department of Rice University to verify whether the request is subject to any intellectual property or confidentiality constraints. Requests for patient-related data not included in the paper will not be considered. Data can be shared for non-commercial research purposes via a material transfer agreement.

Code availability

All requests for code will be reviewed by the Legal Department of Rice University to verify whether the request is subject to any intellectual property or confidentiality constraints. Custom code can be shared for non-commercial research purposes via a material transfer agreement.

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Acknowledgements

This work was supported by NIH grant nos R01CA203964 and R01CA233364, and CPRIT grant no. RP180147 to D.Y.Z. We thank J. Nie for proofreading assistance and G. Bao for providing access to his BioRad QX200 digital droplet PCR instrument. We thank Nuprobe for providing early access VarMap NSCLC kits for cfDNA testing.

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Authors and Affiliations

  1. Department of Bioengineering, Rice University, Houston, TX, USA

    Ping Song, Sherry X. Chen, Yan Helen Yan, Lauren Y. Cheng, Peng Dai & David Yu Zhang

  2. Systems, Synthetic, and Physical Biology, Rice University, Houston, TX, USA

    Yan Helen Yan & David Yu Zhang

  3. NuProbe USA, Houston, TX, USA

    Alessandro Pinto

  4. Department of Therapeutic Radiology, Yale University, New Haven, CT, USA

    Abhijit A. Patel

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Contributions

P.S. and D.Y.Z. conceived the project. P.S., S.X.C. and Y.H.Y. performed the mBDA sequence design for the cell-line contamination panels. L.Y.C. and P.D. performed the mBDA sequence design for the cancer panels. A.A.P. provided clinical cfDNA samples and performed the comparison deep sequencing experiments. P.S. and Y.H.Y. performed experiments and analysed qPCR data. P.S. and A.P. performed NGS experiments. P.S., S.X.C. and D.Y.Z. analysed the NGS data. P.S. and D.Y.Z. wrote the manuscript with input from all authors.

Corresponding author

Correspondence to David Yu Zhang.

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Competing interests

There are patents pending on the BDA (patent number EP3146080B1) and mBDA (patent number WO2019164885A1) methods used in this work. P.S., S.X.C., L.Y.C. and P.D. declare competing interests in the form of consulting for Nuprobe USA. A.A.P. declares a competing interest in the form of consulting for Nuprobe USA as well as consulting for and equity ownership in Binary Genomics. D.Y.Z. declares a competing interest in the form of consulting for and equity ownership in Nuprobe and Torus Biosystems as well as consulting for Avenge Bio.

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Supplementary information

Supplementary Information

Supplementary methods, figures and tables.

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Supplementary Dataset

Design of mBDA for alleles of 80 SNPs.

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Song, P., Chen, S.X., Yan, Y.H. et al. Selective multiplexed enrichment for the detection and quantitation of low-fraction DNA variants via low-depth sequencing. Nat Biomed Eng 5, 690–701 (2021). https://doi.org/10.1038/s41551-021-00713-0

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