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Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
Published on: April 11, 2016
Performance Evaluation of Whole-Genome Amplification Platforms for Clinical Next-Generation Sequencing with Minimal
Namsoo Kim1,2, Hyeon Ah Lee3, Miri Park1
1Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.
Background:
Next-generation sequencing (NGS) is increasingly applied in clinical diagnostics; however, standard workflows are frequently challenged by insufficient DNA yields in diverse clinical scenarios. Although whole-genome amplification (WGA) is used to overcome this limitation, comparative performance data on WGA kits based on different amplification mechanisms under low-input conditions remain scarce.
Methods:
We systematically evaluated four commercial WGA platforms: REPLI-g (Qiagen), which employs multiple displacement amplification; PicoPLEX (Takara Bio) and SurePlex (Illumina), which utilize modified multiple annealing and looping-based amplification cycles (MALBAC); and ResolveDNA (BioSkryb Genomics), which uses primary template-directed amplification (PTA), using 100-pg and 1-ng DNA input. Performance was assessed by examining allelic dropout (ADO), chimerism, copy number variation (CNV), and the total DNA yield.
Results:
ResolveDNA showed the lowest ADO rates across input levels, whereas PicoPLEX offered the most accurate quantification for chimerism and CNV. REPLI-g had the highest DNA yield but exhibited marked amplification bias and ADO under ultra-low-input conditions. SurePlex demonstrated intermediate performance across all metrics. PicoPLEX and SurePlex showed consistent CNV detection and chimerism accuracy, whereas PTA-based ResolveDNA better preserved allelic balance.
Conclusions:
Each platform demonstrated specific strengths and limitations depending on analytical endpoints. Modified MALBAC-based platforms can perform optimally when quantitative accuracy is critical, such as in chimerism or CNV analysis, whereas PTA-based WGA can be preferred when allelic fidelity is essential. Our findings can help guide platform selection tailored to specific clinical applications using low-input NGS, including preimplantation testing or cell-free DNA analysis.

