Evidence map›Paper›PMID 41277018›Full record

ArticleAnnals of laboratory medicine2026

Performance Evaluation of Whole-Genome Amplification Platforms for Clinical Next-Generation Sequencing with Minimal Nucleic Acid Input.

Namsoo Kim, Hyeon Ah Lee, Miri Park, Yehyun Kang, Dongju Won, Seung-Tae Lee, Jong Rak Choi, Yu Jin Park, Saeam Shin

Abstract readEvaluation Study
In one paragraph

Article in Annals of laboratory medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Namsoo KimDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-1098-4782
Hyeon Ah LeeDivision of Zoonotic and Vector Borne Disease Research, Center for Infectious Disease Research, Korea National Institute of Health, Cheongju, Korea.ORCID https://orcid.org/0000-0002-8164-1947
Miri ParkDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-7689-0781
Yehyun KangGraduate School of Medical Science, Brain Korea 21PLUS Project, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0002-4888-1356
Dongju WonDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-0084-0216
Seung-Tae LeeDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-1047-1415
Jong Rak ChoiDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-0608-2989
Yu Jin ParkDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-8673-5256
Saeam ShinDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-1501-3923

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

DNAHigh-Throughput Nucleotide SequencingNucleic Acid Amplification TechniquesAllelesDNA Copy Number VariationsGenome, HumanHumansDNAAllelic dropoutChimerismCopy number variationNext-generation sequencingWhole-genome amplification

Identifiers

PMID41277018
PMCPMC13259937

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.