Evidence map›Paper›PMID 30871467›Full record

ArticleBMC genomics2019

Performance evaluation of commercial library construction kits for PCR-based targeted sequencing using a unique molecular identifier.

Jongsuk Chung, Ki-Wook Lee, Chung Lee, Seung-Ho Shin, Sungkyu Kyung, Hyo-Jeong Jeon, Sook-Young Kim, Eunjung Cho, Chang Eun Yoo, Dae-Soon Son and 2 more

Abstract readEvaluation Study
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

12 authors.

Jongsuk ChungSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, South Korea.
Ki-Wook LeeSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, South Korea.
Chung LeeSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, South Korea.
Seung-Ho ShinSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, South Korea.
Sungkyu KyungDepartment of Bioinformatics and Life Science, Soongsil University, Seoul, 06978, South Korea.
Hyo-Jeong JeonSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, South Korea.
Sook-Young KimSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, South Korea.
Eunjung ChoSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, South Korea.
Chang Eun YooSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, South Korea.
Dae-Soon SonSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, South Korea.
Woong-Yang ParkSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, South Korea. woongyang.park@samsung.com.
Donghyun ParkSamsung Genome Institute, Samsung Medical Center, Seoul, 06351, South Korea. dh37.park@samsung.com.ORCID http://orcid.org/0000-0002-7946-6924

Funding

National Institute of Food and Drug Safety Evaluation 16173MFDS004National Research Foundation of Korea 2017M3A9G5060264National Research Foundation of Korea 2018M3C9A6017315National Research Foundation of Korea 2018R1C1B6003724
6 · The paper itself

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.

Indexed as

Gene LibraryBiomarkersDNAHigh-Throughput Nucleotide SequencingHumansPolymerase Chain ReactionReagent Kits, DiagnosticBiomarkersDNAReagent Kits, DiagnosticComparisonEfficiencyEvaluationNGSPCR-basedUMI

Identifiers

PMID30871467
PMCPMC6416880

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.