Essential Elements for Establishing Clinical Next-generation Sequencing Testing

Kyoung-Jin Park; Woochang Lee; Sail Chun; Won-Ki Min

doi:10.3343/lmo.2019.9.2.37

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Park, Lee, Chun, and Min: Essential Elements for Establishing Clinical Next-generation Sequencing Testing

Original Article

Lab Med Online 2019;9(2):37-44.

Published online: 20 April 2019

DOI: https://doi.org/10.3343/lmo.2019.9.2.37

Essential Elements for Establishing Clinical Next-generation Sequencing Testing

Kyoung-Jin Park, M.D.¹, Woochang Lee, M.D.^2,, Sail Chun, M.D.², Won-Ki Min, M.D.²

¹Department of Laboratory Medicine and Biomedical Research Institute, Pusan National University Yangsan Hospital, Yangsan, Korea

²Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

Corresponding author: Woochang Lee, M.D., Ph.D. https://orcid.org/0000-0003-3956-6397 Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Korea Tel: +82-2-3010-4516, Fax: +82-2-478-0884, E-mail: wlee1@amc.seoul.kr

Received 3 April 2018 Revised 8 July 2018 Accepted 23 July 2018

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Over the past decade, next-generation sequencing (NGS) has evolved at an astonishing pace and has revolutionized clinical medicine as well as genomics research. The rapid advancements in NGS technologies have been accompanied by accumulating evidence of the analytical and clinical validity, and clinical utility of NGS. NGS is used worldwide. This review provides medical technicians and laboratory physicians with the essential elements for establishing clinical NGS testing. Here the authors briefly describe the advantages and drawbacks of currently available NGS platforms, potential sources of error in NGS workflow, and reference materials.

Keywords: Next-generation sequencing (NGS), Quality control (QC), Reference material (RM)

References

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Fig. 1.

Overall workflow of next-generation sequencing.

Table 1.

Summary of major next-generation sequencing

Manufacturer	Amplification	Chemistry	Detection	Error profile	URL
Illumina	Clonal (bridge amplification)	SBS (CRT)	Optical	<1%, Substitution error	https://www.illumina.com/
ThermoFisher (Ion Torrent)	Clonal (emulsion PCR)	SBS (SNA)	Non-optical	1%, Indels at homopolymers	http://www.thermofisher.com/us/en/ home/brands/ion-torrent.html
Pacific Bioscience	Single molecule	SBS (Real-time)	Optical	13% single pass, <1% circular consensus read, Indels	http://www.pacb.com/
Oxford Nanopore	Single molecule	Nanopore	Nanopore	∼12%, Indels	https://nanoporetech.com/
QIAGEN (GeneReader)	Clonal (emulsion PCR)	SBS	Optical	Similar to other SBS system	http://www.qiagen.com/

Abbreviations: PCR, polymerase chain reaction; SBS, sequencing by synthesis; CRT, cyclic reversible termination; SNA, single nucleotide addition; SBL, sequencing by ligation; indel, insertion/deletion. Manufacturer's data is directed to the URL.

Table 2.

Potential sources of error and quality control

	Error sources∗	Quality control and optimization^†
Sample preparation	∙ User errors (mislabeling)	∙ Specimen rejection criteria according to sample types
	∙ Low yield of nucleic acid	∙ OD 260/280, OD 230/280
	∙ Nucleic acid contamination (microorganism, xenograft)	∙ DNA/RNA integrity number
	∙ Low tumor cell fraction (heterogeneity)	∙ DNA integrity (gel image)
	∙ Nucleic acid degradation (FFPE)	∙ Tumor cell fraction (depending on depth of coverage)
Library construction	∙ User errors (carry-over, contamination)	∙ Size and concentration of fragmented DNA
	∙ Adapter dimers	∙ Size distribution of library
	∙ Index swab	∙ Library quantification and normalization
	∙ Low library complexity, PCR duplication	∙ Size selection
	∙ Capture bias (GC contents, repeating elements, pseudogenes, etc.)	∙ Length and match of index and barcode
	∙ Primer dimer, amplification errors, allele dropout	∙ Primer/probe: tiling design or rebalancing
	∙ Flow cell overloading/underloading	∙ Cluster density
Sequencing	∙ Decline in signal intensity	∙ Base call quality scores (Q-score)
	∙ Incorrect base incorporation	∙ Per base GC content
	∙ Sequence context (GC contents, homologous gene, homopolymers)	∙ Sequence length distribution
	∙ Platform-specific error	∙ Duplicate sequence
		∙ Per base N contents
		∙ Ti/Tv ratio
Bioinformatic analyses	∙ Low depth of coverage	∙ On-target coverage
	∙ Uneven of coverage	∙ Mapping rate
	∙ Misalignment	∙ Mapping quality
	∙ Strand bias	∙ Confirmation with orthogonal methods
	∙ Low concordances among different bioinformatics tools	∙ False positive and false negative rates
		∙ Quality trimming
		∙ Duplicate removal
		∙ Local realignment
		∙ Base quality score recalibration
		∙ Variant quality score recalibration

^∗ Some errors are often connected between precedent steps and subsequent steps;

^† Considering the inherent differences among NGS platforms, wet experiments, and bioinformatics pipelines, threshold or cutoff of quality metrics cannot be specifically defined. Abbreviations: FFPE, formalin-fixed paraffin-embedded; OD, optical density; Ti/Tv, transition/transversion.

Table 3.

Comparison of target enrichment methods

	Advantage	Disadvantage
Amplification	∙ Faster than hybridization	∙ High cost
	∙ Lower input DNA required	∙ Low throughput
		∙ Limited to a small number of targets
		∙ SNPs may interfere with primer binding (allele dropout)
		∙ Primer dimers
		∙ Non-specific amplification products
		∙ PCR amplification errors
		∙ Low library complexity
Hybridization	∙ More even coverage	∙ Higher input DNA requirements
	∙ Good reproducibility	∙ Regions with high GC or AT content: not captured optimally
	∙ Ability to detect some structural variants (fusion)	∙ Repetitive DNA elements: overrepresented
	∙ Large sections of DNA and large numbers of genes.	∙ Off-target capture
	∙ Accurate determination of depth of coverage and allele frequency by removal of PCR duplication

Characteristics are compared to each other.

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