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Zhou G, Zhou M, Zeng F, Zhang N, Sun Y, Qiao Z, Guo X, Zhou S, Yun G, Xie J, Wang X, Liu F, Fan C, Wang Y, Fang Z, Tian Z, Dai W, Sun J, Peng Z, Song L. Performance characterization of PCR-free whole genome sequencing for clinical diagnosis. Medicine (Baltimore) 2022; 101:e28972. [PMID: 35451387 PMCID: PMC8913097 DOI: 10.1097/md.0000000000028972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 02/10/2022] [Indexed: 01/04/2023] Open
Abstract
To evaluate the performance of polymerase chain reaction (PCR)-free whole genome sequencing (WGS) for clinical diagnosis, and thereby revealing how experimental parameters affect variant detection.Five NA12878 samples were sequenced using MGISEQ-2000. NA12878 samples underwent WGS with differing deoxyribonucleic acid (DNA) input and library preparation protocol (PCR-based vs PCR-free protocols for library preparation). The depth of coverage and genotype quality of each sample were compared. The performance of each sample was measured for sensitivity, coverage of depth and breadth of coverage of disease-related genes, and copy number variants. We also developed a systematic WGS pipeline (PCR-free) for the analysis of 11 clinical cases.In general, NA12878-2 (PCR-free WGS) showed better depth of coverage and genotype quality distribution than NA12878-1 (PCR-based WGS). With a mean depth of ∼40×, the sensitivity of homozygous and heterozygous single nucleotide polymorphisms (SNPs) of NA12878-2 showed higher sensitivity (>99.77% and >99.82%) than NA12878-1, and positive predictive value exceeded 99.98% and 99.07%. The sensitivity and positive predictive value of homozygous and heterozygous indels for NA12878-2 (PCR-free WGS) showed great improvement than NA128878-1. The breadths of coverage for disease-related genes and copy number variants are slightly better for samples with PCR-free library preparation protocol than the sample with PCR-based library preparation protocol. DNA input also influences the performance of variant detection in samples with PCR-free WGS. All the 19 previously confirmed variants in 11 clinical cases were successfully detected by our WGS pipeline (PCR free).Different experimental parameters may affect variant detection for clinical WGS. Clinical scientists should know the range of sensitivity of variants for different methods of WGS, which would be useful when interpreting and delivering clinical reports.
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Affiliation(s)
- Guiju Zhou
- Department Obstetrics and Gynecology, The Second Affiliated Hospital, Anhui Medical University, Hefei, China
| | | | - Fanwei Zeng
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
- Department of Biology, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Ningzhi Zhang
- Fuyang People's Hospital, 63 Luci Street, Fuyang, Anhui Province, China
| | - Yan Sun
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Zhihong Qiao
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Xueqin Guo
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, Wuhan, China
| | - Shihao Zhou
- Department of Genetics and Eugenics, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal University, Changsha, Hunan Province, China
| | - Guojun Yun
- Rehabilitation Ward, Shenzhen Children's Hospital, 7019 Yitian Road, Futian District, Shenzhen, Guangdong Province, China
| | - Jiansheng Xie
- Department of Prenatal Diagnosis, The University of Hongkong Shenzhen Hospital, 1 Haiyuan one Road, Shenzhen, Guangdong Province, China
| | - Xiaodan Wang
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Fengxia Liu
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Chunna Fan
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Yaoshen Wang
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Zhonghai Fang
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Zhongming Tian
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Wentao Dai
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Jun Sun
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Zhiyu Peng
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Lijie Song
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Bacterial Interactions and Evolution Group, Bioengineering, Technical University of Denmark, Kongens Lyngby, Denmark
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