Performance characterization of PCR-free whole genome sequencing for clinical diagnosis

Zhou, Guiju; Zhou, Meizhen; Zeng, Fanwei; Zhang, Ningzhi; Sun, Yan; Qiao, Zhihong; Guo, Xueqin; Zhou, Shihao; Yun, Guojun; Xie, Jiansheng; Wang, Xiaodan; Liu, Fengxia; Fan, Chunna; Wang, Yaoshen; Fang, Zhonghai; Tian, Zhongming; Dai, Wentao; Sun, Jun; Peng, Zhiyu; Song, Lijie

doi:10.1097/md.0000000000028972

Cited by 7 publications

(5 citation statements)

References 23 publications

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“…In general, DNA of reference samples (Coriell, Camden, NJ) and clinical samples with known variants (Additional file 1 : Table S1) were first extracted using the MagPure Tissue & Blood DNA KF Kit (Magen, China). Subsequently, one microgram of DNA was used to generate paired end reads of 150 bp/100 bp according to the PCR-free library preparation protocols and sequencing protocols [ 13 ]. The bioinformatics analysis pipeline included 4 sections for the detection of potential variants (Fig.…”

Section: Methodsmentioning

confidence: 99%

“…Some parameters (such as DNA input, read length and library preparation) may affect the performance of WGS and ultimately influence variation detection sensitivity. Our previous reports showed that PCR-free WGS with 1 µg DNA input exhibited a better depth of coverage and genotype quality distribution than PCR-based WGS with differing DNA inputs [ 13 ]. With respect to the depth of coverage (DP), a mean depth of 30–50X is the most widely used mean DP for WGS [ 6 , 14 ].…”

Section: Methodsmentioning

confidence: 99%

“…In general, WGS of all samples was performed with a modified protocol using the MGISEQ-2000 platform [ 13 ]. First, the quality of the genomic DNA for all the samples was assessed using Qubit (Thermo Fisher Scientific) and gel electrophoresis.…”

Section: Methodsmentioning

confidence: 99%

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Test development, optimization and validation of a WGS pipeline for genetic disorders

Yang

Sun

et al. 2023

BMC Med Genomics

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Background With advances in massive parallel sequencing (MPS) technology, whole-genome sequencing (WGS) has gradually evolved into the first-tier diagnostic test for genetic disorders. However, deployment practice and pipeline testing for clinical WGS are lacking. Methods In this study, we introduced a whole WGS pipeline for genetic disorders, which included the entire process from obtaining a sample to clinical reporting. All samples that underwent WGS were constructed using polymerase chain reaction (PCR)-free library preparation protocols and sequenced on the MGISEQ-2000 platform. Bioinformatics pipelines were developed for the simultaneous detection of various types of variants, including single nucleotide variants (SNVs), insertions and deletions (indels), copy number variants (CNVs) and balanced rearrangements, mitochondrial (MT) variants, and other complex variants such as repeat expansion, pseudogenes and absence of heterozygosity (AOH). A semiautomatic pipeline was developed for the interpretation of potential SNVs and CNVs. Forty-five samples (including 14 positive commercially available samples, 23 laboratory-held positive cell lines and 8 clinical cases) with known variants were used to validate the whole pipeline. Results In this study, a whole WGS pipeline for genetic disorders was developed and optimized. Forty-five samples with known variants (6 with SNVs and Indels, 3 with MT variants, 5 with aneuploidies, 1 with triploidy, 23 with CNVs, 5 with balanced rearrangements, 2 with repeat expansions, 1 with AOHs, and 1 with exon 7–8 deletion of SMN1 gene) validated the effectiveness of our pipeline. Conclusions This study has been piloted in test development, optimization, and validation of the WGS pipeline for genetic disorders. A set of best practices were recommended using our pipeline, along with a dataset of positive samples for benchmarking.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Test development, optimization and validation of a WGS pipeline for genetic disorders

Yang

Sun

et al. 2023

BMC Med Genomics

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“…Historically, WGS required a DNA amplification step, but with newer protocols this step is no longer needed. Omission of the amplification step eliminates the PCR-bias and provides a more uniform coverage and quality [ 12 ]. The library is generated by fragmenting the high molecular DNA followed by ligation of adapters that will bind to the linker DNA on the chip surface.…”

Section: Whole Genome Sequencingmentioning

confidence: 99%

Whole genome sequencing in clinical practice

Bagger,

Borgwardt,

Jespersen

et al. 2024

BMC Med Genomics

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Whole genome sequencing (WGS) is becoming the preferred method for molecular genetic diagnosis of rare and unknown diseases and for identification of actionable cancer drivers. Compared to other molecular genetic methods, WGS captures most genomic variation and eliminates the need for sequential genetic testing. Whereas, the laboratory requirements are similar to conventional molecular genetics, the amount of data is large and WGS requires a comprehensive computational and storage infrastructure in order to facilitate data processing within a clinically relevant timeframe. The output of a single WGS analyses is roughly 5 MIO variants and data interpretation involves specialized staff collaborating with the clinical specialists in order to provide standard of care reports. Although the field is continuously refining the standards for variant classification, there are still unresolved issues associated with the clinical application. The review provides an overview of WGS in clinical practice - describing the technology and current applications as well as challenges connected with data processing, interpretation and clinical reporting.

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“…Another reason for higher accuracy is the improvement in laboratory technologies. For example, it is nowadays standard to work with a PCR-free library preparation protocol, which outperforms PCR-based protocols (Zhou, Zhou, and Zeng 2022).…”

Section: Figure 18mentioning

confidence: 99%

Biostatistical Aspects of Whole Genome Sequencing Studies: Preprocessing and Quality Control

Betschart,

Riccio,

Aguilera‐Garcia

et al. 2024

Biometrical J

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Rapid advances in high‐throughput DNA sequencing technologies have enabled large‐scale whole genome sequencing (WGS) studies. Before performing association analysis between phenotypes and genotypes, preprocessing and quality control (QC) of the raw sequence data need to be performed. Because many biostatisticians have not been working with WGS data so far, we first sketch Illumina's short‐read sequencing technology. Second, we explain the general preprocessing pipeline for WGS studies. Third, we provide an overview of important QC metrics, which are applied to WGS data: on the raw data, after mapping and alignment, after variant calling, and after multisample variant calling. Fourth, we illustrate the QC with the data from the GENEtic SequencIng Study Hamburg–Davos (GENESIS‐HD), a study involving more than 9000 human whole genomes. All samples were sequenced on an Illumina NovaSeq 6000 with an average coverage of 35× using a PCR‐free protocol. For QC, one genome in a bottle (GIAB) trio was sequenced in four replicates, and one GIAB sample was successfully sequenced 70 times in different runs. Fifth, we provide empirical data on the compression of raw data using the DRAGEN original read archive (ORA). The most important quality metrics in the application were genetic similarity, sample cross‐contamination, deviations from the expected Het/Hom ratio, relatedness, and coverage. The compression ratio of the raw files using DRAGEN ORA was 5.6:1, and compression time was linear by genome coverage. In summary, the preprocessing, joint calling, and QC of large WGS studies are feasible within a reasonable time, and efficient QC procedures are readily available.

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Performance characterization of PCR-free whole genome sequencing for clinical diagnosis

Cited by 7 publications

References 23 publications

Test development, optimization and validation of a WGS pipeline for genetic disorders

Test development, optimization and validation of a WGS pipeline for genetic disorders

Whole genome sequencing in clinical practice

Biostatistical Aspects of Whole Genome Sequencing Studies: Preprocessing and Quality Control

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