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Low-pass genome sequencing: a validated method in clinical cytogenetics

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Abstract

Clinically significant copy-number variants (CNVs) known to cause human diseases are routinely detected by chromosomal microarray analysis (CMA). Recently, genome sequencing (GS) has been introduced for CNV analysis; however, sequencing depth (determined by sequencing read-length and read-amount) is a variable parameter across different laboratories. Variating sequencing depths affect the CNV detection resolution and also make it difficult for cross-laboratory referencing or comparison. In this study, by using data from 50 samples with high read-depth GS (30×) and the reported clinically significant CNVs, we first demonstrated the optimal read-amount and the most cost-effective read-length for CNV analysis to be 15 million reads and single-end 50 bp (equivalent to a read-depth of 0.25-fold), respectively. In addition, we showed that CNVs at mosaic levels as low as 30% are readily detected, furthermore, CNVs larger than 2.5 Mb are also detectable at mosaic levels as low as 20%. Herein, by conducting a retrospective back-to-back comparison study of low-pass GS versus routine CMA for 532 prenatal, miscarriage, and postnatal cases, the overall diagnostic yield was 22.4% (119/532) for CMA and 23.1% (123/532) for low-pass GS. Thus, the overall relative improvement of the diagnostic yield by low-pass GS versus CMA was ~ 3.4% (4/119). Identification of cryptic and clinically significant CNVs among prenatal, miscarriage, and postnatal cases demonstrated that CNV detection at higher resolutions is warranted for clinical diagnosis regardless of referral indications. Overall, our study supports low-pass GS as the first-tier genetic test for molecular cytogenetic testing.

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Availability of data and material

The genome sequencing data in this study have been made available on the CNGB Nucleotide Sequence Archive (CNSA: https://db.cngb.org/cnsa) under the accession number CNP0000901. Code availability: All relative programs are available at https://sourceforge.net/projects/increment-ratio-of-coverage-v2/files/Increment_Ratio_of_Coverage_V2.0.tar.gz/download.

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Funding

This project is supported by the National Natural Science Foundation of China (31801042, 81741004 and 81741009), the Health and Medical Research Fund (04152666) and the Health Department of Guangxi Province (Z20190782). Zirui Dong thanks the Hong Kong Obstetrical & Gynaecological Trust Fund for the support.

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Author notes

  1. Matthew Hoi Kin Chau, Huilin Wang and Yunli Lai contributed equally.

Authors and Affiliations

  1. Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China

    Matthew Hoi Kin Chau, Yanyan Zhang, Tak Yeung Leung, Jacqueline Pui Wah Chung, Yvonne K. Kwok, Kwong Wai Choy & Zirui Dong

  2. Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China

    Matthew Hoi Kin Chau, Yanyan Zhang, Zihan Chen, Tak Yeung Leung, Yvonne K. Kwok, Kwong Wai Choy & Zirui Dong

  3. Hong Kong Hub of Paediatric Excellence, The Chinese University of Hong Kong, Hong Kong, China

    Matthew Hoi Kin Chau, Shuk Ching Chong, Kwong Wai Choy & Zirui Dong

  4. Department of Center Laboratory, Maternal-Fetal Medicine Institute, Shenzhen Key Laboratory of Birth Defects Research, Birth Defects Prevention Research and Transformation Team, Baoan Maternity and Child Health Hospital Affiliated to Jinan University School of Medicine, Shenzhen, 518100, China

    Huilin Wang, Yanfang Wang, Yuanfang Zhu & Likuan Xiong

  5. Birth Defects Prevention and Control Institute of Guangxi Zhuang Autonomous Region, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530000, Guangxi, China

    Yunli Lai, Fuben Xu, Yanqing Tang & Weihong Wei

  6. Genetic and Metabolic Central Laboratory, Guangxi Zhuang Autonomous Region Women and Children Care Hospital, Nanning, 530000, Guangxi, China

    Yunli Lai, Fuben Xu, Yanqing Tang & Weihong Wei

  7. The Chinese University of Hong Kong-Baylor College of Medicine Joint Center For Medical Genetics, Hong Kong, China

    Tak Yeung Leung, Shuk Ching Chong & Kwong Wai Choy

  8. Department of Paediatrics, The Chinese University of Hong Kong, Hong Kong, China

    Shuk Ching Chong

Authors
  1. Matthew Hoi Kin Chau
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  2. Huilin Wang
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  3. Yunli Lai
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  4. Yanyan Zhang
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  5. Fuben Xu
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  16. Weihong Wei
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  17. Zirui Dong
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Contributions

ZD, MHKC, HW, YL, TYL, YK, LX, YZ, WW, and KWC designed the study. HW, YL, TYL, JPWC, SCC, YZ, LX and WW collected the samples and followed up. MHKC, HW, YL, FX, YT, YW and ZC performed CMA and low-pass GS. ZD, MHKC and YK performed the analysis and data interpretation. MHKC, HW and YL conducted the validation. ZD, MHKC, HW, YL, and KWC wrote the manuscript.

Corresponding author

Correspondence to Zirui Dong.

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The study was approved by the institutional review boards of each collaborative site. Written consent for sample storage and genetic analyses of peripheral blood and invasive diagnostic samples was obtained from each participant.

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Chau, M.H.K., Wang, H., Lai, Y. et al. Low-pass genome sequencing: a validated method in clinical cytogenetics. Hum Genet 139, 1403–1415 (2020). https://doi.org/10.1007/s00439-020-02185-9

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