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Low-pass genome sequencing: a validated method in clinical cytogenetics.
Chau, Matthew Hoi Kin; Wang, Huilin; Lai, Yunli; Zhang, Yanyan; Xu, Fuben; Tang, Yanqing; Wang, Yanfang; Chen, Zihan; Leung, Tak Yeung; Chung, Jacqueline Pui Wah; Kwok, Yvonne K; Chong, Shuk Ching; Choy, Kwong Wai; Zhu, Yuanfang; Xiong, Likuan; Wei, Weihong; Dong, Zirui.
Affiliation
  • Chau MHK; Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Wang H; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
  • Lai Y; Hong Kong Hub of Paediatric Excellence, The Chinese University of Hong Kong, Hong Kong, China.
  • Zhang Y; 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.
  • Xu F; 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.
  • Tang Y; Genetic and Metabolic Central Laboratory, Guangxi Zhuang Autonomous Region Women and Children Care Hospital, Nanning, 530000, Guangxi, China.
  • Wang Y; Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Chen Z; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
  • Leung TY; 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.
  • Chung JPW; Genetic and Metabolic Central Laboratory, Guangxi Zhuang Autonomous Region Women and Children Care Hospital, Nanning, 530000, Guangxi, China.
  • Kwok YK; 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.
  • Chong SC; Genetic and Metabolic Central Laboratory, Guangxi Zhuang Autonomous Region Women and Children Care Hospital, Nanning, 530000, Guangxi, China.
  • Choy KW; 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.
  • Zhu Y; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
  • Xiong L; Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Wei W; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
  • Dong Z; The Chinese University of Hong Kong-Baylor College of Medicine Joint Center For Medical Genetics, Hong Kong, China.
Hum Genet ; 139(11): 1403-1415, 2020 Nov.
Article in En | MEDLINE | ID: mdl-32451733
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome, Human / Genetic Testing / Cytogenetic Analysis / Whole Genome Sequencing Type of study: Observational_studies / Prognostic_studies Limits: Female / Humans / Male / Pregnancy Language: En Journal: Hum Genet Year: 2020 Document type: Article Affiliation country: China Country of publication: Alemania

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome, Human / Genetic Testing / Cytogenetic Analysis / Whole Genome Sequencing Type of study: Observational_studies / Prognostic_studies Limits: Female / Humans / Male / Pregnancy Language: En Journal: Hum Genet Year: 2020 Document type: Article Affiliation country: China Country of publication: Alemania