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Related Experiment Video

Updated: Dec 20, 2025

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
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Low-pass genome sequencing: a validated method in clinical cytogenetics.

Matthew Hoi Kin Chau1,2,3, Huilin Wang4, Yunli Lai5,6

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

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|May 27, 2020
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Summary

Low-pass genome sequencing (GS) offers comparable diagnostic yield to chromosomal microarray analysis (CMA) for detecting copy-number variants (CNVs). This study identifies optimal parameters for low-pass GS, supporting its use as a primary genetic test.

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Area of Science:

  • Genetics
  • Genomics
  • Molecular Cytogenetics

Background:

  • Chromosomal microarray analysis (CMA) is standard for detecting clinically significant copy-number variants (CNVs).
  • Genome sequencing (GS) offers potential for CNV analysis, but variable sequencing depths hinder standardization and comparison.
  • Optimizing sequencing parameters is crucial for reliable CNV detection and cross-laboratory consistency.

Purpose of the Study:

  • To determine optimal sequencing read-amount and read-length for cost-effective CNV detection using low-pass genome sequencing (GS).
  • To assess the diagnostic performance of low-pass GS compared to CMA in a large cohort of clinical cases.
  • To establish low-pass GS as a potential first-tier genetic test for molecular cytogenetic diagnostics.

Main Methods:

  • Utilized high read-depth GS data (30×) from 50 samples to identify optimal read-amount (15 million reads) and read-length (single-end 50 bp).
  • Assessed detection limits for mosaic CNVs (down to 30% for 2.5 Mb CNVs).
  • Conducted a retrospective comparison of low-pass GS against routine CMA in 532 prenatal, miscarriage, and postnatal cases.

Main Results:

  • Optimal parameters for CNV detection were established as 15 million reads and single-end 50 bp reads (0.25× read-depth).
  • Low-pass GS detected mosaic CNVs down to 30% and larger CNVs (≥2.5 Mb) down to 20%.
  • Diagnostic yields were comparable: 22.4% for CMA versus 23.1% for low-pass GS, a 3.4% relative improvement for GS.

Conclusions:

  • Low-pass GS demonstrates comparable diagnostic yield to CMA for detecting clinically significant CNVs.
  • Optimized low-pass GS parameters enable reliable detection of CNVs, including mosaic variants.
  • Low-pass GS is supported as a cost-effective and effective first-tier genetic test for molecular cytogenetic analysis.