Validation and depth evaluation of low-pass genome sequencing in prenatal diagnosis using 387 amniotic fluid samples

J Med Genet. 2023 Oct;60(10):933-938. doi: 10.1136/jmg-2022-109112. Epub 2023 Apr 3.

Abstract

Background: Low-pass genome sequencing (LP GS) is an alternative to chromosomal microarray analysis (CMA). However, validations of LP GS as a prenatal diagnostic test for amniotic fluid are rare. Moreover, sequencing depth of LP GS in prenatal diagnosis has not been evaluated.

Objective: The diagnostic performance of LP GS was compared with CMA using 375 amniotic fluid samples. Then, sequencing depth was evaluated by downsampling.

Results: CMA and LP GS had the same diagnostic yield (8.3%, 31/375). LP GS showed all copy number variations (CNVs) detected by CMA and six additional variant of uncertain significance CNVs (>100 kb) in samples with negative CMA results; CNV size influenced LP GS detection sensitivity. CNV detection was greatly influenced by sequencing depth when the CNV size was small or the CNV was located in the azoospermia factor c (AZFc) region of the Y chromosome. Large CNVs were less affected by sequencing depth and more stably detected. There were 155 CNVs detected by LP GS with at least a 50% reciprocal overlap with CNVs detected by CMA. With 25 M uniquely aligned high-quality reads (UAHRs), the detection sensitivity for the 155 CNVs was 99.14%. LP GS using samples with 25 M UAHRs showed the same performance as LP GS using total UAHRs. Considering the detection sensitivity, cost and interpretation workload, 25 M UAHRs are optimal for detecting most aneuploidies and microdeletions/microduplications.

Conclusion: LP GS is a promising, robust alternative to CMA in clinical settings. A total of 25 M UAHRs are sufficient for detecting aneuploidies and most microdeletions/microduplications.

Keywords: Molecular Diagnostic Techniques.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amniotic Fluid*
  • Aneuploidy
  • DNA Copy Number Variations* / genetics
  • Female
  • Humans
  • Microarray Analysis
  • Pregnancy
  • Prenatal Diagnosis / methods