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Updated: Aug 4, 2026

FISH for Pre-implantation Genetic Diagnosis
Published on: February 23, 2011
A Digital PCR Assay for Fetal Fraction Quantification Using Multiplex SNP and Y Chromosome Detection
Chianru Tan1, Peng Dai2, Zhuoyu Zhao1
1School of Biomedical Engineering, Tsinghua University, Beijing, China.
Background:
Fetal fraction (FF) quantification is critical for prenatal cell-free DNA screening. Current methods based on Y chromosome (chrY), differential methylation, or single-nucleotide polymorphisms (SNPs) face limitations including sex dependency, complex workflows, or the need for parental genotyping. An FF quantification method that integrates directly into the digital polymerase chain reaction (dPCR) workflow is needed to support the clinical implementation of dPCR-based prenatal screening.
Methods:
We developed a multiplex dPCR assay quantifying 9 autosomal SNPs and 3 chrY loci across 2 reaction wells. Key innovations include: concurrent SNP and chrY detection for sex-independent estimation; a single-probe, dual-allele discrimination design with a calculation algorithm that eliminates parental genotyping; and a triplex chrY assay to enhance accuracy. The assay was analytically validated using simulated DNA mixtures and clinically evaluated using 143 maternal plasma samples against a next-generation sequencing (NGS) reference.
Results:
Analytical validation showed strong linearity between expected and observed FF for both chrY (R2 = 0.971) and SNP (R2 = 0.924) methods. The chrY assay demonstrated superior accuracy and sensitivity at low FF levels (mean absolute error: 0.94% chrY, 1.61% SNPs). Clinical evaluation showed a 92.3% informative SNP rate, a low 2.8% no-call rate, and strong concordance with NGS-based FF estimates (r = 0.799, P < 0.0001).
Conclusions:
Our dPCR assay provides a practical QC tool for dPCR-based prenatal screening by enabling sex-independent FF quantification without parental genotyping or complex preanalytical steps. Future efforts will include multicenter validation and panel expansion. This methodology also shows potential for applications in transplantation medicine and obstetric monitoring.
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