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Noninvasive prenatal paternity testing using targeted massively parallel sequencing.

Ning- Qu1,2, Yifan Xie3,4, Haiyan Li5

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This study developed a massively parallel sequencing (MPS) approach for noninvasive prenatal paternity testing (NIPAT). The Bayesian method for data interpretation proved more effective than the counting method for accurate paternity determination.

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Area of Science:

  • Genetics
  • Molecular Biology
  • Bioinformatics

Background:

  • Massively parallel sequencing (MPS) offers efficient noninvasive prenatal paternity testing (NIPAT).
  • A standardized protocol for MPS-based NIPAT is currently lacking.
  • This study addresses the need for an established MPS protocol for NIPAT.

Purpose of the Study:

  • To develop and validate an MPS-based approach for noninvasive prenatal paternity testing (NIPAT).
  • To compare the performance of two distinct MPS data interpretation methods for NIPAT.
  • To identify the optimal strategy for reliable paternity determination using prenatal samples.

Main Methods:

  • Selected 1795 single-nucleotide polymorphisms (SNPs) for paternity analysis.
  • Utilized maternal plasma samples from 34 parentage test cases on the Illumina HiSeq platform.
  • Interpreted sequencing data using a straightforward counting method and mathematical algorithms for paternity index (PI) calculation.

Main Results:

  • Both interpretation methods showed significant discrimination between biological fathers and unrelated males (p < 0.0001).
  • The counting method filtered a substantial portion of paternal alleles, leading to insufficient loci, particularly in low fetal fraction samples.
  • The PI calculation model successfully identified the correct biological father, with log-transformed combined PI (Lg(CPI)) values ranging from 68.23 to 158.01.

Conclusions:

  • The Bayesian approach is recommended for NIPAT data interpretation.
  • Utilizing all maternal homozygous SNPs as effective loci improved accuracy.
  • Employing more informative markers or deeper sequencing can enhance NIPAT efficiency.