A theoretical base for non-invasive prenatal paternity testing

Abstract

There is an increasing demand for prenatal paternity testing in the forensic applications, which identify biological fathers before the birth of children. Currently, one of the most effective and safe Non-Invasive Prenatal Paternity Testing (NIPPT) methods is high-throughput Next-Generation Sequencing (NGS)-based SNP genotyping of cell-free DNA in maternal peripheral blood. To the best of our knowledge, nearly all methods being used in such applications are based on traditional postnatal paternity tests and/or statistical models of conventional polymorphism sites. These methods have shown unsatisfactory performance due to the uncertainty of fetal genotype. In this study, we propose a cutting-edge methodology called the Prenatal paternity Test Analysis System (PTAS) for cell-free fetal DNA-based NIPPT using NGS-based SNP genotyping. With the implementation of our proposed PTAS methodology, 63 out of 64 early-pregnancy (i.e., less than seven weeks) samples can be precisely identified to determine paternity, except for one sample that does not meet quality control requirements. Although the fetal fraction of the non-identified sample is extremely low (0.51%), its paternity can still be detected by our proposed PTAS methodology through unique molecular identifier tagging. Paternity of the total 313 samples for mid-to-late pregnancy (i.e., more than seven weeks) can be accurately identified. Extensive experiments indicate that our methodology makes a significant breakthrough in the NIPPT theory and will bring substantial benefits to forensic applications.

Keywords: Cumulative paternity index (CPI); Cumulative probability of exclusion (CPE); Next-generation sequencing (NGS); Non-invasive prenatal paternity testing (NIPPT); Single nucleotide polymorphism (SNP).