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Development of a multiplex methylation-sensitive restriction enzyme-based SNP typing system for deconvolution of semen-containing mixtures

Authors :
Na Liu
Jiangwei Yan
Zeqin Li
Jintao Li
Gengqian Zhang
Jianbo Ren
Yidan Li
Feng Liu
Keming Yun
Source :
International Journal of Legal Medicine. 135:1281-1294
Publication Year :
2021
Publisher :
Springer Science and Business Media LLC, 2021.

Abstract

The identification of mixed stains has always been a difficult problem in personal identification in the forensic field. In recent years, tissue-specific methylation sites have proven to be very stable biomarkers for distinguishing tissue origin. However, it is still challenging to perform tissue source identification and individual identification simultaneously. In this study, we developed a method that uses tissue-specific methylation markers combined with single-nucleotide polymorphism (SNP) markers to detect semen from mixed biofluids and to identify individuals simultaneously. Semen-specific CpG markers were chosen from the literature and further validated utilizing methylation-sensitive restriction endonuclease (MSRE) combined with PCR technology. The neighboring SNP markers were searched in the flanking sequence of the target CpG within 400 bp, and SNP typing was then carried out through a single-base extension reaction followed by capillary electrophoresis. Eventually, a method of MSRE combined with SNaPshot that could detect 12 compound CpG-SNP markers was developed. Using this system, 10 ng of total DNA and DNA mixture with semen content up to 25% could be typed successfully. Moreover, the cumulative discrimination power of the system in the northern Chinese Han population is 0.9998. This study provides a valuable strategy for forensic practice to perform tissue origin and individual identification from mixed stains simultaneously.

Details

ISSN :
14371596 and 09379827
Volume :
135
Database :
OpenAIRE
Journal :
International Journal of Legal Medicine
Accession number :
edsair.doi.dedup.....33abab57d357a3a5bd73cf304a5b8b8b