Objectives

The transmission of genetic information from DNA to RNA is a fundamental biological process. As DNA serves as the template for RNA transcription, RNA sequences are generally perssumed to faithfully reflect their DNA counterparts. However, several mechanisms—including transcriptional errors, RNA editing, and RNA modifications—have been reported to generate discrepancies between RNA and DNA sequences, referred to as RNA-DNA differences (RDD). With the growing interest in using RNA markers individual identification and kinship inference in forensic genetics, a systematic evaluation of RDD in sequencing data derived from forensic body fluids is critically needed.

Material and methods

We analyzed 120 paired DNA and RNA samples obtained from venous blood (VB), menstrual blood (MB), saliva (SA), semen (SE), and vaginal secretions (VS). Total RNA and DNA libraries were sequenced on the DNBSEQ-T7 platform using PE-100 and PE-150 modes, respectively. Variant calling was performed using Sentieon DNAseq and RNA variant calling modules. A step-by-step filtering strategy was applied based on error-prone sequencing or mapping regions, signatures indicative of biologically authentic RDD events, and characteristics of non-strand-specific RNA-seq libraries to minimize technical artifacts while retaining high-confidence RDD candidates.

Results and conclusions

Under a stringent bioinformatics workflow, we identified 1,750 (0.013%), 327 (0.014%), 22 (0.015%), 247 (0.017%), and 175 (0.015%) RDD events in VB, MB, SA, SE and VS respectively, encompassing all 12 types of mismatches. Sanger sequencing validation revealed that the majority of candidate RDD events exhibited concordant DNA and RNA genotypes, with false positive rates of 24% for intronic regions, 0% for exonic regions, and 25% for 3'UTR regions. This study systematically characterized RDD occurrence rates across common forensic body fluids and established body fluid-specific RDD landscapes. These findings provide practical guidance for refining RNA-SNP selection criteria in individual identification and further offer a quantitative basis for incorporating false positive rates into statistical calculations in forensic practice.

Authors

• Enlin Wu (Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, China)
• Zhiyong Liu (Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, China)
• Jiajun Liu (Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, China)
• Riga Wu (Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, China)
• Hongyu Sun (Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, China)