With the advent of massively parallel sequencing (MPS), microhaplotypes (MHs) have been increasingly explored for DNA mixture analysis. Although MPS data inherently contain PCR and sequencing errors, recent studies have demonstrated that the Divisive Amplicon Denoising Algorithm 2 (DADA2) can effectively reduce noise in MH-MPS data. For the interpretation of DNA mixtures, the calculation of likelihood ratios (LRs) based on probabilistic genotyping (PG) is recommended. 

EuroForMix is a widely used open-source PG software for STR analysis, but studies applying it to MH-MPS data remain limited. In this study, we applied a DADA2-based denoising pipeline to MH-MPS data from complex DNA mixtures and interpreted the results using EuroForMix with parameters adjusted for MH-MPS data. 1 ng of DNA mixtures were prepared with two to four contributors, and mixture ratios were designed with minor contributor proportions ranging from 1% to 10%. MH-MPS libraries were constructed using an in-house panel targeting 42 MH markers and sequenced on the MiSeq system. The sequencing data were processed using a DADA2-based denoising pipeline and Visual Microhap for genotyping. LRs for minor contributors were calculated using EuroForMix based on maximum likelihood estimation.  

In addition, results were compared with conventional STR-CE analysis using the PowerPlex Fusion System on a 3500 Genetic Analyzer. The LRs for minor contributors decreased with increasing mixture imbalance. Nevertheless, sufficient evidential support for minor contributors was observed down to 2%, 3%, and 5% in two-, three-, and four-person mixtures, respectively, consistently outperforming STR-CE analysis. This indicates that minor contributors can be detected even at input levels of 20 pg. This study demonstrates that DADA2-based denoising enables reliable evidential support for minor contributors even in complex DNA mixtures through probabilistic interpretation. 

Authors

• Su Min Joo (Yonsei University College of Medicine, South Korea) 
• Ye-Lim Kwon (Yonsei University College of Medicine, South Korea) 
• Kyoung-Jin Shin (Yonsei University College of Medicine, South Korea)