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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Applications of Probabilistic Genotyping Method for Combining Evidence Across Microhaplotype DNA Mixture Profiles.

Xiaohua Ling^1,2, Shuang Han^1,2, Xinyi Lin^1,2

¹Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, P. R. China.

Electrophoresis

|October 15, 2024

Summary

This summary is machine-generated.

Microhaplotype analysis reliably identifies common or related contributors in complex DNA mixtures. This forensic DNA typing method shows promise for challenging criminal cases, even with allele imbalance, and has a zero false-positive rate.

Keywords:

DNA mixture common contributor likelihood ratio microhaplotypes related contributors

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Area of Science:

Forensic Science
Genetics
Molecular Biology

Background:

Challenging DNA samples, such as minor contributors in mixtures, necessitate advanced forensic techniques.
Previous research developed a massively parallel sequencing (MPS)-based assay for 140 microhaplotype markers.

Purpose of the Study:

To evaluate the utility of a microhaplotype panel for identifying common or related contributors in DNA mixtures without reference samples.
To assess the impact of allele imbalance on mixture profile interpretation.

Main Methods:

Utilized a 140-microhaplotype marker panel with massively parallel sequencing (MPS).
Interpreted mixture profiles using the R package KinMix.
Analyzed scenarios involving common contributors and relatedness between mixtures.

Main Results:

Correctly assigned common contributors and relatedness in relatively balanced mixtures.
Observed inclusive assignments significantly associated with mixture proportion in imbalanced profiles.
Achieved a zero false-positive rate across all tested scenarios.

Conclusions:

Microhaplotype data provide reliable interpretation for identifying common or related donors among different DNA mixtures.
The method is effective in forensic casework, particularly for complex mixtures.
Further research with larger sample sizes is recommended for enhanced reliability in complex scenarios.