A microhaplotypes panel for massively parallel sequencing analysis of DNA mixtures

Area of Science:

• Forensic Genetics
• Molecular Biology
• Population Genetics

Background:

• Massively parallel sequencing (MPS) allows detailed analysis of forensic genetic markers and low-level DNA in mixtures.
• Previous work introduced microhaplotype loci for DNA mixture analysis, but key questions on donor identification and mixture proportion inference remained.
• Unbalanced DNA mixtures pose challenges in forensic investigations, particularly in identifying individual contributors.

Purpose of the Study:

• To address limitations in analyzing unbalanced DNA mixtures using microhaplotypes.
• To determine if major and minor contributors in mixtures can be compared to suspects.
• To assess the feasibility of inferring mixture proportions and assigning alleles to specific donors.

Main Methods:

• Developed and utilized a multiplex system with 25 microhaplotype loci (all <50 bp) for MPS.
• Analyzed DNA from 60 Han Chinese individuals and 40 artificial DNA mixtures with varying proportions.
• Compared population genetic data of microhaplotypes with the 1000 Genomes Project (1000G) data across 26 populations.

Main Results:

• Microhaplotypes demonstrated consistently high AE values across diverse populations.
• Likelihood ratios effectively compared mixtures with known suspects, identifying major contributors in all cases.
• Minor contributors were identifiable with sufficient loci captured; allele depth ratios correlated significantly with mixing proportions.
• Distinct allele depth patterns were clarified for balanced and imbalanced mixtures, enabling direct individual identification at certain loci.

Conclusions:

• The 25-microhaplotype panel is effective for analyzing complex forensic DNA mixtures, including unbalanced samples.
• The system facilitates the identification of both major and minor contributors, enhancing suspect comparison capabilities.
• Microhaplotype allele depth patterns provide valuable information for inferring mixture ratios and individual identification.