A phylogenetic approach for haplotype analysis of sequence data from complex mitochondrial mixtures

Area of Science:

• Forensic Science
• Genetics
• Bioinformatics

Background:

• Massively parallel sequencing enables DNA analysis from challenging samples.
• Forensic samples are often mixtures of DNA from multiple individuals.
• Mitochondrial DNA (mtDNA) is useful for mixture analysis due to its haploid nature.

Purpose of the Study:

• To develop a computational approach for deconvoluting mixed mtDNA samples.
• To accurately determine constituent haplotypes and mixture proportions from sequencing data.

Main Methods:

• An expectation maximization algorithm was developed.
• The algorithm co-estimates mixture proportions and source haplogroups for each read.
• The method is implemented in the software package mixemt.

Main Results:

• The mixemt software correctly identifies haplogroups in mixed mtDNA samples.
• The approach works across a range of mixture proportions.
• The method can separate mixed DNA fragments by contributor and reconstruct haplotypes.

Conclusions:

• The developed computational approach effectively deconvolutes mixed mtDNA samples.
• This method enhances the analysis of complex forensic DNA mixtures.
• mixemt provides a powerful tool for reconstructing constituent mtDNA haplotypes.