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A New Tool for Probabilistic Assessment of MPS Data Associated with mtDNA Mixtures

NCJ Number
Genes Volume: 15 Issue: 2 Dated: 31 January 2024 Pages: 194
Date Published
January 2024

This article reports on a study that successfully completed its three goals: to create a new software that deconvolutes mitochondrial DNA mixtures by assessing and combining two existing software tools; to create a dataset of in-silico MPS mixtures from whole mitogenome haplotypes; and to create biological mixture data associated with two common amplification kits.


Mitochondrial (mt) DNA plays an important role in the fields of forensic and clinical genetics, molecular anthropology, and population genetics, with mixture interpretation being of particular interest in medical and forensic genetics. The high copy number, haploid state (only a single haplotype contributed per individual), high mutation rate, and well-known phylogeny of mtDNA, makes it an attractive marker for mixture deconvolution in damaged and low quantity samples of all types. Given the desire to deconvolute mtDNA mixtures, the goals of this study were to (1) create a new software, MixtureAceMT™, to deconvolute mtDNA mixtures by assessing and combining two existing software tools, MixtureAce™ and Mixemt, (2) create a dataset of in-silico MPS mixtures from whole mitogenome haplotypes representing a diverse set of population groups, and consisting of two and three contributors at different dilution ratios, and (3) since amplicon targeted sequencing is desirable, and is a commonly used approach in forensic laboratories, create biological mixture data associated with two amplification kits – PowerSeq™ Whole Genome Mito and Precision ID mtDNA Whole Genome Panel – to further validate the software for use in forensic laboratories. MixtureAceMT™ provides a user-friendly interface while reducing confounding features such as NUMTs and noise, reducing traditionally prohibitive processing times. The new software was able to detect the correct contributing haplogroups and closely estimate contributor proportions in sequencing data generated from small amplicons for mixtures with minor contributions of ≥5 percent. A challenge of mixture deconvolution using small amplicon sequencing is the potential generation of spurious haplogroups resulting from private mutations that differ from Phylotree. MixtureAceMT™ was able to resolve these additional haplogroups by including known haplotype/s in the evaluation. In addition, for some samples, the inclusion of known haplotypes was also able to resolve trace contributors, which remain challenging to resolve even with deep sequencing. (Published Abstract Provided)

Date Published: January 1, 2024