MMDIT: A tool for the deconvolution and interpretation of mitochondrial DNA mixtures

Capillary-Electrophoresis-Based Species Barcoding of Big Cats: CR-mtDNA-Length Polymorphism

This study aimed to provide an overview of the methodological approach used for the species determination of big cats. The molecular system described herein employs mitochondrial DNA control region (CR-mtDNA)-length polymorphism in combination with highly sensitive and precise capillary electrophoresis. We demonstrated that the described CR-mtDNA barcoding system can be utilized for species determination where the presence of biological material from big cats is expected or used as a confirmatory test alongside Sanger or massive parallel sequencing (MPS). We have also addressed the fact that species barcoding, when based on the analysis of mtDNA targets, can be biased by nuclear inserts of the mitochondrial genome (NUMTs). The CR-mtDNA barcoding system is suitable even for problematic and challenging samples, such as hair. CR-mtDNA-length polymorphisms can also distinguish hybrids from pure breeds.

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

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 (Promega™, Madison, WI, USA) and Precision ID mtDNA Whole Genome Panel (Thermo Fisher Scientific by AB™, Waltham, MA, USA) 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%. 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 (minor contribution 1-2%), which remain challenging to resolve even with deep sequencing.

Post hoc deconvolution of human mitochondrial DNA mixtures by EMMA 2 using fine-tuned Phylotree nomenclature

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MtDNA mixtures are observed frequently and difficult to deconvolute.

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Most previous methods require raw data or quantitative information.

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EMMA 2 produces valid splittings from consensus sequences of any sequencing technology.

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EMMA 2 can deconvolute 2 and 3 person mixtures in a fast and traceable way.

In this paper we present a new algorithm for splitting (partial) human mitogenomes into components with high similarity to haplogroup motifs of Phylotree. The algorithm reads a (partial) mitogenome coded by the differences to the reference (rCRS) and outputs the estimated haplogroups of the putative components. The algorithm requires no special information on the raw data of the sequencing process and is therefore suited for the post hoc analysis of mixtures of any sequencing technology. The software EMMA 2 implementing the algorithm will be made available via the EMPOP (https://empop.online) database and extends the nine years old software EMMA for haplogrouping single mitogenomes to mixtures with at most three components.