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

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.

Genetic and phylogeographic evidence for Jewish Holocaust victims at the Sobibór death camp.

Six million Jews were killed by Nazi Germany and its collaborators during World War II. Archaeological excavations in the area of the death camp in Sobibór, Poland, revealed ten sets of human skeletal remains presumptively assigned to Polish victims of the totalitarian regimes. However, their genetic analyses indicate that the remains are of Ashkenazi Jews murdered as part of the mass extermination of European Jews by the Nazi regime and not of otherwise hypothesised non-Jewish partisan combatants. In accordance with traditional Jewish rite, the remains were reburied in the presence of a Rabbi at the place of their discovery.

Fine-Tuning Phylogenetic Alignment and Haplogrouping of mtDNA Sequences.

In this paper, we present a new algorithm for alignment and haplogroup estimation of mitochondrial DNA (mtDNA) sequences. Based on 26,011 vetted full mitogenome sequences, we refined the 5435 original haplogroup motifs of Phylotree Build 17 without changing the haplogroup nomenclature. We adapted 430 motifs (about 8%) and added 966 motifs for yet undetermined subclades. In summary, this led to an 18% increase of haplogroup defining motifs for full mitogenomes and a 30% increase for the mtDNA control region that is of interest for a variety of scientific disciplines, such as medical, population and forensic genetics. The new algorithm is implemented in the EMPOP mtDNA database and is freely accessible.

Pathogenic Variant Filtering for Mitochondrial Genome Haplotype Reporting.

Given the enhanced discriminatory power of the mitochondrial DNA (mtDNA) genome (mitogenome) over the commonly sequenced control region (CR) portion, the scientific merit of mitogenome sequencing is generally accepted. However, many laboratories remain beholden to CR sequencing due to privacy policies and legal requirements restricting the use of disease information or coding region (codR) information. In this report, we present an approach to obviate the reporting of sensitive codR data in forensic haplotypes. We consulted the MitoMap database to identify 92 mtDNA codR variants with confirmed pathogenicity. We determined the frequencies of these pathogenic variants in literature-quality and forensic-quality databases to be very low, at 1.2% and 0.36%, respectively. The observed effect of pathogenic variant filtering on random match statistics in 2488 forensic-quality mitogenome haplotypes from four populations was nil. We propose that pathogenic variant filtering should be incorporated into variant calling algorithms for mitogenome haplotype reporting to maximize the discriminatory power of the locus while minimizing the reveal of sensitive genetic information.

Next generation database search algorithm for forensic mitogenome analyses.

Mitochondrial DNA (mtDNA) variation is being reported relative to the corrected version of the first sequenced human mitochondrial genome. A review of the existing literature across disciplines that employ mtDNA demonstrates that insertions and deletions are not reported in a standardized way. This may lead to false exclusions of identical sequences, unidentified matches in missing persons mtDNA databases, biased mtDNA database frequency estimates and overestimation of the genetic evidence. Seven years ago we introduced alignment-free database search software (SAM) and implemented it into the mtDNA database EMPOP (https://empop.online) to produce reliable and conservative frequency estimates that are required in the forensic context. However, ambiguity remained in how laboratories have been reporting mitotypes, as often more than one single alignment of a given mtDNA sequence was feasible. In order to overcome this limitation we here describe a concept and provide software for producing stable, harmonized phylogenetic alignment of mtDNA sequences for database searches. The new software SAM 2 will be made available via EMPOP and provide the user with the already established conservative frequency estimates. In addition, SAM 2 offers the rCRS-coded haplotype of a given mtDNA sequence following the established and widely accepted phylogenetic alignment. This provides the user with feedback on how mitotypes are stored in EMPOP and how they should be reported in order to harmonize nomenclature. Finally, this approach does not only permit reliable mtDNA nomenclature in forensics but invites related disciplines to take advantage of a standardized way of reporting mtDNA variation, thus closing the ranks between different genetic fields and supporting dialogue and collaboration between mtDNA scholars from various disciplines.

Improved visibility of character conflicts in quasi-median networks with the EMPOP NETWORK software.

AIM: To provide a valuable tool for graphical representation of mitochondrial DNA (mtDNA) data that enables visual emphasis on complex substructures within the network to highlight possible ambiguities and errors. METHOD: We applied the new NETWORK graphical user interface, available via EMPOP (European DNA Profiling Group Mitochondrial DNA Population Database; www.empop.org) by means of two mtDNA data sets that were submitted for quality control. RESULTS: The quasi-median network torsi of the two data sets resulted in complex reticulations, suggesting ambiguous data. To check the corresponding raw data, accountable nodes and connecting branches of the network could be identified by highlighting induced subgraphs with concurrent dimming of their complements. This is achieved by accentuating the relevant substructures in the network: mouse clicking on a node displays a list of all mtDNA haplotypes included in that node; the selection of a branch specifies the mutation(s) connecting two nodes. It is indicated to evaluate these mutations by means of the raw data. CONCLUSION: Inspection of the raw data confirmed the presence of phantom mutations due to suboptimal electrophoresis conditions and data misinterpretation. The network software proved to be a powerful tool to highlight problematic data and guide quality control of mtDNA data tables.

Concept for estimating mitochondrial DNA haplogroups using a maximum likelihood approach (EMMA).

The assignment of haplogroups to mitochondrial DNA haplotypes contributes substantial value for quality control, not only in forensic genetics but also in population and medical genetics. The availability of Phylotree, a widely accepted phylogenetic tree of human mitochondrial DNA lineages, led to the development of several (semi-)automated software solutions for haplogrouping. However, currently existing haplogrouping tools only make use of haplogroup-defining mutations, whereas private mutations (beyond the haplogroup level) can be additionally informative allowing for enhanced haplogroup assignment. This is especially relevant in the case of (partial) control region sequences, which are mainly used in forensics. The present study makes three major contributions toward a more reliable, semi-automated estimation of mitochondrial haplogroups. First, a quality-controlled database consisting of 14,990 full mtGenomes downloaded from GenBank was compiled. Together with Phylotree, these mtGenomes serve as a reference database for haplogroup estimates. Second, the concept of fluctuation rates, i.e. a maximum likelihood estimation of the stability of mutations based on 19,171 full control region haplotypes for which raw lane data is available, is presented. Finally, an algorithm for estimating the haplogroup of an mtDNA sequence based on the combined database of full mtGenomes and Phylotree, which also incorporates the empirically determined fluctuation rates, is brought forward. On the basis of examples from the literature and EMPOP, the algorithm is not only validated, but both the strength of this approach and its utility for quality control of mitochondrial haplotypes is also demonstrated.

SAM: String-based sequence search algorithm for mitochondrial DNA database queries.

The analysis of the haploid mitochondrial (mt) genome has numerous applications in forensic and population genetics, as well as in disease studies. Although mtDNA haplotypes are usually determined by sequencing, they are rarely reported as a nucleotide string. Traditionally they are presented in a difference-coded position-based format relative to the corrected version of the first sequenced mtDNA. This convention requires recommendations for standardized sequence alignment that is known to vary between scientific disciplines, even between laboratories. As a consequence, database searches that are vital for the interpretation of mtDNA data can suffer from biased results when query and database haplotypes are annotated differently. In the forensic context that would usually lead to underestimation of the absolute and relative frequencies. To address this issue we introduce SAM, a string-based search algorithm that converts query and database sequences to position-free nucleotide strings and thus eliminates the possibility that identical sequences will be missed in a database query. The mere application of a BLAST algorithm would not be a sufficient remedy as it uses a heuristic approach and does not address properties specific to mtDNA, such as phylogenetically stable but also rapidly evolving insertion and deletion events. The software presented here provides additional flexibility to incorporate phylogenetic data, site-specific mutation rates, and other biologically relevant information that would refine the interpretation of mitochondrial DNA data. The manuscript is accompanied by freeware and example data sets that can be used to evaluate the new software (http://stringvalidation.org).

EMPOP--a forensic mtDNA database.

Mitochondrial DNA databases stand as the basis for frequency estimations of mtDNA sequences that became relevant in a case. The establishment of mtDNA databases sounds trivial; however, it has been shown in the past that this undertaking is prone to error for several reasons, particularly human error. We have established a concept for mtDNA data generation, analysis, transfer and quality control that meets forensic standards. Due to the complexity of mtDNA population data tables it is often difficult if not impossible to detect errors, especially for the untrained eye. We developed software based on quasi-median network analysis that visualizes mtDNA data tables and thus signposts sequencing, interpretation and transcription errors. The mtDNA data (N=5173; release 1) are stored and made publicly available via the Internet in the form of the EDNAP mtDNA Population Database, short EMPOP. This website also facilitates quasi-median network analysis and provides results that can be used to check the quality of mtDNA sequence data. EMPOP has been launched on 16 October 2006 and is since then available at http://www.empop.org.

Translating DNA data tables into quasi-median networks for parsimony analysis and error detection.

Every DNA data table can be turned into a quasi-median network that faithfully represents the data. We show that for (weighted) condensed data tables the associated network harbors all most parsimonious reconstructions for any tree that connects the sampled haplotypes. Structural features of this network can be computed directly from the data table. The key principle repeatedly used is that the quasi-median network is uniquely determined by the sub-tables for pairs of characters. The translation of a table into a network enhances the understanding of the properties of the data in regard to homoplasy and potential artifacts. The total number of nodes of such a network measures the complexity of the data. In particular, networks that display the results of filter analyses by which hotspot mutations are removed help to detect data idiosyncrasies and thus pinpoint sequencing problems. A pertinent example drawn from human mtDNA illustrates these points.