MitoFREQ: A Novel Approach for Mitogenome Frequency Estimation from Top-level Haplogroups and Single Nucleotide Variants

TL;DR

MitoFREQ is a new method that estimates mitochondrial genome population frequencies using top-level haplogroups and SNV data from large databases, improving forensic evidence evaluation especially for low-quality samples.

Contribution

The paper introduces MitoFREQ, a novel approach leveraging large-scale databases and minimal positions for robust mitogenome frequency estimation in forensic genetics.

Findings

Method guarantees higher frequency estimates than refined haplogroup approaches.

Achieves top-level haplogrouping with only 227 positions for 99.9% of samples.

Produces likelihood ratios up to 100,000, enhancing forensic statistical evaluation.

Abstract

Lineage marker population frequencies can serve as one way to express evidential value in forensic genetics. However, for high-quality whole mitochondrial DNA genome sequences (mitogenomes), population data remain limited. In this paper, we offer a new method, MitoFREQ, for estimating the population frequencies of mitogenomes. MitoFREQ uses the mitogenome resources HelixMTdb and gnomAD, harbouring information from 195,983 and 56,406 mitogenomes, respectively. Neither HelixMTdb nor gnomAD can be queried directly for individual mitogenome frequencies, but offers single nucleotide variant (SNV) allele frequencies for each of 30 "top-level" haplogroups (TLHG). We propose using the HelixMTdb and gnomAD resources by classifying a given mitogenome within the TLHG scheme and subsequently using the frequency of its rarest SNV within that TLHG weighted by the TLHG frequency. We show that this method is guaranteed to provide a higher population frequency estimate than if a refined haplogroup and its SNV frequencies were used. Further, we show that top-level haplogrouping can be achieved by using only 227 specific positions for 99.9% of the tested mitogenomes, potentially making the method available for low-quality samples. The method was tested on two types of datasets: high-quality forensic reference datasets and a diverse collection of scrutinised mitogenomes from GenBank. This dual evaluation demonstrated that the approach is robust across both curated forensic data and broader population-level sequences. This method produced likelihood ratios in the range of 100-100,000, demonstrating its potential to strengthen the statistical evaluation of forensic mtDNA evidence. We have developed an open-source R package `mitofreq` that implements our method, including a Shiny app where custom TLHG frequencies can be supplied.