AQME: A forensic mitochondrial DNA analysis tool for next-generation sequencing data

Abstract

The feasibility of generating mitochondrial DNA (mtDNA) data has expanded considerably with the advent of next-generation sequencing (NGS), specifically in the generation of entire mtDNA genome (mitogenome) sequences. However, the analysis of these data has emerged as the greatest challenge to implementation in forensics. To address this need, a custom toolkit for use in the CLC Genomics Workbench (QIAGEN, Hilden, Germany) was developed through a collaborative effort between the Armed Forces Medical Examiner System - Armed Forces DNA Identification Laboratory (AFMES-AFDIL) and QIAGEN Bioinformatics. The AFDIL-QIAGEN mtDNA Expert, or AQME, generates an editable mtDNA profile that employs forensic conventions and includes the interpretation range required for mtDNA data reporting. AQME also integrates an mtDNA haplogroup estimate into the analysis workflow, which provides the analyst with phylogenetic nomenclature guidance and a profile quality check without the use of an external tool. Supplemental AQME outputs such as nucleotide-per-position metrics, configurable export files, and an audit trail are produced to assist the analyst during review. AQME is applied to standard CLC outputs and thus can be incorporated into any mtDNA bioinformatics pipeline within CLC regardless of sample type, library preparation or NGS platform. An evaluation of AQME was performed to demonstrate its functionality and reliability for the analysis of mitogenome NGS data. The study analyzed Illumina mitogenome data from 21 samples (including associated controls) of varying quality and sample preparations with the AQME toolkit. A total of 211 tool edits were automatically applied to 130 of the 698 total variants reported in an effort to adhere to forensic nomenclature. Although additional manual edits were required for three samples, supplemental tools such as mtDNA haplogroup estimation assisted in identifying and guiding these necessary modifications to the AQME-generated profile. Along with profile generation, AQME reported accurate haplogroups for 18 of the 19 samples analyzed. The single errant haplogroup assignment, although phylogenetically close, identified a bug that only affects partial mitogenome data. Future adjustments to AQME's haplogrouping tool will address this bug as well as enhance the overall scoring strategy to better refine and automate haplogroup assignments. As NGS enables broader use of the mtDNA locus in forensics, the availability of AQME and other forensic-focused mtDNA analysis tools will ease the transition and further support mitogenome analysis within routine casework. Toward this end, the AFMES-AFDIL has utilized the AQME toolbox in conjunction with the CLC Genomics Workbench to successfully validate and implement two NGS mitogenome methods.

Keywords: Data analysis; Forensics; Haplogroup; Mitochondrial DNA; Next-generation sequencing (NGS).