Concordance and reproducibility of a next generation mtGenome sequencing method for high-quality samples using the Illumina MiSeq

Abstract Sanger-type sequencing (STS) of mitochondrial DNA (mtDNA), specifically the control region (CR), is routinely employed in forensics in human identification and missing persons scenarios. Yet next-generation sequencing (NGS) has the potential to overcome some of the major limitations of STS processing, permitting reasonable paths forward for full mitochondrial genome (mtGenome) sequencing, while also offering higher-throughput and higher sensitivity capabilities. To establish the accuracy and reproducibility of NGS for the development of mtDNA data, 90 DNA extracts that were previously used to generate forensic quality full mtGenomes using STS were sequenced using Nextera XT library preparation and the Illumina MiSeq. Using the same amplicon product, replicate library sets were generated and sequenced at different laboratories, and analysis was performed in replicate using the CLC Genomics Workbench. Both sequencing sets resulted in 99.998% of positions with greater than 10X coverage when 96 samples (including controls) were multiplexed. Overall, 99.9996% concordance was observed between the NGS data and the STS data for the full mtGenome. The only "discordant" calls involved low level point heteroplasmies, with the differences resulting from stochastic variation and/or the increased sensitivity of NGS. Higher sensitivity also allowed for the detection of a mixed sample previously not detected with STS. Additionally, variant calls were reproducible between sequencing sets and between software analysis versions with the variant frequency only differing by 0.23% and 0.01%, respectively. Further validation studies and specialized software functionality tailored to forensic practice should facilitate the incorporation of NGS processing into standard casework applications. The data herein comprise the largest, and likely most thoroughly examined, complete mtGenome STS-NGS concordance dataset available.