Nuclear mitochondrial pseudogenes (numts) may hinder the reconstruction of mtDNA genomes and affect the reliability of mtDNA datasets for phylogenetic and population genetic comparisons. Here, we present the program Numt Parser, which allows for the identification of DNA sequences that likely originate from numt pseudogene DNA. Sequencing reads are classified as originating from either numt or true cytoplasmic mitochondrial (cymt) DNA by direct comparison against cymt and numt reference sequences. Classified reads can then be parsed into cymt or numt datasets. We tested this program using whole genome shotgun-sequenced data from two ancient Cape lions (Panthera leo) because mtDNA is often the marker of choice for ancient DNA studies, and the genus Panthera is known to have numt pseudogenes. Numt Parser decreased sequence disagreements that were likely due to numt pseudogene contamination and equalized read coverage across the mitogenome by removing reads that likely originated from numts. We compared the efficacy of Numt Parser to two other bioinformatic approaches that can be used to account for numt contamination. We found that Numt Parser outperformed approaches that rely only on read alignment or Basic Local Alignment Search Tool (BLAST) properties, and was effective at identifying sequences that likely originated from numts while having minimal impacts on the recovery of cymt reads. Numt Parser therefore improves the reconstruction of true mitogenomes, allowing for more accurate and robust biological inferences.

Sequencing reads and alignments generated from ancient DNA of two Cape Lion (Panthera leo melanochaitus) samples. Raw reads were aligned to the Panthera leo mitochondrial reference (NCBI Accession KP202262.1) to obtain mitochondrial-specific reads. These mitochondrial reads were then processed using different methods (BLAST, SAMtools, Numt Parser) to identify and filter Numt-contaminant reads. See de Flamingh, et al. (2022) for additional information on the specific bioinformatic pipeline used and a description of the Numt Parser software.

Files in BAM format (.bam) are stored in binary and require the use of SAMtools for conversion. SAM (.sam) and FASTA (.fa) files are in text format and can be accessed using any text editor software (in either the command line or a graphical application).