Numt Parser: Automated identification and removal of nuclear mitochondrial pseudogenes (numts) for accurate mitochondrial genome reconstruction in Panthera.

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 2 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 2 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.
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