MitoImpute: A Snakemake pipeline for imputation of mitochondrial genetic variants

Abstract

BackgroundVariation in mitochondrial DNA (mtDNA) identified by genotyping microarrays or by sequencing only hypervariable regions of the genome may be insufficient to reliably assign mitochondrial genomes to phylogenetic lineages or haplogroups. This lack of resolution can limit functional and clinical interpretation of a substantial body of existing mtDNA data. To address this limitation, we developed and evaluated a method for imputing missing mtDNA single nucleotide variants (mtSNVs) that uses a large reference alignment of complete mtDNA sequences. The method and reference alignment are combined into a pipeline, which we call MitoImpute. ResultsWe aligned the sequences of 36,960 complete human mitochondrial genomes downloaded from GenBank, filtered and controlled for quality. These sequences were reformatted for use in imputation software, IMPUTE2. We assessed the imputation accuracy of MitoImpute by measuring haplogroup and genotype concordance in data from the 1,000 Genomes Project and the Alzheimers Disease Neuroimaging Initiative (ADNI). The mean improvement of haplogroup assignment in the 1,000 Genomes samples was 42.7% (Matthews correlation coefficient = 0.64). In the ADNI cohort, we imputed missing single nucleotide variants. ConclusionsThese results show that our reference alignment and panel can be used to impute missing mtSNVs in exiting data obtained from using microarrays, thereby broadening the scope of functional and clinical investigation of mtDNA. This improvement may be particularly useful in studies where participants have been recruited over time and mtDNA data obtained using different methods, enabling better integration of early data collected using less accurate methods with more recent sequence data.