New Integrated Mitochondrial DNA Bioinformatics Pipeline to Improve Quality Assessment of Putative Pathogenic Variants from NGS Experiments

Mitochondria represents one of the most essential, investigated organelles of eukaryotic cells. Due to the relevance of the functions, especially cellular respiration, mitochondria are subject to continuous oxidative stress stimuli that, over time, can impair this distinct genome, leading, for example, to several neurodegenerative and age-related diseases. Today, the growth of next generation sequencing techniques allows researchers to improve variant detection of mtDNA, increasing, in the meantime, the quantity and complexity of data produced, making molecular diagnosis of mitochondrial diseases more challenging. The main issues that will be faced working with mtDNA high-throughput sequencing deal with detection and interpretation of low heteroplasmy and homoplasmy levels, variants unrelated to exhibited phenotype and identification of variants of unknown significance (VUS). To perform an accurate analysis of mtDNA variants produced by next generation sequencing experiments, we propose an integrated approach that foresees the complementary use of the most recent algorithms applied to mtDNA data, trying to extract the maximum from each one. This workflow foresaw four macro-phases (mitogenome alignment/assembly, variant calling, variant annotation and in-silico variant effects predictions), each one characterized by a mixed output coming from several tools and databases rich in complementary information on mtDNA variants. In this way, a superior quality output could be obtained, leading to improved genetic counseling for patients affected by primary mitochondrial pathologies.

Keywords: AVM, CCM, CLC Genomics Workbench, Mitochondria, mtDNA, mtDNA-Server, Mitos2, MitoBreak, MVTools, Mitoweb, MtoolBox, MitoTip, MitImpact 3D, RNA-Seq, RP, SMART2, TRIMITOMICS, VUS, Variants, WES.