Hi-MC: A novel method for high-throughput mitochondrial haplogroup classification

Abstract

Effective approaches for assessing mitochondrial DNA (mtDNA) variation are important to multiple scientific disciplines. Mitochondrial haplogroups characterize branch points in the phylogeny of mtDNA. Several tools exist for mitochondrial haplogroup classification.However, most require full or partial mtDNA sequence which is often cost prohibitive for studies with large sample sizes. The purpose of this study was to develop Hi-MC, a highthroughput method for mitochondrial haplogroup classification that is cost effective and applicable to large sample sizes making mitochondrial analysis more accessible in genetic studies. Using rigorous selection criteria, we defined and validated a custom panel of mtDNA single nucleotide polymorphisms (SNPs) that allows for accurate classification of European, African, and Native American mitochondrial haplogroups at broad resolution with minimal genotyping and cost. We demonstrate that Hi-MC performs well in samples of European, African, and Native American ancestries, and that Hi-MC performs comparably to a commonly used classifier. Implementation as a software package in R enables users to download and run the program locally, grants greater flexibility in the number of samples that can be run, and allows for easy expansion in future revisions. The source code is freely available at https://github.com/vserch/himc . Effective aJJroaches for assessing mitochondrial DNA (mtDNA) variation are imJortant to multiJle scientific disciJlines. Mitochondrial haJlogrouJs characterize branch Joints in the Jhylogeny of mtDNA. Several tools exist for mitochondrial haJlogrouJ classification. However, most require full or Jartial mtDNA sequence which is often cost Jrohibitive for studies with large samJle sizes. The JurJose of this study was to develoJ Hi-MC, a high-throughJut method for mitochondrial haJlogrouJ classification that is cost effective and aJJlicable to large samJle sizes making mitochondrial analysis more accessible in genetic studies. Using rigorous selection criteria, we defined and validated a custom Janel of mtDNA single nucleotide JolymorJhisms (SNPs) that allows for accurate classification of EuroJean, African, and Native American mitochondrial haJlogrouJs at broad resolution with minimal genotyJing and cost. We demonstrate that Hi-MC Jerforms well in samJles of EuroJean, African, and Native American ancestries, and that Hi-MC Jerforms comJarably to a commonly used classifier. ImJlementation as a software Jackage in R enables users to download and run the Jrogram locally, grants greater flexibility in the number of samJles that can be run, and allows for easy exJansion in future revisions. The source code is freely available at httJs://github.com/vserch/himc.