Dataset Information

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 high-throughput 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 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. Hi-MC is available in the CRAN repository and the source code is freely available at https://github.com/vserch/himc.

SUBMITTER: Smieszek S

PROVIDER: S-EPMC6022720 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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

Smieszek Sandra S Mitchell Sabrina L SL Farber-Eger Eric H EH Veatch Olivia J OJ Wheeler Nicholas R NR Goodloe Robert J RJ Wells Quinn S QS Murdock Deborah G DG Crawford Dana C DC

PeerJ 20180625

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 high-throughput method for mitochondrial haplogroup classifica ...[more]

PMID: 29967758

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Project description:BackgroundMitochondrial dysfunction is linked to numerous pathological states, in particular related to metabolism, brain health and ageing. Nuclear encoded gene polymorphisms implicated in mitochondrial functions can be analyzed in the context of classical genome wide association studies. By contrast, mitochondrial DNA (mtDNA) variants are more challenging to identify and analyze for several reasons. First, contrary to the diploid nuclear genome, each cell carries several hundred copies of the circular mitochondrial genome. Mutations can therefore be present in only a subset of the mtDNA molecules, resulting in a heterogeneous pool of mtDNA, a situation referred to as heteroplasmy. Consequently, detection and quantification of variants requires extremely accurate tools, especially when this proportion is small. Additionally, the mitochondrial genome has pseudogenized into numerous copies within the nuclear genome over the course of evolution. These nuclear pseudogenes, named NUMTs, must be distinguished from genuine mtDNA sequences and excluded from the analysis.ResultsHere we describe a novel method, named MitoRS, in which the entire mitochondrial genome is amplified in a single reaction using rolling circle amplification. This approach is easier to setup and of higher throughput when compared to classical PCR amplification. Sequencing libraries are generated at high throughput exploiting a tagmentation-based method. Fine-tuned parameters are finally applied in the analysis to allow detection of variants even of low frequency heteroplasmy. The method was thoroughly benchmarked in a set of experiments designed to demonstrate its robustness, accuracy and sensitivity. The MitoRS method requires 5 ng total DNA as starting material. More than 96 samples can be processed in less than a day of laboratory work and sequenced in a single lane of an Illumina HiSeq flow cell. The lower limit for accurate quantification of single nucleotide variants has been measured at 1% frequency.ConclusionsThe MitoRS method enables the robust, accurate, and sensitive analysis of a large number of samples. Because it is cost effective and simple to setup, we anticipate this method will promote the analysis of mtDNA variants in large cohorts, and may help assessing the impact of mtDNA heteroplasmy on metabolic health, brain function, cancer progression, or ageing.

Dataset Information

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

Publications

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

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