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Updated: Oct 13, 2026

Simultaneous Mapping and Quantitation of Ribonucleotides in Human Mitochondrial DNA
Published on: November 14, 2017
Himito: a graph-based toolkit for mitochondrial genome analysis using long reads
Hang Su1, Yongqing Huang2, Timothy J Durham3,4,5
1Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA. suhang@broadinstitute.org.
Abstract:
Understanding the genetic and epigenetic regulation of mitochondrial DNA (mtDNA) is essential for elucidating mechanisms of aging and disease. Long-read sequencing can span the mitochondrial genome and capture base-modification signals, yet analytical tools remain limited. We developed Himito, a graph-based toolkit for analyzing mitochondrial genome using long reads. Himito filters reads originating from nuclear mitochondrial insertions (NUMTs), constructs a sequence graph to represent mtDNA diversity, assembles primary haplotypes, calls variants, and analyzes 5-methylcytosine (5mC) modifications within a unified framework. Benchmarking on reference datasets shows Himito achieves superior performance in assembly and variant calling compared with existing tools. Applied to the All of Us (AoU) v8 dataset, Himito identified pathogenic mtDNA variants, revealed population-scale haplogroup diversity, and uncovered age-related genetic and epigenetic patterns. These results demonstrate that long-read sequencing, combined with graph-based analysis, enables integrated characterization of mitochondrial genomic and epigenomic variation. Himito is available at https://github.com/broadinstitute/Himito .
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