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A Scalable Framework for Harmonized mtDNA Analysis Across Diverse Biobanks

Schecter, D. R.; Lee, S. S.; Vimal, T.; Lahoti, Y.; Goncalves, V. F.; Retallick-Townsley, K.; Pang, J.; Guvenek, A.; Preuss, M.; Tinker, R. J.; Morava, E.; Kozicz, T.; Hirano, M.; Ganesh, J.; Naini, A.; Liang, J.; Davis, L.

2026-08-25 genetic and genomic medicine
10.64898/2026.08.21.26361041 medRxiv
Show abstract

Mitochondrial DNA (mtDNA) is increasingly recognized as an important contributor to human disease and population variation, yet most genomic biobanks do not provide standardized mtDNA variant datasets despite abundant mitochondrial sequencing reads in existing whole exome and whole-genome sequencing data. We developed a scalable framework based on the Mitoverse mtDNA Server 2 Fusion workflow to generate harmonized, analysis-ready mtDNA resources across diverse biobank infrastructures. The framework was implemented in the Mount Sinai Million Health Discoveries Program (54,151 participants) using the native Nextflow workflow and adapted for the All of Us Research Program (197,361 participants) using a custom cloud implementation that preserved the same analytical strategy. Across 251,512 participants, the framework generated standardized mtDNA datasets containing 12.9 million variant observations suitable for downstream genomic and electronic health record linked analyses. This framework enables reproducible, population-scale mitochondrial genomics across institutional and national biobanks without requiring additional sequencing or development of new variant calling methods.

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