Evaluation of mitochondrial DNA copy number estimation techniques
Evaluation of mitochondrial DNA copy number estimation techniques
Abstract Mitochondrial DNA copy number (mtDNA-CN), a measure of the number of mitochondrial genomes per cell, is a minimally invasive proxy measure for mitochondrial function and has been associated with several aging-related diseases. Although quantitative real-time PCR (qPCR) is the current gold standard method for measuring mtDNA-CN, mtDNA-CN can also be measured from genotyping microarray probe intensities and DNA sequencing read counts. To conduct a comprehensive examination on the performance of these methods, we use known mtDNA-CN correlates (age, sex, white blood cell count, Duffy locus genotype, incident cardiovascular disease) to evaluate mtDNA-CN calculated from qPCR, two microarray platforms, as well as whole genome (WGS) and whole exome sequence (WES) data across 1,085 participants from the Atherosclerosis Risk in Communities (ARIC) study and 3,489 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). We observe mtDNA-CN derived from WGS data is significantly more associated with known correlates compared to all other methods (p < 0.001). Additionally, mtDNA-CN measured from WGS is on average more significantly associated with traits by 5.6 orders of magnitude and has effect size estimates 5.8 times more extreme than the current gold standard of qPCR. We further investigated the role of DNA extraction method on mtDNA-CN estimate reproducibility and found mtDNA-CN estimated from cell lysate is significantly less variable than traditional phenol-chloroform-isoamyl alcohol (p = 5.44×10-4) and silica-based column selection (p = 2.82×10-7). In conclusion, we recommend the field moves towards more accurate methods for mtDNA-CN, as well as re-analyze trait associations as more WGS data becomes available from larger initiatives such as TOPMed.
Arking DE、Longchamps RJ、Newcomb CE、Sumpter JA、Pankratz N、Taylor KD、Rotter JI、Yang SY、Castellani CA、Lane J、Boerwinkle E、Grove ML、Guallar E
McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of MedicineMcKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of MedicineMcKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of MedicineMcKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of MedicineDepartment of Laboratory Medicine and Pathology, University of Minnesota Medical SchoolInstitute for Translational Genomics and Population Sciences, LABioMed and Department of Pediatrics, at Harbor-UCLA Medical CenterInstitute for Translational Genomics and Population Sciences, LABioMed and Department of Pediatrics, at Harbor-UCLA Medical CenterMcKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of MedicineMcKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of MedicineDepartment of Laboratory Medicine and Pathology, University of Minnesota Medical SchoolHuman Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston||Baylor College of Medicine, Human Genome Sequencing CenterHuman Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at HoustonDepartment of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health
基础医学生物科学研究方法、生物科学研究技术遗传学
Arking DE,Longchamps RJ,Newcomb CE,Sumpter JA,Pankratz N,Taylor KD,Rotter JI,Yang SY,Castellani CA,Lane J,Boerwinkle E,Grove ML,Guallar E.Evaluation of mitochondrial DNA copy number estimation techniques[EB/OL].(2025-03-28)[2025-08-03].https://www.biorxiv.org/content/10.1101/610238.点此复制
评论