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Digital Polymerase Chain Reaction for Assessment of Mutant Mitochondrial Carry-over after Nuclear Transfer for In Vitro Fertilization.

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BACKGROUND The quantification of mitochondrial DNA heteroplasmy for the diagnosis of mitochondrial disease or after mitochondrial donation, is performed mainly using next-generation sequencing strategies (NGS). Digital PCR (dPCR) has the… Click to show full abstract

BACKGROUND The quantification of mitochondrial DNA heteroplasmy for the diagnosis of mitochondrial disease or after mitochondrial donation, is performed mainly using next-generation sequencing strategies (NGS). Digital PCR (dPCR) has the potential to offer an accurate alternative for mutation load quantification. METHODS We assessed the mutation load of 23 low-input human samples at the m.11778 locus, which is associated with Leber's hereditary optic neuropathy (LHON) using 2 droplet digital PCR platforms (Stilla Naica and Bio-Rad QX200) and the standard NGS strategy. Assay validation was performed by analyzing a titration series with mutation loads ranging from 50% to 0.01%. RESULTS A good concordance in mutation rates was observed between both dPCR techniques and NGS. dPCR established a distinctly lower level of background noise compared to NGS. Minor alleles with mutation loads lower than 1% could still be detected, with standard deviations of the technical replicates varying between 0.07% and 0.44% mutation load. Although no significant systematic bias was observed when comparing dPCR and NGS, a minor proportional bias was detected. A slight overestimation of the minor allele was observed for the NGS data, most probably due to amplification and sequencing errors in the NGS workflow. CONCLUSION dPCR has proven to be an accurate tool for the quantification of mitochondrial heteroplasmy, even for samples harboring a low mutation load (<1%). In addition, this alternative technique holds multiple benefits compared to NGS (e.g., less hands-on time, more straightforward data-analysis, and a lower up-front capital investment).

Keywords: mutation load; chain reaction; polymerase chain; digital polymerase; mutation

Journal Title: Clinical chemistry
Year Published: 2021

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