Accurate mitochondrial DNA sequencing using off-target reads provides a single test to identify pathogenic point...

Area of Science:

• Genetics
• Molecular Biology
• Genomics

Background:

• Mitochondrial disorders are a frequent cause of inherited metabolic diseases, stemming from mutations in either mitochondrial DNA or nuclear DNA.
• Current diagnostic methods involve stepwise, time-consuming, and expensive targeted resequencing of mitochondrial and nuclear genes.
• Whole-exome sequencing (WES) data has shown potential for identifying mitochondrial DNA variations, suggesting a unified diagnostic approach.

Purpose of the Study:

• To evaluate the feasibility of obtaining reliable mitochondrial DNA sequences from off-target reads in WES data.
• To compare the accuracy of WES-derived mitochondrial DNA sequences with conventional Sanger sequencing.
• To explore the potential of WES for comprehensive screening of both nuclear and mitochondrial DNA for pathogenic mutations.

Main Methods:

• Comparison of mitochondrial DNA sequences derived from off-target exome reads against conventional Sanger sequencing.
• Analysis of data from 46 subjects utilizing three distinct WES capture kits.
• Assessment of sequence coverage, heteroplasmy levels, and sequencing error rates.

Main Results:

• Mitochondrial DNA sequences were reliably obtained across three different WES capture kits.
• Sequence coverage demonstrated a correlation with the amount of mitochondrial DNA in the initial sample.
• Accurate determination of heteroplasmy levels was possible using variant and total read depths, with error rates comparable to Sanger sequencing at a minimum 20-fold read depth.

Conclusions:

• WES can serve as a single diagnostic test for screening pathogenic mutations in both nuclear and mitochondrial DNA genes.
• Off-target mitochondrial DNA reads offer additional benefits, including quality control, assessment of maternal ancestry, and ethnic origin determination.
• This approach facilitates genetic disease association studies previously unfeasible with existing WES datasets.