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Characterization of human mitochondrial genome sequences is important for the molecular diagnosis of mitochondrial diseases, especially in samples with a low level of mitochondrial DNA (mtDNA) heteroplasmy (>or=5%). Currently, no single methodology can simultaneously determine complete mtDNA sequences, identify mitochondrial genome-wide heteroplasmies, and quantify mtDNA heteroplasmy levels. The deep sampling inherent in "next-generation" sequencing approaches should enable the efficient detection of low-level DNA heteroplasmies and address this need. Herein, we used the Illumina Genome Analyzer to re-sequence human mtDNA samples from two subjects that were combined at five different ratios (1:99, 5:95, 10:90, 20:80, and 50:50). We assessed the sensitivity, specificity, and accuracy of this system, and our results show that mtDNA heteroplasmies >or=5% were detected 100% of the time with virtually no false positives and that the estimates of mtDNA heteroplasmy levels were remarkably close to the theoretical values (correlation coefficient = 0.96). Therefore, parallel sequencing provides a simple, high-throughput, and cost-effective platform for mitochondrial genome sequencing with sensitivity and specificity for mtDNA heteroplasmy detection.
Tang et al. (Thu,) studied this question.