2Center for Molecular and Mitochondrial Medicine and Genetics, University of California, Irvine, CA, USA
3Department of Developmental and Cell Biology, University of California, Irvine, CA, USA
4Department of Pathology, University of California, Irvine, CA, USA
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 (≥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 ≥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.
Mitochondria are the “powerhouses” of human cells and disturbances in mitochondrial functions have been implicated in a wide range of human diseases, including cancer, heart disease, diabetes, Alzheimer's disease, and Parkinson's disease (1). The human mitochondrial genome, which is a circular DNA molecule that consists of 16,569 bp, encodes 13 polypeptides that are components of the electron transport chain (ETC), as well as 22 tRNAs and two rRNAs that contribute to mitochondrial protein synthesis. A variety of human diseases are directly associated with mitochondrial DNA (mtDNA) mutations and hundreds of putative pathogenic mtDNA variants have been identified (2,3).
Mitochondrial DNA is present in hundreds to thousands of copies per cell and also has a very high mutation rate. New mtDNA mutations arise in cells, coexist with wild-type mtDNAs (heteroplasmy), and segregate randomly during cell division (2). The vast majority of deleterious mtDNA point mutations are heteroplasmic and their mutant load can vary significantly among different tissues, even in the same subject. Moreover, different percentages of mutant mtDNA can be associated with completely distinct clinical manifestations (3). Currently, it is challenging to identify all of mutations in the mitochondrial genome and simultaneously quantify the mtDNA heteroplasmy levels. In addition to the molecular diagnosis of mitochondrial diseases, there is a rapidly growing need for methods to analyze mtDNA variants for other applications, including evolutionary and forensic studies (1,4). Therefore, it is critical that mitochondrial genome sequences can be acquired and detected in a reliable, high-throughput, and cost-effective manner, especially in samples with clinically relevant levels of mtDNA heteroplasmy.
Currently, the two most popular complete mitochondrial genome sequencing methods are direct sequencing and the MitoChip. However, these two methods are neither sensitive nor specific enough to detect mtDNA heteroplasmy (5). Methods used for mitochondrial genome–wide heteroplasmic position screening include denaturing HPLC (6), Surveyor Nuclease digestion (7), and high-resolution melt (HR M) profiling (8). Although these methods can be used to detect mtDNA heteroplasmy, they cannot localize or quantify the heteroplasmic position(s). Several other techniques have been developed for the specific quantification of mtDNA heteroplasmy levels. These methods include PCR-RFLP analysis (9), allele-specific oligonucleotide dot-blot analysis (10), real-time amplification refractory mutation system quantitative PCR (11), and pyrosequencing (12). However, these methods are labor-intensive and can only be used to analyze a known mutation.
Recently developed parallel sequencing methods (13) have the capacity for massive sequencing and offer a highly robust and less labor-intensive approach to genome-wide sequencing. Currently, there are four next-generation sequencing platforms: the Illumina Genome Analyzer (GA; San Diego, CA, USA), the Roche 454 Genome Sequencer FLX system (Indianapolis, IN, USA), the Applied Biosystems SOLiD system (Foster City, CA, USA), and the Helicos True Single Molecule Sequencing system (Cambridge, MA, USA). The small size of the human mitochondrial genome and the resulting high coverage for each nucleotide position generated by parallel sequencing should enable the detection of low levels of mtDNA heteroplasmy. Previously, 454 sequencing was used to generate 34.9-fold coverage of the mtDNA from ~0.3-g bone of a 38,000-year-old Neanderthal individual (14). The Illumina GA, coupled with target microarray-based capture, was successfully employed to re-sequence the entire mitochondrial genome (coverage >2,900) and the exons of 362 nuclear genes encoding mitochondrial proteins (15). However, neither of these studies investigated the capability of the technologies for heteroplasmy identification and quantification. In the current study, we utilized the Illumina GA system to sequence the entire human mitochondrial genome and determined the sensitivity and specificity of this platform for the analysis of heteroplasmic mtDNA samples.Materials and methods Subjects and DNA isolation
NS01 and NS09 are two human subjects who were recruited in our previous studies. The complete mtDNA sequences of NS01 and NS09 were determined previously. Total genomic DNA was extracted from peripheral blood using the QIAamp DNA extraction kit (QIAGEN, Valencia, CA, USA).