Abstract
Massive parallel sequencing technologies are promising a highly sensitive detection of low-level mutations, especially in mitochondrial DNA (mtDNA) studies. However, processes from DNA extraction and library construction to bioinformatic analysis include several varying tasks. Further, there is no validated recommendation for the comprehensive procedure. In this study, we examined potential pitfalls on the sequencing results based on two-person mtDNA mixtures. Therefore, we compared three DNA polymerases, six different variant callers in five mixtures between 50% and 0.5% variant allele frequencies generated with two different amplification protocols. In total, 48 samples were sequenced on Illumina MiSeq. Low-level variant calling at the 1% variant level and below was performed by comparing trimming and PCR duplicate removal as well as six different variant callers. The results indicate that sensitivity, specificity, and precision highly depend on the investigated polymerase but also vary based on the analysis tools. Our data highlight the advantage of prior standardization and validation of the individual laboratory setup with a DNA mixture model. Finally, we provide an artificial heteroplasmy benchmark dataset that can help improve somatic variant callers or pipelines, which may be of great interest for research related to cancer and aging.
Highlights
One of the most precious benefits of massive parallel sequencing (MPS) technologies in the field of mitochondrial DNA research is the increase in sensitivity for detecting heteroplasmy, a state where at least two different mtDNA molecules are present in one mitochondrion, cell, or tissue
The DNA of two individuals was mixed at five different ratios (M1 (1:2), M2 (1:10), M3 (1:50), M4 (1:100), M5 (1:200)), which was amplified by three different enzymes
We investigated the impact of bioinformatic quality control (QC) steps on the data quality of mitochondrial genome sequences by performing adapter trimming and quality filtering, as well as duplication removal
Summary
One of the most precious benefits of massive parallel sequencing (MPS) technologies in the field of mitochondrial DNA (mtDNA) research is the increase in sensitivity for detecting heteroplasmy, a state where at least two different mtDNA molecules are present in one mitochondrion, cell, or tissue. While the detection level is limited to approximately 10% with former gold standard Sanger-type sequencing [1,2], the abundance of resulting sequencing reads from a single run derived from MPS platforms allows for a much more precise estimation of minor variant allele frequencies. The most widely used sequencing technology stems from Illumina. The method is based on the sequencing-by-synthesis approach. Illumina uses fluorescently labeled nucleotides to sequence library clusters on a flow cell surface. Incorporated deoxynucleoside triphosphates (dNTPs) are visualized by an optics-based technology identifying the signal intensity of the dye
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