1.0.0 • Published 1 year ago

m9a_p3x v1.0.0

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Custom Rom Mito A330

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First, the custom bioinformatics pipeline can work directly on archived FASTQ files of MitoChip data. This would allow a transition from a state-of-the-art technology to the next-generation sequencing, which are much more cost-effective, and even a relatively low-cost custom platform such as MitoChip v.2.0. Here, we have used a single bioinformatics pipeline to analyze the entire mitochondrial genome in a set of 24 DNA samples that include a series of known and novel heteroplasmic mitochondrial mutations, as well as large and subtle structural variants. All but one of the 24 samples were successfully analyzed at a high-resolution of base-by-base with regard to both known and novel variants. Results from other independent sequence analyses are compared for a cross-validation of the bioinformatics pipeline. Here, we demonstrate that MitoChip v.2.0 can also provide accurate analysis of the mitochondrial genome, which makes it possible to find more pathogenic mutations and possibly even discover new pathogenic mutations in the human mitochondrial DNA. Following this initial validation study, we plan to analyze a larger number of samples of diverse genetic backgrounds, and compare MitoChip data to data from Sanger sequencing, exon sequencing, or whole-exome sequencing.


An additional reason for developing a custom bioinformatics pipeline is that it provides the capability of performing new analysis of MitoChip v.2.0 data beyond that of previous software. The MitoChip v.2.0 arrays were originally designed with a limited number of probes to interrogate the most common mtDNA haplogroups with the standard Affymetrix protocols [ 2 ]. However, a relatively large number of aberrant patterns have been detected by comparing MitoChip data to those from conventional mitochondrial DNA sequence analysis. To address these issues, Zhou et al developed a bioinformatics pipeline that aligned the raw probe sequence against the revised Cambridge reference sequence (version rCRS), as well as to detect aberrations with reference to probes that are extended downstream of the previously defined range. This resulted in an improved detection of the problematic probe hybridization patterns [ 3 ]. As our custom bioinformatics pipeline is based on the known 1716 rCRS, the pipeline can be easily applied to new variant data without the need to modify the experimental design. Because some of the aberrant hybridization patterns observed from MitoChip v.2. 84d34552a1
1.0.0

1 year ago