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Detection and quantification of mitochondrial DNA deletions from next-generation sequence data.
Colleen M Bosworth1, Sneha Grandhi1, Meetha P Gould1
1Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, 44106, USA.
BMC Bioinformatics
|October 27, 2017
Summary
MitoDel is a new tool that detects large mitochondrial DNA deletions from next-generation sequencing data. It can identify these deletions even when they are present at very low levels in cells.
Area of Science:
- Genomics
- Molecular Biology
- Bioinformatics
Background:
- Chromosomal deletions are a significant source of human genetic variation.
- Existing next-generation sequencing (NGS) methods primarily focus on nuclear genome deletions, neglecting mitochondrial DNA (mtDNA).
- Detecting mtDNA deletions presents unique challenges due to the mtDNA's small size and high copy number per cell.
Purpose of the Study:
- To introduce MitoDel, a novel computational method for detecting large deletions in the mitochondrial genome using NGS data.
- To address the specific challenges associated with identifying mtDNA deletions at low heteroplasmy levels.
Main Methods:
- Development of a specialized bioinformatics tool, MitoDel.
- Application of MitoDel to analyze simulated and real-world NGS datasets.
Main Results:
- MitoDel successfully identifies both novel and previously documented mtDNA deletions.
- The method demonstrates sensitivity in detecting deletions, such as the common deletion, at heteroplasmy levels below 1%.
Conclusions:
- MitoDel is an effective tool for the detection of large mitochondrial deletions.
- The tool is capable of identifying deletions present at low heteroplasmy levels.
- MitoDel is publicly available for download.
