Detection and quantification of mitochondrial DNA deletions from next-generation sequence data.

BACKGROUND: Chromosomal deletions represent an important class of human genetic variation. Various methods have been developed to mine "next-generation" sequencing (NGS) data to detect deletions and quantify their clonal abundances. These methods have focused almost exclusively on the nuclear genome, ignoring the mitochondrial chromosome (mtDNA). Detecting mtDNA deletions requires special care. First, the chromosome's relatively small size (16,569 bp) necessitates the ability to detect extremely focal events. Second, the chromosome can be present at thousands of copies in a single cell (in contrast to two copies of nuclear chromosomes), and mtDNA deletions may be present on only a very small percentage of chromosomes. Here we present a method, termed MitoDel, to detect mtDNA deletions from NGS data.

RESULTS: We validate the method on simulated and real data, and show that MitoDel can detect novel and previously-reported mtDNA deletions. We establish that MitoDel can find deletions such as the "common deletion" at heteroplasmy levels well below 1%.

CONCLUSIONS: MitoDel is a tool for detecting large mitochondrial deletions at low heteroplasmy levels. The tool can be downloaded at https://mendel.gene.cwru.edu/laframboiselab/ .