Abstract
BackgroundChromosomal 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.ResultsWe 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%.ConclusionsMitoDel is a tool for detecting large mitochondrial deletions at low heteroplasmy levels. The tool can be downloaded at http://mendel.gene.cwru.edu/laframboiselab/.
Highlights
Chromosomal deletions represent an important class of human genetic variation
To simulate an experiment generating R pairedend Illumina reads from a sample with a given deletion present in proportion p of Mitochondrial DNA (mtDNA) copies, we first modified the .fasta file containing the revised Cambridge Reference Sequence [16], removing a string of bases corresponding to the desired deletion
When designing Next-generation sequencing (NGS) experiments for this purpose, researchers must take into account the high numbers of nuclear genome reads present in the sequencing data, which will decrease the average number of reads per mitochondrial base position
Summary
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). Human genetic variation takes many forms, including single nucleotide variants, small insertions/deletions, larger chromosomal gains and losses, and inter-chromosomal translocations. Robust and accurate algorithms to detect all forms of human genetic variation from the ever-increasing number of large genomic data sets are necessary. The vast majority of human DNA variant-detection algorithms focus exclusively on the 24 chromosomes (22 autosomes, X, and Y) comprising the nuclear genome. The mutation rate of the mitochondrial genome is much higher than that of the nuclear genome
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