Abstract
Background: Mitochondrial DNA sequences are used for inter- and intra-specific comparison analysis in ecological studies. Instead of using short regions as marker sequences, analyzing longer regions, such as whole mitochondrial DNA sequences, can improve the accuracy of such studies by increasing the likelihood of detecting species or specific sequences. However, current methods for sequencing whole mitochondrial DNA require primer design for each target species or long fragments of genomic DNA as a PCR template. We developed a method and accompanying tool for PCR-based long-read sequencing of whole mitochondrial DNA, named MitoCOMON, which is applicable to wide-target taxonomic clades and partially digested template DNA. Results: PCR amplification of whole mitochondrial DNA as four fragments facilitates the successful assembly of the whole mitochondrial DNA sequence, even when a sample is a mixture of multiple species or partially degraded. The tool that we developed consists of two modules that can design a primer set for species in a target taxonomic clade and assemble the whole mitochondrial DNA sequence from amplicons which were amplified using the designed primer set. Primer sets were designed for mammal and bird species, which showed a high success rate for whole mitochondrial DNA sequencing with high sequence accuracy. Multiple whole mitochondrial DNA sequences were also assembled from samples mixed with the genomic DNA of several species without forming chimeric sequences. In addition to the accuracy, some assembled sequences also retained a long duplication at the D-loop region, suggesting that the method addresses large rearrangements. Compared with a method that amplifies the whole mitochondrial DNA as a single amplicon, our method was effective for partially degraded samples. Conclusions: Our method and accompanying tool, named MitoCOMON, enables an easier acquisition of whole mitochondrial DNA sequences from samples with some DNA degradation without designing species-specific primers. This approach can enhance the accessibility of mitochondrial genomic data and is expected to improve the resolution of ecological analyses, including accurate species identification and individual-level discrimination.