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Long-read Sequencing Data Reveals Dynamic Evolution of Mitochondrial Genome Size and the Phylogenetic Utility of Mitochondrial DNA in Hercules Beetles (Dynastes; Scarabaeidae).

Brett MorganTzi-Yuan WangYi-Zhen ChenVictor MoctezumaOscar BurgosMy Hanh LeJen-Pan Huang
Published in: Genome biology and evolution (2022)
The evolutionary dynamics and phylogenetic utility of mitochondrial genomes (mitogenomes) have been of particular interest to systematists and evolutionary biologists. However, certain mitochondrial features, such as the molecular evolution of the control region in insects, remain poorly explored due to technological constraints. Using a combination of long- and short-read sequencing data, we assembled ten complete mitogenomes from ten Hercules beetles. We found large-sized mitogenomes (from 24 to 28 kb), which are among the largest in insects. The variation in genome size can be attributed to copy-number evolution of tandem repeats in the control region. Furthermore, one type of tandem repeat was found flanking the conserved sequence block in the control region. Importantly, such variation, which made up around 30% of the size of the mitogenome, may only become detectable should long-read sequencing technology be applied. We also found that, although different mitochondrial loci often inferred different phylogenetic histories, none of the mitochondrial loci statistically reject a concatenated mitochondrial phylogeny, supporting the hypothesis that all mitochondrial loci share a single genealogical history. We on the other hand reported statistical support for mito-nuclear phylogenetic discordance in 50% of mitochondrial loci. We argue that long-read DNA sequencing should become a standard application in the rapidly growing field of mitogenome sequencing. Furthermore, mitochondrial gene trees may differ even though they share a common genealogical history, and ND loci could be better candidates for phylogenetics than the commonly used COX1.
Keyphrases
  • genome wide
  • copy number
  • oxidative stress
  • mitochondrial dna
  • single cell
  • single molecule
  • dna methylation
  • genome wide association study
  • machine learning
  • genome wide association
  • big data
  • deep learning
  • amino acid