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With the rapid increase of sequenced metazoan mitochondrial genomes, a detailed manual annotation is becoming more and more infeasible. While it is easy to identify the approximate location of protein-coding genes within mitogenomes, the peculiar processing of mitochondrial transcripts, however, makes the determination of precise gene boundaries a surprisingly difficult problem. We have analyzed the properties of annotated start and stop codon positions in detail, and use the inferred patterns to devise a new method for predicting gene boundaries in de novo annotations. Our method benefits from empirically observed prevalances of start/stop codons and gene lengths, and considers the dependence of these features on variations of genetic codes. Albeit not being perfect, our new approach yields a drastic improvement in the accuracy of gene boundaries and upgrades the mitochondrial genome annotation server MITOS to an even more sophisticated tool for fully automatic annotation of metazoan mitochondrial genomes. PMC6847864

During the last decades, mitochondria and their DNA have become a hot topic of research due to their essential roles which are necessary for cells survival and pathology. In this study, multiple methods have been developed to help with the understanding of mitochondrial DNA and its evolution. These methods tackle two essential problems in this area: the accurate annotation of protein-coding genes and mitochondrial genome rearrangements. Mitochondrial genome sequences are published nowadays with increasing pace, which creates the need for accurate and fast annotation tools that do not require manual intervention. In this work, an automated pipeline for fast de-novo annotation of mitochondrial protein-coding genes is implemented. The pipeline includes methods for enhancing multiple sequence alignment, detecting frameshifts and building protein profiles guided by phylogeny. The methods are tested on animal mitogenomes available in RefSeq, the comparison with reference annotations highlights the high quality of the produced annotations. Furthermore, the frameshift method predicted a large number of frameshifts, many of which were unknown. Additionally, an eficient partially-local alignment method to investigate genomic rearrangements in mitochondrial genomes is presented in this study. The method is novel and introduces a partially-local dynamic programming algorithm on three sequences around the breakpoint region. Unlike the existing methods which study the rearrangement at the genes order level, this method allows to investigate the rearrangement on the molecular level with nucleotides precision. The algorithm is tested on both artificial data and real mitochondrial genomic sequences. Surprisingly, a large fraction of rearrangements involve the duplication of local sequences. Since the implemented approach only requires relatively short parts of genomic sequence around a breakpoint, it should be applicable to non-mitochondrial studies as well.

Mitochondrial genome sequences are available in large number and new sequences become published nowadays with increasing pace. Fast, automatic, consistent, and high quality annotations are a prerequisite for downstream analyses. Therefore, we present an automated pipeline for fast de novo annotation of mitochondrial protein-coding genes. The annotation is based on enhanced phylogeny-aware hidden Markov models (HMMs). The pipeline builds taxon-specific enhanced multiple sequence alignments (MSA) of already annotated sequences and corresponding HMMs using an approximation of the phylogeny. The MSAs are enhanced by fixing unannotated frameshifts, purging of wrong sequences, and removal of non-conserved columns from both ends. A comparison with reference annotations highlights the high quality of the results. The frameshift correction method predicts a large number of frameshifts, many of which are unknown. A detailed analysis of the frameshifts in nad3 of the Archosauria-Testudines group has been conducted.

Background: Genomic DNA frequently undergoes rearrangement of the gene order that can be localized by comparing the two DNA sequences. In mitochondrial genomes different mechanisms are likely at work, at least some of which involve the duplication of sequence around the location of the apparent breakpoints. We hypothesize that these different mechanisms of genome rearrangement leave distinctive sequence footprints. In order to study such effects it is important to locate the breakpoint positions with precision. Results: We define a partially local sequence alignment problem that assumes that following a rearrangement of a sequence F, two fragments L, and R are produced that may exactly fit together to match F, leave a gap of deleted DNA between L and R, or overlap with each other. We show that this alignment problem can be solved by dynamic programming in cubic space and time. We apply the new method to evaluate rearrangements of animal mitogenomes and find that a surpr isingly large fraction of these events involved local sequence duplications. Conclusions: The partially local sequence alignment method is an effective way to investigate the mechanism of genomic rearrangement events. While applied here only to mitogenomes there is no reason why the method could not be used to also consider rearrangements in nuclear genomes.

Remolding of tRNAs is a well-documented process in mitochondrial genomes that changes the identity of a tRNA. It involves a duplication of a tRNA gene, a mutation that changes the anticodon and the loss of the ancestral tRNA gene. The net effect is a functional tRNA that is more closely related to tRNAs of a different alloacceptor family than to tRNAs with the same anticodon in related species. Beyond being of interest for understanding mitochondrial tRNA function and evolution, tRNA remolding events can lead to artifacts in the annotation of mitogenomes and thus in studies of mitogenomic evolution. Therefore, it is important to identify and catalog these events. Here we describe novel methods to detect tRNA remolding in large-scale data sets and apply them to survey tRNA remolding throughout animal evolution. We identify several novel remolding events in addition to the ones previously mentioned in the literature. A detailed analysis of these remoldings showed that many of them are derived from ancestral events.