Mitochondrial genome annotation with MFannot: a critical analysis of gene identification and gene model prediction

Abstract

Compared to nuclear genomes, mitochondrial genomes (mitogenomes) are small and usually code for only a few dozen genes. Still, identifying genes and their structure can be challenging and time-consuming. Even automated tools for mitochondrial genome annotation often require manual analysis and curation by skilled experts. The most difficult steps are (i) the structural modelling of intron-containing genes; (ii) the identification and delineation of Group I and II introns; and (iii) the identification of moderately conserved, non-coding RNA (ncRNA) genes specifying 5S rRNAs, tmRNAs and RNase P RNAs. Additional challenges arise through genetic code evolution which can redefine the translational identity of both start and stop codons, thus obscuring protein-coding genes. Further, RNA editing can render gene identification difficult, if not impossible, without additional RNA sequence data. Current automated mito- and plastid-genome annotators are limited as they are typically tailored to specific eukaryotic groups. The MFannot annotator we developed is unique in its applicability to a broad taxonomic scope, its accuracy in gene model inference, and its capabilities in intron identification and classification. The pipeline leverages curated profile Hidden Markov Models (HMMs), covariance (CMs) and ERPIN models to better capture evolutionarily conserved signatures in the primary sequence (HMMs and CMs) as well as secondary structure (CMs and ERPIN). Here we formally describe MFannot, which has been available as a web-accessible service (https://megasun.bch.umontreal.ca/apps/mfannot/) to the research community for nearly 16 years. Further, we report its performance on particularly intron-rich mitogenomes and describe ongoing and future developments.

Organellar genomic characterization of Anunuuluaehu liula representing a new genus and species of Phyllophoraceae (Gigartinales, Rhodophyta) from the mesophotic zone of Hawai‘i

“…We provided an additional reference with complete mitochondrial genomes of Rhodymeniophycidae (Table S2 in the Supporting Information) to assemble the mitochondrial genome. Preliminary annotations for both organellar genomes were acquired using MFannot (Lang et al., 2023). GeSeq (Tillich et al., 2017), which also supports the use of tRNAscan‐SE v2.0.7 (Chan & Lowe, 2019), was utilized with default settings to corroborate the protein‐coding genes rRNA, and tRNA using published Gigartinales organellar genomes as its BLAT (BLAST‐Like Alignment Tool) reference.…”

A new and widespread group of fish apicomplexan parasites

“…A full mitochondrion genome and a preliminary apicoplast genome were identified and these contigs were used as seed inputs for GetOrganelle v1.7.7 14 to generate a complete and circularized apicoplast genome. MFANNOT v1.36 40 was used to annotate both the apicoplast and mitochondrion genomes using genetic code 4 as done previously with apicomplexan organelles 3 . OrganellarGenomeDRAW v1.3.1 was used to visualize the organelle genomes 41 .…”

High-quality genome assemblies of four members of thePodospora anserinaspecies complex

“…Mitochondrial annotation was done with the online version of MFannot (Lang et al, 2023), setting the genetic code to 4 (https://megasun.bch.umontreal.ca/apps/mfannot/; consulted during the second half of July 2023). The resulting tbl format was modified with the script MFannot4ncbi.py to make it closer to NCBI requirements, and further transformed to a gff3 file with the script tbl2gff.py (available at https://github.com/SLAment/Genomics/blob/master/GenomeAnnotation).…”