biostudies-literatureUnknown13Prince SMitochondrial genomes-in particular those of fungi-often encode genes with a large number of Group I and Group II introns that are conserved at both the sequence and the RNA structure level. They provide a rich resource for the investigation of intron and gene structure, self- and protein-guided splicing mechanisms, and intron evolution. Yet, the degree of sequence conservation of introns is limited, and the primary sequence differs considerably among the distinct intron sub-groups. It makes intron identification, classification, structural modeling, and the inference of gene models a most challenging and error-prone task-frequently passed on to an "expert" for manual intervention. To reduce the need for manual curation of intron structures and mitochondrial gene models, computational methFrontiers in microbiology866187https://www.ebi.ac.uk/biostudies/studies/S-EPMC8971849biostudies-literatureRefining Mitochondrial Intron Classification With ERPIN: Identification Based on Conservation of Sequence Plus Secondary Structure Motifs.PMC8971849Prince SSarrasin MRioux PFilion-Bienvenue FLang BFMunoz CfalseRefining Mitochondrial Intron Classification With ERPIN: Identification Based on Conservation of Sequence Plus Secondary Structure Motifs.Mitochondrial genomes-in particular those of fungi-often encode genes with a large number of Group I and Group II introns that are conserved at both the sequence and the RNA structure level. They provide a rich resource for the investigation of intron and gene structure, self- and protein-guided splicing mechanisms, and intron evolution. Yet, the degree of sequence conservation of introns is limited, and the primary sequence differs considerably among the distinct intron sub-groups. It makes intron identification, classification, structural modeling, and the inference of gene models a most challenging and error-prone task-frequently passed on to an "expert" for manual intervention. To reduce the need for manual curation of intron structures and mitochondrial gene models, computational meth2022-01-01T00:00:00Z20222025-04-04T12:57:52.901Z2025-04-04T12:57:52.901ZS-EPMC89718493536949210.3389/fmicb.2022.866187