Evidence map›Paper›PMID 35369492›Full record

ArticleFrontiers in microbiology2022

Refining Mitochondrial Intron Classification With ERPIN: Identification Based on Conservation of Sequence Plus Secondary Structure Motifs.

Samuel Prince, Carl Munoz, Fannie Filion-Bienvenue, Pierre Rioux, Matt Sarrasin, B Franz Lang

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
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  5. The mitogenomes ofFrontiers in microbiology · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Samuel PrinceDépartement de Biochimie, Robert Cedergren Center for Bioinformatics and Genomics, Université de Montréal, Montréal, QC, Canada.
Carl MunozDépartement de Biochimie, Robert Cedergren Center for Bioinformatics and Genomics, Université de Montréal, Montréal, QC, Canada.
Fannie Filion-BienvenueDépartement de Biochimie, Robert Cedergren Center for Bioinformatics and Genomics, Université de Montréal, Montréal, QC, Canada.
Pierre RiouxDépartement de Biochimie, Robert Cedergren Center for Bioinformatics and Genomics, Université de Montréal, Montréal, QC, Canada.
Matt SarrasinDépartement de Biochimie, Robert Cedergren Center for Bioinformatics and Genomics, Université de Montréal, Montréal, QC, Canada.
B Franz LangDépartement de Biochimie, Robert Cedergren Center for Bioinformatics and Genomics, Université de Montréal, Montréal, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 methods using ERPIN sequence profiles were initially developed in 2007. Here we present a refinement of search models and alignments using the now abundant publicly available fungal mtDNA sequences. In addition, we have tested in how far members of the originally proposed sub-groups are clearly distinguished and validated by our computational approach. We confirm clearly distinct mitochondrial Group I sub-groups IA1, IA3, IB3, IC1, IC2, and ID. Yet, IB1, IB2, and IB4 ERPIN models are overlapping substantially in predictions, and are therefore combined and reported as IB. We have further explored the conversion of our ERPIN profiles into covariance models (CM). Current limitations and prospects of the CM approach will be discussed.

Indexed as

covariance modelsERPINgroup Iinfernalmitochondrial intronsRNA structure

Identifiers

PMID35369492
PMCPMC8971849

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.