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Record W4389727489 · doi:10.3389/fmicb.2023.1344877

Editorial: The significance of mitogenomics in mycology, volume II

2023· editorial· en· W4389727489 on OpenAlexafffund
Tomasz Kulik, Anne D. van Diepeningen, Georg Hausner

Bibliographic record

VenueFrontiers in Microbiology · 2023
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsUniversity of Manitoba
FundersWageningen University and ResearchNatural Sciences and Engineering Research Council of Canada
KeywordsMycologyVolume (thermodynamics)Medical mycologyBiologyComputational biologyMicrobiologyBotanyPhysics

Abstract

fetched live from OpenAlex

The Significance of Mitogenomics in Mycology, Volume II Mitochondria are essential organelles in most eukaryotic organisms including obligate aerobic fungi. The mitochondria house essential metabolic pathways and components required for oxidative phosphorylation. Their genomes or 'mitogenomes' have limited coding capacity and most genes required for the biogenesis, maintenance and metabolic activity of mitochondria are encoded within the nuclear genome (Calderone et al., 2015;Zardoya, 2020). Fungal mitogenomes are present in multiple copies and represented as circular molecules although they may exist as linear concatemers (Valach et al., 2011;Chen and Clark-Walker, 2018) that are compacted into mitochondrial nucleoids (Miyakawa, 2017). In fungi, mitogenomes range from 12.055 kb to > 500 kb (James et al., 2013;Liu et al., 2020), the size variation can be due to gene content differences, intron mobility, size variation in intergenic spacers, and in some instances the proliferation of repeats (Liu et al., 2020).Fungal mitogenomes encode for components needed for translation (small and large ribosomal subunit RNAs, a set of tRNAs), and protein components involved in the oxidative phosphorylation pathway. This includes protein components of Complex I (subunits of NADH dehydrogenase: nad1 to nad6 and nad4L, components of Complex III (cob) and Complex IV (cox1, cox2, and cox3), plus some members of Complex V (ATP synthase: atp6, atp8, and usually atp9). Some fungal lineages lost the typical Complex I genes (e.g., members of the Taphrinomycota and Sacharomycetales, Schikora-Tamarit et al., 2021;Wolters et al., https://www.frontiersin.org/articles/10.3389/fmicb.2023.1268944/full) and some fungal mitogenomes lost some of the ATP synthase subunit genes (Zubaer et al., 2019;Mukhopadhyay and Hausner, https://www.frontiersin.org/articles/10.3389/fmicb.2023.1240407/full). Fungal mitogenomes frequently encode a ribosomal protein (rps3; Freel et al., 2015) and sometimes the RNA (rnpB gene) component for RNaseP (Lang, 2018). Mitogenomes can include orphan genes (genes with unknown function and no homologs), plasmid derived components (Himmelstrand et al., https://www.frontiersin.org/articles/10.3389/fmicb.2023.1159811/full), and there are records of mitogenomes that encode N-acetyltransferases and amino-transferases (Wai et al., 2019).Across the Mycota, mitogenomes are variable due to recombination events promoted by repeats and by the presence and activities of mobile elements such group I and group II introns and intron-encoded proteins (IEPs) (e.g. Aguileta et al., 2014;Repar and Warnecke, 2017;Wu and Hao, 2019;Fonseca et al. 2021). Intron encoded proteins for group I introns tend to be homing endonucleases and for group II introns reverse transcriptase-like proteins and these IEPs catalyze intron mobility to cognate intron-less alleles (Belfort et al., 2002). The IEPs can also be involved in aiding the removal of the self-splicing intron RNAs from precursor transcripts by stabilizing intron RNA folds that are splicing competent (Prince et al., 2022). Mitochondrial introns are gained and lost and their impact on gene function and phenotypes are still a subject for debate (Goddard and Burt, 1999;Chatre and Ricchetti, 2014;Rudan et al., 2018).Mitogenome sequences may provide a source for molecular markers for fungal identification and core protein coding gene sequences can be applied towards resolving evolutionary relationships (Kanzi et al., 2016;Kulik et al., 2020;Kouvelis et al., 2023;Castrillo et al., Mitochondrial gene expression is assumed to be regulated at the post-transcriptional level. One aspect of fungal mitochondrial gene expression that is different from most metazoans is the removal of introns from the transcripts that encode products that are essential for translation (rRNAs) and for respiration and energy production (Lipinski et al. 2010;Dujon 2020). The removal of introns is facilitated by IEPs and various nuclear encoded protein factors (Mukhopadhyay and Hausner, 2021;Prince et al., 2022). Mitochondrial ribogenesis, processing of mitogenome derived transcripts, RNA degradation/turnover, and mRNA translation requires many nuclear encoded factors (De Silva et al., 2017;Golik, 2023). The reliance on nuclear elements for mitochondrial gene expression links organellar function with nuclear cues in response to environmental and developmental factors.Wolters et al. https://www.frontiersin.org/articles/10.3389/fmicb.2023.1268944/full observed that among the various Orders within the Saccharomycotina the protein coding genes for Complex I were lost independently in several lineages. They propose that variations in the mitochondrially-encoded protein genes could be driven by evolutionary pressures at the nuclear level. Mukhopadhyay and Hausner, https://www.frontiersin.org/articles/10.3389/fmicb.2023.1240407/full observed that among members of the Ophiostomatales mitogenomes there are some biases with regards to intron insertion sites and genes that are more likely to be intron-rich, but there are no conserved introns (except for mL2450 that encodes for RPS3). If introns are beneficial (Belfort, 2017;Rudan et al., 2018) for fine-tuning mitochondrial gene regulation, it is not based on specific introns, instead the mitogenome intron complement is composed of various introns (located at different sites) that are "functionally" redundant. The reliance on nuclear factors for organellar intron splicing impacts mitonuclear compatibilities (or incompatibilities) and potentially imposes reproductive barriers, thereby they could be promoting speciation events (Dujon, 2020). There are still many questions that need to be addressed with regards to mitonuclear interactions and the associated "cross talk" that impact mitogenome sequence diversity and gene expression (Wu et al., 2022).Codon usage or biases for fungal mitochondrial genes so far has not been explored, Li et al. https://www.frontiersin.org/articles/10.3389/fmicb.2023.1134228/full demonstrate that there are indeed synonymous codon preferences and among the examined Amanita species these appear to be under selection. These findings add one more criterion that can influence mitochondrial protein coding sequence diversity as codon usage may have implications for environmental adaptation of mitochondrial genes related to energy metabolism. This research topic in its second volume presents exciting new findings with regards to fungal mitogenomes and mtDNA gene expression, plus their utility in resolving taxonomic issues, and providing insights into impact of nuclear mitochondrial interactions that may in part shape mitochondrial gene evolution.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.024
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.001
Science and technology studies0.0030.003
Scholarly communication0.0070.005
Open science0.0030.002
Research integrity0.0120.014
Insufficient payload (model declined to judge)0.0240.018

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.218
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes2
Has abstractyes

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