MétaCan
Menu
Back to cohort
Record W3203733810 · doi:10.1111/1462-2920.15792

Dynamic evolution of eukaryotic mitochondrial and nuclear genomes: a case study in the gourmet pine mushroom <i>Tricholoma matsutake</i>

2021· article· en· W3203733810 on OpenAlexaff
Shu Zhang, Xue Bai, Li‐Yuan Ren, Huihui Sun, Hui‐Ping Tang, Lu‐Min Vaario, Jianping Xu, Yongjie Zhang

Bibliographic record

VenueEnvironmental Microbiology · 2021
Typearticle
Languageen
FieldMedicine
TopicFungal Biology and Applications
Canadian institutionsMcMaster University
FundersNational Natural Science Foundation of China
KeywordsBiologyMitochondrial DNAHeteroplasmyGenomeNuclear DNANuclear geneGeneticsGenePhylogenetic treeIntronDNAGenome sizePhylogeneticsEvolutionary biology

Abstract

fetched live from OpenAlex

Fungi, as eukaryotic organisms, contain two genomes, the mitochondrial genome and the nuclear genome, in their cells. How the two genomes evolve and correlate to each other is debated. Herein, taking the gourmet pine mushroom Tricholoma matsutake as an example, we performed comparative mitogenomic analysis using samples collected from diverse locations and compared the evolution of the two genomes. The T. matsutake mitogenome encodes 49 genes and is rich of repetitive and non-coding DNAs. Six genes were invaded by up to 11 group I introns, with one cox1 intron cox1P372 showing presence/absence dynamics among different samples. Bioinformatic analyses suggested limited or no evidence of mitochondrial heteroplasmy. Interestingly, hundreds of mitochondrial DNA fragments were found in the nuclear genome, with several larger than 500 nt confirmed by PCR assays and read count comparisons, indicating clear evidence of transfer of mitochondrial DNA into the nuclear genome. Nuclear DNA of T. matsutake showed a higher mutation rate than mitochondrial DNA. Furthermore, we found evidence of incongruence between phylogenetic trees derived from mitogenome and nuclear DNA sequences. Together, our results reveal the dynamic genome evolution of the gourmet pine mushroom.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental MicrobiologySame topicFungal Biology and ApplicationsFrench-language works237,207