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Record W2765711633 · doi:10.1038/s41598-017-14286-z

Keeping it complicated: Mitochondrial genome plasticity across diplonemids

2017· article· en· W2765711633 on OpenAlexafffund
Matus Valach, Sandrine Moreira, Steve Hoffmann, Peter F. Stadler, Gertraud Burger

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaJapan Agency for Marine-Earth Science and TechnologyCanadian Institutes of Health ResearchUniversité de MontréalGordon and Betty Moore Foundation
KeywordsBiologyGeneticsGeneGenomeMitochondrial DNAGenome evolution

Abstract

fetched live from OpenAlex

Chromosome rearrangements are important drivers in genome and gene evolution, with implications ranging from speciation to development to disease. In the flagellate Diplonema papillatum (Euglenozoa), mitochondrial genome rearrangements have resulted in nearly hundred chromosomes and a systematic dispersal of gene fragments across the multipartite genome. Maturation into functional RNAs involves separate transcription of gene pieces, joining of precursor RNAs via trans-splicing, and RNA editing by substitution and uridine additions both reconstituting crucial coding sequence. How widespread these unusual features are across diplonemids is unclear. We have analyzed the mitochondrial genomes and transcriptomes of four species from the Diplonema/Rhynchopus clade, revealing a considerable genomic plasticity. Although gene breakpoints, and thus the total number of gene pieces (~80), are essentially conserved across this group, the number of distinct chromosomes varies by a factor of two, with certain chromosomes combining up to eight unrelated gene fragments. Several internal protein-coding gene pieces overlap substantially, resulting, for example, in a stretch of 22 identical amino acids in cytochrome c oxidase subunit 1 and NADH dehydrogenase subunit 5. Finally, the variation of post-transcriptional editing patterns across diplonemids indicates compensation of two adverse trends: rapid sequence evolution and loss of genetic information through unequal chromosome segregation.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.287
Teacher spread0.262 · 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 designObservational
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

Citations27
Published2017
Admission routes2
Has abstractyes

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