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Record W4233710036 · doi:10.3410/f.735763839.793562364

Faculty Opinions recommendation of Mitochondrial fragmentation drives selective removal of deleterious mtDNA in the germline.

2019· dataset· en· W4233710036 on OpenAlexfundno aff
Hyung Don Ryoo

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2019
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Institutes of HealthCanada First Research Excellence FundHoward Hughes Medical Institute
KeywordsMitochondrial DNAFragmentation (computing)GermlineDNA fragmentationBiologyGeneticsGeneEcologyApoptosis

Abstract

fetched live from OpenAlex

Mitochondria contain their own genomes, and unlike nuclear genomes, mitochondrial genomes are inherited maternally.With a high mutation rate and little recombination, special selection mechanisms exist in the female germline to prevent the accumulation of deleterious mutations [1][2][3][4][5] .The molecular mechanisms underpinning selection remain poorly understood 6 .Here, using an allele-specific fluorescent in situ-hybridization approach to distinguish wildtype from mutant mtDNA, we have visualized germline selection for the first time.Selection first manifests in the early stages of Drosophila oogenesis, triggered by reduction of the pro-fusion protein Mitofusin.This leads to the physical separation of mitochondrial genomes into different mitochondrial fragments, preventing the mixing of genomes and their products, and thereby reducing complementation.Once fragmentated, mitochondria harboring mutant genomes are less able to make ATP, which marks them for selection through a process requiring the mitophagy proteins Atg1 and BNIP3.Surprisingly, a reduction in Atg1 or BNIP3 decreases the amount of wildtype mtDNA, suggesting a link between mitochondrial turnover and mtDNA replication.Remarkably, fragmentation is not only necessary for selection in germline tissues, but also sufficient to induce selection in somatic tissues where selection is normally absent.Our studies posit a generalizable mechanism to select against deleterious mtDNA mutations that may allow the development of strategies for treatment of mtDNA disorders.To visualize germline selection, we designed fluorescently labeled DNA probes that bind specifically to unique regions of the D-loops of mtDNA from either D. melanogaster or a Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/

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)0.001
metaresearch head score (Gemma)0.007
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.054
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0540.041

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 head0.343
Teacher spread0.318 · 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
GenreDataset

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

Citations0
Published2019
Admission routes1
Has abstractyes

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