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Record W2108610326 · doi:10.1093/molbev/msu092

Overexpression of Molecular Chaperone Genes in Nucleomorph Genomes

2014· article· en· W2108610326 on OpenAlexaff
Yoshihisa Hirakawa, S. Suzuki, John M. Archibald, Patrick J. Keeling, Ken‐ichiro Ishida

Bibliographic record

VenueMolecular Biology and Evolution · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsDalhousie UniversityUniversity of British ColumbiaCanadian Institute for Advanced Research
Fundersnot available
KeywordsBiologyGeneGenomeGeneticsPlastidHeat shock proteinCell biologyChloroplast

Abstract

fetched live from OpenAlex

Chlorarachniophytes and cryptophytes possess complex plastids that were acquired by the ingestion of a green and red algal endosymbiont, respectively. The plastids are surrounded by four membranes, and a relict nucleus, called the nucleomorph, remains in the periplastidal compartment, which corresponds to the remnant cytoplasm of the endosymbiont. Nucleomorphs contain a greatly reduced genome that possesses only several hundred genes with high evolutionary rates. We examined the relative transcription levels of the genes of all proteins encoded by the nucleomorph genomes of two chlorarachniophytes and three cryptophytes using an RNA-seq transcriptomic approach. The genes of two heat shock proteins, Hsp70 and Hsp90, were highly expressed under normal conditions. It has been shown that molecular chaperone overexpression allows an accumulation of genetic mutations in bacteria. Our results suggest that overexpression of heat shock proteins in nucleomorph genomes may play a role in buffering the mutational destabilization of proteins, which might allow the high evolutionary rates of nucleomorph-encoded proteins.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.538

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 head0.007
GPT teacher head0.270
Teacher spread0.264 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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