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Record W2152126517 · doi:10.1371/journal.pone.0034340

A Full Suite of Histone and Histone Modifying Genes Are Transcribed in the Dinoflagellate Lingulodinium

2012· article· en· W2152126517 on OpenAlexaff
Sougata Roy, David Morse

Bibliographic record

VenuePLoS ONE · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHistoneDinoflagellateBiologyGeneticsTranscriptomeCell biologyGeneGene expressionBotany

Abstract

fetched live from OpenAlex

BACKGROUND: Dinoflagellates typically lack histones and nucleosomes are not observed in DNA spreads. However, recent studies have shown the presence of core histone mRNA sequences scattered among different dinoflagellate species. To date, the presence of all components required for manufacturing and modifying nucleosomes in a single dinoflagellate species has not been confirmed. METHODOLOGY AND RESULTS: Analysis of a Lingulodinium transcriptome obtained by Illumina sequencing of mRNA shows several different copies of each of the four core histones as well as a suite of histone modifying enzymes and histone chaperone proteins. Phylogenetic analysis shows one of each Lingulodinium histone copies belongs to the dinoflagellate clade while the second is more divergent and does not share a common ancestor. All histone mRNAs are in low abundance (roughly 25 times lower than higher plants) and transcript levels do not vary over the cell cycle. We also tested Lingulodinium extracts for histone proteins using immunoblotting and LC-MS/MS, but were unable to confirm histone expression at the protein level. CONCLUSION: We show that all core histone sequences are present in the Lingulodinium transcriptome. The conservation of these sequences, even though histone protein accumulation remains below currently detectable levels, strongly suggests dinoflagellates possess histones.

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 score0.010
Threshold uncertainty score0.357

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 head0.049
GPT teacher head0.264
Teacher spread0.215 · 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

Citations60
Published2012
Admission routes1
Has abstractyes

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