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Record W2106396995 · doi:10.1073/pnas.0501321102

A high frequency of overlapping gene expression in compacted eukaryotic genomes

2005· article· en· W2106396995 on OpenAlexaff
Ben Williams, Claudio H. Slamovits, Nicola J. Patron, Naomi M. Fast, Patrick J. Keeling

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2005
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsUniversity of British ColumbiaCanadian Institute for Advanced Research
FundersWellcome Trust
KeywordsBiologyGenomeGeneGeneticsNuclear geneGene expressionComputational biology

Abstract

fetched live from OpenAlex

The gene density of eukaryotic nuclear genomes is generally low relative to prokaryotes, but several eukaryotic lineages (many parasites or endosymbionts) have independently evolved highly compacted, gene-dense genomes. The best studied of these are the microsporidia, highly adapted fungal parasites, and the nucleomorphs, relict nuclei of endosymbiotic algae found in cryptomonads and chlorarachniophytes. These systems are now models for the effects of compaction on the form and dynamics of the nuclear genome. Here we report a large-scale investigation of gene expression from compacted eukaryotic genomes. We have conducted EST surveys of the microsporidian Antonospora locustae and nucleomorphs of the cryptomonad Guillardia theta and the chlorarachniophyte Bigelowiella natans. In all three systems we find a high frequency of mRNA molecules that encode sequence from more than one gene. There is no bias for these genes to be on the same strand, so it is unlikely that these mRNAs represent operons. Instead, compaction appears to have reduced the intergenic regions to such an extent that control elements like promoters and terminators have been forced into or beyond adjacent genes, resulting in long untranslated regions that encode other genes. Normally, transcriptional overlap can interfere with expression of a gene, but these genomes cope with high frequencies of overlap and with termination signals within expressed genes. These findings also point to serious practical difficulties in studying expression in compacted genomes, because many techniques, such as arrays or serial analysis of gene expression will be misleading.

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 score0.297
Threshold uncertainty score0.201

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 studies0.0000.001
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 head0.028
GPT teacher head0.288
Teacher spread0.261 · 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

Citations104
Published2005
Admission routes1
Has abstractyes

Explore more

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