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Islands of co‐expressed neighbouring genes in <i>Arabidopsis thaliana</i> suggest higher‐order chromosome domains

2006· article· en· W2129378637 on OpenAlexafffund
Shuhua Zhan, Julie Horrocks, Lewis Lukens

Bibliographic record

VenueThe Plant Journal · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversity of Guelph
FundersUniversity of Toronto
KeywordsArabidopsis thalianaGeneGeneticsBiologyChromosomeOrder (exchange)ArabidopsisMutant

Abstract

fetched live from OpenAlex

Biochemical and cytogenetic experiments have led to the hypothesis that eukaryotic chromatin is organized into a series of distinct domains that are functionally independent. Two expectations of this hypothesis are: (i) adjacent genes are more frequently co-expressed than is expected by chance; and (ii) co-expressed neighbouring genes are often functionally related. Here we report that over 10% of Arabidopsis thaliana genes are within large, co-expressed chromosomal regions. Two per cent (497/22,520) of genes are highly co-expressed (r > 0.7), about five times the number expected by chance. These genes fall into 226 groups distributed across the genome, and each group typically contains two to three genes. Among the highly co-expressed groups, 40% (91/226) have genes with high amino acid sequence similarity. Nonetheless, duplicate genes alone do not explain the observed levels of co-expression. Co-expressed, non-homologous genes are transcribed in parallel, share functions, and lie close together more frequently than expected. Our results show that the A. thaliana genome contains domains of gene expression. Small domains have highly co-expressed genes that often share functional and sequence similarity and are probably co-regulated by nearby regulatory sequences. Genes within large, significantly correlated groups are typically co-regulated at a low level, suggesting the presence of large chromosomal domains.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.794
Threshold uncertainty score0.367

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 science0.0010.000
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 head0.020
GPT teacher head0.232
Teacher spread0.212 · 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

Citations76
Published2006
Admission routes2
Has abstractyes

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