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<i>APETALA1</i> and <i>SEPALLATA3</i> interact to promote flower development

2001· article· en· W2046944468 on OpenAlexafffund
Soraya Pelaz, Cindy Gustafson‐Brown, Susanne E. Kohalmi, William L. Crosby, Martin F. Yanofsky

Bibliographic record

VenueThe Plant Journal · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsPlant Biotechnology InstituteWestern University
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Department of Agriculture
KeywordsMADS-boxBiologySepalPetalAP-1 transcription factorGeneArabidopsisMeristemGeneticsBotanyMutantGene expression

Abstract

fetched live from OpenAlex

In Arabidopsis, the closely related APETALA1 (AP1) and CAULIFLOWER (CAL) MADS-box genes share overlapping roles in promoting flower meristem identity. Later in flower development, the AP1 gene is required for normal development of sepals and petals. Studies of MADS-domain proteins in diverse species have shown that they often function as heterodimers or in larger ternary complexes, suggesting that additional proteins may interact with AP1 and CAL during flower development. To identify proteins that may interact with AP1 and CAL, we used the yeast two-hybrid assay. Among the five MADS-box genes identified in this screen, the SEPALLATA3 (SEP3) gene was chosen for further study. Mutations in the SEP3 gene, as well as SEP3 antisense plants that have a reduction in SEP3 RNA, display phenotypes that closely resemble intermediate alleles of AP1. Furthermore, the early flowering phenotype of plants constitutively expressing AP1 is significantly enhanced by constitutive SEP3 expression. Taken together, these studies suggest that SEP3 interacts with AP1 to promote normal flower development.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.027
GPT teacher head0.234
Teacher spread0.207 · 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 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

Citations325
Published2001
Admission routes2
Has abstractyes

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