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Record W3046524939 · doi:10.1111/nph.16837

The FUSED LEAVES1‐ <i>ADHERENT1</i> regulatory module is required for maize cuticle development and organ separation

2020· article· en· W3046524939 on OpenAlexafffund
Xue Liu, Richard Bourgault, Mary Galli, Josh Strable, Zongliang Chen, Fan Feng, Jiaqiang Dong, Isabel Molina, Andrea Gallavotti

Bibliographic record

VenueNew Phytologist · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Surface Properties and Treatments
Canadian institutionsAlgoma University
FundersCanada Research ChairsNational Science Foundation
KeywordsMYBBiologyCuticle (hair)MutantCell biologyTranscription factorGeneArabidopsisBiochemistryGenetics

Abstract

fetched live from OpenAlex

All aerial epidermal cells in land plants are covered by the cuticle, an extracellular hydrophobic layer that provides protection against abiotic and biotic stresses and prevents organ fusion during development. Genetic and morphological analysis of the classic maize adherent1 (ad1) mutant was combined with genome-wide binding analysis of the maize MYB transcription factor FUSED LEAVES1 (FDL1), coupled with transcriptional profiling of fdl1 mutants. We show that AD1 encodes an epidermally-expressed 3-KETOACYL-CoA SYNTHASE (KCS) belonging to a functionally uncharacterized clade of KCS enzymes involved in cuticular wax biosynthesis. Wax analysis in ad1 mutants indicates that AD1 functions in the formation of very-long-chain wax components. We demonstrate that FDL1 directly binds to CCAACC core motifs present in AD1 regulatory regions to activate its expression. Over 2000 additional target genes of FDL1, including many involved in cuticle formation, drought response and cell wall organization, were also identified. Our results identify a regulatory module of cuticle biosynthesis in maize that is conserved across monocots and eudicots, and highlight previously undescribed factors in lipid metabolism, transport and signaling that coordinate organ development and cuticle formation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.322

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 head0.056
GPT teacher head0.244
Teacher spread0.188 · 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 designNot applicable
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

Citations38
Published2020
Admission routes2
Has abstractyes

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