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Record W2104523084 · doi:10.1534/g3.112.003368

Genetic Interactions Between Arabidopsis<i>DET1</i>and<i>UVH6</i>During Development and Abiotic Stress Response

2012· article· en· W2104523084 on OpenAlexafffund
Esther Kim, Valentina Ly, Avril Hatherell, Dana F. Schroeder

Bibliographic record

VenueG3 Genes Genomes Genetics · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLight effects on plants
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEtiolationEpistasisBiologyAbiotic componentHeat stressMutantArabidopsis thalianaArabidopsisPhenotypePhotomorphogenesisAbiotic stressCell biologyGeneticsBiophysicsGeneBiochemistryEcologyEnzyme

Abstract

fetched live from OpenAlex

Plants must adapt to a variety of abiotic inputs, including visible light, ultraviolet (UV) light, and heat. In Arabidopsis thaliana, DE-ETIOLATED 1 (DET1) plays a role in visible light signaling, UV tolerance, and development. UV-HYPERSENSITIVE 6 (UVH6) mutants are UV and heat sensitive, as well as dwarf and pale, like det1. In this study, we examine the genetic interactions between these two genes. In dark-grown seedlings, uvh6 exhibits a weak de-etiolated phenotype but does not affect the stronger de-etiolated phenotype of det1. In the light, det1 is epistatic to uvh6 with regard to chlorophyll level, but their effect on all size parameters is additive and therefore independent. With regard to UV tolerance, det1 UV resistance is epistatic to uvh6 UV sensitivity. In heat stress experiments, det1 enhances heat-induced tissue damage in the uvh6 background but suppresses heat-induced growth inhibition. Thus, det1 acts epistatically to uvh6 with respect to de-etiolation, chlorophyll level, UV tolerance, and heat-induced growth inhibition, whereas det1 and uvh6 act additively to regulate plant size and heat-induced cell death. These data provide insight into interplay between light and heat signaling.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.565

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 head0.021
GPT teacher head0.225
Teacher spread0.204 · 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 designObservational
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

Citations3
Published2012
Admission routes2
Has abstractyes

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