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Record W2777492485 · doi:10.3390/genes9010008

RAD4 and RAD23/HMR Contribute to Arabidopsis UV Tolerance

2017· article· en· W2777492485 on OpenAlexafffund
Triparna Lahari, Janelle Lazaro, Dana Schroeder

Bibliographic record

VenueGenes · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNucleotide excision repairXeroderma pigmentosumArabidopsisBiologyDNA repairBimolecular fluorescence complementationDNA damageSaccharomyces cerevisiaeUltraviolet lightComplementationDNAArabidopsis thalianaMutantGeneticsCell biologyGeneChemistry

Abstract

fetched live from OpenAlex

In plants, exposure to solar ultraviolet (UV) light is unavoidable, resulting in DNA damage. Damaged DNA causes mutations, replication arrest, and cell death, thus efficient repair of the damaged DNA is essential. A light-independent DNA repair pathway called nucleotide excision repair (NER) is conserved throughout evolution. For example, the damaged DNA-binding protein Radiation sensitive 4 (Rad4) in Saccharomyces cerevisiae is homologous to the mammalian NER protein Xeroderma Pigmentosum complementation group C (XPC). In this study, we examined the role of the Arabidopsis thaliana Rad4/XPC homologue (AtRAD4) in plant UV tolerance by generating overexpression lines. AtRAD4 overexpression, both with and without an N-terminal yellow fluorescent protein (YFP) tag, resulted in increased UV tolerance. YFP-RAD4 localized to the nucleus, and UV treatment did not alter this localization. We also used yeast two-hybrid analysis to examine the interaction of AtRAD4 with Arabidopsis RAD23 and found that RAD4 interacted with RAD23B as well as with the structurally similar protein HEMERA (HMR). In addition, we found that hmr and rad23 mutants exhibited increased UV sensitivity. Thus, our analysis suggests a role for RAD4 and RAD23/HMR in plant UV tolerance.

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 score0.138
Threshold uncertainty score0.429

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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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

Citations27
Published2017
Admission routes2
Has abstractyes

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