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Record W2936055315 · doi:10.1038/s41467-019-09467-5

Biosynthesis of DHGA12 and its roles in Arabidopsis seedling establishment

2019· article· en· W2936055315 on OpenAlexfundno aff
Hao Liu, Siyi Guo, Minghua Lu, Yu Zhang, Junhua Li, Wei Wang, Pengtao Wang, Junli Zhang, Zhubing Hu, Liangliang Li, Lingyu Si, Jie Zhang, Qi Qi, Xiangning Jiang, José Ramón Botella, Hua Wang, Chun‐Peng Song

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsnot available
FundersInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijing Forestry UniversityHenan UniversityChinese Academy of SciencesInstitute of Zoology, Chinese Academy of SciencesInstitute of GeneticsNational Natural Science Foundation of China
KeywordsAbscisic acidGerminationGibberellinArabidopsisHypocotylArabidopsis thalianaSeedlingCotyledonChemistryGreeningBotanyBiochemistryBiologyMutantGene

Abstract

fetched live from OpenAlex

Abstract Seed germination and photoautotrophic establishment are controlled by the antagonistic activity of the phytohormones gibberellins (GAs) and abscisic acid (ABA). Here we show that Arabidopsis thaliana GAS2 (Gain of Function in ABA-modulated Seed Germination 2), a protein belonging to the Fe-dependent 2-oxoglutarate dioxygenase superfamily, catalyzes the stereospecific hydration of GA 12 to produce GA 12 16, 17-dihydro-16α-ol (DHGA 12 ). We show that DHGA 12 , a C 20 -GA has an atypical structure compared to known active GAs but can bind to the GA receptor (GID1c). DHGA 12 can promote seed germination, hypocotyl elongation and cotyledon greening. Silencing and over-expression of GAS2 alters the ABA/GA ratio and sensitivity to ABA during seed germination and photoautotrophic establishment. Hence, we propose that GAS2 acts to modulate hormonal balance during early seedling 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 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 score0.792
Threshold uncertainty score0.139

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 head0.022
GPT teacher head0.271
Teacher spread0.250 · 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

Citations76
Published2019
Admission routes1
Has abstractyes

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