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Record W2984607351 · doi:10.1101/830620

Separable regulation of <i>POW1</i> in <i>TAF2</i> -mediated grain development and BR-mediated leaf angle formation in rice

2019· preprint· en· W2984607351 on OpenAlexfundno aff
Li Zhang, Ruci Wang, Yueming Wang, Yufang Xu, Shuang Fang, Jinfang Chu, Shanguo Yao

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaChinese Academy of Agricultural SciencesInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesChinese Academy of SciencesInstitute of GeneticsNational Natural Science Foundation of China
KeywordsBrassinosteroidMutantGeneTranscription factorBiologyLeaf sizePhenotypeTranscription (linguistics)Grain yieldCell biologyBotanyAgronomyGeneticsArabidopsis

Abstract

fetched live from OpenAlex

ABSTRACT Leaf angle is one of the key factors determining rice plant architecture. However, improvement of the leaf angle appears to be unsuccessful in practical breeding because of the simultaneous occurrence of unfavorable traits such as grain size reduction. In this study, we identified the pow1 ( p ut o n w eight 1 ) mutant with enlarged grain size and leaf angle, typical brassinosteroid (BR)-related phenotypes caused by excessive cell proliferation and cell expansion. We show that POW1 encodes a novel protein functioning in grain size regulation by repressing the transcription activity of the interacting protein TAF2, a highly conserved member of the transcription initiation complex TFIID. Loss of function of POW1 increases the phosphorylation of OsBZR1 and decreases the inhibitory effect of OsBZR1 on the transcription of BR biosynthesis genes OsDWARF4 ( D4 ) and D11 , thus participates in BR-mediated leaf angle regulation. The separable functions of POW1 in grain size and leaf angle control provide a promising strategy to design high-yielding varieties in which both traits would be favorably developed, i.e., compact plant architecture and increased grain size, thus would promote the high-yield breeding a step forward in rice.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.209
Teacher spread0.194 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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