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Record W4414232736 · doi:10.1101/2025.09.10.675464

Transfer RNA modifications during rhizome development in <i>Oryza longistaminata</i>

2025· preprint· en· W4414232736 on OpenAlexaff
W.J. Li, Guangzhao Yang, Ruichen Ma, Chaoying Zhang, Rui Yao, Yajun Li, Xukai Li, Fengyi Hu, Peng Chen, Zheng Li

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsMinistry of Agriculture
FundersNational Cancer InstituteNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsRhizomeTransfer RNAGeneRNAModel organismPlant development

Abstract

fetched live from OpenAlex

ABSTRACT The rhizome organ endows many clonal plants with the ability to reproduce under stressful climates. Such rhizome-mediated perenniality also underlies the recent success of perennial rice breeding. Despite the importance of this organ, its developmental regulation is poorly understood. Here, using Oryza longistaminata , an emerging model for rhizome biology, we explored the involvement of tRNA modification in rhizome development. Through comparative profiling of modified nucleotides in rhizome samples at different developmental stages and/or subjected to various treatments, we identified a number of key rhizome-related tRNA modifications and revealed that, akin to the observations in many non-plant organisms, tRNA modifications are associated with hormonal signalling to regulate rhizomes’ responses to environmental cues. Furthermore, genome-wide analysis of tRNA-modifying genes was performed to facilitate future functional studies. These results and analyses not only deepen our understanding of rhizome development but also underscore the regulatory roles of tRNA modification in plant organ 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 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.223
Teacher spread0.211 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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