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Record W4281259382 · doi:10.1111/ppl.13721

Transcriptional cascades in the regulation of 2‐AP biosynthesis under Zn supply in fragrant rice

2022· article· en· W4281259382 on OpenAlexaff
Muhammad Imran, Yanhua Liu, Sarfraz Shafiq, Farhat Abbas, Sara Ilahi, Naveed ur Rehman, Sunny Ahmar, Sajid Fiaz, Nurettin Baran, Shenggang Pan, Zhaowen Mo, Xiangru Tang

Bibliographic record

VenuePhysiologia Plantarum · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGABA and Rice Research
Canadian institutionsWestern University
FundersNational Natural Science Foundation of China
KeywordsWRKY protein domainMYBTranscription factorBiosynthesisBiologyTranscriptomeAromaGeneTranscriptional regulationBiochemistryRegulator geneCell biologyRegulation of gene expressionGene expressionFood science

Abstract

fetched live from OpenAlex

Transcription factors (TFs) regulate gene expression to control certain genetic programs, such as growth and development, phytohormone regulation, and environmental stresses. 2-acetyl-1-pyrroline (2-AP) is the key element involved in aroma biosynthesis pathway, and the application of micronutrients can increase the 2-AP levels. However, little is known about the micronutrient-induced TFs involved in 2-AP biosynthesis. Here, we identify a number of TF families in two fragrant rice varieties, "Meixiangzhan-2" (M) and "Xiangyaxiangzhan" (X), in response to Zinc (Zn) application through transcriptomic analysis. A total of ~678 TFs were identified and grouped into 26 TF families, each of which was found to be involved in numerous signaling pathways. The WRKY TF family was found to be the most abundant, followed by bHLH and MYB. Furthermore, members of the WRKY, bHLH, MYB, ERF, HSF, MADS-box, NFY, and AP2 TF families were significantly upregulated and may be involved in the transcriptional regulation of aroma biosynthesis. In brief, this study enhances our understanding of the molecular mechanism of 2-AP biosynthesis and highlights the key TFs potentially involved in the production of aroma in fragrant 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 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 score0.987
Threshold uncertainty score0.550

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)0.0010.000

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 head0.031
GPT teacher head0.236
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

Citations12
Published2022
Admission routes1
Has abstractyes

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