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Record W2337246737 · doi:10.5539/jas.v8n5p61

Cloning of TaPRP from Wheat and Its Cold Tolerance Analysis in Transgenic Tobacco

2016· article· en· W2337246737 on OpenAlexvenueno aff
Da Li, Weidong Zhang, Gao Qingrong, Tian Ji-chun

Bibliographic record

VenueJournal of Agricultural Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGABA and Rice Research
Canadian institutionsnot available
FundersShandong Agricultural University
KeywordsTransgeneBiologyGenetically modified cropsComplementary DNAMolecular biologyGeneProlineAmino acidGenetics

Abstract

fetched live from OpenAlex

<p><em>TaPRP</em>, a proline rich protein (PRP) cDNA, was cloned by RT-PCR from winter wheat. Nucleotide sequence analysis showed <em>TaPRP</em> is composed of 1137 bp (378 amino acid residues with a Mr of 42.19 kD).<em> TaPRP</em> shows 92.6%, 89.3%, 73.0%, and 73.3% sequence homologies with <em>PRP</em> genes from wheat, sorghum, rice, and maize, respectively. The deduced protein includes 170 prolines, presenting a normal <em>PRP</em> primary structure. Expression vector pBI<em>-TaPRP</em> was constructed, in which <em>TaPRP</em> was driven by CaMV35S promoter and stopped by NospolyA. Tobaccos were transformed by<em> Agrobacterium</em> containing the constructed vectors. Three transgenic lines were confirmed by PCR detection and Southern blot. Under the same low temperature stress conditions, transgenic plants had lower conductivity rate compared with the non-transgenic plants, suggesting that cold tolerance in transgenic tobacco plants was improved. However, the different transgenic plants showed significant differences in cold resistant, and there also existed significant interactions between plant and treatment temperature. <em>TaPRP </em>might have an important role in wheat in cold adaptation process.</p>

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.111

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.020
GPT teacher head0.250
Teacher spread0.230 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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