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Record W2161505925 · doi:10.4141/cjps2013-084

<i>SlPMEI</i>, a pollen-specific gene in tomato

2013· article· en· W2161505925 on OpenAlexvenueno aff
Woong Bom Kim, Chan Ju Lim, Hyun A Jang, So Young Yi, Sang‐Keun Oh, Ha Yeon Lee, Hyun A Kim, Youn‐Il Park, Suk‐Yoon Kwon

Bibliographic record

VenueCanadian Journal of Plant Science · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Reproductive Biology
Canadian institutionsnot available
FundersKorea Research Institute of Bioscience and BiotechnologyRural Development Administration
KeywordsPollenSolanumStamenBiologyArabidopsisPectinTransgeneBotanyGenetically modified tomatoAbiotic stressGeneGenetically modified cropsGeneticsMutant

Abstract

fetched live from OpenAlex

Kim, W. B., Lim, C. J., Jang, H. A., Yi, S. Y., Oh, S.-K., Lee, H. Y., Kim, H. A., Park, Y.-I. and Kwon, S.-Y. 2014. SlPMEI, a pollen-specific gene in tomato. Can. J. Plant Sci. 94: 73–83. Pectin is one of the main components of plant cell walls, and its biosynthesis is controlled by pectin methylesterase (PME). Pectin methylesterase inhibitors (PMEIs) are key regulators of PME. We report here the cloning and characterization of a novel Solanum lycopersicum L. PMEI gene, SlPMEI. RT-PCR studies of leaf, seed, fruit, flower, and flower organs confirmed that SlPMEI is expressed specifically in pollen. Promoter analysis of SlPMEI revealed pollen-specific cis-acting elements (pollen lat52 and g10). In addition, SlPMEI is expressed independently of abiotic stress, pathogen exposure, and growth stage in tomato, and a histochemical analysis of promoter activity revealed pollen-specific expression in both Arabidopsis and tomato. Under the microscope, we observed pollen-specific GUS expression in the stamen of transgenic tomato plant. These results indicate that the promoter of SlPMEI has strong pollen-specific activity, and could therefore be useful for development of industrially and agronomically important transgenic plants.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.371

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)0.0000.000

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 head0.009
GPT teacher head0.196
Teacher spread0.187 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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