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Record W2077565090 · doi:10.1139/g06-020

Distribution, structure, organ-specific expression, and phylogenic analysis of the pathogenesis-related protein-3 chitinase gene family in rice (<i>Oryza sativa</i>L.)

2006· article· en· W2077565090 on OpenAlexvenueno aff
Testuya Nakazaki, Takuji Tsukiyama, Yutaka Okumoto, Ken Naito, Kuniyo Inouye, Takatoshi Tanisaka

Bibliographic record

VenueGenome · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicStudies on Chitinases and Chitosanases
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyOryza sativaChitinaseGeneOryzaGeneticsGenomePhylogenetic treeGene familyPhylogeneticsBotany

Abstract

fetched live from OpenAlex

Rice (Oryza sativa L.) pathogenesis-related (PR)-3 chitinases, like other PR proteins, are each coded by one of the genes of a multigene family in the plant genome. We assembled the database information about rice PR-3 chitinase sequences. A total of 12 PR-3 chitinase loci (Cht1 to Cht12) were found deployed in the rice genome. Some of the loci were occupied by 2 or more alleles. For all the loci expect Cht4, Cht5, Cht6, and Cht11, the amino acid sequence was polymorphic between japonica and indica varieties of rice, but glutamic acid acting as a catalytic residue was completely conserved in all the loci expect Cht7. All the genes except Cht7, which was not tested in this study, were transcripted in some organs (leaf, sheath, root, and meristem) of rice plants. These results suggest that chitinase proteins encoded by the genes at these loci have important biological effects, at least antifungal activities, on rice plants. We also proposed a new classification of rice PR-3 chitinases based on their domain structures. This classification was consistent with the results of phylogenetic analysis of rice chitinases.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.004
GPT teacher head0.191
Teacher spread0.186 · 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 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

Citations30
Published2006
Admission routes1
Has abstractyes

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