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Record W2111106407 · doi:10.1371/journal.pgen.1002159

Transportin-SR Is Required for Proper Splicing of Resistance Genes and Plant Immunity

2011· article· en· W2111106407 on OpenAlexafffund
Shaohua Xu, Zhibin Zhang, Beibei Jing, Patrick J. Gannon, Jinmei Ding, Fang Xu, Xin Li, Yuelin Zhang

Bibliographic record

VenuePLoS Genetics · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersNational Key Research and Development Program of ChinaNatural Sciences and Engineering Research Council of CanadaMinistry of Science and Technology of the People's Republic of China
KeywordsBiologyRNA splicingSR proteinCell biologyNuclear transportGeneticsGeneNuclear localization sequenceCloning (programming)ImportinPositional cloningRNA-binding proteinRNACell nucleusMutant

Abstract

fetched live from OpenAlex

Transportin-SR (TRN-SR) is a member of the importin-β super-family that functions as the nuclear import receptor for serine-arginine rich (SR) proteins, which play diverse roles in RNA metabolism. Here we report the identification and cloning of mos14 (modifier of snc1-1, 14), a mutation that suppresses the immune responses conditioned by the auto-activated Resistance (R) protein snc1 (suppressor of npr1-1, constitutive 1). MOS14 encodes a nuclear protein with high similarity to previously characterized TRN-SR proteins in animals. Yeast two-hybrid assays showed that MOS14 interacts with AtRAN1 via its N-terminus and SR proteins via its C-terminus. In mos14-1, localization of several SR proteins to the nucleus was impaired, confirming that MOS14 functions as a TRN-SR. The mos14-1 mutation results in altered splicing patterns of SNC1 and another R gene RPS4 and compromised resistance mediated by snc1 and RPS4, suggesting that nuclear import of SR proteins by MOS14 is required for proper splicing of these two R genes and is important for their functions in plant immunity.

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 score0.003
Threshold uncertainty score0.394

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 head0.055
GPT teacher head0.264
Teacher spread0.208 · 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

Citations104
Published2011
Admission routes2
Has abstractyes

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