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Record W3008450616 · doi:10.1038/s41467-020-14991-w

Divergent receptor proteins confer responses to different karrikins in two ephemeral weeds

2020· article· en· W3008450616 on OpenAlexfundno aff
Yueming K. Sun, Jiaren Yao, Adrian Scaffidi, Kim T. Melville, Sabrina F. Davies, Charles S. Bond, Steven M. Smith, Gavin R. Flematti, Mark T. Waters

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsnot available
FundersAustralian Research CouncilAgriculture and Agri-Food CanadaAustralian Government
KeywordsArabidopsisBiologyArabidopsis thalianaWeedNoxious weedEphemeral keyBotanyGeneBiochemistryEcology

Abstract

fetched live from OpenAlex

Abstract Wildfires can encourage the establishment of invasive plants by releasing potent germination stimulants, such as karrikins. Seed germination of Brassica tournefortii , a noxious weed of Mediterranean climates, is strongly stimulated by KAR 1 , the archetypal karrikin produced from burning vegetation. In contrast, the closely-related yet non-fire-associated ephemeral Arabidopsis thaliana is unusual because it responds preferentially to KAR 2 . The α/β-hydrolase KARRIKIN INSENSITIVE 2 (KAI2) is the putative karrikin receptor identified in Arabidopsis . Here we show that B. tournefortii expresses three KAI2 homologues, and the most highly-expressed homologue is sufficient to confer enhanced responses to KAR 1 relative to KAR 2 when expressed in Arabidopsis . We identify two amino acid residues near the KAI2 active site that explain the ligand selectivity, and show that this combination has arisen independently multiple times within dicots. Our results suggest that duplication and diversification of KAI2 proteins could confer differential responses to chemical cues produced by environmental disturbance, including fire.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.480

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 science0.0010.000
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 head0.039
GPT teacher head0.296
Teacher spread0.256 · 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

Citations49
Published2020
Admission routes1
Has abstractyes

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