MétaCan
Menu
Back to cohort
Record W4367676995 · doi:10.7554/elife.87135.1.sa2

eLife Assessment: Tetraose steroidal glycoalkaloids from potato can provide complete protection against fungi and insects

2023· peer-review· en· W4367676995 on OpenAlexaff
Jacqueline Monaghan

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldAgricultural and Biological Sciences
TopicPotato Plant Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsBiologyBiotechnologySolanumPlant disease resistanceResistance (ecology)Host (biology)Plant defense against herbivoryGenetically modified cropsGeneBotanyTransgeneGeneticsEcology

Abstract

fetched live from OpenAlex

Plants with innate disease and pest resistance can contribute to more sustainable agriculture. Plant breeders typically focus on immune receptors or impaired susceptibility genes to develop resistant crops, but these can present challenges in terms of strength, durability or pleotropic effects. Although natural defence compounds produced by plants have the potential to provide a general protective effect against pathogens and pests, they are not a primary target in resistance breeding. The precise contribution of defence metabolites to plant immunity is often unclear and the genetics underlying their biosynthesis is complex. Here, we identified a wild relative of potato, Solanum commersonii, that provides us with unique insight in the role of glycoalkaloids in plant immunity. We cloned two atypical resistance genes that can provide complete resistance to Alternaria solani and Colorado potato beetle through the production of tetraose steroidal glycoalkaloids. Moreover, we show that these compounds are active against a wide variety of fungi. This research provides a direct link between specific modifications to steroidal glycoalkaloids of potato and resistance against diseases and pests. Further research on the biosynthesis of plant defence compounds in different tissues, their toxicity, and the mechanisms for detoxification, can aid the effective use of such compounds to improve sustainability of our food production.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.510
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.078
GPT teacher head0.299
Teacher spread0.221 · 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 designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicPotato Plant ResearchFrench-language works237,207