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Record W4405018683 · doi:10.1139/cjps-2024-0199

Genomic structural variation and herbicide resistance

2024· article· en· W4405018683 on OpenAlexvenueno aff
Nicholas A. Johnson, John Lemas, Jacob E. Montgomery, Todd A. Gaines, Eric L. Patterson

Bibliographic record

VenueCanadian Journal of Plant Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsnot available
Fundersnot available
KeywordsHerbicide resistanceBiologyVariation (astronomy)Resistance (ecology)GeneticsStructural variationGenetic variationBiotechnologyAgronomyGenomeGene

Abstract

fetched live from OpenAlex

The coinciding increase in genomics resources for weedy plant species and herbicide resistance evolution has led to a rapid expansion of our understanding of the relationship between genomic structural variation and herbicide resistance mechanisms. Since the first discovery of 5-enolpyruvylshikimate-3-phosphate synthase ( EPSPS) copy number variation conferring glyphosate resistance in Amaranthus palmeri, we have seen rapid convergent evolution of the same herbicide-resistance mechanism in eleven diverse weed species by a variety of unique structural variant-generating mechanisms. These mechanisms include extrachromosomal circular DNA replication, unequal crossing over, and subtelomeric duplication. More recently, target-site duplication has been found to cause resistance for other herbicides with different modes of action, including acetyl-CoA carboxylase (ACCase) inhibitors and glutamine synthetase inhibitors. Additionally, the first transposon-generated structural variants that confer herbicide resistances are beginning to be discovered. This review summarizes our current understanding of structural variation in agronomic weed genomes as it relates to herbicide resistance and emphasizes necessary future research to clarify the size, nature, and mechanisms that give rise to genomic structural variation. While we limit our review to herbicide resistance traits, this work also highlights the importance of structural variation as a critical component of total genetic diversity and its importance for the rapid evolution of novel traits.

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 score0.970
Threshold uncertainty score0.997

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 head0.010
GPT teacher head0.195
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 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

Citations7
Published2024
Admission routes1
Has abstractyes

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