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Record W4382631547 · doi:10.1186/s13059-023-02990-1

Efficient and versatile multiplex prime editing in hexaploid wheat

2023· article· en· W4382631547 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGenome biology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesChinese Universities Scientific FundChinese Academy of SciencesInstitute of GeneticsNational Natural Science Foundation of China
KeywordsBiologyMultiplexHuman geneticsPrime (order theory)Computational biologyGeneticsEvolutionary biologyGene

Abstract

fetched live from OpenAlex

Prime editing is limited by low efficiency in plants. Here, we develop an upgraded engineered plant prime editor in hexaploid wheat, ePPEplus, by introducing a V223A substitution into reverse transcriptase in the ePPEmax* architecture. ePPEplus enhances the efficiency by an average 33.0-fold and 6.4-fold compared to the original PPE and ePPE, respectively. Importantly, a robust multiplex prime editing platform is established for simultaneous editing of four to ten genes in protoplasts and up to eight genes in regenerated wheat plants at frequencies up to 74.5%, thus expanding the applicability of prime editors for stacking of multiple agronomic 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.

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 score0.603
Threshold uncertainty score0.411

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 head0.009
GPT teacher head0.295
Teacher spread0.286 · 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