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Record W4385406156 · doi:10.1093/pcp/pcad086

CRISPR/Cas9 Disruption of <i>MYB134</i> and <i>MYB115</i> in Transgenic Poplar Leads to Differential Reduction of Proanthocyanidin Synthesis in Roots and Leaves

2023· article· en· W4385406156 on OpenAlexafffund
Yalin Liu, Dawei Ma, C. Peter Constabel

Bibliographic record

VenuePlant and Cell Physiology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Gene Expression Analysis
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Victoria
KeywordsProanthocyanidinTransgeneCRISPRGenetically modified cropsBiologyReduction (mathematics)BotanyChemistryGeneticsGeneBiochemistryPolyphenol

Abstract

fetched live from OpenAlex

Proanthocyanidins (PAs) are common specialized metabolites and particularly abundant in trees and woody plants. In poplar (Populus spp.), PA biosynthesis is stress-induced and regulated by two previously studied transcription factors MYB115 and MYB134. To determine the relative contribution of these regulators to PA biosynthesis, we created single- and double-knockout (KO) mutants for both genes in transgenic poplars using CRISPR/Cas9. Knocking out either MYB134 or MYB115 showed reduced PA accumulation and downregulated flavonoid genes in leaves, but MYB134 disruption had the greatest impact and reduced PAs to 30% of controls. In roots, by contrast, only the MYB134/MYB115 double-KOs showed a significant change in PA concentration. The loss of PAs paralleled the lower expression of PA biosynthesis genes and concentrations of flavan-3-ol PA precursors catechin and epicatechin. Interestingly, salicinoids were also affected in double-KOs, with distinct patterns in roots and shoots. We conclude that the regulatory pathways for PA biosynthesis differ in poplar leaves and roots. The residual PA content in the double-KO plants indicates that other transcription factors must also be involved in control of the PA pathway.

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 score0.034
Threshold uncertainty score0.470

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 head0.229
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 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

Citations15
Published2023
Admission routes2
Has abstractyes

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