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Record W3005077351 · doi:10.1371/journal.pone.0227840

Molecular identification and functional characterization of a cyanogenic glucosyltransferase from flax (Linum unsitatissimum)

2020· article· en· W3005077351 on OpenAlexafffund
Michael Kazachkov, Qiang Li, Wenyun Shen, Liping Wang, Peng Gao, Daoquan Xiang, Raju Datla, Jitao Zou

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCassava research and cyanide
Canadian institutionsUniversity of SaskatchewanNational Research Council CanadaSaskatchewan Research Council (Canada)
FundersGenome PrairieNational Research Council CanadaGenome Canada
KeywordsLinumGlucosyltransferaseIdentification (biology)BiologyComputational biologyBiochemistryChemistryBotanyEnzyme

Abstract

fetched live from OpenAlex

Flax seed has become consumers' choice for not only polyunsaturated alpha-linolenic fatty acid but also nutraceuticals such as lignans and soluble fiber. There is, however, a major drawback of flax as a source of functional food since the seeds contain significant level of cyanogenic glucosides. The final step of cyanogenic glucoside biosynthesis is mediated by UDP-glucose dependent glucosyltransferase. To date, no flax cyanogenic glucosyl transferase genes have been reported with verified biochemical functionality. Here we present a study on the identification and enzymatic characterization of a first flax cyanogenic glucosyltransferase, LuCGT1. We show that LuCGT1 was highly active towards both aliphatic and aromatic substrates. The LuCGT1 gene is expressed in leaf tissues as well as in developing seeds, and its expression level was drastically reduced in flax mutant lines low in cyanogenic glucosides. Identification of LuCGT1 provides a molecular handle for developing gene specific markers for targeted breeding of low cyanogenic glucosides in flax.

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 score0.217
Threshold uncertainty score0.547

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 head0.047
GPT teacher head0.200
Teacher spread0.153 · 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

Citations11
Published2020
Admission routes2
Has abstractyes

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Same venuePLoS ONESame topicCassava research and cyanideFrench-language works237,207