MétaCan
Menu
Back to cohort
Record W4385620822 · doi:10.1111/jipb.13553

A recently evolved BAHD acetyltransferase, responsible for bitter soyasaponin A production, is indispensable for soybean seed germination

2023· article· en· W4385620822 on OpenAlexaff
Jia Yuan, Liya Ma, Yan Wang, Xindan Xu, Rui Zhang, Chengyuan Wang, Wenxiang Meng, Zhixi Tian, Yihua Zhou, Guodong Wang

Bibliographic record

VenueJournal of Integrative Plant Biology · 2023
Typearticle
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsInstitute of Genetics
Fundersnot available
KeywordsAcetyltransferaseBiochemistryGlycineAcetylationBiologyChemistryGeneBotanyAmino acid

Abstract

fetched live from OpenAlex

Soyasaponins are major small molecules that accumulate in soybean (Glycine max) seeds. Among them, type-A soyasaponins, fully acetylated at the terminal sugar of their C22 sugar chain, are responsible for the bitter taste of soybean-derived foods. However, the molecular basis for the acetylation of type-A soyasaponins remains unclear. Here, we identify and characterize GmSSAcT1, encoding a BADH-type soyasaponin acetyltransferase that catalyzes three or four consecutive acetylations on type-A soyasaponins in vitro and in planta. Phylogenetic analysis and biochemical assays suggest that GmSSAcT1 likely evolved from acyltransferases present in leguminous plants involved in isoflavonoid acylation. Loss-of-function mutants of GmSSAcT1 exhibited impaired seed germination, which attribute to the excessive accumulation of null-acetylated type-A soyasaponins. We conclude that GmSSAcT1 not only functions as a detoxification gene for high accumulation of type-A soyasaponins in soybean seeds but is also a promising target for breeding new soybean varieties with lower bitter soyasaponin content.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.363
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), 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

Citations22
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Integrative Plant BiologySame topicPhytoestrogen effects and researchFrench-language works237,207