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B-GATA factors are required to repress high-light stress responses in Marchantia polymorpha and Arabidopsis thaliana

2023· preprint· en· W4319602239 on OpenAlexaff
Claus Schwechheimer, Peter Schröder, Nora Gutsche, Jana Barbro Winkler, Boris Hedtke, Bernhard Grimm

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsAdler
FundersTechnische Universität MünchenDeutsche Forschungsgemeinschaft
KeywordsMarchantia polymorphaBiologyMutantArabidopsis thalianaArabidopsisZinc fingerGeneticsTranscription factorCell biologyGene

Abstract

fetched live from OpenAlex

GATAs are evolutionarily conserved zinc-finger transcription factors from eukaryotes. In plants, GATAs can be subdivided into four classes, A – D, based on their DNA-binding domain, and into further subclasses based on additional protein motifs. B-GATAs with a so-called LLM-domain can already be found in algae, but bryophytes and angiosperms also contain B-GATAs with a HAN-domain. The angiosperm B-GATA family is expanded and can be subdivided into family members with either a HAN- or an LLM-domain. The B-GATA family in the liverwort Marchantia polymorpha and the moss Physcomitrium patens is restricted to one and four family members, respectively, and all family members contain a HAN- as well as an LLM-domain. Here, we characterize mutants of the single B-GATA from Marchantia polymorpha . We reveal that this mutant has defects in thallus growth and in gemma formation. Transcriptomic studies uncover that the B-GATA mutant displays a constitutive high-light stress response, a phenotype that we then also confirm in mutants of Arabidopsis thaliana LLM-domain B-GATAs, suggesting that the B-GATAs have a protective role towards high-light stress.

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 score0.002
Threshold uncertainty score0.004

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)0.0010.001

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 head0.075
GPT teacher head0.291
Teacher spread0.216 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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