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Record W4224292753 · doi:10.1139/cjb-2020-0227

Analysis of <i>MYB</i> genes in four plant species and the detection of genes associated with drought resistance

2022· article· en· W4224292753 on OpenAlexvenueno aff
Yanli Zhou, Lu Lin, Ningyawen Liu, Hua Cao, Han Li, Daping Gui, Jihua Wang, Chengjun Zhang

Bibliographic record

VenueBotany · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Gene Expression Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMYBBiologyGeneEricaceaeGeneticsGene familyBotanyTranscription factorGene expression

Abstract

fetched live from OpenAlex

MYB transcription factor, which contains a conserved DNA binding domain, has been found in almost all eukaryotes. MYB genes have variable functions in plants and are involved in many pathways. We systemically analyzed the MYB gene family in three Ericaceae species, Rhododendron williamsianum Rehder &amp; E.H. Wilson, Rhododendron delavayi Franch., and Vaccinium corymbosum L., and one outgroup, Actinidia chinensis Planch., with 99, 156, 480, and 185 MYB genes found, respectively. The MYB genes were classified into five types based on the number of conserved MYB motifs, and the two repeat (2R) types were dominant in all four species. The percentage of 2R type MYB ranged from 48.5% to 87.9% depending on the species. We further classified the conserved MYB motifs into M1, M2, and M3 types based on motif definition. We found an abundance of 3xM2 type in the 3R group, but found a species-specific type preference for 1R and 2R genes. In searching for Arabidopsis drought-resistant genes, we detected 34 potential candidates in four species. The expression profile of R. delavayi showed 11 candidate drought-resistant RdMYB genes, which provide a potential molecular design target for breeders. Our results describe the MYB gene family in these four species and could play an important role in future analyses.

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 score0.158
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.198
Teacher spread0.190 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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