Analysis of Transcriptome Sequencing and MYB Transcription Factor Family in <i>Rhododendron lapponicum</i>
Bibliographic record
Abstract
MYB transcription factor is the largest family of transcription factors in plants, and they are involved in the regulation of plant growth and development, secondary metabolism, adversity stress and other biological processes. So far, there is no the study on the MYB transcription factor of Rhododendron lapponicum . In this study, the Rhododendron lapponicum variety ‘Fuli Jinling’ transcriptome was generated by SMRT sequencing technology. A total of 15.37 Gb data was obtained, and 75 002 transcript sequences were obtained by removing redundancy. 71 155, 33 653 and 30 359 transcripts were assigned to the Nr, GO and COG databases, respectively. Based on the transcriptome sequencing data, 64 transcription factor gene families were identified, including 220 MYB genes. According to the structural characteristics, the MYB gene is divided into four categories, including 1R-MYB, R2R3-MYB, R1R2R3-MYB and 4R-MYB. The amino acid sequence of MYB transcription factor contains 20 conserved elements. Phylogenetic analysis showed that the MYB genes of Rhododendron lapponicum could be divided into 28 subclasses. In this study, we first used SMRT sequencing technology to generate the Rhododendron lapponicum transcriptome. In this study, single molecule real time (SMRT) technology was used to sequence the transcriptome of the Rhododendron lapponicum variety 'Fuli Jinling', and the obtained transcript sequences were functionally annotated and classified, and 220 MYB genes for bioinformatics analysis, these related results have certain reference significance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".