Cloning and <i>in silico</i> and expression analyses of the heterotrimeric G protein α subunit gene (<i>EjLGA1</i>) from loquat (<i>Eriobotrya japonica</i>) fruits under cold storage with different pretreatments
Bibliographic record
Abstract
Cold-stored fruits of the loquat (Eriobotrya japonica Lindl.) plant suffer from strong lignification, which leads to a hard texture and a crude mouthfeel of the pulp. However, the signalling mechanisms of loquat fruits under cold storage remain unclear. In this study, the heterotrimeric G protein α subunit (Gα) gene (EjLGA1) from loquat was isolated, and in silico analysis was performed. The levels of EjLGA1 expression in cold-stored loquat fruits with different pretreatments were also investigated. The largest open-reading frame of EjLGA1 is 1173 bp, encoding a polypeptide of 390 amino acids. The nucleotide and amino acid sequences of the Gα subunit are highly conserved among loquat and 48 other seed plants, indicating that the loquat Gα subunit likely has similar functions in other plants. A reliable model of the loquat Gα subunit was constructed, which revealed the structure of the subunit. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) results showed that EjLGA1 is highly expressed under cold storage, which suggests the significance of EjLGA1 function in loquat fruits in response to cold stress. However, ethephon and 1-methylcyclopropene (1-MCP) pretreatments did not regulate EjLGA1expression. These results provide new insight into the signalling mechanism in cold-stored loquat fruits.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".