PI signal transduction and ubiquitination respond to dehydration stress in the red seaweed Gloiopeltis furcata under successive tidal cycles
Bibliographic record
Abstract
BACKGROUND: Intermittent dehydration caused by tidal changes is one of the most important abiotic factors that intertidal seaweeds must cope with in order to retain normal growth and reproduction. However, the underlying molecular mechanisms for the adaptation of red seaweeds to repeated dehydration-rehydration cycles remain poorly understood. RESULTS: We chose the red seaweed Gloiopeltis furcata as a model and simulated natural tidal changes with two consecutive dehydration-rehydration cycles occurring over 24 h in order to gain insight into key molecular pathways and regulation of genes which are associated with dehydration tolerance. Transcription sequencing assembled 32,681 uni-genes (GC content = 55.32%), of which 12,813 were annotated. Weighted gene co-expression network analysis (WGCNA) divided all transcripts into 20 modules, with Coral2 identified as the key module anchoring dehydration-induced genes. Pathways enriched analysis indicated that the ubiquitin-mediated proteolysis pathway (UPP) and phosphatidylinositol (PI) signaling system were crucial for a successful response in G. furcata. Network-establishing and quantitative reverse transcription PCR (qRT-PCR) suggested that genes encoding ubiquitin-protein ligase E3 (E3-1), SUMO-activating enzyme sub-unit 2 (SAE2), calmodulin (CaM) and inositol-1,3,4-trisphosphate 5/6-kinase (ITPK) were the hub genes which responded positively to two successive dehydration treatments. Network-based interactions with hub genes indicated that transcription factor (e.g. TFIID), RNA modification (e.g. DEAH) and osmotic adjustment (e.g. MIP, ABC1, Bam1) were related to these two pathways. CONCLUSIONS: RNA sequencing-based evidence from G. furcata enriched the informational database for intertidal red seaweeds which face periodic dehydration stress during the low tide period. This provided insights into an increased understanding of how ubiquitin-mediated proteolysis and the phosphatidylinositol signaling system help seaweeds responding to dehydration-rehydration cycles.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 teacher head, 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".