Genome-wide identification and functional prediction of long non-coding RNAs in Sprague-Dawley rats during heat stress
Bibliographic record
Abstract
Abstract Background Heat stress (HS) is a major stress event in the life of an animal, with detrimental upshots in production and health. Long-non-coding RNAs (lncRNAs) play an important role in many biological processes by transcriptional regulation. However, no research has been reported on the characterization and functionality of lncRNAs in heat-stressed rats. Results We studied expression levels of lncRNAs in rats during HS, using strand-specific RNA sequencing. Six rats, three in each of Control (22 ± 1 °C) and H120 (42 °C for 120 min) experimental groups, were used to screen for lncRNAs in their liver and adrenal glands. Totally, 4498 and 7627 putative lncRNAs were identified in liver and adrenal glands of the Control and H120 groups, respectively. The majority of lncRNAs were relatively shorter and contained fewer exons than protein-coding transcripts. In total, 482 (174 up-regulated and 308 down-regulated) and 271 (126 up-regulated and 145 down-regulated) differentially-expressed lncRNAs (DElncRNAs, P < 0.05) were identified in the liver and adrenal glands of the Control and H120 groups, respectively. Furthermore, 1274, 121, and 73 target differentially-expressed genes (DEGs) in the liver were predicted to interact with DElncRNAs based on trans−/cis- and sequence similarity regulatory modes. Functional annotation analyses indicated that these DEGs were mostly significantly enriched in insulin signalling, myeloid leukaemia, and glucagon signalling pathways. Similarly, 437, 73 and 41 target DEGs in the adrenal glands were mostly significantly enriched in the cell cycle (trans-prediction) and lysosome pathways (cis-prediction). The DElncRNAs interacting with DEGs that encode heat shock proteins (HSPs) may play an important role in HS response, which include Hsf4, Dnaja1, Dnajb4, Hsph1 and Hspb1 in the liver, and Dnajb13 and Hspb8 in the adrenal glands. The strand-specific RNA sequencing findings were also further verified through RT-qPCR. Conclusions This study is the first to provide a detailed characterization and functional analysis of expression levels of lncRNAs in liver and adrenal glands of heat-stressed rats, which provides basis for further studies on the biological functions of lncRNAs under heat stress in rats and other mammalian species.
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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 | 0.000 |
| 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 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".