Better Transcriptomic Stability and Broader Transcriptomic Thermal Response Range Drive the Greater Thermal Tolerance in a Global Invasive Turtle Relative to Native Turtle
Why this work is in the frame
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Bibliographic record
Abstract
Greater thermal tolerance of invasive species benefits their survival and spread under extreme climate events, especially under global warming. Revealing the mechanisms underlying the interspecific differences in thermal tolerance between invasive and native species can help understand the invasion process and predict potential invaders. Here, we link the changes in global transcriptomics and antioxidant defense at multiple temperatures with the differences in thermal limits in the juveniles of a successful globally invasive turtle, Trachemys scripta elegans, and a native turtle in China, Mauremys reevesii. The two species show different thermal tolerances and have co-existed in habitats with the risk of overheating. The majority of the transcriptional response to thermal stress is conserved in the two turtle species, including protein folding or DNA damage responses activated under relatively moderate thermal stress and regulation of the cell cycle and apoptosis during severe thermal stress. Greater thermal tolerance of T. scripta elegans can be associated with a more stable global transcriptome during thermal stress, except for necessary stress responses, and a broader thermal range of continuous up-regulation of the core mechanisms promoting survival under thermal stress, mainly protein folding and negative regulation of apoptosis. Under extreme hot conditions, the opposite change trends of genes involved in survival mechanisms during thermal stress between invasive and native turtles can be due to differences in energy turnover. The present study provides insights into the mechanisms of physiological differences between invasive and native species given global transcriptional changes and helps understand successful invasion and predict potential invasive species.
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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 | 0.001 |
| 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 it