Data from: Plasticity in gene transcription explains the differential performance of two invasive fish species
Bibliographic record
Abstract
Phenotypic plasticity buffers organisms from environmental change and is hypothesized to aid the initial establishment of non-indigenous species in novel environments and post-establishment range expansion. The genetic mechanisms that underpin phenotypically plastic traits are generally poorly characterized; however, there is strong evidence that modulation of gene transcription is an important component of these responses. Here we use RNA sequencing to examine the transcriptional basis of temperature tolerance for round and tubenose goby, two non-indigenous fish species that differ dramatically in the extent of their Great Lakes invasions despite similar invasion dates. We used generalized linear models of read count data to compare gene transcription responses of organisms exposed to increased and decreased water temperature from those at ambient conditions. We identify greater response in the magnitude of transcriptional changes for the more successful round goby compared with the less successful tubenose goby. Round goby transcriptional responses reflect alteration of biological function consistent with adaptive responses to maintain or regain homeostatic function in other species. In contrast, tubenose goby transcription patterns indicate a response to stressful conditions, but the pattern of change in biological functions do not match those expected for a return to homeostatic status. Transcriptional plasticity plays an important role in the acute thermal tolerance for these species; however, the impaired response to stress we demonstrate in the tubenose goby may contribute to their limited invasion success relative to the round goby. Transcriptional profiling allows the simultaneous assessment of the magnitude of transcriptional response as well as the biological functions involved in the response to environmental stress and is thus a valuable approach for evaluating invasion potential.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.064 | 0.018 |
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".