Changes in transcriptomic response to salinity stress induce the brackish water adaptation in a freshwater snail
Bibliographic record
Abstract
Studying the mechanisms of the establishment of a population in a novel environment allows us to examine the process of local adaptations and subsequent range expansion. In a river system, detecting genetic or phenotypic differences between a freshwater and brackish water population could contribute to our understanding of the initial process of brackish water adaptation. Here, we investigated behavioural and gene expression responses to salt water in a freshwater and brackish water population of the freshwater snail, Semisulcospira reiniana. Although the individuals in brackish water exhibited significantly higher activity in saltwater than freshwater individuals just after sampling, the activity of freshwater individuals had increased in the second observation after rearing, suggesting that their salinity tolerance was plastic rather than genetic. We found 476 and 1002 differentially expressed genes across salinity conditions in the freshwater and brackish water populations, respectively. The major biological process involved in the salinity response of the freshwater population was the biosynthesis and metabolic processing of nitrogen-containing compounds, but that of the brackish water population was influenced by the chitin metabolic process. These results suggest that phenotypic plasticity induces adaptation to brackish water in the freshwater snail by modifying its physiological response to salinity.
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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".