Differential Mitochondrial Genome Expression of Four Skink Species Under High-Temperature Stress and Selection Pressure Analyses in Scincidae
Bibliographic record
Abstract
As ectotherms highly sensitive to environmental temperature fluctuations, skinks (a small lizard) are increasingly vulnerable to population instability due to global heatwaves. A clade model analysis of four Chinese skink species (Plestiodon capito, Plestiodon chinensis, Sphenomorphus indicus, and Scincella modesta) revealed positive selection acting on the ND6 gene in Sp. indicus. This species exhibits codon alterations in ND6, shifts its expression pathway and potentially decouples ND6 from high-temperature stress response mechanisms. To validate these findings, transcriptomic profiling was conducted to assess mitochondrial protein-coding gene (PCG) expression patterns under thermal stress. Using RT-qPCR, liver mitochondrial PCG transcript levels were compared between high-temperature (34 °C) and control (25 °C) groups in skink populations from distinct latitudes. Low-latitude species (P. chinensis and Sc. modesta) exhibited metabolic downregulation, characterized by a significant suppression of mitochondrial gene expression. Specifically, P. chinensis showed the downregulation of six mitochondrial genes (COII, COIII, ATP6, ND2, ND4, ND6) while upregulating one (ND1). By contrast, Sc. modesta showed the downregulation of nine genes (COI, COII, COIII, ATP8, ND1, ND3, ND4, ND4L, CYTB) and upregulated two (ND5, ND6). By contrast, high-latitude species exhibited divergent patterns: P. capito downregulated four genes (COI, COII, COIII, ND4L) and upregulated four others (ND1, ND2, ND3, ND4), whereas Sp. indicus downregulated six genes (COI, COII, ND2, ND3, ND4, ND4L) and upregulated one (ND5). These regulatory disparities suggest that low-latitude skinks have a greater capacity for metabolic depression to cope with chronic stress, whereas their high-latitude counterparts exhibit different adaptations. The findings provide valuable insights into assessing the adaptive potential of species in warming environments, particularly for ectotherms with limited thermoregulatory capacities.
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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 | 0.001 | 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".