Data from: Mitochondrial genotype and phenotypic plasticity of gene expression in response to cold acclimation in killifish
Bibliographic record
Abstract
Adjustments of aerobic metabolic processes are critical components of organismal responses to environmental change that require tight co-ordination between the nuclear and mitochondrial genomes. Intraspecific differences in mitochondrial genotype can affect gene transcription in both genomes. Thus, variation in mitochondrial genotype may be associated with differences in the plasticity of gene expression when organisms are faced with changes in environmental conditions. Cold acclimation is known to result in metabolic responses involving increases in mitochondrial amount and capacity, suggesting that low temperatures may pose a particular challenge when co-ordinating the functions of the nuclear and mitochondrial genomes. In this study, we utilized RNA-seq to assess transcriptome-wide gene expression in the muscle of Atlantic killifish (Fundulus heteroclitus) from a population that contains segregating variation in mitochondrial genotype. We examined gene expression plasticity in response to 5°C acclimation and the effects of mitochondrial genotype on this plasticity. Cold acclimation resulted in changes in gene expression consistent with up-regulation of genes involved in many cellular functions, including spliceosomal and proteasomal processes, and with down-regulation of genes involved in extracellular matrix, muscle contraction and oxidative phosphorylation functions. There were few differences in gene expression between killifish with different mitochondrial genotypes: 14 genes demonstrated significant interactions between mitochondrial genotype and acclimation temperature and 3 genes demonstrated effects of mitochondrial genotype alone. These results indicate that variation in mitochondrial genotype has modest effects on gene expression; the majority of which are revealed as differences in plasticity as a result of environmental change.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.014 |
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".