Abiotic environmental adaptation in vertebrates is characterized by functional genomic constraint
Bibliographic record
Abstract
Abstract Understanding the genomic basis of adaptation to different abiotic environments is important for understanding organismal responses to current short-term environmental fluctuations. Using functional and comparative genomics approaches, we here investigated whether genomic adaptation to a set of environmental parameters is contingent across vertebrate genomes or, alternatively, contains an element of evolutionary constraint that would be evident through recurrent involvement of specific subsets of genes and functions in adaptation to similar environments. We first identified 200 genes with signatures of selection from transcriptomes of 24 species of lacertid lizards with known adaptations in preferred temperature, correlated with thermal environment experienced by these lizards in their range. In order to discern genes adapting to climate from other selective factors, we then performed a meta-analysis of 1100 genes with signatures of selection obtained from-omics studies in vertebrate species adapted to different abiotic environments. We found that this gene set formed a tightly connected interactome which was to 23% enriched in predicted functions of adaptation to climate and to 18% involved in organismal stress response. We found a much higher degree of recurrent use of identical genes (43.6%) and functional similarity than expected by chance, and no clear division between genes used in ectotherm and endotherm physiological strategies. 171 out of 200 genes of Lacertidae were part of this network, indicating that a comparative genomic approach can help to disentangle genes functionally related to adaptation to different abiotic environments from other selective factors. These results furthermore highlight an important role of genomic constraint in adaptation to the abiotic environment, and narrows the set of candidate markers to be used in future research on environmental adaptability related to climate change. Significance Statement / Nontechnical summary While the convergent evolution of phenotypes in similar environments is a well-studied phenomenon, the genomic basis of such common phenotypes and physiologies is still enigmatic. The prevalent notion is that re-use of the same genes to adapt to similar environments in different species is about as likely as winning the lottery – but organismal systems are also, to some extent, comparable between different species such as man and fruit fly through shared genes and gene functions. In this paper, we test whether constraint or contingency is more prevalent in genomic adaptation of vertebrates to aspects of their abiotic environment. We find evidence for strong functional constraint and stress responsiveness of the genes involved, which might help understand how currently experienced stress under changing climates may result in future adaptation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".