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Wollenberg Valero, K.

Publications and source records attributed to Wollenberg Valero, K..

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Abiotic environmental adaptation in vertebrates is characterized by functional genomic constraint

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.\n\nSignificance Statement / Nontechnical summaryWhile 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.

evolutionary biology↗

Aligning functional network constraint to evolutionary outcomes

It is likely that there are constraints on how evolution can progress, and well-known evolutionary phenomena such as convergent evolution, rapid adaptation, and genic evolution would be difficult to explain under the absence of any such evolutionary constraint. One dimension of constraint results from a finite number of environmental conditions, and thus natural selection scenarios, leading to convergent phenotypes. This limits which genetic variants are adaptive, and consequently, constrains how variation is inherited across generations. Another, less explored dimension of evolution is functional constraint at the molecular level. Some widely accepted examples for this dimension of evolutionary constraint include genetic linkage, codon position, and architecture of developmental genetic pathways, that together constrain how evolution can shape genomes through limiting which mutations can increase fitness. Genomic architecture, which describes how all gene products interact, has been discussed to be another dimension of functional genetic constraint. This notion had been largely discredited by the modern synthesis, especially because macroevolution was not always found to be perfectly deterministic. But debates on whether evolutionary constraint stems mostly from environmental (extrinsic) or genetic (intrinsic) factors have mostly been held at the intellectual level using sporadic evidence. Quantifying the relative contributions of these different dimensions of constraint is, however, fundamentally important to understand the mechanistic basis of seemingly deterministic evolutionary outcomes. In some model organisms, genetic constraint has already been quantitatively explored. Forays into testing the relationship between genomic architecture and evolution included studies on protein evolutionary rate variation in essential versus nonessential genes, and observations that the number of protein interactions within a cell (gene pleiotropy) determines the fitness effect of mutations. In this contribution, existing evidence for functional genetic constraint as shaping evolutionary outcomes is reviewed and testable hypotheses are defined for functional genetic constraint influencing (i) convergent evolution, (ii) rapid adaptation, and genic adaptation. An analysis of the yeast interactome incorporating recently published data on its evolution, reveals new support for the existence of genomic architecture as a functional genetic dimension of evolutionary constraint. As functional genetic networks are becoming increasingly available, evolutionary biologists should strive to evaluate functional genetic network constraint, against variables describing complex phenotypes and environments, for better understanding commonly observed deterministic patterns of evolution in non-model organisms. This may help to quantify the extrinsic versus intrinsic dimensions of evolutionary constraint, and result in a better understanding of how fast, effectively, or deterministically organisms adapt.\n\nGlossary

evolutionary biology↗