Abstract
BackgroundFunctional constraint through genomic architecture is suggested to be an important dimension of genome evolution, but quantitative evidence for this idea is rare. In this contribution, existing evidence and discussions on genomic architecture as constraint for convergent evolution, rapid adaptation, and genic adaptation are summarized into alternative, testable hypotheses. Network architecture statistics from protein-protein interaction networks are then used to calculate differences in evolutionary outcomes on the example of genomic evolution in yeast, and the results are used to evaluate statistical support for these longstanding hypotheses.ResultsA discriminant function analysis lent statistical support to classifying the yeast interactome into hub, intermediate and peripheral nodes based on network neighborhood connectivity, betweenness centrality, and average shortest path length. Quantitative support for the existence of genomic architecture as a mechanistic basis for evolutionary constraint is then revealed through utilizing these statistical parameters of the protein-protein interaction network in combination with estimators of protein evolution.ConclusionsAs functional genetic networks are becoming increasingly available, it will now be possible to evaluate functional genetic network constraint against variables describing complex phenotypes and environments, for better understanding of commonly observed deterministic patterns of evolution in non-model organisms. The hypothesis framework and methodological approach outlined herein 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.
Highlights
Functional constraint through genomic architecture is suggested to be an important dimension of genome evolution, but quantitative evidence for this idea is rare
These observations made in natural populations suggest that the variants available to mutation and selection may be constrained at the genomic level, enabling faster adaptations and higher rates of convergent evolution than were possible without constraint
Statistics computed on edge distributions in non-model organisms may change over time as more experimental evidence on interactions becomes available, and evolutionary constraint might differ by the type of interactions studied
Summary
Functional constraint through genomic architecture is suggested to be an important dimension of genome evolution, but quantitative evidence for this idea is rare. Divergent genetic populations of the well-studied Caribbean lizard Anolis cybotes [3] have evolved convergent phenotypic, ecological, reproductive, and physiological adaptations to high elevations on three separate mountain chains, which is mirrored by genomic adaptations in a subset of genes [4,5,6,7]. These observations made in natural populations suggest that the variants available to mutation and selection may be constrained at the genomic level, enabling faster adaptations and higher rates of convergent evolution than were possible without constraint. Mayr [10] stated that
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