BACKGROUND Functional 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. RESULTS A 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. CONCLUSIONS As 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.

中文翻译：

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使功能网络约束与进化结果保持一致。

背景技术通过基因组结构的功能限制被认为是基因组进化的重要方面，但是这种想法的定量证据很少。在这一贡献中，关于基因组架构作为收敛进化，快速适应和基因适应的约束条件的现有证据和讨论被总结为可供选择的可检验的假设。然后，使用蛋白质-蛋白质相互作用网络的网络架构统计数据，以酵母基因组进化为例计算进化结果的差异，并使用结果评估这些长期存在的假设的统计支持。结果判别函数分析提供了统计支持，可根据网络邻域连通性将酵母相互作用组分类为中心，中间和外围节点，中间性中心和平均最短路径长度。然后，通过利用蛋白质-蛋白质相互作用网络的这些统计参数与蛋白质进化的估计值相结合，揭示了对基因组架构作为进化约束机制基础存在的定量支持。结论随着功能遗传网络的日益普及，现在有可能根据描述复杂表型和环境的变量评估功能遗传网络的约束条件，以更好地理解非模式生物中通常观察到的确定性进化模式。本文概述的假设框架和方法论方法可能有助于量化进化约束的外在与内在维度，