Department of Mathematics, University of Maryland, College Park, MD 20740, USA.
Institute for Physical Science and Technology, University of Maryland, College Park, MD 20740, USA.
J R Soc Interface. 2021 Apr;18(177):20200790. doi: 10.1098/rsif.2020.0790. Epub 2021 Apr 14.
We study a simplified model of gene regulatory network evolution in which links (regulatory interactions) are added via various selection rules that are based on the structural and dynamical features of the network nodes (genes). Similar to well-studied models of 'explosive' percolation, in our approach, links are selectively added so as to delay the transition to large-scale damage propagation, i.e. to make the network robust to small perturbations of gene states. We find that when selection depends only on structure, evolved networks are resistant to widespread damage propagation, even without knowledge of individual gene propensities for becoming 'damaged'. We also observe that networks evolved to avoid damage propagation tend towards disassortativity (i.e. directed links preferentially connect high degree 'source' genes to low degree 'target' genes and vice versa). We compare our simulations to reconstructed gene regulatory networks for several different species, with genes and links added over evolutionary time, and we find a similar bias towards disassortativity in the reconstructed networks.
我们研究了一个简化的基因调控网络演化模型，其中链接（调控相互作用）是通过各种基于网络节点（基因）的结构和动态特征的选择规则添加的。与研究得很好的“爆发性”渗流模型类似，在我们的方法中，链接是有选择地添加的，以延迟大规模破坏传播的转变，即使网络对基因状态的小扰动具有鲁棒性。我们发现，当选择仅取决于结构时，即使没有关于单个基因易受损的知识，进化后的网络也能抵抗广泛的破坏传播。我们还观察到，为避免破坏传播而进化的网络往往具有非聚类性（即有向链接优先将高度数的“源”基因连接到低度数的“目标”基因，反之亦然）。我们将我们的模拟与为几个不同物种重建的基因调控网络进行了比较，这些网络在进化过程中添加了基因和链接，我们发现重建网络中也存在类似的非聚类性偏差。
