Conservation and coevolution in the scale-free human gene coexpression network
Conservation and coevolution in the scale-free human gene coexpression network
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DOI：
10.1093/molbev/msh222
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发表时间：
2004-11-01
影响因子：
10.7
通讯作者：
Koonin, EV
中科院分区：
文献类型：
--
作者：
Jordan, IK;Mariño-Ramírez, L;Koonin, EV
自然选择在生物学中的作用得到了很好的赞赏。然而，最近，已经揭示了网络自我组织的物理原理在生物系统中的关键作用。在这里，我们采用了基因组尺度序列和表达数据的系统级别观察，以检查人类基因调控的演变这两个秩序来源，自然选择和物理自组织之间的相互作用。从组织特异性表达曲线得出的人基因共表达网络的拓扑表现出无尺度的特性，这些特性暗示着通过优先节点附着的进化自我组织。与具有较少共表达伴侣的基因相比，具有众多共表达伴侣（共表达网络的枢纽）的基因的平均发展速度较慢，而共表达的基因显示出相似的进化速率。因此，基因序列的选择性约束的强度受基因共表达网络拓扑的影响。对于编码区域和3'非翻译区域（UTRS），这种连接很强，但是5'UTR似乎在不同的制度下发展。令人惊讶的是，我们发现基因序列差异速率与人与小鼠之间的基因表达谱差异之间没有联系。这表明自然选择的不同模式可能控制序列与表达差异，我们提出了一个基于自然选择如何影响基因表达差异的基因表达模式的快速，适应驱动的差异和基因表达模式的收敛演化的模型。
The role of natural selection in biology is well appreciated. Recently, however, a critical role for physical principles of network self-organization in biological systems has been revealed. Here, we employ a systems level view of genome-scale sequence and expression data to examine the interplay between these two sources of order, natural selection and physical self-organization, in the evolution of human gene regulation. The topology of a human gene coexpression network, derived from tissue-specific expression profiles, shows scale-free properties that imply evolutionary self-organization via preferential node attachment. Genes with numerous coexpressed partners (the hubs of the coexpression network) evolve more slowly on average than genes with fewer coexpressed partners, and genes that are coexpressed show similar rates of evolution. Thus, the strength of selective constraints on gene sequences is affected by the topology of the gene coexpression network. This connection is strong for the coding regions and 3' untranslated regions (UTRs), but the 5' UTRs appear to evolve under a different regime. Surprisingly, we found no connection between the rate of gene sequence divergence and the extent of gene expression profile divergence between human and mouse. This suggests that distinct modes of natural selection might govern sequence versus expression divergence, and we propose a model, based on rapid, adaptation-driven divergence and convergent evolution of gene expression patterns, for how natural selection could influence gene expression divergence.