De novo evolution of complex, global and hierarchical gene regulatory mechanisms.
De novo evolution of complex, global and hierarchical gene regulatory mechanisms.
复制标题
DOI：
10.1007/s00239-010-9369-4
复制
发表时间：
2010-08
影响因子：
3.9
通讯作者：
Stekel, Dov J.
中科院分区：
文献类型：
--
作者：
Jenkins, Dafyd J.;Stekel, Dov J.
基因调控网络具有复杂的层次结构，如全局调控和网络基序。关于这些特征的进化起源是适应的结果，还是DNA复制的非适应过程的副产品，有很多争论。由于缺乏进化时间尺度上祖先物种的基因调控网络，这是一个特别难以解决的问题。然而，数字有机体可以用来提供谱系的完整进化记录。我们使用一个包含基因表达、调控、代谢和生物合成的生物学现实进化模型来研究基因调控网络中复杂功能的进化。我们发现：（i）网络架构和复杂性响应环境复杂性而进化，（ii）在复杂环境中选择全局基因调节，（iii）复杂的、相互关联的、分层结构分阶段进化，能量调节先于压力反应，压力反应先于生长率适应和（iv）进化模型对突变的鲁棒性取决于分层水平：能量调节和应激反应往往对突变不敏感，而生长速率适应在突变时更敏感且不致命。这些结果突出了复杂生物网络的适应性和增量进化，以及研究现实的计算机进化系统作为理解生命系统的一种方式的价值和潜力。本文的在线版本（doi：10.1007/s 00239 -010-9369-4）包含补充材料，可供授权用户使用。
Gene regulatory networks exhibit complex, hierarchical features such as global regulation and network motifs. There is much debate about whether the evolutionary origins of such features are the results of adaptation, or the by-products of non-adaptive processes of DNA replication. The lack of availability of gene regulatory networks of ancestor species on evolutionary timescales makes this a particularly difficult problem to resolve. Digital organisms, however, can be used to provide a complete evolutionary record of lineages. We use a biologically realistic evolutionary model that includes gene expression, regulation, metabolism and biosynthesis, to investigate the evolution of complex function in gene regulatory networks. We discover that: (i) network architecture and complexity evolve in response to environmental complexity, (ii) global gene regulation is selected for in complex environments, (iii) complex, inter-connected, hierarchical structures evolve in stages, with energy regulation preceding stress responses, and stress responses preceding growth rate adaptations and (iv) robustness of evolved models to mutations depends on hierarchical level: energy regulation and stress responses tend not to be robust to mutations, whereas growth rate adaptations are more robust and non-lethal when mutated. These results highlight the adaptive and incremental evolution of complex biological networks, and the value and potential of studying realistic in silico evolutionary systems as a way of understanding living systems. The online version of this article (doi:10.1007/s00239-010-9369-4) contains supplementary material, which is available to authorized users.
登录
查看更多内容
DOI：
10.1073/pnas.0702207104
发表时间：
2007-05-15
影响因子：
11.1
作者：
Lynch, Michael
通讯作者：
Lynch, Michael
影响因子：
5.6
作者：
Babu, MM;Teichmann, SA;Aravind, L
通讯作者：
Aravind, L
影响因子：
2
作者：
Dekel, E;Mangan, S;Alon, U
通讯作者：
Alon, U
影响因子：
56.9
作者：
Milo, R;Shen-Orr, S;Alon, U
通讯作者：
Alon, U
影响因子：
64.8
作者：
Lenski, RE;Ofria, C;Adami, C
通讯作者：
Adami, C