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使用互信息适应度和计算机模拟进化预测胚胎模式。

Predicting embryonic patterning using mutual entropy fitness and in silico evolution.

机构信息

Center for studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, 10065 New York, NY, USA.

出版信息

Development. 2010 Jul;137(14):2385-95. doi: 10.1242/dev.048033.

Abstract

During vertebrate embryogenesis, the expression of Hox genes that define anterior-posterior identity follows general rules: temporal colinearity and posterior prevalence. A mathematical measure for the quality or fitness of the embryonic pattern produced by a gene regulatory network is derived. Using this measure and in silico evolution we derive gene interaction networks for anterior-posterior (AP) patterning under two developmental paradigms. For patterning during growth (paradigm I), which is appropriate for vertebrates and short germ-band insects, the algorithm creates gene expression patterns reminiscent of Hox gene expression. The networks operate through a timer gene, the level of which measures developmental progression (a candidate is the widely conserved posterior morphogen Caudal). The timer gene provides a simple mechanism to coordinate patterning with growth rate. The timer, when expressed as a static spatial gradient, functions as a classical morphogen (paradigm II), providing a natural way to derive the AP patterning, as seen in long germ-band insects that express their Hox genes simultaneously, from the ancestral short germ-band system. Although the biochemistry of Hox regulation in higher vertebrates is complex, the actual spatiotemporal expression phenotype is not, and simple activation and repression by Hill functions suffices in our model. In silico evolution provides a quantitative demonstration that continuous positive selection can generate complex phenotypes from simple components by incremental evolution, as Darwin proposed.

摘要

在脊椎动物胚胎发生过程中,定义前后身份的 Hox 基因的表达遵循一般规则:时间线性和后向优势。为基因调控网络产生的胚胎模式的质量或适应性导出了一个数学度量。使用该度量和计算机模拟进化,我们为两种发育范例下的前后(AP)模式生成了基因相互作用网络。对于生长过程中的模式形成(范例 I),它适用于脊椎动物和短体节昆虫,该算法创建了类似于 Hox 基因表达的基因表达模式。网络通过计时器基因运作,其水平衡量发育进展(一个候选者是广泛保守的后形态发生因子 Caudal)。计时器提供了一种简单的机制来协调模式形成与生长速度。当计时器表达为静态空间梯度时,它作为经典形态发生因子(范例 II)发挥作用,为从同时表达其 Hox 基因的祖先短体节系统中衍生出长体节昆虫所见的 AP 模式提供了一种自然方式。尽管高等脊椎动物中 Hox 调节的生物化学非常复杂,但实际的时空表达表型并非如此,并且我们的模型中简单的 Hill 函数激活和抑制就足够了。计算机模拟进化提供了定量证明,即连续正选择可以通过渐进进化从简单组件生成复杂表型,正如达尔文所提出的。

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