Modelling speciation: Problems and implications.

Q2 Medicine
Jonathan B L Bard
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引用次数: 0

Abstract

Darwin's and Wallace's 1859 explanation that novel speciation resulted from natural variants that had been subjected to selection was refined over the next 150 years as genetic inheritance and the importance of mutation-induced change were discovered, the quantitative theory of evolutionary population genetics was produced, the speed of genetic change in small populations became apparent and the ramifications of the DNA revolution became clear. This paper first discusses the modern view of speciation in its historical context. It then uses systems-biology approaches to consider the many complex processes that underpin the production of a new species; these extend in scale from genes to populations with the processes of variation, selection and speciation being affected by factors that range from mutation to climate change. Here, events at a particular scale level (e.g. protein network activity) are activated by the output of the level immediately below (i.e. gene expression) and generate a new output that activates the layer above (e.g. embryological development), with this change often being modulated by feedback from higher and lower levels. The analysis shows that activity at each level in the evolution of a new species is marked by stochastic activity, with mutation of course being the key step for variation. The paper examines events at each of these scale levels and particularly considers how the pathway by which mutation leads to phenotypic variants and the wide range of factors that drive selection can be investigated computationally. It concludes that, such is the complexity of speciation, most steps in the process are currently difficult to model and that predictions about future speciation will, apart from a few special cases, be hard to make. The corollary is that opportunities for novel variants to form are maximised.

建模物种形成:问题和影响。
达尔文和华莱士1859年的解释是,新物种的形成是由自然变异经过选择而产生的。随着基因遗传和突变诱导变化的重要性的发现,进化种群遗传学的定量理论的产生,小种群中基因变化的速度变得明显,DNA革命的后果变得清晰起来,达尔文和华莱士的解释在接下来的150年里得到了完善。本文首先在历史背景下讨论现代物种形成观。然后,它使用系统生物学的方法来考虑支撑新物种产生的许多复杂过程;这些变化在规模上从基因扩展到种群,变异、选择和物种形成的过程受到从突变到气候变化等因素的影响。在这里,特定规模水平的事件(如蛋白质网络活动)被紧接在下一级的输出(如基因表达)激活,并产生一个新的输出,激活上面的层(如胚胎发育),这种变化通常由来自更高和更低水平的反馈调节。分析表明,在新物种进化的每个层面上的活动都以随机活动为特征,突变当然是变异的关键步骤。本文研究了这些尺度水平上的事件,并特别考虑了如何通过突变导致表型变异的途径以及驱动选择的广泛因素可以通过计算来研究。它的结论是,由于物种形成的复杂性,这个过程中的大多数步骤目前都很难建模,而且除了少数特殊情况外,对未来物种形成的预测将很难做出。其必然结果是,新变体形成的机会被最大化了。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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