Theoretical Biology and Bioinformatics, Department of Biology, Faculty of Science, Utrecht University, Padualaan 8, 3584CH Utrecht, The Netherlands.
BMC Evol Biol. 2012 Jun 25;12:99. doi: 10.1186/1471-2148-12-99.
The study of biological networks and how they have evolved is fundamental to our understanding of the cell. By investigating how proteins of different ages are connected in the protein interaction network, one can infer how that network has expanded in evolution, without the need for explicit reconstruction of ancestral networks. Studies that implement this approach show that proteins are often connected to proteins of a similar age, suggesting a simultaneous emergence of interacting proteins. There are several theories explaining this phenomenon, but despite the importance of gene duplication in genome evolution, none consider protein family dynamics as a contributing factor.
In an S. cerevisiae protein interaction network we investigate to what extent edges that arise from duplication events contribute to the observed tendency to interact with proteins of a similar age. We find that part of this tendency is explained by interactions between paralogs. Age is usually defined on the level of protein families, rather than individual proteins, hence paralogs have the same age. The major contribution however, is from interaction partners that are shared between paralogs. These interactions have most likely been conserved after a duplication event. To investigate to what extent a nearly neutral process of network growth can explain these results, we adjust a well-studied network growth model to incorporate protein families. Our model shows that the number of edges between paralogs can be amplified by subsequent duplication events, thus explaining the overrepresentation of interparalog edges in the data. The fact that interaction partners shared by paralogs are often of the same age as the paralogs does not arise naturally from our model and needs further investigation.
We amend previous theories that explain why proteins of a similar age prefer to interact by demonstrating that this observation can be partially explained by gene duplication events. There is an ongoing debate on whether the protein interaction network is predominantly shaped by duplication and subfunctionalization or whether network rewiring is most important. Our analyses of S. cerevisiae protein interaction networks demonstrate that duplications have influenced at least one property of the protein interaction network: how proteins of different ages are connected.
研究生物网络及其进化方式对于我们理解细胞至关重要。通过研究不同年龄的蛋白质在蛋白质相互作用网络中的连接方式，可以推断出该网络在进化过程中是如何扩展的，而无需明确重建祖先网络。实施这种方法的研究表明，蛋白质通常与年龄相似的蛋白质相连接，这表明相互作用的蛋白质同时出现。有几种理论可以解释这种现象，但尽管基因复制在基因组进化中很重要，但没有一种理论将蛋白质家族的动态变化视为一个促成因素。
在一个酿酒酵母蛋白质相互作用网络中，我们研究了源于复制事件的边在多大程度上有助于解释观察到的与年龄相似的蛋白质相互作用的趋势。我们发现，这种趋势的一部分可以用旁系同源物之间的相互作用来解释。年龄通常是在蛋白质家族的层面上定义的，而不是单个蛋白质，因此旁系同源物具有相同的年龄。然而，主要的贡献来自于旁系同源物之间共享的相互作用伙伴。这些相互作用很可能在复制事件后得到了保留。为了研究网络增长的近乎中性过程在多大程度上可以解释这些结果，我们调整了一个经过充分研究的网络增长模型，以纳入蛋白质家族。我们的模型表明，旁系同源物之间的边数可以通过随后的复制事件放大，从而解释了数据中旁系同源物之间边的过度表示。旁系同源物共享的相互作用伙伴通常与旁系同源物年龄相同，这并不是我们模型自然产生的，需要进一步研究。
我们通过证明这种观察结果可以部分解释为基因复制事件，修正了先前解释为什么年龄相似的蛋白质喜欢相互作用的理论。关于蛋白质相互作用网络主要是由复制和亚功能化塑造的，还是网络重布线最重要，目前仍存在争议。我们对酿酒酵母蛋白质相互作用网络的分析表明，复制至少影响了蛋白质相互作用网络的一个特性：不同年龄的蛋白质是如何连接的。
