Predicting evolution
Predicting evolution
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DOI：
10.1038/s41559-017-0077
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发表时间：
2017-03-01
影响因子：
16.8
通讯作者：
Walczak, Aleksandra M.
中科院分区：
文献类型：
--
作者：
Laessig, Michael;Mustonen, Ville;Walczak, Aleksandra M.
进化生物学的面貌正在发生变化：从重建和分析过去到预测未来的进化过程。最近的发展包括预测平行进化实验中的可重复模式，使用过去的数据预测个体种群的未来，以及控制操纵进化动力学。在这里，我们进行了一个综合的核心概念的进化预测，微生物和病毒系统，癌细胞群，免疫受体库的基础上的例子。这些系统具有惊人相似的进化动力学，由种群内进化枝的竞争驱动。这些动态是预测进化枝频率以及广泛的遗传和表型变化的模型的基础。此外，预测和控制之间存在密切联系，这对于疫苗或治疗设计等干预措施非常重要。所有这些都是可能成为预测性进化理论的关键要素。
The face of evolutionary biology is changing: from reconstructing and analysing the past to predicting future evolutionary processes. Recent developments include prediction of reproducible patterns in parallel evolution experiments, forecasting the future of individual populations using data from their past, and controlled manipulation of evolutionary dynamics. Here we undertake a synthesis of central concepts for evolutionary predictions, based on examples of microbial and viral systems, cancer cell populations, and immune receptor repertoires. These systems have strikingly similar evolutionary dynamics driven by the competition of clades within a population. These dynamics are the basis for models that predict the evolution of clade frequencies, as well as broad genetic and phenotypic changes. Moreover, there are strong links between prediction and control, which are important for interventions such as vaccine or therapy design. All of these are key elements of what may become a predictive theory of evolution.