Wortel Meike T, Agashe Deepa, Bailey Susan F, Bank Claudia, Bisschop Karen, Blankers Thomas, Cairns Johannes, Colizzi Enrico Sandro, Cusseddu Davide, Desai Michael M, van Dijk Bram, Egas Martijn, Ellers Jacintha, Groot Astrid T, Heckel David G, Johnson Marcelle L, Kraaijeveld Ken, Krug Joachim, Laan Liedewij, Lässig Michael, Lind Peter A, Meijer Jeroen, Noble Luke M, Okasha Samir, Rainey Paul B, Rozen Daniel E, Shitut Shraddha, Tans Sander J, Tenaillon Olivier, Teotónio Henrique, de Visser J Arjan G M, Visser Marcel E, Vroomans Renske M A, Werner Gijsbert D A, Wertheim Bregje, Pennings Pleuni S
Swammerdam Institute for Life Sciences University of Amsterdam Amsterdam The Netherlands.
National Centre for Biological Sciences Bangalore India.
Evol Appl. 2022 Dec 9;16(1):3-21. doi: 10.1111/eva.13513. eCollection 2023 Jan.
Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.
传统上,进化是一门历史和描述性科学,长期以来,预测未来的进化过程一直被认为是不可能的。然而,进化预测在医学、农业、生物技术和保护生物学中越来越多地得到发展和应用。进化预测可用于不同目的,例如为未来做准备、尝试改变进化进程或确定我们对进化过程的理解程度。同样,我们想要预测的进化种群的确切方面也可能不同。例如,我们可以尝试预测哪种基因型将占主导地位、种群的适应性或种群的灭绝概率。此外,进化预测还有许多用途可能并不总是被人们所认识到。本综述的主要目标是通过展示进行进化预测的各种情况,提高不同研究领域对方法和数据的认识。我们描述了不同的进化预测如何共享一个由预测范围、时间尺度和精度所描述的共同结构。然后,通过使用从新冠病毒和流感到基于CRISPR的基因驱动以及生物技术中可持续产品形成等各种例子,我们讨论了预测进化的方法、影响可预测性的因素以及预测如何用于防止进化朝着不良方向发展或促进有益进化(即进化控制)。我们希望本综述将通过建立进化预测的通用语言来促进不同领域之间的合作。