拉,推或失败:基因驱动的人口影响可以改变其空间传播的性质
Léna Kläy1, Léo Girardin2, Vincent Calvez2
1Institute of Ecology and Environmental Sciences Paris (IEES Paris), Sorbonne Université, CNRS, IRD, INRAE, Université Paris Est Creteil, Université de Paris, Paris Cedex 5, Paris, France. lena.klay@sorbonne-universite.fr.
Journal of mathematical biology
|July 16, 2023
概括
在野外释放之前,建模基因驱动等位基因的传播至关重要. 这项研究表明,人口增长率显著影响基因驱动的入侵速度和传播,对生态应用有影响.
科学领域:
- 人口遗传学 人口遗传学
- 数学生物学 数学生物学
- 生态生态学 生态生态学
背景情况:
- 基因驱动等位基因偏向自身的传播,需要安全部署的预测模型.
- 以前的模型通常假定100%的基因转换,限制了对现实世界的应用.
研究的目的:
- 为基因驱动等位基因在1D空间环境中传播开发一个决定性的反应-扩散模型.
- 调查人口和等位基因动态对基因驱动器入侵速度的影响.
- 分析不同基因转换时间和概率以及人口增长率的影响.
主要方法:
- 开发了一个确定性的反应-扩散模型,将人口增长和基因驱动动力学纳入其中.
- 专注于移动波解决方案来确定基因驱动器入侵速度.
- 分析了内在增长率 (无限和消失) 的极端情况,并对中间值进行了数值模拟.
主要成果:
- 基因驱动的入侵可能是成功的或不成功的,根据人口增长率",拉"或"推"的波传播.
- 消失的增长率防止"推"波,通过SI模型类比允许通过分析解决方案.
- 假设在极端状态下"拉"波意味着一致的"拉"传播和独立于增长率的速度.
结论:
- 人口因素,特别是人口增长率,极大地影响了基因驱动传播动力学.
- 部分基因转换和不同的时间影响了入侵结果.
- 该模型提供了基因驱动传播独立于人口增长的条件,这对于风险评估至关重要.
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