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用基因组数据预测物种入侵性:基因组偏移与建立概率有关吗?

Louise Camus¹, Mathieu Gautier¹, Simon Boitard¹

¹CBGP, INRAE, CIRAD, IRD, L'institut Agro, Université de Montpellier Montpellier France.

Evolutionary applications

|June 17, 2024

概括

基因组偏移 (GO) 统计可以预测入侵物种的建立概率. 这种进化生物学工具可以通过测量人口适应新环境来评估入侵风险.

科学领域:

进化生物学进化生物学
基因组学就是基因组学.
侵入性物种研究侵入性物种研究

背景情况:

预测原生范围之外的物种的建立是一个重大挑战.
基因组偏移 (GO) 统计提供了一个有希望的方法,使用基因组数据来评估人口适应新环境.
在入侵物种研究中,GO方法未得到充分利用.

研究的目的:

评估基因组偏移 (GO) 与新环境中人口建立概率之间的关系.
使用模拟来评估两个GO计算方法 (几何GO和梯度森林) 的预测性能.
探索几何GO值的解释性作为适应性遗传距离的测量.

主要方法:

进行了in silico入侵模拟,以测试几何GO和梯度森林方法.
分析了来自侵入性果 *Bactrocera tryoni* 的实证数据.
在本地"来源"人口和各种入侵地点之间计算了GO.

主要成果:

基因组偏移统计表明,对建立概率有很强的预测能力.
模拟证实了GO方法在各种条件下预测建立的能力.
经验应用突出了GO在对"Bactrocera tryoni"的入侵风险评估中的有用性.

结论:

基因组偏移统计是有效预测人口建立概率的指标.
GO可以为入侵风险评估提供信息,帮助管理和预测.
需要进一步的研究来调查影响GO预测性能的诸如传导压力和添加剂等因素.

关键词:

巴克特罗塞拉试 (Bactrocera tryoni) 是一种植物.在GEAEA中,GEA是GEA.生物入侵生物入侵基因组偏移的抵消地方适应地方适应

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