在全球气候变化下,多态信息传达入侵风险
Yiyong Chen1, Yangchun Gao2, Zhixin Zhang3,4
1Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China.
Global change biology
|November 16, 2024
概括
基因组和表观基因组变异在物种适应气候变化的过程中发挥着互补作用. 将这些多omics数据集成到预测模型中,有助于评估未来的生物入侵风险.
科学领域:
- 生态生态学 生态生态学
- 进化生物学 进化生物学
- 遗传学 是一个遗传学.
背景情况:
- 全球气候变化加剧了生物入侵.
- 基因组和表观基因组变异在适应气候变化的作用尚未完全理解.
研究的目的:
- 在入侵性树中研究基因组和表观基因组对未来气候的反应 *Botryllus schlosseri*.
- 通过整合多个领域的数据,制定一个框架来评估未来的入侵风险.
主要方法:
- 利用了通用的不相似性建模和梯度森林分析.
- 在预测的气候变化场景下评估基因组和表观基因组偏移.
- 开发了一个基因组-表观基因组指数来预测入侵风险.
主要成果:
- 在不同的种群中发生了基因组和表观基因组的不适应,这表明在适应中发挥了互补作用.
- 较低的基因组-表观基因组指数值与未来更高的入侵风险相关.
- 原生种群的抵消率低于入侵种群,这表明了更大的适应能力和更高的入侵风险.
结论:
- 多主题数据集成对于准确预测气候 (不良) 适应至关重要.
- 开发的框架加强了对气候变化下的生物入侵风险的评估.
- 了解基因组和表观基因组的贡献是管理在气候变化中的入侵物种的关键.
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