未知未知:评估环境DNA测定特异性与未采样种类对比的框架
Taylor M Wilcox1, John A Kronenberger1, Michael K Young1
1USDA Forest Service, Rocky Mountain Research Station, National Genomics Center for Wildlife and Fish Conservation, Forestry Sciences Laboratory, Missoula, Montana, USA.
Molecular ecology resources
|January 24, 2024
概括
这项研究引入了一个新的框架,用于评估环境DNA (eDNA) 监测的定量PCR (qPCR) 分析特异性,即使缺少分类学数据. 该方法准确地预测了交叉放大风险,提高了eDNA检测可靠性.
科学领域:
- 环境DNA (eDNA) 监测监测
- 分子生态学分子生态学
- 生物信息学是一种生物信息学.
背景情况:
- 定量PCR (qPCR) 试验对于基于eDNA的动物存在检测至关重要.
- 鉴定验证是具有挑战性的,因为有很多非目标类型和不完整的分类学数据.
- 确保qPCR特异性对于准确的eDNA推断至关重要.
研究的目的:
- 开发和演示一个框架来评估使用交叉放大风险的定量模型的qPCR测定特异性.
- 为解决因非目标种群的序列信息缺失而导致的测试验证方面的挑战.
- 为支持eDNA测试验证工作提供可复制的方法.
主要方法:
- 利用交叉放大风险的定量模型来预测试验特异性.
- 将框架应用于四个不同的案例研究试验 (淡水关节动物,海洋,淡水甲类动物,淡水飞).
- 模拟缺少的信息,通过对非目标分类的分样进行测试,以测试框架的稳定性.
主要成果:
- 建模框架准确估计了交叉放大风险,显示与观察到的水平一致,即使有显著的数据缺失.
- 该方法在模拟数据缺口方面被证明是稳健的,这表明它对现实应用的可靠性.
- 案例研究证明了该框架在不同种类和环境中的适用性.
结论:
- 开发的框架为在eDNA监测中评估qPCR测定特异性的可靠方法提供了可靠的方法,特别是当序列数据不完整时.
- 这种方法提高了基于eDNA的生物多样性评估的准确性和可靠性.
- 提供了一个R Markdown模板,以促进可重现的测试验证报告.
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