通过对环境样本进行元编码来研究真菌多样性:使用多个定义模拟社区的不同分类方法和参考数据库评估ITS1和ITS2Illumina测序
Raf Winand1, Elizabet D'hooge2, Alexander Van Uffelen1,3
1Transversal activities in Applied Genomics, Sciensano, 1050, Brussels, Belgium.
BMC genomics
|August 7, 2025
概括
使用元编码准确地捕捉环境样本中的真菌多样性,需要仔细选择测序区域,数据库和软件. 结果显示,性能各不相同,基因级分类和特定数据库提供更好的真菌识别.
科学领域:
- 环境微生物学环境微生物学
- 菌类学 菌类学是指菌类学.
- 生物信息学是一种生物信息学.
背景情况:
- 环境样本中真菌的准确分类对了解生物多样性至关重要.
- 使用内部转录间隔器 (ITS) 区域进行的元编码是一种常见的真菌识别方法.
- 各种因素影响元编码的准确性,包括ITS区域的选择,参考数据库和生物信息学工具.
研究的目的:
- 为了比较评估不同的菌多样性评估的metabarcoding方法.
- 评估测序区域 (ITS1/ITS2),参考数据库 (UNITE/BCCM/IHEM),软件 (BLAST/mothur) 和分类层 (物种/属) 对分类准确性的影响.
- 为选择最佳的元编码策略提供指导,用于复杂样本中的真菌识别.
主要方法:
- 利用了37个定义的真菌模拟群落 (DMCs),涵盖了Ascomycota,Basidiomycota和Mucoromycota.
- 对ITS1和ITS2区域进行了Sanger和Illumina测序的比较.
- 使用BLAST和其它生物信息学软件对UNITE和BCCM/IHEM数据库进行物种和属级别的性能评估.
主要成果:
- 根据所有测试的变量,分类性能差异很大 (56-100%的物种被正确分配).
- 属级分类通常比物种级分类更好.
- BCCM/IHEM数据库的表现优于UNITE;BLAST在专家策划下表现更好,而Mothur在自动化工作流程方面表现更好.
结论:
- 没有单一的元编码方法是普遍最佳的;选择取决于研究目标.
- 照明测序为真菌多样性研究提供了强大的工具,但需要仔细优化工作流程.
- 数据库和分类层面的选择对真菌识别的准确性产生了重大影响.
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