参考数据库中持续存在的空白和错误阻碍了18S rRNA研究中的生态意义上的分类学赋值:陆地和海洋线虫的案例研究
Alejandro De Santiago1,2, Tiago José Pereira1,2, Timothy John Ferrero3
1Department of Marine Sciences, University of Georgia, 325 Sanford Drive, Athens, GA 30602, USA.
概括
改善环境DNA (eDNA) 分类学对线虫等研究不足的群体的分配,需要精心策划的参考数据库和更好的分类型采样. 这提高了对生态解释的元编码分析的准确性.
科学领域:
- 分子生态学分子生态学
- 生物信息学是一种生物信息学.
- 基因组学就是基因组学.
背景情况:
- 操作分类单元 (OTU) 或扩展序列变异 (ASV) 的林纳分类学赋值对于环境DNA (eDNA) 元编码研究至关重要.
- 公共分子数据库对许多微生物甲基动物类群体的人口稀少,阻碍了准确的分类学赋值和生态解释.
- 生物信息学参数和算法可以显著影响eDNA分类学分配的精度和准确性.
研究的目的:
- 为了证明精心策划的林内亚分类学字符串和改进的分类学抽样如何在元编码中增强基于18S rRNA基因的分类学赋值.
- 为了评估BLAST+和QIIME2纯贝叶斯分类器在精选和未精选的参考数据库上的性能,使用自由生活的线虫作为案例研究.
主要方法:
- 使用了两个in-silico数据集来评估分类学赋值的准确性.
- 在SILVA 138参考数据库的六个代中应用了BLAST+和QIIME2纯粹贝叶斯分类器.
- 专注于自由生活的线虫,作为评估分类学分配精度和准确性的模型组.
主要成果:
- 策划林纳的分类学字符串和改善分类学样本显著增强了18S rRNA基因分类学赋值.
- 具有90%序列相似度截止值的BLAST+经常产生最高比例的正确的属级分类学赋值.
- 在使用具有纠正分类学字符串的参考数据库时,QIIME2天真贝叶斯分类器的性能与BLAST+相比.
结论:
- 迫切需要对公共参考数据库进行基因组学信息的扩展,特别是对于通过eDNA元编码恢复的样本不佳的基因系.
- 对于像SILVA这样的流行的数据库来说,分类学策划工作是必不可少的.
- 通过将新发布的GenBank序列与属/物种标识相结合,可以实现对分类型采样的快速改进.
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