Department of Genetics and Evolution, University of Geneva, boulevard d'Yvoy 4, 1205, Geneva, Switzerland.
Water Ecology Service, Department of Territorial Management, Canton of Geneva, avenue de Sainte-Clotilde 23, 1211, Geneva, Switzerland.
Mol Ecol Resour. 2017 Nov;17(6):1231-1242. doi: 10.1111/1755-0998.12668. Epub 2017 Apr 13.
Current biodiversity assessment and biomonitoring are largely based on the morphological identification of selected bioindicator taxa. Recently, several attempts have been made to use eDNA metabarcoding as an alternative tool. However, until now, most applied metabarcoding studies have been based on the taxonomic assignment of sequences that provides reference to morphospecies ecology. Usually, only a small portion of metabarcoding data can be used due to a limited reference database and a lack of phylogenetic resolution. Here, we investigate the possibility to overcome these limitations using a taxonomy-free approach that allows the computing of a molecular index directly from eDNA data without any reference to morphotaxonomy. As a case study, we use the benthic diatoms index, commonly used for monitoring the biological quality of rivers and streams. We analysed 87 epilithic samples from Swiss rivers, the ecological status of which was established based on the microscopic identification of diatom species. We compared the diatom index derived from eDNA data obtained with or without taxonomic assignment. Our taxonomy-free approach yields promising results by providing a correct assessment for 77% of examined sites. The main advantage of this method is that almost 95% of OTUs could be used for index calculation, compared to 35% in the case of the taxonomic assignment approach. Its main limitations are under-sampling and the need to calibrate the index based on the microscopic assessment of diatoms communities. However, once calibrated, the taxonomy-free molecular index can be easily standardized and applied in routine biomonitoring, as a complementary tool allowing fast and cost-effective assessment of the biological quality of watercourses.
目前的生物多样性评估和生物监测在很大程度上基于对选定生物指标类群的形态识别。最近，已经有几项尝试使用 eDNA 代谢组学作为替代工具。然而，到目前为止，大多数应用的代谢组学研究都是基于对序列的分类学分配，这为形态种的生态学提供了参考。通常，由于参考数据库有限和缺乏系统发育分辨率，只有一小部分代谢组学数据可以使用。在这里，我们研究了使用无分类学方法克服这些限制的可能性，该方法允许直接从 eDNA 数据计算分子指数，而无需参考形态分类学。作为案例研究，我们使用了底栖硅藻指数，该指数常用于监测河流和溪流的生物质量。我们分析了来自瑞士河流的 87 个附生样本，这些河流的生态状况是基于硅藻物种的微观鉴定建立的。我们比较了从 eDNA 数据中获得的有或没有分类学分配的硅藻指数。我们的无分类学方法通过为 77%的受检地点提供正确的评估，取得了有希望的结果。该方法的主要优势是，与分类学分配方法相比，几乎 95%的 OTU 可用于指数计算，而分类学分配方法只能使用 35%的 OTU。其主要限制是采样不足和需要根据硅藻群落的微观评估对指数进行校准。然而，一旦校准，无分类学的分子指数可以很容易地标准化，并在常规生物监测中应用，作为一种补充工具，允许快速和具有成本效益的评估水道的生物质量。
