Section for Evolutionary Genomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
Department of Biology, Faculty of Science, University of Copenhagen, Copenhagen, Denmark.
Mol Ecol Resour. 2021 Oct;21(7):2249-2263. doi: 10.1111/1755-0998.13425. Epub 2021 May 25.
Metagenomics can generate data on the diet of herbivores, without the need for primer selection and PCR enrichment steps as is necessary in metabarcoding. Metagenomic approaches to diet analysis have remained relatively unexplored, requiring validation of bioinformatic steps. Currently, no metagenomic herbivore diet studies have utilized both chloroplast and nuclear markers as reference sequences for plant identification, which would increase the number of reads that could be taxonomically informative. Here, we explore how in silico simulation of metagenomic data sets resembling sequences obtained from faecal samples can be used to validate taxonomic assignment. Using a known list of sequences to create simulated data sets, we derived reliable identification parameters for taxonomic assignments of sequences. We applied these parameters to characterize the diet of western capercaillies (Tetrao urogallus) located in Norway, and compared the results with metabarcoding trnL P6 loop data generated from the same samples. Both methods performed similarly in the number of plant taxa identified (metagenomics 42 taxa, metabarcoding 43 taxa), with no significant difference in species resolution (metagenomics 24%, metabarcoding 23%). We further observed that while metagenomics was strongly affected by the age of faecal samples, with fresh samples outperforming old samples, metabarcoding was not affected by sample age. On the other hand, metagenomics allowed us to simultaneously obtain the mitochondrial genome of the western capercaillies, thereby providing additional ecological information. Our study demonstrates the potential of utilizing metagenomics for diet reconstruction but also highlights key considerations as compared to metabarcoding for future utilization of this technique.
宏基因组学可以生成有关食草动物饮食的数据，而无需像代谢条形码那样进行引物选择和 PCR 富集步骤。宏基因组学方法在饮食分析中仍然相对未被探索，需要验证生物信息学步骤。目前，没有利用叶绿体和核标记作为植物鉴定参考序列的宏基因组食草动物饮食研究，这将增加可以进行分类学信息的读取数量。在这里，我们探讨了如何使用类似于从粪便样本中获得的序列的模拟宏基因组数据集来验证分类分配。使用已知的序列列表创建模拟数据集，我们为序列的分类分配得出了可靠的鉴定参数。我们将这些参数应用于描述位于挪威的西方松鸡（Tetrao urogallus）的饮食，并将结果与从相同样本生成的代谢条形码 trnL P6 环数据进行比较。这两种方法在鉴定的植物分类群数量上表现相似（宏基因组学 42 个分类群，代谢条形码 43 个分类群），物种分辨率没有显著差异（宏基因组学 24%，代谢条形码 23%）。我们还观察到，尽管宏基因组学受到粪便样本年龄的强烈影响，新鲜样本的表现优于旧样本，但代谢条形码不受样本年龄的影响。另一方面，宏基因组学允许我们同时获得西方松鸡的线粒体基因组，从而提供了额外的生态信息。我们的研究表明了利用宏基因组学进行饮食重建的潜力，但也强调了与代谢条形码相比，未来利用这项技术的关键考虑因素。
