School of Biological Sciences, University of East Anglia, Norwich, UK.
School of Environmental Sciences, University of East Anglia, Norwich, UK.
Mol Ecol. 2019 Jan;28(2):420-430. doi: 10.1111/mec.14920. Epub 2018 Dec 7.
Metabarcoding has been used in a range of ecological applications such as taxonomic assignment, dietary analysis and the analysis of environmental DNA. However, after a decade of use in these applications there is little consensus on the extent to which proportions of reads generated corresponds to the original proportions of species in a community. To quantify our current understanding, we conducted a structured review and meta-analysis. The analysis suggests that a weak quantitative relationship may exist between the biomass and sequences produced (slope = 0.52 ± 0.34, p < 0.01), albeit with a large degree of uncertainty. None of the tested moderators, sequencing platform type, the number of species used in a trial or the source of DNA, were able to explain the variance. Our current understanding of the factors affecting the quantitative performance of metabarcoding is still limited: additional research is required before metabarcoding can be confidently utilized for quantitative applications. Until then, we advocate the inclusion of mock communities when metabarcoding as this facilitates direct assessment of the quantitative ability of any given study.
代谢条码已被广泛应用于生态学研究中,例如分类学鉴定、饮食分析和环境 DNA 分析等。然而,尽管代谢条码在这些应用中已经使用了十年,但对于所产生的读取比例与群落中原始物种比例之间的对应程度,仍然没有达成共识。为了量化我们目前的理解程度,我们进行了一项结构化的综述和荟萃分析。分析表明,生物量和产生的序列之间可能存在微弱的定量关系(斜率= 0.52±0.34,p<0.01),尽管存在很大的不确定性。经过测试的调节因子,包括测序平台类型、试验中使用的物种数量或 DNA 的来源,均无法解释这种差异。我们目前对于影响代谢条码定量性能的因素的理解仍然有限:在可以自信地将代谢条码用于定量应用之前,还需要进行更多的研究。在那之前,我们提倡在进行代谢条码分析时加入模拟群落,因为这可以直接评估任何给定研究的定量能力。