Ficetola Gentile Francesco, Taberlet Pierre
Department of Environmental Science and Policy, Università degli Studi di Milano, Milan, Italy.
University Grenoble Alpes, University Savoie Mont Blanc, CNRS, LECA, Laboratoire d'Écologie Alpine, Grenoble, France.
Mol Ecol. 2023 Dec;32(23):6320-6329. doi: 10.1111/mec.16881. Epub 2023 Feb 23.
Exhaustive biodiversity data, covering all the taxa in an environment, would be fundamental to understand how global changes influence organisms living at different trophic levels, and to evaluate impacts on interspecific interactions. Molecular approaches such as DNA metabarcoding are boosting our ability to perform biodiversity inventories. Nevertheless, even though a few studies have recently attempted exhaustive reconstructions of communities, holistic assessments remain rare. The majority of metabarcoding studies published in the last years used just one or two markers and analysed a limited number of taxonomic groups. Here, we provide an overview of emerging approaches that can allow all-taxa biological inventories. Exhaustive biodiversity assessments can be attempted by combining a large number of specific primers, by exploiting the power of universal primers, or by combining specific and universal primers to obtain good information on key taxa while limiting the overlooked biodiversity. Multiplexes of primers, shotgun sequencing and capture enrichment may provide a better coverage of biodiversity compared to standard metabarcoding, but still require major methodological advances. Here, we identify the strengths and limitations of different approaches, and suggest new development lines that might improve broad scale biodiversity analyses in the near future. More holistic reconstructions of ecological communities can greatly increase the value of metabarcoding studies, improving understanding of the consequences of ongoing environmental changes on the multiple components of biodiversity.
涵盖某一环境中所有分类群的详尽生物多样性数据，对于理解全球变化如何影响生活在不同营养级的生物，以及评估对种间相互作用的影响至关重要。诸如DNA宏条形码分析等分子方法正在提升我们进行生物多样性编目的能力。然而，尽管最近有一些研究尝试对群落进行详尽的重建，但全面评估仍然很少见。过去几年发表的大多数宏条形码分析研究仅使用一两种标记，并分析了有限数量的分类群。在此，我们概述了一些新兴方法，这些方法可以实现全分类群生物编目。通过组合大量特异性引物、利用通用引物的优势或结合特异性引物和通用引物，在限制被忽视的生物多样性的同时获取关键分类群的良好信息，可以尝试进行详尽的生物多样性评估。与标准宏条形码分析相比，引物多重化、鸟枪法测序和捕获富集可能会提供更好的生物多样性覆盖，但仍需要重大的方法学进展。在此，我们确定了不同方法的优势和局限性，并提出了新的发展方向，这些方向可能在不久的将来改进大规模生物多样性分析。对生态群落进行更全面的重建可以极大地提高宏条形码分析研究的价值，增进对当前环境变化对生物多样性多个组成部分的影响的理解。
