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通过宏条形码技术揭示的原生生物多样性与生态学。

Diversity and ecology of protists revealed by metabarcoding.

机构信息

Department of Organismal Biology (Systematic Biology), Uppsala University, Norbyv. 18D, 75236 Uppsala, Sweden; Science For Life Laboratory, Uppsala University, 75236 Uppsala, Sweden.

Department of Organismal Biology (Systematic Biology), Uppsala University, Norbyv. 18D, 75236 Uppsala, Sweden.

出版信息

Curr Biol. 2021 Oct 11;31(19):R1267-R1280. doi: 10.1016/j.cub.2021.07.066.

Abstract

Protists are the dominant eukaryotes in the biosphere where they play key functional roles. While protists have been studied for over a century, it is the high-throughput sequencing of molecular markers from environmental samples - the approach of metabarcoding - that has revealed just how diverse, and abundant, these small organisms are. Metabarcoding is now routine to survey environmental diversity, so data have rapidly accumulated from a multitude of environments and at different sampling scales. This mass of data has provided unprecedented opportunities to study the taxonomic and functional diversity of protists, and how this diversity is organised in space and time. Here, we use metabarcoding as a common thread to discuss the state of knowledge in protist diversity research, from technical considerations of the approach to important insights gained on diversity patterns and the processes that might have structured this diversity. In addition to these insights, we conclude that metabarcoding is on the verge of an exciting added dimension thanks to the maturation of high-throughput long-read sequencing, so that a robust eco-evolutionary framework of protist diversity is within reach.

摘要

原生生物是生物圈中占主导地位的真核生物,它们在其中发挥着关键的功能作用。虽然人们对原生生物的研究已经超过一个世纪,但正是通过对环境样本中的分子标记进行高通量测序——即代谢组学分析的方法——才揭示出这些微小生物的多样性和丰富程度。代谢组学现在已经成为环境多样性调查的常规手段,因此,来自众多环境和不同采样尺度的数据已经迅速积累。这些海量数据为研究原生生物的分类和功能多样性,以及这种多样性在空间和时间上的组织方式提供了前所未有的机会。在这里,我们使用代谢组学作为一条共同的线索,从方法的技术考虑因素到关于多样性模式和可能塑造这种多样性的过程的重要见解,来讨论原生生物多样性研究的现状。除了这些见解之外,我们还得出结论,由于高通量长读测序的成熟,代谢组学即将迎来一个令人兴奋的附加维度,因此,一个健全的原生生物多样性的生态进化框架即将实现。

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