Department of Integrative Marine Ecology, Stazione Zoologica Anton Dohrn, Naples, Italy.
Department of Biology, Botanical Garden of Naples, University of Naples Federico II, Naples, Italy.
ISME J. 2021 Jul;15(7):1931-1942. doi: 10.1038/s41396-021-00895-0. Epub 2021 Feb 15.
Marine protists have traditionally been assumed to be lowly diverse and cosmopolitan. Yet, several recent studies have shown that many protist species actually consist of cryptic complexes of species whose members are often restricted to particular biogeographic regions. Nonetheless, detection of cryptic species is usually hampered by sampling coverage and application of methods (e.g. phylogenetic trees) that are not well suited to identify relatively recent divergence and ongoing gene flow. In this paper, we show how these issues can be overcome by inferring phylogenetic haplotype networks from global metabarcoding datasets. We use the Chaetoceros curvisetus (Bacillariophyta) species complex as study case. Using two complementary metabarcoding datasets (Ocean Sampling Day and Tara Oceans), we equally resolve the cryptic complex in terms of number of inferred species. We detect new hypothetical species in both datasets. Gene flow between most of species is absent, but no barcoding gap exists. Some species have restricted distribution patterns whereas others are widely distributed. Closely related taxa occupy contrasting biogeographic regions, suggesting that geographic and ecological differentiation drive speciation. In conclusion, we show the potential of the analysis of metabarcoding data with evolutionary approaches for systematic and phylogeographic studies of marine protists.
海洋原生生物传统上被认为是低多样性和世界性的。然而，最近的几项研究表明，许多原生生物物种实际上由物种的隐种复合体组成，其成员通常局限于特定的生物地理区域。尽管如此，隐种的检测通常受到采样覆盖范围和方法（如系统发育树）的限制，这些方法不太适合识别相对较近的分化和持续的基因流。在本文中，我们展示了如何通过从全球宏条形码数据集推断系统发育单倍型网络来克服这些问题。我们使用 Chaetoceros curvisetus（Bacillariophyta）种复合体作为研究案例。使用两个互补的宏条形码数据集（Ocean Sampling Day 和 Tara Oceans），我们同样根据推断出的物种数量解决了隐种复合体的问题。我们在两个数据集都检测到了新的假设物种。大多数物种之间没有基因流，但不存在条形码差距。一些物种的分布模式受到限制，而另一些则分布广泛。密切相关的类群占据着截然不同的生物地理区域，这表明地理和生态分化驱动了物种形成。总之，我们展示了用进化方法分析宏条形码数据在海洋原生生物系统学和系统地理学研究中的潜力。
