4.8 Article

Resolving cryptic species complexes in marine protists: phylogenetic haplotype networks meet global DNA metabarcoding datasets

Journal

ISME JOURNAL
Volume 15, Issue 7, Pages 1931-1942

Publisher

SPRINGERNATURE
DOI: 10.1038/s41396-021-00895-0

Keywords

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Funding

  1. H2020 RI Cluster project EMBRIC [GA-654008]
  2. FP7 project ASSEMBLE [GA-227799]
  3. Stazione Zoologica Anton Dohrn of Naples (The Open University-Stazione Zoologica Anton Dohrn Ph.D. Programme)

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Marine protists have traditionally been considered low in diversity and widespread, but recent studies have shown the presence of cryptic species complexes. Overcoming sampling and methodological limitations, global metabarcoding data analysis reveals geographic and ecological differentiation driving speciation among marine protists.
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.

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