Comparative analysis of zooplankton diversity in freshwaters: What can we gain from metagenomic analysis?

Abstract

Abstract Molecular genetic approaches applied to environmental DNA have great potential for biodiversity research and ecosystem monitoring. A metagenome is produced via shotgun sequencing of DNA collected directly from the environment and represents a sample of genetic information from all organisms captured in an environmental sample. Metagenomes have been primarily used to study bacteria and archaea, but promising reports focusing on metazoan diversity are emerging. However, methodological uncertainties remain, and studies are required to validate the power and the limitations of such an approach when applied to macro‐eukaryotes. Here, we analyzed water sample metagenomes to estimate zooplankton diversity in 22 freshwater lakes across eastern Canada. We tested the coherence of data based on field samples collected at the same time: 1) morphologically identified zooplankton specimens and 2) molecular genetic data derived from shotgun sequencing of environmental DNA for which we applied two different bioinformatic workflows: a whole metagenome mapping approach and a small subunit (SSU) rRNA gene prediction approach. We further evaluated diversity trends emerging from each dataset in relation to major environmental gradients. We found a significant correlation between the relative abundance of zooplankton families identified based on SSU rRNA gene prediction and morphology. However, differences in congruence between metagenomes and morphological identifications were detected when varied bioinformatic approaches were applied to the presence–absence data. This study presents one of the first diversity assessments of a group of aquatic metazoans using metagenomes and validates the coherence of the community composition derived from genomic and classical species surveys. Overall, our results suggest that metagenomics has the potential to be further developed to describe metazoan biodiversity in aquatic ecosystems, and to advance this area we provide key recommendations for workflow improvement.

Keywords

• biodiversity survey
• ecological assessment
• environmental DNA (eDNA)
• freshwater ecology
• shotgun sequencing