Metabarcoding Techniques for Assessing Biodiversity of Marine Animal Forests

Abstract

The “marine animal forests” are among the most diverse ecosystems in the Biosphere. However, exhaustive biodiversity assessment of these communities has been so far elusive. The real extent of biodiversity and its temporal and spatial variability patterns remain unknown for most animal forests, mainly due to the inability of traditional taxonomy methods to cope with such degree of diversity and structural complexity.

The development of metabarcoding techniques has revolutionized biomonitoring. Using this approach, thousands of species present in any environmental sample can be detected by high-throughput DNA sequencing and identified using public databases. Though initially limited to homogeneous substrates such as plankton or sediments, the applications of metabarcoding have been recently extended to communities on heterogeneous complex hard bottom substrates.

Here we present novel metabarcoding protocols, based on the use of short fragments of 18S rRNA or cytochrome c oxidase I genes as genetic markers. We aim to develop methods for robust, reproducible eukaryotic biodiversity assessment of structurally complex communities such as marine animal forests, allowing characterization of communities living on hard-bottom substrates or other marine benthic ecosystems.

We propose some guidelines focusing on sampling techniques, sample preprocessing, DNA extraction, selection of genetic markers, and bioinformatic pipelines, including steps such as sequence filtering (removal of low quality reads), clustering algorithms for delimiting molecular operational taxonomic units, and automated taxonomic assignment using reference databases. We expect these recommendations will help marine ecologists to become familiar with the paradigm shift that metabarcoding represents in the way marine ecosystems will be monitored and managed in the next future.