Metabarcoding the zooplankton species of the Saudi Arabian Gulf: A study employing mock communities and two gene markers

Abstract

Ecosystem health can be monitored by analyzing the species diversity and abundance in a region. The process of recognizing species based on morphology takes a lot of time and expertise. Metabarcoding and other modern molecular taxonomic methods can help speed up species identification. However, the choice of gene markers and primers, the lack of reference sequences in public databases, and the choice of tools used in bioinformatic analyses have a substantial impact on the observed diversity. To test the effectiveness of metabarcoding in assessing the species diversity, mock communities of zooplankton species found in the Saudi Arabian Gulf were assembled and subjected to high-throughput sequencing (HTS) using an Illumina MiSeq platform. Short CO1 and 28S nuclear gene fragments, containing the D2 region, of lengths 313 bp and 400 bp, respectively, were used as gene markers. Trimmomatic, Cutadapt, the FLASH read-merge software tool, and the USEARCH pipeline for OTU clustering were used in the bioinformatic analyses. Around 90% of the zooplankton species in the mock communities were detected. We conclude that the combination of CO1 and 28S markers is a quick and effective tool for evaluating zooplankton species diversity.

Keywords

• Biodiversity
• BOLD database
• Gene markers
• High-throughput sequencing
• Primers
• Zooplankton