A comparison of two gene regions for assessing community composition of eukaryotic marine microalgae from coastal ecosystems

Two gene regions commonly used to characterise the diversity of eukaryotic communities using metabarcoding are the 18S ribosomal DNA V4 and V9 gene regions. We assessed the effectiveness of these two regions for characterising diverisity of coastal eukaryotic microalgae communities (EMCs) from tropi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Scientific reports 2024-03, Vol.14 (1), p.6442-6442, Article 6442
Hauptverfasser: Stuart, Jacqui, Ryan, Ken G., Pearman, John K., Thomson-Laing, Jacob, Hampton, Hannah G., Smith, Kirsty F.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Two gene regions commonly used to characterise the diversity of eukaryotic communities using metabarcoding are the 18S ribosomal DNA V4 and V9 gene regions. We assessed the effectiveness of these two regions for characterising diverisity of coastal eukaryotic microalgae communities (EMCs) from tropical and temperate sites. We binned amplicon sequence variants (ASVs) into the high level taxonomic groups: dinoflagellates, pennate diatoms, radial centric diatoms, polar centric diatoms, chlorophytes, haptophytes and ‘other microalgae’. When V4 and V9 generated ASV abundances were compared, the V9 region generated a higher number of raw reads, captured more diversity from all high level taxonomic groups and was more closely aligned with the community composition determined using light microscopy. The V4 region did resolve more ASVs to a deeper taxonomic resolution within the dinoflagellates, but did not effectively resolve other major taxonomic divisions. When characterising these communities via metabarcoding, the use of multiple gene regions is recommended, but the V9 gene region can be used in isolation to provide high-level community biodiversity to reflect relative abundances within groups. This approach reduces the cost of sequencing multiple gene regions whilst still providing important baseline ecosystem function information.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-56993-4