Document Type
Article
Publication Title
Phycology
Publication Date
2024
Abstract
Coastal areas are the most biologically productive and undoubtedly among the most complex ecosystems. Algae are responsible for most of the gross primary production in these coastal regions. However, despite the critical importance of algae for the global ecosystem, the biodiversity of many algal groups is understudied, partially due to the high complexity of morphologically identifying algal species. The current study aimed to take advantage of the recently developed technology for biotic community assessment through the high-throughput sequencing (HTS) of environmental DNA (eDNA), known as the “eDNA metabarcoding”, to characterize littoral algal communities in the Northern Gulf of Mexico (NGoM). This study demonstrated that eDNA metabarcoding, based on the universal plastid amplicon (UPA) and part of the large nuclear ribosomal subunit (LSU) molecular markers, could successfully differentiate coastal biotic communities among littoral zones and geographical locations along the shoreline of the NGoM. The statistical significance of separation between biotic communities was partially dependent on the dissimilarity calculation metric; thus, the differentiation of algal community structure according to littoral zones was more distinct when phylogenetic distances were incorporated into the diversity analysis. Current work demonstrated that the relative abundance of algal species obtained with eDNA metabarcoding matches previously established zonation patterns for these species. In addition, the present study detected molecular signals of 44 algal species without previous reports for the Gulf of Mexico, thus providing an important, molecular-validated baseline of species richness for this region.
Volume
4
Issue
4
DOI
https://doi.org/10.3390/phycology4040033
Recommended Citation
Bombin, S., Bombin, A., Wysor, B., & Lopez-Bautista, J. M. (2024). Application of Environmental DNA Metabarcoding to Differentiate Algal Communities by Littoral Zonation and Detect Unreported Algal Species. Phycology, 4(4), 605-620.
ISSN
2673-9410
Comments
Published in: Phycology, vol. 4, issue 4, 2024.