Investigating non-fungal eukaryotic diversity in snow in the Antarctic Peninsula region using DNA metabarcoding

Câmara, Paulo E.A.S.; de Menezes, Graciéle C.A.; Lopes, Fabyano A.C.; da Silva Paiva, Thiago; Carvalho-Silva, Micheline; Convey, Peter ORCID: https://orcid.org/0000-0001-8497-9903; Amorim, Eduardo T.; Rosa, Luiz H.. 2024 Investigating non-fungal eukaryotic diversity in snow in the Antarctic Peninsula region using DNA metabarcoding. Extremophiles, 28 (3). 11, pp. https://doi.org/10.1007/s00792-023-01322-2

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Official URL: https://link.springer.com/article/10.1007/s00792-0...

Abstract/Summary

Snow is a unique microhabitat, despite being a harsh environment, multiple life forms have adapted to survive in it. While algae, bacteria and fungi are dominant microorganisms in Antarctic snow, little is known about other organisms that may be present in this habitat. We used metabarcoding to investigate DNA sequence diversity of non-fungal eukaryotes present in snow obtained from six different sites across the Maritime Antarctica. A total of 20 taxa were assigned to obtained sequences, representing five Kingdoms (Chromista, Protozoa, Viridiplantae and Metazoa) and four phyla (Ciliophora, Cercozoa, Chlorophyta and Cnidaria). The highest diversity indices were detected in Trinity Peninsula followed by Robert Island, Arctowski Peninsula, Deception Island, King George Island and Snow Island. The most abundant assignments were to Trebouxiophyceae, followed by Chlamydomonas nivalis and Chlamidomonadales. No taxa were detected at all sites. Three potentially new records for Antarctica were detected: two Ciliophora (Aspidisca magna and Stokesia sp.) and the green algae Trebouxia potteri. Our data suggested that similarities found between the sites may be more related with snow physicochemical properties rather than geographic proximity or latitude. This study provides new insights into the diversity and distribution of eukaryotic organisms in Antarctic snow.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1007/s00792-023-01322-2
ISSN:	14310651
Additional Keywords:	High Throughput Sequencing, microalgae, Chlorophyta, South Shetland Islands, biodiversity
Date made live:	20 Nov 2023 08:20 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/535728

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1007/s00792-023-01322-2

ISSN:

14310651

Additional Keywords:

High Throughput Sequencing, microalgae, Chlorophyta, South Shetland Islands, biodiversity

Date made live:

20 Nov 2023 08:20 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/535728