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Data from: Metagenetic community analysis of microbial eukaryotes illuminates biogeographic patterns in deep-sea and shallow water sediments

Bik, Holly M.;Sung, Way;De Ley, Paul;Baldwin, James G.;Sharma, Jyotsna;Rocha-Olivares, Axayácatl;Thomas, W. Kelley

Description

Microbial eukaryotes (nematodes, protists, fungi, etc., loosely referred to as meiofauna) are ubiquitous in marine sediments and likely play pivotal roles in maintaining ecosystem function. Although the deep-sea benthos represents one of the world’s largest habitats, we lack a firm understanding of the biodiversity and community interactions amongst meiobenthic organisms in this ecosystem. Within this vast environment key questions concerning the historical genetic structure of species remain a mystery, yet have profound implications for our understanding of global biodiversity and how we perceive and mitigate the impact of environmental change and anthropogenic disturbance. Using a metagenetic approach, we present an intensive assessment of microbial eukaryote communities across depth gradients (shallow water to abyssal) and ocean basins (deep-sea Pacific and Atlantic). Our results show that while some taxa can maintain eurybathic ranges and cosmopolitan deep-sea distributions, the majority of species appear to be regionally restricted in marine habitats. For OCTUs reporting wide distributions, there appears to be a taxonomic bias towards a small subset of taxa in most phyla; such bias may be driven by specific life history traits amongst these organisms. In addition, low genetic divergence between geographically disparate deep-sea sites suggests either a shorter coalescence time between deep-sea regions or slower rates of evolution across this vast oceanic ecosystem. While high-throughput studies allow for broad assessment of genetic patterns across microbial eukaryote communities, intragenomic variation in rRNA gene copies and the patchy coverage of reference databases currently present substantial challenges for robust taxonomic interpretations of eukaryotic datasets.

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Mentions (0)

Metrics

Dataset Index

0.7

FAIR Score

81%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Dryad

License

Creative Commons Zero v1.0 Universal

Assigned Domain

Subfield

Ecology

Field

Environmental Science

Domain

Physical Sciences

Confidence Score

59%

Source

Scholar Data Model

Keywords

45418S rRNABioinfomatics/PhyloinfomaticsEukaryotic Metagenetics

Normalization Factors

FT

73.08

CTw

1.00

MTw

1.00