Integrative Systematics of Deep-Sea Invertebrates

Authors

  • Hugo Klein Department of Computer Science, Baltic AI Research University, Tallinn, Estonia Author
  • Sofia Kovacs School of Data Science, Swiss Institute of Machine Intelligence, Zurich, Switzerland Author

Keywords:

convergent evolution, Atlantic, eDNA, deep-sea biodiversity, species delimitation, transcriptomics, phylogenetics, micro-CT, ROV sampling, COI, molecular barcoding, new species, integrative systematics, deep-sea invertebrates

Abstract

Deep-sea invertebrates -- organisms inhabiting marine environments below 200 m, where high pressure, low
temperature, perpetual darkness, and low food availability impose extreme physiological demands -- constitute a vast
and largely uncharacterised component of global biodiversity, with conservative estimates suggesting that fewer than
10% of deep-sea species have been formally described. The morphological convergence driven by the uniform deep-sea
environment, combined with the rarity and fragility of specimens recovered by trawl or remotely operated vehicle (ROV)
sampling, makes integrative systematic approaches combining morphology, multi-locus molecular barcoding, and
transcriptomics essential for reliable species delimitation and phylogenetic placement of deep-sea taxa. This study
applied an integrative systematic framework to 284 deep-sea invertebrate specimens from seven phyla (Porifera,
Cnidaria, Annelida, Mollusca, Arthropoda, Echinodermata, Hemichordata) collected by ROV (RV Polarstern; RV Meteor;
RV Sarmiento de Gamboa) from 800-4,200 m depth across the Atlantic, Mediterranean, and Arctic deep-sea basins.
Molecular barcoding (COI, 16S, 28S; n = 284 specimens) combined with morphological examination and micro-CT
scanning identified 48 putative new species (confirmed by integrative diagnosis), of which 28 were formally described as
new to science. Multi-locus phylogenetic analysis (IQ-TREE2; RAxML-NG; ASTRAL-III) recovered nine new generic-level
placements that alter established deep-sea invertebrate family classifications. Transcriptomic comparison of five
sympatric species pairs revealed convergent gene expression at pressure-response, cold-adaptation, and
bioluminescence pathway genes (enrichment 6.4x above genome background; p < 0.001). These results demonstrate
the power of ROV-enabled integrative systematics for accelerating deep-sea biodiversity inventory and provide a
molecular reference library for environmental DNA (eDNA) monitoring of deep-sea invertebrate communities.

Author Biographies

  • Hugo Klein, Department of Computer Science, Baltic AI Research University, Tallinn, Estonia

    Hugo Klein
    Assistant Professor, Department of Computer Science, Baltic AI Research University, Tallinn, Estonia. Email:
    hugo.klein769@gmail.com | ORCID: 0000-2593-3710-2906-5292

  • Sofia Kovacs, School of Data Science, Swiss Institute of Machine Intelligence, Zurich, Switzerland

     Sofia Kovacs
    Senior Lecturer, School of Data Science, Swiss Institute of Machine Intelligence, Zurich, Switzerland. Email:
    sofia.kovacs686@gmail.com | ORCID: 0000-7489-6731-8466-4483

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Published

2024-01-18

How to Cite

Integrative Systematics of Deep-Sea Invertebrates. (2024). International Journal of Animal Biodiversity, Conservation and Systematics ( IJABC), 4(1), 1-8. https://stanfordgroup.org/index.php/IJABC/article/view/194

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