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Diel metabolic tuning revealed by in situ transcriptome and proteome in a vertically migratory copepod
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  • Amy Maas,
  • Emma Timmins-Schiffman,
  • Ann Tarrant,
  • Brook Nunn,
  • Jea Park,
  • Leocadio Blanco-Bercial
Amy Maas
Bermuda Institute of Ocean Sciences
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Emma Timmins-Schiffman
University of Washington Department of Genome Sciences
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Ann Tarrant
Woods Hole Oceanographic Institution
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Brook Nunn
University of Washington Department of Genome Sciences
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Jea Park
University of Washington Department of Genome Sciences
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Leocadio Blanco-Bercial
Bermuda Institute of Ocean Sciences
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Abstract

Zooplankton undergo a vertical migration which exposes them to gradients of light, temperature, oxygen and food availability on a predictable daily schedule. Anticipating and responding to these environmental conditions, which independently are known to influence metabolic rates, likely has an appreciable effect on the delivery of waste products to the distinctly different daytime (deep) and nighttime (surface) habitats. Disentangling the co-varying and potentially synergistic interactions on metabolic rates has proven difficult, despite the importance of this migration to oceanic biogeochemical cycling. This study examines the transcriptomic and proteomic profile of the circumglobal migratory copepod, Pleuromamma xiphias, over the diel cycle. The transcriptome showed a large number of up-regulated genes during the middle of the day – the period often considered to be of lowest metabolic activity. There were proteomic and transcriptomic peaks in oxidative stress response and muscle proteins after the periods of migration, suggestive of a physiological consequence of migration. There were changes in metabolic pathways over time, with increased ammonium production signals during the evening and chitin synthesis and degradation pathways during the day. Comparisons of patterns across the paired datasets suggest that 1) estimates of physiological rates made in the laboratory in steady state conditions that don’t account for time of day may not be adequate to predict in situ phenotypes 2) use of ‘omics datasets to predict organismal phenotypes must be done cautiously as highly dynamic patterns in the transcriptome and proteome are often dampened and sometimes asynchronous at the enzyme or organismal level.
02 Aug 2022Submitted to Molecular Ecology
03 Aug 2022Assigned to Editor
03 Aug 2022Submission Checks Completed
16 Aug 2022Reviewer(s) Assigned