Dataset: Symbiodiniaceae communities (via ITS-2 rDNA amplicon sequencing) in reef-associated fish feces, corals, water and sediments

This dataset has not been validatedPreliminary and in progressVersion 1 (2021-03-09)Dataset Type:Unknown

Principal Investigator: Adrienne M.S. Correa (Rice University)

Contact: Carsten Grupstra (Rice University)

BCO-DMO Data Manager: Amber D. York (Woods Hole Oceanographic Institution)


Project: Collaborative Research: Viral Reefscapes: The Role of Viruses in Coral Reef Health, Disease, and Biogeochemical Cycling (Moorea Virus Project)


Abstract

SRA accessions and collection information for ITS-2 rDNA amplicon data from fish feces, corals, water and sediments sampled from Mo’orea, French Polynesia in August 2019. Sequences will be made available at the National Center for Biotechnology Information (NCBI).

Methodology summary: 

ITS-2 rDNA Symbiodiniaceae community libraries were prepared and PE 300bp reads were generated using Illumina MiSeq platform. 

Sampling and analytical procedures: 

Samples were preserved in DNA/RNA shield (Zymo Research, CA) and stored at -20℃ until further processing. DNA was extracted using the ZymoBIOMICs DNA/RNA Miniprep kit (Zymo Research, CA) from 20-200 mg of feces, small coral tissue sections (~5 mm2), 250 ml sediments and ~1890 ml water using a ZymoBIOMICs DNA/RNA Miniprep kit (Zymo Research, CA).

Sample subject list with aphiaIDs for taxonomic names:

Acropora, 205469
Amanses scopas, 212242
Chaetodon citrinellus, 218744
Chaetodon lunulatus, 398549
Chaetodon ornatissimus, 273352
Chaetodon pelewensis, 273353
Chaetodon reticulatus, 273359
Chlorurus spilurus, 712772
Ctenochaetus flavicauda, 277560
Ctenochaetus striatus, 219659
Pocillopora, 206938
Porites, 206485
Sediment
Water


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Related Publications

Results

Grupstra, C. G. B., Rabbitt, K. M., Howe-Kerr, L. I., & Correa, A. M. S. (2020). Fish predation on corals promotes the dispersal of coral symbionts. doi:10.1101/2020.08.10.243857
Software

R Core Team (2019). R: A language and environment for statistical computing. R v3.6.1. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/