Dataset: Application of a rapid microbiome characterization pipeline to corals afflicted with Stony Coral Tissue Loss Disease in St. Thomas, US Virgin Islands.

Final no updates expectedDOI: 10.26008/1912/bco-dmo.833133.1Version 1 (2020-12-07)Dataset Type:Other Field Results

Principal Investigator: Amy Apprill (Woods Hole Oceanographic Institution)

Co-Principal Investigator: Marilyn Brandt (University of the Virgin Islands Center for Marine and Environmental Studies)

Student: Cynthia Carroll Becker (Woods Hole Oceanographic Institution)

BCO-DMO Data Manager: Nancy Copley (Woods Hole Oceanographic Institution)

Project: RAPID: Collaborative Research: Predicting the Spread of Multi-Species Coral Disease Using Species Immune Traits (Multi-Species Coral Disease)

Abstract

Application of a rapid microbiome characterization pipeline to corals afflicted with Stony Coral Tissue Loss Disease in St. Thomas, United States Virgin Islands.

Cite Dataset

Application of a rapid microbiome characterization pipeline to corals afflicted with Stony Coral Tissue Loss Disease in St. Thomas, United States Virgin Islands. 

Related Datasets

IsRelatedTo
Dataset: NCBI accessions for RNAseq data from apparently healthy and SCTLD-affected Montastraea cavernosa
Beavers, K., Mydlarz, L. (2024) RNAseq data from apparently healthy and Stony Coral Tissue Loss Disease-affected Montastraea cavernosa coral collected from St. Thomas, US Virgin Islands in 2020. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-12-10 doi:10.26008/1912/bco-dmo.935630.1

Related Publications

Methods
Apprill, A., McNally, S., Parsons, R., & Weber, L. (2015). Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquatic Microbial Ecology, 75(2), 129–137. doi:10.3354/ame01753
Methods
Berger, S. A., Krompass, D., & Stamatakis, A. (2011). Performance, Accuracy, and Web Server for Evolutionary Placement of Short Sequence Reads under Maximum Likelihood. Systematic Biology, 60(3), 291–302. doi:10.1093/sysbio/syr010
Methods
Davis, N. M., Proctor, D. M., Holmes, S. P., Relman, D. A., & Callahan, B. J. (2018). Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome, 6(1). doi:10.1186/s40168-018-0605-2
Methods
Huggett, M. J., & Apprill, A. (2018). Coral microbiome database: Integration of sequences reveals high diversity and relatedness of coral‐associated microbes. Environmental Microbiology Reports, 11(3), 372–385. doi:10.1111/1758-2229.12686
Methods
Letunic, I., & Bork, P. (2016). Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Research, 44(W1), W242–W245. doi:10.1093/nar/gkw290

Apprill, A., Brandt, M. (2021) Application of a rapid microbiome characterization pipeline to corals afflicted with Stony Coral Tissue Loss Disease in St. Thomas, US Virgin Islands.. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2020-12-07 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.833133.1 [access date]

Terms of Use

This dataset is licensed under Creative Commons Attribution 4.0.


If you wish to use this dataset, it is highly recommended that you contact the original principal investigators (PI). Should the relevant PI be unavailable, please contact BCO-DMO (info@bco-dmo.org) for additional guidance. For general guidance please see the BCO-DMO Terms of Use document.

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Funded by the U.S. National Science Foundation