Abstract
PCR amplification followed by deep sequencing of homologous gene regions is increasingly used to characterize the diversity and taxonomic composition of marine eukaryotic communities. This approach may generate millions of sequences for hundreds of samples simultaneously. Therefore, tools that researchers can use to visualize complex patterns of diversity for these massive datasets are essential. Efforts by microbiologists to understand the Earth and human microbiomes using high-throughput sequencing of the 16S rRNA gene has led to the development of several user-friendly, open-source software packages that can be similarly used to analyze eukaryotic datasets. Quantitative Insights Into Microbial Ecology (QIIME) offers some of the most helpful data visualization tools. Here, we describe functionalities to import OTU tables generated with any molecular marker (e.g., 18S, COI, ITS) and associated metadata into QIIME. We then present a range of analytical tools implemented within QIIME that can be used to obtain insights about patterns of alpha and beta diversity for marine eukaryotes.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Mora C, Tittensor DP, Adl S et al (2011) How many species are there on Earth and in the Ocean? PLoS Biol 9:1001127. doi:10.1371/journal.pbio.1001127
Appeltans W, Ahyong ST, Anderson G et al (2012) The magnitude of global marine species diversity. Curr Biol 22:2189–202. doi:10.1016/j.cub.2012.09.036
Tittensor DP, Mora C, Jetz W et al (2010) Global patterns and predictors of marine biodiversity across taxa. Nature 466:1098–101. doi:10.1038/nature09329
Fonseca VG, Carvalho GR, Sung W et al (2011) Second-generation environmental sequencing unmasks marine metazoan biodiversity. Nat Commun 1:1–8. doi:10.1038/ncomms1095
Leray M, Knowlton N (2015) DNA barcoding and metabarcoding of standardized samples reveal patterns of marine benthic diversity. Proc Natl Acad Sci U S A 112:2076–2081. doi:10.1073/pnas.1424997112
Leray M, Yang JY, Meyer CP et al (2013) A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Front Zool 10:34. doi:10.1186/1742-9994-10-34
Taberlet P, Coissac E, Pompanon F et al (2012) Towards next-generation biodiversity assessment using DNA metabarcoding. Mol Ecol 21:2045–50. doi:10.1111/j.1365-294X.2012.05470.x
Caporaso JG, Kuczynski J, Stombaugh J et al (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–6. doi:10.1038/nmeth.f.303
Schloss PD, Westcott SL, Ryabin T et al (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537–7541. doi:10.1128/aem.01541-09
Angiuoli SV, Matalka M, Gussman A et al (2011) CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing. BMC Bioinformatics 12:356. doi:10.1186/1471-2105-12-356
Hildebrand F, Tadeo R, Voigt A et al (2014) LotuS: an efficient and user-friendly OTU processing pipeline. Microbiome 2:30. doi:10.1186/2049-2618-2-30
Vázquez-Baeza Y, Pirrung M, Gonzalez A, Knight R (2013) EMPeror: a tool for visualizing high-throughput microbial community data. Gigascience 2:16. doi:10.1186/2047-217X-2-16
McDonald D, Clemente JC, Kuczynski J et al (2012) The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome. Gigascience 1:7. doi:10.1186/2047-217X-1-7
Acknowledgments
We thank Sarah Bourlat for inviting this submission. This work was supported by the Sant Chair and the Smithsonian Tennenbaum Marine Observatories Network, for which this is Contribution No. 3.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media New York
About this protocol
Cite this protocol
Leray, M., Knowlton, N. (2016). Visualizing Patterns of Marine Eukaryotic Diversity from Metabarcoding Data Using QIIME. In: Bourlat, S. (eds) Marine Genomics. Methods in Molecular Biology, vol 1452. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3774-5_15
Download citation
DOI: https://doi.org/10.1007/978-1-4939-3774-5_15
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-3772-1
Online ISBN: 978-1-4939-3774-5
eBook Packages: Springer Protocols