Analysis of Illumina MiSeq Metabarcoding Data: Application to Benthic Indices for Environmental Monitoring

Protocol
First Online:
Part of the Methods in Molecular Biology book series (MIMB, volume 1452)

Abstract

This protocol details the analysis of Illumina MiSeq amplicon libraries derived from marine benthic macroinvertebrate samples and based on two barcodes of the mitochondrial cytochrome oxidase 1 (CO1) gene: a “short region,” covered by overlapping forward and reverse reads and a “long region” for which forward and reverse reads do not overlap. Aside from providing guidelines for analyzing both types of amplicons, we show how amplicon reads can be used for the calculation of benthic indices for environmental monitoring.

Key words

Marine benthic macroinvertebrates Amplicon sequencing CO1 Folmer region MiSeq 
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Notes

Acknowledgements

This work was funded by the European Union (7th Framework Program ‘The Ocean of Tomorrow’ Theme, grant agreement no. 308392) through the DEVOTES (DEVelopment Of innovative Tools for understanding marine biodiversity and assessing good Environmental Status—http://www.devotes-project.eu) project and by the Basque Water Agency (URA) through a Convention with AZTI. E. Aylagas was supported by a doctoral grant from Fundación Centros Tecnológicos—Iñaki Goenaga. This is contribution number 742 from the Marine Research Division (AZTI).

References

  1. 1.
    Zepeda Mendoza ML, Sicheritz-Ponten T, Gilbert MT (2015) Environmental genes and genomes: understanding the differences and challenges in the approaches and software for their analyses. Brief Bioinform. doi: 10.1093/bib/bbv001 PubMedPubMedCentralGoogle Scholar
  2. 2.
    Aylagas E, Borja A, Rodriguez-Ezpeleta N (2014) Environmental status assessment using DNA metabarcoding: towards a genetics based Marine Biotic Index (gAMBI). PLoS One 9(3), e90529. doi: 10.1371/journal.pone.0090529 CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Tedersoo L, Ramirez KS, Nilsson RH, Kaljuvee A, Koljalg U, Abarenkov K (2015) Standardizing metadata and taxonomic identification in metabarcoding studies. GigaScience 4:34. doi: 10.1186/s13742-015-0074-5 CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Hebert PD, Ratnasingham S, deWaard JR (2003) Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species. Proc Biol Sci 270(Suppl 1):S96–S99. doi: 10.1098/rsbl.2003.0025 CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R (1994) DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol Mar Biol Biotechnol 3(5):294–299PubMedGoogle Scholar
  6. 6.
    Meyer PC (2003) Molecular systematics of cowries (Gastropoda: Cypraeidae) and diversification patterns in the tropics. Biol J Linn Soc 79:401–459CrossRefGoogle Scholar
  7. 7.
    Geller J, Meyer C, Parker M, Hawk H (2013) Redesign of PCR primers for mitochondrial cytochromecoxidase subunit I for marine invertebrates and application in all-taxa biotic surveys. Mol Ecol Resour 13(5):851–861. doi: 10.1111/1755-0998.12138 CrossRefPubMedGoogle Scholar
  8. 8.
    Leray M, Yang YJ, Meyer PC, Mills CS, Agudelo N, Ranwez V, Boehm TJ, Machida JR (2013) 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)Google Scholar
  9. 9.
    Borja A, Franco J, Perez V (2000) A marine biotic index to establish the ecological quality of soft-bottom benthos within european estuarine and coastal environments. Mar Pollut Bull 40:12CrossRefGoogle Scholar
  10. 10.
    Yu DW, Ji Y, Emerson BC, Wang X, Ye C, Yang C, Ding Z (2012) Biodiversity soup: metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring. Meth Ecol Evol 3(4):613–623. doi: 10.1111/j.2041-210X.2012.00198.x CrossRefGoogle Scholar
  11. 11.
    Elbrecht V, Leese F (2015) Can DNA-based ecosystem assessments quantify species abundance? Testing primer bias and biomass--sequence relationships with an innovative metabarcoding protocol. PLoS One 10(7), e0130324. doi: 10.1371/journal.pone.0130324 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Andrews S (2010) FastQC: a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc
  13. 13.
    Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina Sequence Data. Bioinformatics 30:2114–2120CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Magoč T, Salzberg S (2011) FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27(21):2957–2963CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Schloss PD (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75(23):7537–7541CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Li W, Godzik A (2006) Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22(13):1658–1659. doi: 10.1093/bioinformatics/btl158 CrossRefPubMedGoogle Scholar
  17. 17.
    Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD (2013) Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 79(17):5112–5120. doi: 10.1128/AEM.01043-13 CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Hall TA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser 41:4Google Scholar
  19. 19.
    Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27(16):2194–2200. doi: 10.1093/bioinformatics/btr381 CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73(16):5261–5267. doi: 10.1128/AEM.00062-07 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Borja A, Muxika I, Mader J (2012) Instructions for the use of the AMBI index software (Version 50). Rev Invest Mar 19(3):11Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.AZTI, Marine Research DivisionSukarrieta, BizkaiaSpain

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