Jump to ContentJump to Main Navigation
Show Summary Details
More options …

DNA Barcodes

1 Issue per year


Emerging Science

Open Access
Online
ISSN
2299-1077
See all formats and pricing
More options …

Ground-truthing Phylotype Assignments for Antarctic Invertebrates

Paul Czechowski
  • Corresponding author
  • Antarctic Biological Research Initiative, 31 Jobson Road, Bolivar, South Australia 5110, Australia
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Laurence Clarke
  • Australian Centre for Ancient DNA, University of Adelaide, North Terrace, Adelaide, South Australia 5000, Australia
  • Australian Antarctic Division, 203 Channel Highway, Kingston, Tasmania 7050, Australia
  • Antarctic Climate & Ecosystems Cooperative, Research Centre, University of Tasmania, Private Bag 80, Hobart, Tasmania 7001, Australia
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Alan Cooper
  • Australian Centre for Ancient DNA, University of Adelaide, North Terrace, Adelaide, South Australia 5000, Australia
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Mark Stevens
  • South Australian Museum, Science Centre, North Terrace, Adelaide, South Australia 5001, Australia
  • School of Pharmacy and Medical Sciences, University of South Australia, North Terrace Adelaide, South Australia 5000, Australia
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2017-06-16 | DOI: https://doi.org/10.1515/dna-2017-0001

Abstract

Biodiversity information from Antarctic terrestrial habitats helps conservation efforts, but the distribution and diversity particularly of microinvertebrates remains poorly understood. Springtails, mites, tardigrades, nematodes and rotifers are difficult to identify using morphological features, hence DNA-based metabarcoding methods are well suited for their study. We compared taxonomy assignments of a high throughput sequencing metabarcoding approach using one ribosomal DNA (18S rDNA) and one mitochondrial DNA (cytochrome c oxidase subunit I - COI) marker with morphological reference data. Specifically, we compared metabarcoding or morphological taxonomic assignments on multiple taxonomic levels in an artificial DNA blend containing Australian invertebrates, and in seven extracts of Antarctic soils containing known micro-faunal taxa. Avoiding arbitrary application of metabarcoding analysis parameters, we calibrated those parameters with metabarcoding data from non-Antarctic soils. Metabarcoding approaches employing 18S rDNA and COI markers enabled detection of small and cryptic Antarctic invertebrates, and on low taxonomic ranks 18S data outperformed COI data in this respect. Morphological taxonomy determination did not outperform metabarcoding approaches. Our study demonstrates how barcoding markers can be tested prior to their application to specific taxonomic groups, and that taxonomy fidelity of markers needs to be validated in relation to environment, taxa, and available reference information.

This article offers supplementary material which is provided at the end of the article.

Keywords : environmental DNA; metataxonomic; mitochondrial cytochrome c oxidase I; COI; 18S rDNA; Illumina; 454; biodiversity survey

References

  • [1] Freckman D. W. & Virginia R.A., Low-Diversity Antarctic Soil Nematode Communities: Distribution and Response to Disturbance, Ecology, 1997, 78, 363. (doi:CrossrefGoogle Scholar

  • [2] Nielsen U. N., Wall D. H., Adams B. J. & Virginia R. A., Antarctic nematode communities: observed and predicted responses to climate change, Polar Biol., 2011, 34, 1701-1711. (doi:CrossrefGoogle Scholar

  • [3] Chown S. L., Lee J. E., Hughes K. A., Barnes J., Barrett P. J., Bergstrom D. M., et al., Challenges to the Future Conservation of the Antarctic, Science, 2012, 337(6091), 158-159. (doi:CrossrefGoogle Scholar

  • [4] Convey P. & Stevens M. I., Antarctic Biodiversity, Science, 2007, 317(5846), 1877-1878. (doi:CrossrefGoogle Scholar

  • [5] Convey P., Terrestrial biodiversity in Antarctica - Recent advances and future challenges, Polar Sci., 2010, 4, 135-147. (doi:CrossrefGoogle Scholar

  • [6] Fretwell P. T., Convey P., Fleming A. H., Peat H. J. & Hughes K. A., Detecting and mapping vegetation distribution on the Antarctic Peninsula from remote sensing data, Polar Biol., 2011, 34, 273-281.CrossrefGoogle Scholar

  • [7] Casanovas P., Black M., Fretwell P. & Convey P., Mapping lichen distribution on the Antarctic Peninsula using remote sensing, lichen spectra and photographic documentation by citizen scientists, Polar Res., 2015, 34. (doi:CrossrefGoogle Scholar

  • [8] McGaughran A., Stevens M. I., Hogg I. D. & Carapelli A., Extreme Glacial Legacies: A Synthesis of the Antarctic Springtail Phylogeographic Record, Insects, 2011, 2, 62-82. (doi:CrossrefGoogle Scholar

  • [9] Terauds A., Chown S. L., Morgan F. J., Peat H., Watts D. J., Keys H., et al, Conservation biogeography of the Antarctic, Divers. Distrib., 2012, 18, 726-741. (doi:CrossrefGoogle Scholar

  • [10] Wall D. H., Global Change in a Low Diversity Terrestrial Ecosystem: The McMurdo Dry Valleys. In Antarctic Ecosystems: An Extreme Environment in a Changing World (eds A. D. Rogers N. M. Johnston E. J. Murphy & A. Clarke), Chichester, UK: John Wiley & Sons, Ltd., 2012Google Scholar

  • [11] Stevens M. I. & Hogg I. D., Contrasting levels of mitochondrial DNA variability between mites (Penthalodidae) and springtails (Hypogastruridae) from the Trans-Antarctic Mountains suggest long-term effects of glaciation and life history on substitution rates, and speciation processes, Soil Biol. Biochem.,2006, 38, 3171-3180. (doi:CrossrefGoogle Scholar

  • [12] Velasco-Castrillón A., Gibson J. A. E. & Stevens M. I., A review of current Antarctic limno-terrestrial microfauna, Polar Biol., 2014, 37, 1517-1531. (doi:CrossrefGoogle Scholar

  • [13] Velasco-Castrillón A. & Stevens M. I., Morphological and molecular diversity at a regional scale: A step closer to understanding Antarctic nematode biogeography, Soil Biol. Biochem., 2014, 70, 272-284. (doi:CrossrefGoogle Scholar

  • [14] Velasco-Castrillón A., Schultz M. B., Colombo F., Gibson J. A. E., Davies K. A., Austin, A. D., et al., Distribution and Diversity of Soil Microfauna from East Antarctica: Assessing the Link between Biotic and Abiotic Factors, PLoS One, 2014, 9, e87529. (doi:CrossrefGoogle Scholar

  • [15] Rogers A. D., Evolution and biodiversity of Antarctic organisms: a molecular perspective, Philos. Trans. R. Soc. B Biol. Sci., 2007, 362, 2191-2214. (doi:CrossrefGoogle Scholar

  • [16] Czechowski P., Clarke L. J., Cooper A. & Stevens M. I., A primer to metabarcoding surveys of Antarctic terrestrial biodiversity, Antarct. Sci., 2017, 29(1), 3-15. (doi:CrossrefGoogle Scholar

  • [17] Makhalanyane T. P., Valverde A., Birkeland N.-K., Cary S. C., Marla Tuffin I. & Cowan, D. A., Evidence for successional development in Antarctic hypolithic bacterial communities, ISME J., 2013, 7, 2080-2090. (doi:CrossrefGoogle Scholar

  • [18] Dreesens L., Lee C. & Cary S., The Distribution and Identity of Edaphic Fungi in the McMurdo Dry Valleys, Biology, 2014, 3, 466-483. (doi:CrossrefGoogle Scholar

  • [19] Lawley B., Ripley S., Bridge P. & Convey P., Molecular Analysis of Geographic Patterns of Eukaryotic Diversity in Antarctic Soils, Appl. Environ. Microbiol.,2004, 70, 5963-5972. (doi:CrossrefGoogle Scholar

  • [20] Nakai R., Abe T., Baba T., Imura S., Kagoshima H., Kanda H., et al., Eukaryotic phylotypes in aquatic moss pillars inhabiting a freshwater lake in East Antarctica, based on 18S rRNA gene analysis, Polar Biol. 35, 2012, 1495-1504. (doi:CrossrefGoogle Scholar

  • [21] Taberlet P., Coissac E., Pompanon F., Brochmann C. & Willerslev E., Towards next-generation biodiversity assessment using DNA metabarcoding, Mol. Ecol., 2012, 21, 2045-2050. (doi:CrossrefGoogle Scholar

  • [22] Bik H. M., Porazinska D. L., Creer S., Caporaso J. G., Knight R. & Thomas W. K., Sequencing our way towards understanding global eukaryotic biodiversity, Trends Ecol. Evol., 2012, 27, 233-243. (doi:CrossrefGoogle Scholar

  • [23] Bohmann K., Evans A., Gilbert M. T. P., Carvalho G. R., Creer S., Knapp M., et al., Environmental DNA for wildlife biology and biodiversity monitoring, Trends Ecol. Evol., 2014, 29, 358-367. (doi:CrossrefGoogle Scholar

  • [24] Clarke L. J., Soubrier J., Weyrich L. S. & Cooper A., Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias, Mol. Ecol. Resour., 2014, 14, 1160-1170. (doi:CrossrefGoogle Scholar

  • [25] Drummond A. J. et al., Evaluating a multigene environmental DNA approach for biodiversity assessment, Gigascience, 2015 4, 46. (doi:CrossrefGoogle Scholar

  • [26] Czechowski P., Clarke L. J., Breen J., Cooper A. & Stevens M. I., Antarctic eukaryotic soil diversity of the Prince Charles Mountains revealed by high-throughput sequencing, Soil Biol. Biochem., 2016 95, 112-121. (doi:CrossrefGoogle Scholar

  • [27] Lopez-Bueno A., Tamames J., Velazquez D., Moya A., Quesada A. & Alcami A., High Diversity of the Viral Community from an Antarctic Lake, Science, 2009, (80-. ). 326, 858-861. (doi:CrossrefGoogle Scholar

  • [28] Bottos E. M., Scarrow J. W., Archer S. D. J., Mcdonald I. R. & Cary S. C., Bacterial community structures of Antarctic soils, In: Cowan, D. A. (Eds.), Antarctic Terrestrial Microbiology pp. 9-33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014Google Scholar

  • [29] Teixeira L. C. R. S., Peixoto R. S., Cury J. C., Sul W. J., Pellizari V. H., Tiedje J., et al., Bacterial diversity in rhizosphere soil from Antarctic vascular plants of Admiralty Bay, maritime Antarctica, ISME J., 2010, 4, 989-1001. (doi:CrossrefGoogle Scholar

  • [30] Niederberger T. D., Sohm J. A., Gunderson T. E., Parker A. E., Tirindelli J., Capone, D. G., et al., Microbial community composition of transiently wetted Antarctic Dry Valley soils, Front. Microbiol., 2015, 6, 1-12. (doi:CrossrefGoogle Scholar

  • [31] Kelly R. P., Making environmental DNA count, Mol. Ecol. Resour., 2016, 16, 10-12. (doi:CrossrefGoogle Scholar

  • [32] Medlin L., Elwood H. J., Stickel S. & Sogin M. L., The characterization of enzymatically amplified eukaryotic 16S-like rRNA-coding regions, Gene, 1988, 71, 491-499. (doi:CrossrefGoogle Scholar

  • [33] Folmer O., Black M., Hoeh W., Lutz R. & Vrijenhoek R., DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates, Mol. Mar. Biol. Biotechnol., 1994, 3, 294-9.Google Scholar

  • [34] Benson D. A., Karsch-Mizrachi I., Lipman D. J., Ostell J. & Sayers E. W., GenBank, Nucleic Acids Res., 2011, 39, D32-7. (doi:CrossrefGoogle Scholar

  • [35] Koskinen K., Auvinen P., Björkroth K. J. & Hultman J., Inconsistent Denoising and Clustering Algorithms for Amplicon Sequence Data, J. Comput. Biol., 2015, 22, 743-751. (doi:CrossrefGoogle Scholar

  • [36] Pankhurst C. E., Ophel-Keller K., Doube B. M. & Gupta V. V. S. R., Biodiversity of soil microbial communities in agricultural systems, Biodivers. Conserv., 1996, 5, 197-209. (doi:CrossrefGoogle Scholar

  • [37] Ophel-Keller K., McKay A., Hartley D., Curran H. & Curran J., Development of a routine DNA-based testing service for soilborne diseases in Australia, Australas. Plant Pathol.,2008, 37, 243. (doi:CrossrefGoogle Scholar

  • [38] Haling R. E. et al., Direct measurement of roots in soil for single and mixed species using a quantitative DNA-based method, Plant Soil, 2011, 348, 123-137. (doi:CrossrefGoogle Scholar

  • [39] Huang C. Y. et al., A DNA-based method for studying root responses to drought in field-grown wheat genotypes, Sci. Rep., 2013, 3, 1-7. (doi:CrossrefGoogle Scholar

  • [40] Gilbert J. A. et al., Meeting Report: The Terabase Metagenomics Workshop and the Vision of an Earth Microbiome Project, Stand. Genomic Sci., 2010, 3, 243-248. (doi:CrossrefGoogle Scholar

  • [41] Parfrey L. W. et al., Communities of microbial eukaryotes in the mammalian gut within the context of environmental eukaryotic diversity, Front. Microbiol., 2014, 5, 1-13. (doi:CrossrefGoogle Scholar

  • [42] Leray M., Yang J. Y., Meyer C. P., Mills S. C., Agudelo N., Ranwez V., et al., 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., 2013, 10, 34. (doi:CrossrefGoogle Scholar

  • [43] Ding J. et al., Integrated metagenomics and network analysis of soil microbial community of the forest timberline, Sci. Rep., 2015, 5, 7994. (doi:CrossrefGoogle Scholar

  • [44] Yu D. W., Ji Y., Emerson B. C., Wang X., Ye C., Yang C. & Ding Z., Biodiversity soup: metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring, Methods Ecol. Evol., 2012, 3, 613-623. (doi:CrossrefGoogle Scholar

  • [45] Lenz T. L. & Becker S., Simple approach to reduce PCR artefact formation leads to reliable genotyping of MHC and other highly polymorphic loci - Implications for evolutionary analysis, Gene, 2008, 427, 117-123. (doi:CrossrefGoogle Scholar

  • [46] Pruesse E., Quast C., Knittel K., Fuchs B. M., Ludwig W., Peplies J. & Glockner F. O., SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB, Nucleic Acids Res., 2007 35, 7188-7196. (doi:CrossrefGoogle Scholar

  • [47] Velasco-Castrillón A., Page T. J., Gibson J. A. E. & Stevens M. I., Surprisingly high levels of biodiversity and endemism amongst Antarctic rotifers uncovered with mitochondrial DNA, Biodiversity, 2014, 15, 130-142. (doi:CrossrefGoogle Scholar

  • [48] Caporaso J. G. et al., QIIME allows analysis of high-throughput community sequencing data, Nat. Methods, 2010 , 7, 335-336. (doi:CrossrefGoogle Scholar

  • [49] R Development Core Team, R: A language and environment for statistical computing, R Foundation for Statistical Computing, 2016, Vienna, Austria. URL http://www.R-project.org/.Google Scholar

  • [50] Dray S. & Dufour, A.-B., The ade4 Package: Implementing the Duality Diagram for Ecologists, J. Stat. Softw., 2007, 22, 1-20. (doi:CrossrefGoogle Scholar

  • [51] Chessel D., Dufour A. B. & Thioulouse J., The ade4 package I: One-table methods. R News, 2004, 4, 5-10.Google Scholar

  • [52] McMurdie P. J. & Holmes S., Phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data, PLoS One, 2013, 8, e61217. (doi:CrossrefGoogle Scholar

  • [53] Wickham H., The Split-Apply-Combine Strategy for Data Analysis, J. Stat. Softw., 2011, 40, 1-20. (doi:CrossrefGoogle Scholar

  • [54] Wickham H., ggplot2, Springer New York, 2009. (doi:CrossrefGoogle Scholar

  • [55] Dixon P., VEGAN, a package of R functions for community ecology, J. Veg. Sci., 2003, 14, 927-930. (doi:CrossrefGoogle Scholar

  • [56] Edgar R. C., Search and clustering orders of magnitude faster than BLAST, Bioinformatics, 2010, 26, 2460-2461. (doi:CrossrefGoogle Scholar

  • [57] Koch G. G., Intraclass Correlation Coefficient, In: Encyclopedia of Statistical Sciences, pp. 213-217. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2006 (doi:CrossrefGoogle Scholar

  • [58] Leray M. & Knowlton N., Censusing marine eukaryotic diversity in the twenty-first century, Philos. Trans. R. Soc. B Biol. Sci., 2016, 371, 20150331. (doi:CrossrefGoogle Scholar

  • [59] Tang C. Q., Leasi F., Obertegger U., Kieneke A., Barraclough T. G. & Fontaneto D., The widely used small subunit 18S rDNA molecule greatly underestimates true diversity in biodiversity surveys of the meiofauna, Proc. Natl. Acad. Sci., 2012, 109, 16208-16212. (doi:CrossrefGoogle Scholar

  • [60] Zhan A., Bailey S. A., Heath D. D. & Macisaac H. J., Performance comparison of genetic markers for high-throughput sequencing-based biodiversity assessment in complex communities, Mol. Ecol. Resour., 2014, 14, 1049-1059. (doi:CrossrefGoogle Scholar

  • [61] Wu T., Ayres E., Li G., Bardgett R. D., Wall D. H. & Garey J. R., Molecular profiling of soil animal diversity in natural ecosystems: Incongruence of molecular and morphological results, Soil Biol. Biochem., 2009, 41, 849-857. (doi:CrossrefGoogle Scholar

  • [62] Cowart D. A., Pinheiro M., Mouchel O., Maguer M., Grall J., Miné J. & Arnaud-Haond S. Metabarcoding is powerful yet still blind: A comparative analysis of morphological and molecular surveys of seagrass communities. PLoS One 10, 2015, e0117562.Google Scholar

  • [63] Tréguier A., Paillisson J.-M., Dejean T., Valentini A., Schlaepfer M. A. & Roussel J.-M., Environmental DNA surveillance for invertebrate species: advantages and technical limitations to detect invasive crayfish Procambarus clarkii in freshwater ponds, J. Appl. Ecol., 2014, 51, 871-879. (doi:CrossrefGoogle Scholar

  • [64] Olds B. P., Jerde C. L., Renshaw M. A., Li Y., Evans N. T., Turner C. R., et al., Estimating species richness using environmental DNA, Ecol. Evol., 2016 , 6, 4214-4226. (doi:CrossrefGoogle Scholar

  • [65] Lee C. K., Herbold C. W., Polson S. W., Wommack K. E., Williamson S. J., McDonald I. R. & Cary S. C., Groundtruthing Next-Gen Sequencing for Microbial Ecology-Biases and Errors in Community Structure Estimates from PCR Amplicon Pyrosequencing, PLoS One, 2012, 7, e44224. (doi:CrossrefGoogle Scholar

  • [66] Bokulich N. A., Subramanian S., Faith J. J., Gevers D., Gordon J. I., Knight R., Mills D. A. & Caporaso J. G., Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing, Nat. Methods, 2012, 10, 57-59. (doi:CrossrefGoogle Scholar

  • [67] Berney C., Fahrni J. & Pawlowski J., How many novel eukaryotic ‘kingdoms’? Pitfalls and limitations of environmental DNA surveys, BMC Biol., 2004, 2, 13. (doi:CrossrefGoogle Scholar

  • [68] Kwong S., Srivathsan A. & Meier R., An update on DNA barcoding: low species coverage and numerous unidentified sequences, Cladistics, 2012, 28, 639-644. (doi:CrossrefGoogle Scholar

  • [69] Smith D. P. & Peay K. G., Sequence Depth, Not PCR Replication, Improves Ecological Inference from Next Generation DNA Sequencing, PLoS One, 2014, 9, e90234. (doi:CrossrefGoogle Scholar

  • [70] Zhan A., Xiong W., He S. & MacIsaac H. J., Influence of Artifact Removal on Rare Species Recovery in Natural Complex Communities Using High-Throughput Sequencing, PLoS One, 2014, 9, e96928. (doi:CrossrefGoogle Scholar

  • [71] Dartnall H. J. G., Rotifers of the Antarctic and Subantarctic. Hydrobiologia, 1983, 104, 57-60. (doi:CrossrefGoogle Scholar

  • [72] Egan S. P., Grey E., Olds B., Feder J. L., Ruggiero S. T., Tanner C. E. & Lodge D. M., Rapid Molecular Detection of Invasive Species in Ballast and Harbor Water by Integrating Environmental DNA and Light Transmission Spectroscopy, Environ. Sci. Technol., 2015, 49, 4113-4121. (doi:CrossrefGoogle Scholar

  • [73] Taberlet, P., Prud’homme S. M., Campione E., Roy J., Miquel C., Shehzad W. et al., Soil sampling and isolation of extracellular DNA from large amount of starting material suitable for metabarcoding studies, Mol. Ecol., 2012, 21, 1816-1820. (doi:CrossrefGoogle Scholar

  • [74] Deagle B. E., Jarman S. N., Coissac E., Pompanon F. & Taberlet P., DNA metabarcoding and the cytochrome c oxidase subunit I marker: Not a perfect match, Biol. Lett., 2014, 10, 20140562-20140562. (doi:CrossrefGoogle Scholar

  • [75] Abouheif E., Zardoya R. & Meyer A., Limitations of Metazoan 18S rRNA Sequence Data: Implications for Reconstructing a Phylogeny of the Animal Kingdom and Inferring the Reality of the Cambrian Explosion, J. Mol. Evol., 1998, 47, 394-405. (doi:CrossrefGoogle Scholar

  • [76] Moritz C., Dowling T. E. & Brown W. M., Evolution of Animal Mitochondrial DNA: Relevance for Population Biology and Systematics, Annu. Rev. Ecol. Syst., 1987, 18, 269-292. (doi:CrossrefGoogle Scholar

  • [77] Wiemers M. & Fiedler K., Does the DNA barcoding gap exist? - A case study in blue butterflies (Lepidoptera: Lycaenidae), Front. Zool., 2007, 4, 8. (doi:CrossrefGoogle Scholar

  • [78] Turrill W. B., The expansion of taxonomy with special reference to Spermatophyta. Biol. Rev., 1938, 13, 342-373. (doi:CrossrefGoogle Scholar

  • [79] Stevens M. I., Porco D., D’Haese C. A., Deharveng L., Comment on ‘Taxonomy and the DNA barcoding enterprise’ by Ebach (2011), Zootaxa, 2011, 88, 85-88.Google Scholar

  • [80] Liu S., Li Y., Lu J., Su X., Tang M.,Zhang R., et al, SOAP Barcode: Revealing arthropod biodiversity through assembly of Illumina shotgun sequences of PCR amplicons, Methods Ecol. Evol., 2013, 4, 1142-1150. (doi:CrossrefGoogle Scholar

About the article

Received: 2015-02-28

Accepted: 2016-12-19

Published Online: 2017-06-16

Published in Print: 2017-06-27


Citation Information: DNA Barcodes, Volume 5, Issue 1, Pages 1–13, ISSN (Online) 2299-1077, DOI: https://doi.org/10.1515/dna-2017-0001.

Export Citation

© 2017. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

Supplementary Article Materials

Comments (0)

Please log in or register to comment.
Log in