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The DNA metabarcoding approach
   for analyzing environmental
samples: high throughput plant and
        animal identification
 Pierre Taberlet, Eric Coissac, François Pompanon,
    Johan Pansu, Wasim Shehzad, Tiayyba Riaz
      Laboratoire d'Ecologie Alpine, CNRS UMR 5553
        Université Joseph Fourier, Grenoble, France
Need for high throughput
      collection of biodiversity data

•  For research
•  For management


     At the moment, no
 possibilty to use satellites
  for identifying taxa and
collecting biodiversity data.
    Why not using DNA
       metabarcoding?
                                NASA Earth Observing System: Terra Satellite Platform
Our goal: a new high throughput
    approach for obtaining
       biodiversity data
  (based on the DNA-barcoding concept, and
      using next generation sequencers)


•  A single sampling in the field
•  Simple and robust metabarcoding
   experiments at the bench
•  Complete biodiversity assessment at
   the sampling site
Environmental DNA (eDNA)

•  Environmental DNA refers to DNA that can be
   extracted from air, water, or soil, without isolating
   any specific type of organism beforehand
•  Two types:
   –  intracellular eDNA
   –  extracellular eDNA
•  Intracellular eDNA commonly used by
   microbiologists
•  We focus on extracellular eDNA
Constraints of working with
           environmental DNA
•  Complex mixture containing degraded DNA
•  The eDNA extract must be representative of the local
   biodiversity
•  The standard DNA barcodes are not optimal (they are by
   far too long to reveal the whole spectrum of biodiversity)
•  The primers must be highly versatile (to equally amplify
   the different target DNAs)
•  Problem of the taxonomic resolution when using very
   short barcodes
•  At the moment, problem of the reference database when
   using non-standard barcodes
"Roche Noire" experiment
     in French Alps


 •  Four plant communities
      –    dry high alpine meadows dominated by Kobresia myosuroides
      –    low alpine meadows dominated by Carex sempervirens
      –    subalpine heath dominated by Vaccinium sp.
      –    subalpine grasslands dominated by Festuca paniculata
 •    Three plots per plant community (12 plots)
 •    Two soil samples per plot (with 80 cores per sample)
 •    Two DNA extractions per sample
 •    Two DNA amplifications per extraction
"Roche Noire" experiment in
             French Alps
    80 soil cores per sample




               10m

● Extraction of extracellular DNA from kilograms of soil using a phosphate buffer
● DNA amplification of the P6 loop of the chloroplast trnL (UAA) intron
● Sequencing on the 454
"Roche Noire" experiment: projections
          of a between class analysis
                           Axe 2 (15.4%)                                 Axe 3 (13.2%)




  Axe 1 (18.9%)                                 Axe 2 (15.4%)




                                                                                  Carex
                                                                                  Festuca
                                                                                  Kobresia
                                                                                  Vaccinium




  A                                             B

Taberlet P, Prud'homme S, Campione E, et al. (2012) Extraction of extracellular DNA from large
            amount of soil for metabarcoding studies. Molecular Ecology, 21, in press.
                             doi: 10.1111/j.1365-1294X.2011.05317.x.
Simple and robust
         metabarcoding experiments
   •  In silico analysis: design and test of short
      metabarcodes (ecoPrimers, ecoPCR)
   •  Empirical experiments
        –  DNA amplification with barcode primers
        –  Sequencing of the PCR products on next generation
           sequencers
   •  Sequence analysis
        –  OBITools (www.prabi.grenoble.fr/trac/OBITools)
Ficetola GF, Coissac E, Zundel S, et al. (2010) An in silico approach for the evaluation of DNA
                            barcodes. BMC Genomics, 11, 434.
Riaz T, Shehzad W, Viari A, Pompanon F, Taberlet P, Coissac E (2011) ecoPrimers: inference of
 new DNA barcode markers from whole genome sequence analysis. Nucleic Acids Research,
                                 doi:10.1093/nar/gkr1732.
A collection of metabarcoding primers
  Taxonomic group                Gene            Length      Accuracy (Bs)
Angiosperms/Gymnosperms     cpDNA trnL intron   10-100 bp    Genus/Species
        Poaceae                   ITS1           54-88 bp       Species
          Fungi                   ITS1           ~ 200 bp      Species ?
       Vertebrates          mtDNA 12S V05       76-110 bp    Genus/Species
      Teleost fishes          mtDNA 12S          60-70 bp       Species
        Batrachia             mtDNA 12S         ~ 42-57 bp      Species
      Earthworms          mtDNA 16S (ewB/ewC)    ~ 30 bp        Species
      Earthworms          mtDNA 16S (ewD/ewE)    ~ 70 bp        Species
      Oligochaetes        mtDNA 16S (ewB/ewE)    ~ 120 bp       Species
   Arthropods/Mollusks        mtDNA 16S          35-40 bp     Family/Genus
        Termites              mtDNA 12S          ~ 30 bp       Species ?
        Termites              mtDNA 12S          ~ 70 bp       Species ?
       Collembola             mtDNA 12S          39-44 bp      Species ?
       Collembola             mtDNA 12S         125-138 bp     Species ?

    More information soon on www.metabarcoding.org
Earthworms from soil DNA
•  Eight soil samples collected per plot
•  Universal short metabarcodes for earthworms
•  Reference database built using samples identified with the
   standardized COI barcoding approach
•  Sequencing on Illumina GA IIx
                            d                   e
                  b              c
mtDNA 12S
                        30 bp        70 bp
Earthworms from soil DNA: results
                                                                Chartreuse            Grenoble
       Species                        Barcode                 Plot 1     Plot 2    Plot 1    Plot 2
Aporrectodea icterica     catcttaatgaagactaaaacttcactaaa      836954    649677    834031    1359355
  Aporrectodea longa      tattttaacaaaaacccaaaaattttcaataaa     2         6       244463    271829
    Aporrectodea sp       cattttaataaaaattataaattttactaaa       0         0       236024    236678
  Octolasion cyaneum      cattttaatagaagcttactattctaataaa     468462     3823       0         2
  Lumbricus terrestris    aatttaaataaatataaaaaatttactaaa        0         0       174286    143682
  Octolasion tyrtaeum     cattttaatagaaaaataatatcctaataaa     306476      0         0         2
 Lumbricus castaneus      aatttaaataaatataaaaaaatttactaaa       0         0         56      131001
  Aporrectodea longa      tattttaacaaaacccaaaaattttcaataaa     2469     105312     159       145
 Allobophora chlorotica   cattttaataaagatataaactttactaaa        0         0       51953     43196
Aporrectodea caliginosa   tattttaataaaaaaatataaatttttaataa      0       23005       0         0
                                                                       number of sequence reads



  Bienert R, de Danieli S, Miquel C, Coissac E, Poillot C, Brun JJ, Taberlet P (2012) Tracking
            earthworm communities from soil DNA. Molecular Ecology, 21, in press.
Current limitations of the PCR-
      based approach
•  Dependency on PCR
  –  Amplification introduces errors
  –  Difficulty to find suitable barcodes
  –  Different groups of organisms are analyzed
     separately
•  Lack of comprehensive taxonomic reference
   databases for non-standard metabarcodes
•  Limitations linked to the use of organellar
   markers
Future: capture
  •  Easier to find a single
     conserved region for designing
     the probe for the capture than
     two close conserved regions for
     PCR
  •  ecoProbes: computer program
     for designing suitable probes
     (comparable to ecoPrimers)
  •  Possibility to use hundreds of
     probes at the same time
  •  Both organellar and nuclear
     DNA can be analyzed at the
     same time

e.g. Briggs AW, Good JM, Green RE, et al. (2009) Targeted retrieval and analysis of five Neandertal
                           mtDNA genomes. Science, 325, 318-321.
An idea of the HiSeq 2000
              production per run

•    6 billions of reads of 100 bp
•    6 lines per read
•    55 lines per page (time 11)
•    654 545 454 pages
•    194 400 km long
•    70.5 km high
•    more than 3,000 tons of
     paper
Future: shotgun sequencing

•  Shotgun sequencing of soil extracellular
   DNA on HiSeq 2000
•  We do not know the percentage of
   informative reads
•  Might allow to use the standard barcode
   reference libraries
•  Real bioinformatics challenge
•  Ongoing experiments…
Acknowledgements




 Rike Bienert, Kari Anne Bråthen, Christian Brochmann, Anne Krag Brysting, Etienne
    Campione, Corinne Cruaud; Francesco de Bello, Tony Dejean, Mary Edwards,
Francesco Ficetola, Frédérick Gavory, Ludovic Gielly, James Haile, Christelle Melo de
Lima, Christian Miquel, Stéphanie Pellier-Cuit, Sophie Prud'homme, Delphine Rioux,
 Julien Roy, Jorn Henrik Sønstebø, Wilfried Thuiller, Alice Valentini, Eske Willerslev,
                            Patrick Wincker, Nigel Yoccoz
Thank you for
                    your attention



             Contacts: eric.coissac@inria.f; pierre.taberlet@ujf-grenoble.fr

Molecular Ecology will publish in 2012 a special issue on Environmental DNA

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Pierre Taberlet - Saturday Closing Plenary

  • 1. The DNA metabarcoding approach for analyzing environmental samples: high throughput plant and animal identification Pierre Taberlet, Eric Coissac, François Pompanon, Johan Pansu, Wasim Shehzad, Tiayyba Riaz Laboratoire d'Ecologie Alpine, CNRS UMR 5553 Université Joseph Fourier, Grenoble, France
  • 2. Need for high throughput collection of biodiversity data •  For research •  For management At the moment, no possibilty to use satellites for identifying taxa and collecting biodiversity data. Why not using DNA metabarcoding? NASA Earth Observing System: Terra Satellite Platform
  • 3. Our goal: a new high throughput approach for obtaining biodiversity data (based on the DNA-barcoding concept, and using next generation sequencers) •  A single sampling in the field •  Simple and robust metabarcoding experiments at the bench •  Complete biodiversity assessment at the sampling site
  • 4. Environmental DNA (eDNA) •  Environmental DNA refers to DNA that can be extracted from air, water, or soil, without isolating any specific type of organism beforehand •  Two types: –  intracellular eDNA –  extracellular eDNA •  Intracellular eDNA commonly used by microbiologists •  We focus on extracellular eDNA
  • 5. Constraints of working with environmental DNA •  Complex mixture containing degraded DNA •  The eDNA extract must be representative of the local biodiversity •  The standard DNA barcodes are not optimal (they are by far too long to reveal the whole spectrum of biodiversity) •  The primers must be highly versatile (to equally amplify the different target DNAs) •  Problem of the taxonomic resolution when using very short barcodes •  At the moment, problem of the reference database when using non-standard barcodes
  • 6.
  • 7. "Roche Noire" experiment in French Alps •  Four plant communities –  dry high alpine meadows dominated by Kobresia myosuroides –  low alpine meadows dominated by Carex sempervirens –  subalpine heath dominated by Vaccinium sp. –  subalpine grasslands dominated by Festuca paniculata •  Three plots per plant community (12 plots) •  Two soil samples per plot (with 80 cores per sample) •  Two DNA extractions per sample •  Two DNA amplifications per extraction
  • 8. "Roche Noire" experiment in French Alps 80 soil cores per sample 10m ● Extraction of extracellular DNA from kilograms of soil using a phosphate buffer ● DNA amplification of the P6 loop of the chloroplast trnL (UAA) intron ● Sequencing on the 454
  • 9.
  • 10.
  • 11.
  • 12.
  • 13. "Roche Noire" experiment: projections of a between class analysis Axe 2 (15.4%) Axe 3 (13.2%) Axe 1 (18.9%) Axe 2 (15.4%) Carex Festuca Kobresia Vaccinium A B Taberlet P, Prud'homme S, Campione E, et al. (2012) Extraction of extracellular DNA from large amount of soil for metabarcoding studies. Molecular Ecology, 21, in press. doi: 10.1111/j.1365-1294X.2011.05317.x.
  • 14. Simple and robust metabarcoding experiments •  In silico analysis: design and test of short metabarcodes (ecoPrimers, ecoPCR) •  Empirical experiments –  DNA amplification with barcode primers –  Sequencing of the PCR products on next generation sequencers •  Sequence analysis –  OBITools (www.prabi.grenoble.fr/trac/OBITools) Ficetola GF, Coissac E, Zundel S, et al. (2010) An in silico approach for the evaluation of DNA barcodes. BMC Genomics, 11, 434. Riaz T, Shehzad W, Viari A, Pompanon F, Taberlet P, Coissac E (2011) ecoPrimers: inference of new DNA barcode markers from whole genome sequence analysis. Nucleic Acids Research, doi:10.1093/nar/gkr1732.
  • 15. A collection of metabarcoding primers Taxonomic group Gene Length Accuracy (Bs) Angiosperms/Gymnosperms cpDNA trnL intron 10-100 bp Genus/Species Poaceae ITS1 54-88 bp Species Fungi ITS1 ~ 200 bp Species ? Vertebrates mtDNA 12S V05 76-110 bp Genus/Species Teleost fishes mtDNA 12S 60-70 bp Species Batrachia mtDNA 12S ~ 42-57 bp Species Earthworms mtDNA 16S (ewB/ewC) ~ 30 bp Species Earthworms mtDNA 16S (ewD/ewE) ~ 70 bp Species Oligochaetes mtDNA 16S (ewB/ewE) ~ 120 bp Species Arthropods/Mollusks mtDNA 16S 35-40 bp Family/Genus Termites mtDNA 12S ~ 30 bp Species ? Termites mtDNA 12S ~ 70 bp Species ? Collembola mtDNA 12S 39-44 bp Species ? Collembola mtDNA 12S 125-138 bp Species ? More information soon on www.metabarcoding.org
  • 16. Earthworms from soil DNA •  Eight soil samples collected per plot •  Universal short metabarcodes for earthworms •  Reference database built using samples identified with the standardized COI barcoding approach •  Sequencing on Illumina GA IIx d e b c mtDNA 12S 30 bp 70 bp
  • 17. Earthworms from soil DNA: results Chartreuse Grenoble Species Barcode Plot 1 Plot 2 Plot 1 Plot 2 Aporrectodea icterica catcttaatgaagactaaaacttcactaaa 836954 649677 834031 1359355 Aporrectodea longa tattttaacaaaaacccaaaaattttcaataaa 2 6 244463 271829 Aporrectodea sp cattttaataaaaattataaattttactaaa 0 0 236024 236678 Octolasion cyaneum cattttaatagaagcttactattctaataaa 468462 3823 0 2 Lumbricus terrestris aatttaaataaatataaaaaatttactaaa 0 0 174286 143682 Octolasion tyrtaeum cattttaatagaaaaataatatcctaataaa 306476 0 0 2 Lumbricus castaneus aatttaaataaatataaaaaaatttactaaa 0 0 56 131001 Aporrectodea longa tattttaacaaaacccaaaaattttcaataaa 2469 105312 159 145 Allobophora chlorotica cattttaataaagatataaactttactaaa 0 0 51953 43196 Aporrectodea caliginosa tattttaataaaaaaatataaatttttaataa 0 23005 0 0 number of sequence reads Bienert R, de Danieli S, Miquel C, Coissac E, Poillot C, Brun JJ, Taberlet P (2012) Tracking earthworm communities from soil DNA. Molecular Ecology, 21, in press.
  • 18. Current limitations of the PCR- based approach •  Dependency on PCR –  Amplification introduces errors –  Difficulty to find suitable barcodes –  Different groups of organisms are analyzed separately •  Lack of comprehensive taxonomic reference databases for non-standard metabarcodes •  Limitations linked to the use of organellar markers
  • 19. Future: capture •  Easier to find a single conserved region for designing the probe for the capture than two close conserved regions for PCR •  ecoProbes: computer program for designing suitable probes (comparable to ecoPrimers) •  Possibility to use hundreds of probes at the same time •  Both organellar and nuclear DNA can be analyzed at the same time e.g. Briggs AW, Good JM, Green RE, et al. (2009) Targeted retrieval and analysis of five Neandertal mtDNA genomes. Science, 325, 318-321.
  • 20. An idea of the HiSeq 2000 production per run •  6 billions of reads of 100 bp •  6 lines per read •  55 lines per page (time 11) •  654 545 454 pages •  194 400 km long •  70.5 km high •  more than 3,000 tons of paper
  • 21. Future: shotgun sequencing •  Shotgun sequencing of soil extracellular DNA on HiSeq 2000 •  We do not know the percentage of informative reads •  Might allow to use the standard barcode reference libraries •  Real bioinformatics challenge •  Ongoing experiments…
  • 22. Acknowledgements Rike Bienert, Kari Anne Bråthen, Christian Brochmann, Anne Krag Brysting, Etienne Campione, Corinne Cruaud; Francesco de Bello, Tony Dejean, Mary Edwards, Francesco Ficetola, Frédérick Gavory, Ludovic Gielly, James Haile, Christelle Melo de Lima, Christian Miquel, Stéphanie Pellier-Cuit, Sophie Prud'homme, Delphine Rioux, Julien Roy, Jorn Henrik Sønstebø, Wilfried Thuiller, Alice Valentini, Eske Willerslev, Patrick Wincker, Nigel Yoccoz
  • 23. Thank you for your attention Contacts: eric.coissac@inria.f; pierre.taberlet@ujf-grenoble.fr Molecular Ecology will publish in 2012 a special issue on Environmental DNA