EukRef workshop (Vancouver, 2015)

1. Global ocean’s protist
metabarcoding
Colomban de Vargas, Stéphane Audic, Nicolas Henry,
Johan Decelle, Frédéric Mahé, Cédric Berney,
Sébastien Colin, Sarah Romac, Daniel Richter, Ian
Probert, Raffaele Siano, Gipsi Lima-Mendez, Jeroen
Raes, Chris Bowler, Patrick Wincker, Eric Karsenti, &
the Tara Oceans Consortium.

5. 43 samples (viral fraction <0.22um) from 26 stations; 2.16 billion
Illumina reads (200X larger than the Pacific Ocean Virome).
pelagic upper-ocean viral community
sequence space is now well-sampled and
approaches a limit of ca. 1 million PCs
Protein Clusters
(ORFs)

6. • 68 stations68 stations 7.2 Tbp DNA data7.2 Tbp DNA data
• 3 depths3 depths in the context ofin the context of
• 243 samples243 samples the environmentthe environment
A genetic inventory of the ocean:A genetic inventory of the ocean:
Ocean Microbial Reference Gene CatalogOcean Microbial Reference Gene Catalog
High sequencing coverageHigh sequencing coverage
• only few new genes per
additional sample
• 4 x more genes than in
human gut microbiome

8. meta-barcoding – V9 rDNA, the microscope of the III millenary
334 plankton communities
4 organismal size fractions
47 stations,sub-surface + DCM layers (photic zone)
~ 2 millions genetic barcodes per sample (total of ~800
million metabarcodes)

9. 13,432 / 24,435 eukaryotic genera / species
all main lineages known from environmental sequences (Sanger
clone libraries)
77,500 V9 rDNA reference sequences
V9 PR2* database:
Super Groups taxo coco #seq Total #slc Total
Alveolata MALV-I 17892138 24813
Alveolata Ciliophora 6245421 5631
Alveolata MALV-II - Amoebophryidae 11670735 2035
Alveolata Apicomplexa 3590126 1963
Alveolata Other Alveolata 3322251 1910
Alveolata Dinophyceae 69628078 512
Alveolata MALV-III 557884 182
Alveolata MALV-IV 431436 158
Alveolata Perkinsea 6067 27
Alveolata MALV-V 72967 22
Alveolata Ellobiopsidae 11644 10
Alveolata Syndiniales_X 441 1
Alveolata X-cell 0 0
Amoebozoa Discosea 1002688 145
Amoebozoa Lobosa_X 190465 29
Amoebozoa Variosea 19779 21
Amoebozoa Tubulinea w.o. Arcellinida 10116 18
Amoebozoa Mycetozoa & Myxogastrea 3014 5
Amoebozoa Other Amoebozoa 83 4
Amoebozoa Arcellinida 0 0
Amoebozoa Breviatea 0 0
Amoebozoa Dictyostelida 0 0
Archaeplastida Mamiellophyceae 733072 400
Archaeplastida Other Archaeplastida 53604 231
Archaeplastida Chlorophyceae 11753 227
Archaeplastida Other Chlorophyta 104350 186
Archaeplastida Prasino-Clade-7 2104607 159
Archaeplastida Trebouxiophyceae 8822 140
Archaeplastida Streptophyta 12982 103
Archaeplastida Pyramimonadales 125182 94
Archaeplastida Rhodophyta 9105 57
Archaeplastida Ulvophyceae 1376 27
Archaeplastida Glaucocystophyta 215 3
Excavata Other Discoba 5759069 7475
Excavata Diplonema 2124409 4850
Excavata Kinetoplastida 342384 150
Excavata Euglenida 8246 30
Excavata Heterolobosea 6556 25
Excavata Parabasalia 51 4
Excavata Fornicata 5 1
Excavata Jakobida 10099 1
Excavata Other Excavata 0 0
Excavata Oxymonadida 0 0
Excavata Symbiontida 0 0
Incertae sedis Haptophyta 4566634 713
Incertae sedis Katablepharidophyta 944501 413
Incertae sedis Telonemia 1897627 240
Incertae sedis Cryptophyta 863773 192
Incertae sedis Picozoa 1039003 123
Incertae sedis Other Incertae Sedis Eukaryota 423448 72
Incertae sedis Centroheliozoa 89136 69
Incertae sedis Cryptophyta-nucleomorph 158882 62
Incertae sedis Apusozoa 16178 36
Incertae sedis root 745 4
Opisthokonta Metazoa 246962646 17010
Opisthokonta Ascomycota 1440328 410
Opisthokonta Other Opisthokonta 76429 227
Opisthokonta Basidiomycota 2745504 223
Opisthokonta Choanoflagellida 646149 201
Opisthokonta Mesomycetozoa 83885 75
Opisthokonta Other Fungi 4830 44
Opisthokonta Other Mycota 2337 21
Opisthokonta Chytridiomycota 3702 18
Opisthokonta Entomophthoromycota 582 12
Opisthokonta Microsporidiomycota 588 9
Rhizaria Collodaria 97085064 5636
Rhizaria Other Cercozoa 1517263 1097
Rhizaria Acantharea 2658359 1043
Rhizaria Spumellarida 5199377 586
Rhizaria Nasselaria & Eucyrtidium 656961 383
Rhizaria RAD-B 2784940 253
Rhizaria Foraminifera 371908 248
Rhizaria Phaeodarea 286696 147
Rhizaria RAD-A 1294910 139
Rhizaria Chlorarachnea 202288 74
Rhizaria RAD-C 214401 57
Rhizaria Other Radiolara 121950 41
Rhizaria Euglyphida 3741 13
Rhizaria Other Rhizaria 0 0
Stramenopiles Bacillariophyta 14586250 3276
Stramenopiles MAST-3-12 2807201 536
Stramenopiles Other Stramenopile 880878 338
Stramenopiles Labyrinthulea 317816 322
Stramenopiles MAST-4-6-7-8-9-10-11 2862798 314
Stramenopiles Dictyochophyceae 2068358 224
Stramenopiles Chrysophyceae-Synurophyceae 943987 203
Stramenopiles MAST-1 1727353 114
Stramenopiles Bicoecea 491295 110
Stramenopiles Pelagophyceae 2100247 97
Stramenopiles Other MAST 183672 87
Stramenopiles MOCH-1-2 581183 74
Stramenopiles Oomyceta 216048 71
Stramenopiles Bolidophyceae-and-relatives 107240 60
Stramenopiles MAST-16-22-24 46152 31
Stramenopiles Other identified Stramenopile 6019 22
Stramenopiles Phaeophyceae 63540 20
Stramenopiles Raphidophyceae 4432 14
Stramenopiles MOCH-4 114585 13
Stramenopiles Pirsonia 3989 13
Stramenopiles MOCH-5 94089 11
Stramenopiles MOCH-3 29555 9
Stramenopiles Pinguiophyceae 16116 9
Stramenopiles Opalinata 177 5
Sub-divided into 97 major morpho-lineages
Annotated for basic ecological functions: auto/heterotrophy;
symbioses sensu lato (from parasitism to mutualism, for both
host and symbionts)
Stephane AUDIC
Cedric BERNEY
Database available at:
http://taraoceans.sb-roscoff.fr/EukDiv/

10. Reaching the boundary of total eukaryotic plankton diversity
in the world sunlit oceans (tropical to temperate):
Illumina reads # (million)
0 100 200 300 400 500
All together ‘pico-nano’ - [0.8-5 ]μm ‘nano’ - [5-20 ]μm ‘micro’ - [20-180 ]μm ‘meso’ - [180-2,000 ]μm
OTU #
30,000
60,000
90,000
0
‘pico-nano’ ‘nano’ ‘micro’ ‘meso’
OTUdiversity-Shannon
1
2
3
4
5
6
1.2./100,000
1.3/10,000
7.7/100,000
1.1/10,000
8.0/100,000
Organismal size
fraction(µm)
3 - 20
0.8 - inf
0.8 - 5
0.8 - 20
million reads
2,000,000
1,500,000
1,000,000
500,000
0
#ofmetabarcodes
5,000
4,000
3,000
2,000
1,000
0
ResampledOTUrichness
0.06
0.04
0.02
A
B
0.2 - 3
Slopeofrarefactoncurve
180 - 2,000
5 - 20
20 - 180
All together
million reads
‘pico-nano’ ‘nano’ ‘micro’ ‘meso’
[0.8-5µm] [5-20µm] [20-180µm] [180-2,000µm]
0 100 200 300 400 500
‘pico-nano’ ‘nano’ ‘micro’ ‘meso’ 10 2 3 4
C
Abundance(reads#)Richness(OTU#)
‘pico‐nano’ ‘nano’ ‘micro’ ‘meso’
Alv
Dinoflagellate
Metazoa
Metazoa
Metazoa (93%)
Metazoa (94%)
Metazoa (96%)
Metazoa (99.5%)
Metazoa (99.9%)
MetazoaFungi
Fungi
Fungi
Dinoflagellate Dinoflagellate
Dinoflagellate
Dinoflagellate
Dino-
flagellate
Dino-
flagellate
Dino
Others
Others
Others
Others
Others
Others
Others
MALV
MALV MALV
MALV
MALV
MALV
MALV
A lv A lv A lv
A lv
Alv
Alv
Alv
Alv - Alveolata
Amoe - Amoebozoa
Und - UndeterminedUna - Unassigned Prok - Prokaryote
Rhiz
Rhiz
Rhiz
Rhiz
Prok
Prok
Prok
Prok
Prok
Prok
R h iz
U n a
U n a
U n a U n a
Una Una
R h iz
R h iz
E x c
E x c
E x c
Exc
Rhiz
Arch - Archaeplastida
Arch
A r c h
A r c h
Arch
Rhiz - RhizariaExc - Excavata
Exc Exc
Inc - Incerta sedis
Inc
In c
Opis - Opisthokonta
Opis
Opis
O p is
O p is
O p is
O p is
Opis
Opis
Stram - Stramenopila
Stram
S t r a m
S tr a m
Stram
Stram
Stram
Stram
N = ~114 million
N = ~92,000 N = ~57,000 N = ~46,000 N = ~45,000
N = ~135 million N = ~121 million N = ~135 million
150 000 genetic types (rDNA OTUs) of eukaryotic plankton
Following a Preston curve

11. described
species
Tara-Oceans
rDNA
OTUs
4,350/12,800 1,350/10,000 5,500/15,300
66X
113X 92X
65X 38X

12. phototroph (phytoplancton)
parasite
osmotroph/saprotroph
phagotroph
✓ <1% of the OTUs are strictly identical to reference sequences.
✓ Even in known groups, genetic novelty is massive (e.g.
diatoms, dinoflagellates).
✓ ~60 branches of the tree (2/3) are basically ignored from
plankton ecology (~25% of assignable OTUs).
✓11 lineages are ‘hyper-
diversified (>1,000 OTUs);
mostly heterotrophic protists
in poorly known eukaryotic
supergroups (e.g.
diplonemids).
✓ Overall poor diversity of
phototrophic lineages
(phytoplankton), in
comparison to heterotrophic
protists)
✓ Hyper-diversification in
lineages extending across
larger size-fractions, as well
as their known parasites.
✓ >85% of eukaryotic OTUs belong to protists (zoo- not that
important)

13. A large proportion of the uncovered diversity
represents known or putative parasites / parasitoids.
examples of
lineages
infecting
diatoms
Rhynchopus coscinodiscivorus
(Diplonemida) infecting
Coscinodiscus concinnus
Cryothecomonas
longipes (Cercozoa)
feeding on
Thalassiosira rotula
plasmodium of
Phagomyxa odontellae
(Cercozoa) inside cells
of Odontella sinensis
Pirsonia diadema
(Stramenopila) infecting
Coscinodiscus wailesii

14. Dinomyces arenysensis
(Chytridiomycota) infecting
Alexandrium sp.
examples of
lineages infecting
dinoflagellates
Amoebophrya sp.
(MALV-II, Alveolata)
infecting Alexandrium sp.
zoospores of Parvilucifera sinerae
(Perkinsea, Alveolata) released
from Dinophysis caudata

15. examples of lineages
infecting metazoans
Vampyrophrya
pelagica
(Ciliophora,
Alveolata)
infecting
a copepod
Paramikrocytos canceri
(Ascetosporea, Cercozoa)
infecting Cancer pagurus
Cephaloidophoroids
(Apicomplexa, Alveolata),
parasites of copepods
Blastodinium sp.
(Dinophyceae, Alveolata)
infecting a copepod
Paradinium poucheti
(Ascetosporea, Cercozoa)
infecting Clausocalanus sp.

16. Functional metabarcoding
inference of basic trophic and
symbiotic ecological modes

17. 227 tree species (out of ±16,000) account for half of all trees in Amazonia
269 OTUs:
hyperdominant & cosmopolitan 48%
of all reads
’Hyperdominance and cosmopolitasnism’
25% have poorly
defined identity
(< 95%)
11 are not
assignable
at 85%

18. If 2 species always occur together (co-occurrence)
-> mutualism, commensalism, similar niche?
If 2 species never occur together (mutual exclusion)
-> competition, amensalism, opposing niches?
127,995 associations
92,633 taxon-taxon
35,362 taxon-env
co-occurrence much
more common than
exclusion
•Data processing: sample-size
normalization, keeping proportion of
unclassified + filtered.
• 2 similarity measures: Spearman and KL
similarity
• P-value calculation by matrix
permutation (row shuffling),
renormalization and bootstrapping (Faust
et al. 2012).
•P-value merging (edges supported by >=
2 methods)
•Multiple test correction (Benjamini-
Hochberg).
Prokaryotes: miTag abundances
Phages: metagenomic contig abundances
Protists: 18S metabarcode abundances
Environmental contextual data
68 stations, 2 depths, 7 size fractions

19. Top-down interactions potentially driving plankton
community structure: (1) parasites
Dinophyceae
Acantharea
Ciliophora
Metazoa
Dictyochophyceae
Spumellarida
Bacillariophyta
Nasselaria
Foraminifera
Collodaria
Hostcount
Dinoflagellates infected by syndiniales

20. Experimental validation of network-predicted interaction
(photosymbiosis)
Model for network-driven
hypothesis generation
Laser scanning confocal microscopy (LSCM) of acoel flatworm
with endosymbiotic green algae (Tetraselmis)

22. UniEuk – towards a universal taxonomic framework
and integrated reference gene databases for
eukaryotic biology, ecology, and evolution
A community-based initiative, highly complementary to EukRef

23. UniEuk organizational scheme
A community-based initiative, highly complementary to EukRef

24. To address the current deluge of genetic data from environmental
genetic surveys, meta-barcoding, -transcriptomics, -genomics, single-cell
transcriptomics and genomics, a common taxonomic framework is critical.
Without it, results of different studies using different genes
and different reference databases would not be comparable.
common taxonomic framework
gene 1
reference
database
gene 2
reference
database
gene 3
reference
database
gene 4
reference
database
One taxonomic framework for multiple genetic markers

25. UniEuk: a pragmatic implementation
gene reference
databases
universal
taxonomic
framework
existing
genetic data
repositories

26. UniEuk: a pragmatic implementation
gene reference
databases
taxonomy
table
sequence
table
marker
tables
universal
taxonomic
framework
existing
genetic data
repositories

27. UniEuk: a community-based effort
UniEuk web
portal
Redmine
environment
taxonomy
implemente
r
database
implemente
r
experts / curators
on a web protal, experts/curators have access to the
latest version of the framework and databases
experts/curators use a redmine environment to provide
feedback, flag issues, make suggestions of changes
the implementers use this feedback to improve the
framework/databases and regularly update the web
portal

28. UniEuk Steering Committee
Sina Adl, University of Saskatchewan
Guy Cochrane, EMBL-EBI
Colomban de Vargas, Station Biologique de Roscoff
Frank Oliver Glöckner, Max Planck Institute and Jakobs University
Eunsoo Kim, American Museum of Natural History
Laura Wegener-Parfrey, University of British Columbia
Pelin Yilmaz, Max Planck Institute and Jakobs University