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ACKNOWLEDGMENTS
We thank N. Ollikainen and M. Guttman for help with Hi-C analysis;
R. J. Oakey for providing the processed ChIP-seq data; C.-H. L. Eng for
helpful discussion; C. Karp for making custom-made flow cells;
L. Sanchez and E. Buitrago-Delgado for help with the perfusion
setup; I. Strazhnik for help with figures; and A. Anderson for help
with the manuscript.Funding:This work was supported by NIH 4DN
DA047732 and supplement (L.C.) and by the Paul G. Allen Frontiers
Foundation Discovery Center (L.C.).Author contributions:Y.T.
and L.C. conceived of the idea and designed experiments. Y.T.
designed probes with input from C.H.T. Y.T., J.Y., and S.Sc. prepared
and validated experimental materials. Y.T. performed imaging
experiments. Y.T., S.Sh., N.P., and J.W. wrote image processing
scripts, and Y.T. performed image processing. Y.T., S.Z., and L.C.
analyzed data with input from G.-C.Y. Y.T. and L.C. wrote the
manuscript with input from S.Z., C.H.T., and G.-C.Y. L.C. supervised
all aspects of the projects.Competing interests:L.C. is a cofounder
of Spatial Genomics, Inc.Data and materials availability:The
custom-written scripts and seqFISH probe sequences used in this
study are available in a Zenodo repository ( 18 ) associated with a
GitHub repository (https://github.com/CaiGroup/dna-seqfish-plus-
tissue). The source data and processed data from this study are
available in a Zenodo repository ( 23 ).

SUPPLEMENTARY MATERIALS
science.org/doi/10.1126/science.abj1966
Materials and Methods
Figs. S1 to S25
Tables S1 to S4
References ( 41 – 81 )
MDAR Reproducibility Checklist

26 April 2021; accepted 15 September 2021
Published online 30 September 2021
10.1126/science.abj1966

REPORTS

◥

PLANKTON

Global drivers of eukaryotic plankton biogeography

in the sunlit ocean

Guilhem Sommeria-Klein1,2*, Romain Watteaux^3 †, Federico M. Ibarbalz^1 ‡,

Juan José Pierella Karlusich^1 , Daniele Iudicone^3 , Chris Bowler^1 , Hélène Morlon^1 *

Eukaryotic plankton are a core component of marine ecosystems with exceptional taxonomic and

ecological diversity, yet how their ecology interacts with the environment to drive global distribution

patterns is poorly understood. In this work, we useTaraOceans metabarcoding data, which cover all

major ocean basins, combined with a probabilistic model of taxon co-occurrence to compare the

biogeography of 70 major groups of eukaryotic plankton. We uncover two main axes of biogeographic

variation. First, more-diverse groups display clearer biogeographic patterns. Second, large-bodied

consumers are structured by oceanic basins, mostly through the main current systems, whereas

small-bodied phototrophs are structured by latitude and follow local environmental conditions. Our study

highlights notable differences in biogeographies across plankton groups and investigates their

determinants at the global scale.

M

arine plankton communities play key

ecological roles at the base of oceanic

food chains and in driving global bio-

geochemical fluxes ( 1 , 2 ). Understand-

ing their spatial patterns of distribution

is a long-standing challenge in marine ecology

thathaslatelybecomeakeypartoftheeffortto

model the response of oceans to environmental

changes ( 3 – 6 ). Part of the difficulty lies in the

constant recirculation of plankton communi-

ties by ocean currents ( 7 ), along which many

physical, chemical, and biological processes—

theso-calledseascape( 8 )—modify community

composition ( 9 ). Recent planetary-scale ocean

sampling expeditions have revealed that eu-

karyotic plankton are taxonomically and ecolog-

ically extremely diverse, possibly even more

so than prokaryotic plankton ( 10 ). Eukaryotic

plankton cover an exceptional range of sizes,

from picosized (0.2 to 2mm) to mesosized (0.2

to 20 mm) organisms and larger, and ecological

functions, including phototrophy (e.g., Bacillario-

phyta), phagotrophy (e.g., Ciliophora), mixotrophy

(e.g., Dinophyceae), parasitism (e.g., marine al-

veolates), grazing (e.g., copepods), and filter

feeding (e.g., tunicates). How these differences

in body size and ecological function modu-

late the influence of oceanic currents and local

environmental conditions on geographic dis-

tributions is poorly known ( 11 – 13 ).

In this research, we studied plankton bio-

geography across all major eukaryotic groups

in the sunlit ocean by using 18S-V9 ribosomal

DNA (rDNA) metabarcoding data from the

TaraOceans global survey [including recently

released data from the Arctic Ocean ( 14 )]. The

data encompass 250,057 eukaryotic operational

taxonomic units (OTUs) that were sampled

at the surface and at the deep chlorophyll max-

imum (DCM) across 129 stations. We use a

probabilistic model that allows identification

of sets of OTUs that tend to co-occur across

samples, which we coin“assemblages”( 15 , 16 );

see materials and methods ( 17 ). A given OTU

may belong to several assemblages, and each

local community (i.e., the set of OTUs found in

a given station) can be seen as a sample drawn

in various proportions from the assemblages.

Across theTaraOceans samples and consid-

ering all eukaryotic OTUs together, we identi-

fied 16 geographically structured assemblages,

each composed of OTUs that cover the full

taxonomic range of eukaryotic plankton (Fig.

1, figs. S1 to S4, and supplementary text S1).

Local planktonic communities often cannot

be assigned to a single assemblage, as would

be typical for terrestrial macro-organisms on

a fixed landscape ( 18 , 19 ), but are instead mix-

turesofassemblages(Fig.1A).Thisisconsistent

with previous findings that suggest that neigh-

boring plankton communities are continuously

mixed and dispersed by currents ( 9 , 13 ).

In addition to the global biogeography rep-

resented in Fig. 1, we investigated the biogeog-

raphy of the 70 most-diversified deep-branching

groups of eukaryotic plankton by fitting our

probabilistic assemblage model separately to

each group (Fig. 2; figs. S5 and S6, A to C; and

594 29 OCTOBER 2021•VOL 374 ISSUE 6567 science.orgSCIENCE

(^1) Institut de Biologie de l’École Normale Supérieure (IBENS),
École Normale Supérieure, CNRS, INSERM, Université PSL,
75005 Paris, France.^2 Department of Computing, University
of Turku, Yliopistonmäki, 20014 Turku, Finland.^3 Stazione
Zoologica Anton Dohrn, Villa Comunale, 80121 Naples, Italy.
*Corresponding author. Email: [email protected] (G.S.-K.);
[email protected] (H.M.)
†Present address: CEA, DAM–Île de France (DIF), 91297 Arpajon,
France.
‡Present address: Universidad de Buenos Aires, CONICET, Centro
de Investigaciones del Mar y la Atmósfera (CIMA), C1428EGA
Buenos Aires, Argentina.
RESEARCH