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Copyright © 2008 Dufresne et al.; licensee BioMed Central Ltd. Unraveling the genomic mosaic of a ubiquitous genus of marine cyanobacteria 1Université Paris 6 and CNRS, UMR 7144, Station Biologique, 29682 Roscoff, France 2Université Rennes 1, UMR 6553 EcoBio, IFR90/FR2116, CAREN, 35042 Rennes, France 3Department of Biological Sciences, University of Warwick, Coventry CV4 7AL, UK 4Scripps Institution of Oceanography, UCSD, San Diego, CA 92093, USA 5Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW, Australia 2109 6Institut Pasteur, Dépt de Microbiologie, Unité des Cyanobactéries, URA 2172 CNRS, Paris, France 7Genoscope (CEA) and UMR 8030 CNRS-Genoscope-Université d'Evry, 91057 Evry, France 8J Craig Venter Institute, Rockville, MD 20850, USA 9The Interuniversity Institute for Marine Science, Hebrew University, Eilat 88103, Israel 10University of Freiburg, Faculty of Biology, D-79104 Freiburg, Germany Corresponding author.#Contributed equally. Alexis Dufresne: dufresne/at/sb-roscoff.fr; Martin Ostrowski: M.Ostrowski/at/warwick.ac.uk; David J Scanlan: D.J.Scanlan/at/warwick.ac.uk; Laurence Garczarek: garczarek/at/sb-roscoff.fr; Sophie Mazard: s.mazard/at/warwick.ac.uk; Brian P Palenik: bpalenik/at/ucsd.edu; Ian T Paulsen: ipaulsen/at/cbms.mq.edu.au; Nicole Tandeau de Marsac: ntmarsac/at/pasteur.fr; Patrick Wincker: pwincker/at/genoscope.cns.fr; Carole Dossat: cdossat/at/genoscope.cns.fr; Steve Ferriera: sferriera/at/jcvi.org; Justin Johnson: jjohnson/at/jcvi.org; Anton F Post: anton.post/at/huji.ac.il; Wolfgang R Hess: wolfgang.hess/at/biologie.uni-freiburg.de; Frédéric Partensky: partensky/at/sb-roscoff.fr Received March 7, 2008; Revised May 17, 2008; Accepted May 28, 2008. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article has been cited by other articles in PMC.Abstract Background The picocyanobacterial genus Synechococcus occurs over wide oceanic expanses, having colonized most available niches in the photic zone. Large scale distribution patterns of the different Synechococcus clades (based on 16S rRNA gene markers) suggest the occurrence of two major lifestyles ('opportunists'/'specialists'), corresponding to two distinct broad habitats ('coastal'/'open ocean'). Yet, the genetic basis of niche partitioning is still poorly understood in this ecologically important group. Results Here, we compare the genomes of 11 marine Synechococcus isolates, representing 10 distinct lineages. Phylogenies inferred from the core genome allowed us to refine the taxonomic relationships between clades by revealing a clear dichotomy within the main subcluster, reminiscent of the two aforementioned lifestyles. Genome size is strongly correlated with the cumulative lengths of hypervariable regions (or 'islands'). One of these, encompassing most genes encoding the light-harvesting phycobilisome rod complexes, is involved in adaptation to changes in light quality and has clearly been transferred between members of different Synechococcus lineages. Furthermore, we observed that two strains (RS9917 and WH5701) that have similar pigmentation and physiology have an unusually high number of genes in common, given their phylogenetic distance. Conclusion We propose that while members of a given marine Synechococcus lineage may have the same broad geographical distribution, local niche occupancy is facilitated by lateral gene transfers, a process in which genomic islands play a key role as a repository for transferred genes. Our work also highlights the need for developing picocyanobacterial systematics based on genome-derived parameters combined with ecological and physiological data. Background Unicellular picocyanobacteria of the genera Synechococcus and Prochlorococcus contribute significantly to global oceanic chlorophyll biomass and primary production and play an important role in biogeochemical cycles [1-3]. Despite their close phylogenetic relatedness, these two groups differ markedly in their light-harvesting apparatus and nutrient physiology and, thus, ecological performance [4]. Synechococcus is ubiquitous, since cells of this genus are found in estuarine, coastal or offshore waters over a large range of latitudes [5,6], whereas Prochlorococcus is confined to warm (45°N-40°S) and mostly nutrient-poor oceanic areas [7-9]. Genetically distinct clades displaying different vertical depth distributions occur in the latter genus, explaining its wider vertical distribution in oceanic waters relative to Synechococcus [10]. These high light- (HL) and low light- (LL) adapted clades have been further subdivided into at least six ecotypes exhibiting distinct light and/or temperature optima as well as distributions in the field [11]. In Synechococcus, at least 10 [12], and as many as 16 [13-15], clades have been defined based on different phylogenetic markers and physiological characteristics [16]. For several of these clades, distinct broad spatial and seasonal distribution patterns have been described, mainly over horizontal scales [17-19]. Some clades are confined to high latitude, temperate waters (for example, clades I and IV), while others preferentially thrive at lower latitudes in warm, permanently stratified oceanic waters (for example, clades II and III [19-21]). Examination of the relationships between ecology, gene content and genome structure in the Prochlorococcus genus has revealed evidence for drastic genome reduction in several Prochlorococcus clades [22,23], a process clearly started prior to the differentiation of HL and LL clades [24]. This sequential loss of genes, including some involved in nutrient uptake or photosynthesis, appears to have affected HL and LL clades differently, since HL isolates share 95 clade-specific genes and LL isolates 48 [23]. Pair-wise comparison of two closely related Prochlorococcus isolates (MED4 and MIT9312) revealed that gene losses are partially compensated by gains from lateral gene transfer (LGT) events [25]. Many of these horizontally acquired genes were found to be located in highly variable genomic regions or 'islands'. More generally, it seems that much of the genomic diversity between Prochlorococcus isolates occurs in 'the leaves of the tree', that is, between the most closely related strains, and that gene islands are important in maintaining this diversity as reservoirs for laterally transferred genes [23]. Less is known about the extent and causes of genome diversity in marine Synechococcus. Strain WH8102 was also shown to possess genomic regions comparable to 'pathogenicity islands' and containing many glycosyltransferases [26]. A pair-wise comparison between this oligotrophic strain and a coastal isolate (CC9311) showed that LGT may have an important role in niche differentiation in this group, for example, by allowing acquisition of novel metal utilization capacity [27]. With the aim of further understanding the evolutionary processes driving genome divergence and niche adaptation in marine Synechococcus, we obtained sequences of nine additional genomes. By comparing them alongside three representative Prochlorococcus genomes, we calculated the relative sizes of the core and accessory genomes, estimated the importance and relative contribution of vertical inheritance and LGT for the core and accessory gene complements and examined the distributions of accessory genes with regard to genomic islands. In so doing, we identified a major influence of these islands in genome flexibility and found evidence that at least one of them plays a major role in colonization of new light niches. Moreover, by exploring the picocyanobacterial species concept, through study of the relationships between ribotype and genome diversity, we significantly advance our understanding of the phylogeny and evolution of this major group of marine photosynthetic prokaryotes. Results and discussion General features of the Synechococcus genomes The 11 Synechococcus strains analyzed here include isolates from the Mediterranean Sea, the Red Sea, and the Pacific and Atlantic Oceans (Table 1). This set of strains covers nine of the ten clades defined by Fuller and co-workers [12] in marine sub-cluster 5.1, and also includes one sub-cluster 5.2 representative, the euryhaline, phycocyanin-rich strain WH5701. Though some of these genomes are incomplete, the estimated genome coverage is above 99.8% and, therefore, only a few genes are potentially missing, making global genome comparisons legitimate. Genomes range in size from 2.22 to approximately 2.86 Mbp and GC contents vary from 52.5% to 66.0%. This relatively small range of variation in genome characteristics is strikingly different from that observed in the Prochlorococcus genus, in which genome size varies between 1.64 and 2.68 Mbp, whilst GC content varies between 30.8% and 50.7% [23]. This observation suggests that, in sharp contrast to what has occurred in Prochlorococcus [22,24], no extensive genome streamlining, concomitant with a drop in GC content, has occurred during the evolution of Synechococcus.
Core genome As a framework for comparative analyses and annotation, we constructed clusters of protein-coding genes for the 14 genomes analyzed in this study. From a set of 35,946 protein-coding genes, 7,826 distinct groups of homologous proteins were identified. The estimated core genome of marine Synechococcus is composed of 1,572 gene families (Figure (Figure1a)1a
Only 70 gene families of the marine Synechococcus core genome are not present in any of the three Prochlorococcus genomes, including 23 linked to photosynthesis (Additional data file 1). Among these, there are nine gene families encoding allophycocyanin and phycocyanin components, which are shared with freshwater cyanobacteria [29]. Indeed, Prochlorococcus have lost all phycobilisome genes except those encoding phycoerythrin, with LL ecotypes having kept many of the latter genes and HL ecotypes only a few [30,31]. The RubisCo gene region includes three genes involved in low affinity carbon transport (ndhD4, ndhF4 and chpX homologs) that are missing in Prochlorococcus, confirming earlier results on a limited set of picocyanobacterial genomes [32]. Also notable in this Synechococcus-specific set are ftrC and ftrV, two genes encoding subunits of ferredoxin:thioredoxin reductase, an enzyme involved in a redox system between thioredoxin and ferredoxin [33]. All Synechococcus also have one gene coding for a thioredoxin and another for a [2Fe-2S] ferredoxin that have no orthologs in Prochlorococcus and it is tempting to speculate that their products might specifically be involved in the interaction with ferredoxin:thioredoxin reductase. This system could ensure the regulation by light of photosynthetic CO2 assimilation enzymes, a capacity that could have been lost (or evolved into a less iron-dependent form) in Prochlorococcus. Accessory genome and gene islands The accessory genome of marine Synechococcus comprises a fairly constant number (748 ± 85) of genes shared by 2-10 genomes (Additional data file 2). Among the most notable genes are isiA and isiB (encoding the photosystem I-associated antenna protein CP43' and the soluble electron transport protein flavodoxin, respectively), which are systematically found associated in an iron-stress inducible operon in freshwater cyanobacteria but which in marine Synechococcus are found separated and present in only four strains (BL107, CC9311, CC9605 and CC9902). The absence of these genes in the oligotrophic strain WH8102 is particularly surprising, given their potential importance in the adaptation to low iron environments [34,35]. Interestingly, the four aforementioned Synechococcus strains also have a specific ferredoxin gene (among four to five gene copies in total) and it is possible, therefore, that this form is functionally interchangeable with flavodoxin, when cells are shifted from an iron-replete to an iron-limited environment [36]. The number of unique genes - that is, genes specific to one genome - is much more variable (91-845; Figure Figure1a).1a
Island size and position are very variable among genomes (Additional data file 3), except for the closely related strains BL107 and CC9902 (Figure (Figure2a),2a Gene composition of islands is also highly variable among Synechococcus genomes. A high percentage (37-79%) of island genes are shared by several genomes (though this is most often a small subset of the 11 genomes), suggesting that many genes acquired by LGT are maintained over time periods long enough to be disseminated within the host clade and eventually to more recently diverged Synechococcus lineages. The high variability of gene composition in these genomic regions is further demonstrated by comparing Synechococcus genomes with the Global Ocean Sampling (GOS) expedition database [37]. Environmental sequences from oceanic areas showed highest similarity to the WH8102 and CC9605 genomes whereas sequences from a hypersaline lagoon were most similar to RS9917. For all three genomes, there was generally a low recruitment of environmental sequences to island regions (Figure (Figure3),3 Altogether, our data suggest that, like for Prochlorococcus [23], genomic islands have a key role in the variability of Synechococcus genome sizes (and, therefore, their diversity), acting as a repository for novel genes. Those genes providing a sufficient selective advantage can be kept long term while others are more or less rapidly eliminated, depending on their effect on cell fitness. However, the underlying mechanism leading to preferential insertion of laterally transferred genes into these regions still needs to be elucidated. Function of island genes Most island genes (60-78%) cannot be assigned to functional categories based on homology. Among island genes with known function (Additional data file 5), the predominant category comprises members of the glycosyltransferases and glycoside hydrolase gene families, potentially involved in outer membrane or cell wall biogenesis. As suggested previously [26,27], they may have a key role in grazer and phage avoidance. Other major categories include genes encoding enzymes involved in carbohydrate modification, ABC transport, mobility of DNA (for example, phage integrases and transposases) or transcriptional regulators (Additional data file 5). Also, putative genes of unusually large size (ranging from 5,016-84,534 bp), so-called 'giant open reading frames'; highlighted in blue in Figure Figure33 In a recent study, we described a region that gathers most genes encoding phycobilisome rod components (Figure (Figure44
Phylogenomics of marine picocyanobacteria The availability of numerous complete genomes of marine picocyanobacteria allowed us to refine the phylogenetic relationships between members of this group. An unrooted distance tree using 1,129 concatenated alignments of core proteins is shown in Figure Figure4a.4a Although Figure Figure4a4a
Phyletic patterns In order to analyze the relationships between phylogeny based on protein sequences and genome composition further, we constructed a phylogenetic network based on shared gene content (Figure (Figure6a).6a
Towards a better systematics of marine picocyanobacteria The availability of numerous complete genome sequences of marine picocyanobacteria provides an opportunity to compare ribotype diversity with protein-coding gene diversity and test the applicability of the bacterial species concept for this set of strains. Although 16S rRNA gene identity is greater than 95.5% across the Synechococcus group, the average nucleotide identity (ANI) of genes shared between every pair of genomes is significantly lower than the threshold value of approximately 94%, which, according to Konstantinidis and Tiedje [44], is equivalent to the currently accepted species threshold of 70% DNA-DNA hybridization [45]. Indeed, when considering the picocyanobacterial core proteins, the ANI value ranges from 65.7% between CC9902 (or BL107, clade IV) and RCC307 (clade X) up to only 91.3% between strains BL107 and CC9902 (both clade IV), though the latter strains have identical 16S rRNA gene sequences (Figure (Figure7).7
It is important to note that neither ANI nor 16S rRNA gene sequence identity make it possible to completely resolve the Prochlorococcus and Synechococcus genera from one another. As a result of their biased GC content and accelerated evolution [22,24,48], Prochlorococcus strains with streamlined genomes (SS120 and MED4) fall well apart from Synechococcus spp., with ANI values generally below 65% (Figure (Figure7).7 Ecological implications The distribution and relative abundance of sub-cluster 5.1 clades in the natural environment suggests the existence of two major lifestyle strategies for marine Synechococcus: 'open ocean/specialists' that dominate in warm-oligotrophic or temperate/polar-mesotrophic waters; and 'coastal/opportunists' that can be found either in coastal areas or across a broad range of ecosystems in relatively low numbers, but occasionally reaching higher numbers in the vicinity of upwelling areas or following environmental perturbations [21]. The newly proposed sub-groups A and B within sub-cluster 5.1 may reflect this dichotomy and correspond to ecologically coherent groups. Separation between these two lifestyles, reminiscent of the distinction between HL and LL Prochlorococcus clades [10], could have occurred early in the evolutionary history of marine Synechococcus. The partition of these two 'eco-groups' is further supported by the number of genes encoding two-component system histidine kinases and response regulators. Synechococcus clades II, III, IV ( sub-group A), which are prevalent in open-ocean waters, exhibit characteristically low numbers of regulatory systems (Figure (Figure8).8
Conclusion Comparative genomics on a large set of Synechococcus isolates allowed us to precisely define the core genome and enlightened us to the considerable flexibility of the accessory genome in this group, which is due in large part to a highly variable number of unique genes, preferentially located in islands. The large genomic and physiological diversity occurring between and within current Synechococcus 'clades' [12-15] suggests the use of smaller, ecologically distinct fundamental units (that is, 'species' or 'ecotypes') for evaluating taxonomic diversity within this group. Since the identification of populations of marine Synechococcus adapted to different ecological niches is now relatively well advanced [12,18,19,21,22,51], the incorporation of such ecological data, together with robust DNA sequence clusters resulting from genome comparisons of cultured strains and of environmental isolates, will undoubtedly make it possible to establish an ecologically meaningful systematics for marine picocyanobacteria. Even though the distribution of Synechococcus clades within broad habitats (that is, over large spatial or temporal scales) can be defined using core gene markers, for example, the 16S rRNA gene [19,21] or rpoC1 gene [17], adaptation to narrow ecological niches (that is, at local scales) is most likely made possible by the flexibility and/or diversity of the accessory genome. The most obvious illustration of this is the absence of congruence between cell pigmentation and phylogeny that can be related to lateral transfer between Synechococcus lineages of the gene region encoding phycobilisome rod components. Thus, horizontal transfer of novel genes (or homologs of existing genes) within genomic islands appears to be a key mechanism for acquiring novel phenotypes and ecological functions. The apparently high turnover of many of these laterally transferred genes increases the probability that they may be useful for cells to adapt to local environmental conditions. Materials and methods Sequencing, assembly and genome annotation Whole genome sequencing was performed, starting from DNA of axenic strains or strains with low bacterial contamination, either by the Genoscope for Synechococcus spp. WH7803 and RCC307, by the J Craig Venter Institute for WH7805, BL107, RS9916, RS9917 and WH5701, or by the Joint Genome Institute for CC9902 and CC9605, according to the standard protocols used by these different sequencing centers [23,48]. The genome sequences reported in this paper have been deposited in the GenBank database. Delineation of protein families Protein families were delineated using all-against-all BLASTp comparison [52] and the TRIBEMCL clustering algorithm [53] with an e-value threshold of 10-12. Open reading frames encoding proteins smaller than 100 amino acids were compared against the whole protein set using a less stringent threshold (10-5) and those with significant hits were added to protein families. A number of missing genes were added to the data set by searching intergenic regions with TBLASTN [52] against the whole proteome of the 14 genomes and then against the NCBI non-redundant protein database. An in-house database system (Cyanorak), accessible to all annotators through a web front-end, was set up to manually refine the annotation of protein families. A read-only version of this database is publicly accessible [54]. Determination of islands In a previous study [25], islands were identified by breaks in synteny in closely related Prochlorococcus. However, this approach was not applicable for the strains analyzed here, due to the simultaneous comparison of multiple genomes and a high background of numerous genomic rearrangements that interrupt synteny. Instead, we used methods modified from Hsiao and co-workers [55] and Rusch and co-workers [56] that were less dependent on genome comparisons. Briefly, gene islands of ≥ 6 genes were suggested by deviation in tetranucleotide frequency greater than 1 standard deviation in the 1st principal component as compared to the genome average. The borders of individual islands were determined with the aid of: proximity of mobility genes (that is, insertion sequence elements or phage integrases) or tRNA genes; and/or the occurrence of blocks of core genes. Finally, a few contiguous blocks of unique and accessory genes that did not display significant deviation in tetranucleotide frequency were manually added to the predicted set of islands for several genomes. Phylogenetic analysis Phylogenetic reconstructions were based on manually aligned full-length 16S rRNA gene sequences using previous alignments [12]. Where possible, 16S rRNA gene sequences were obtained from complete or draft genome sequences, otherwise they were assembled from whole genome shotgun (WGS) sequence reads using Phred, Phrap and Consed [57]. For the 16S rRNA gene phylogenies, the confidence of branch points was determined by three separate analyses (NJ, ML and maximum parsimony), with multifurcations indicating branch points that were collapsed until supported in a majority of analyses. Core protein families containing only one gene copy per genome (1,129 families) were used to make a refined analysis of the phylogeny of marine picocyanobacteria. Amino acid sequences were aligned using MUSCLE [58] with default parameters. After exclusion of ambiguously aligned regions with Gblocks [59], individual alignments were concatenated in one super-alignment of 307,757 amino acid sites. ML pairwise distances between sequences of the super-alignment were computed with TREE-PUZZLE 5.2 [60] using the JTT model of amino acid substitution and a gamma distribution parameter alpha of 0.34 (estimated from data set). A least-square tree was constructed from the distance matrix using the Fitch program of the Phylip package [61]. Parsimony and ML trees were constructed with Protpars [61] and TREE-PUZZLE, respectively. Bootstrap analyses were performed by sampling 1% of the sites of the original super-alignment to produce 100 alignments of 3,007 positions with the SeqBoot program [61]. Distance, parsimony and ML trees were also constructed for individual alignments of protein families. For ML trees, we used the PhyML program [62] using the JTT model and an alpha parameter estimated from the data set. A majority rule consensus tree was constructed from these individual trees with the Consense program [61]. Gene content phylogeny was built with the phyletic distribution of sequences in orthologous clusters, using genes shared between 2-13 genomes, with the ML estimator of Huson and Steel [63] and bootstrapping of 100 replicates as implemented in SplitsTree 4.8. Analysis of bipartition spectra was used to detect transfer and replacement of orthologous genes in lineages of marine Synechococcus and in Prochlorococcus sp. MIT9313. A bipartition corresponds to the splitting of a phylogenetic tree in two parts linked by a single internal branch. ML trees (100 replicates) were built using the PhyML program [62] for 1,317 families of 12 protein-coding genes (that is, excluding P. marinus MED4 and SS120). A consensus tree was built with the Consense program from the 1,317 ML trees. Bipartitions supported with 70% or higher bootstrap values were extracted from the set of phylogenetic trees. The method of detection of horizontally transferred genes is based on the identification of protein families showing one or more bipartitions that conflict significantly with plurality bipartitions of the consensus tree. Average nucleotide identity between orthologous genes Pairwise ANI was calculated across the entire genome, as described by Konstantinidis and Tiedje [44], resulting in a majority of values clustered in a narrow band between 70% and 73%. An additional, unrestrained estimate of ANI was calculated across the conserved core component of each genome, with gene families containing paralogs ignored and the minimum blast percentage identity threshold (60%) removed, to provide an alternative estimate of the sequence divergence of this more restricted set of conserved orthologues. Abbreviations ANI, average nucleotide identity; GOS, Global Ocean Sampling; HL, high light; LGT, lateral gene transfer; LL, low light; ML, maximum likelihood; NJ, neighbor joining; WGS, whole genome shotgun. Authors' contributions AD, MO, DJS and FP conceived the study. They also wrote the paper together with LG, NT, BPP, AFP and WRH. MO, SM and BPP grew cultures and provided the DNA used to sequence the nine unpublished Synechococcus strains described in this study. PW, CD, JJ and SF worked on the sequencing and/or assembly of, altogether, seven strains, and DJS, FP and BPP coordinated their manual genome annotation. AD performed the clustering of orthologous proteins and set-up a web site for annotating these clusters. AD, MO, DJS, LG, SM, BPP, ITP, NT, AFP, WRH and FP contributed to manual annotation of these protein families. AD and MO did most of the bioinformatic and phylogenetic analyses. All authors read and approved the final manuscript. Additional data files The following additional data files are available with the online version of this paper. Additional data file 1 is a table listing the 70 Synechococcus-specific genes. Additional data file 2 is a table listing all accessory protein families found in 2-10 Synechococcus strains, including the 61 families shared only by the euryhaline Synechococcus spp. strains WH5701 and RS9917. Additional data file 3 shows genome plots of recently acquired islands in the nine genomes not shown in Figures Figures22 Additional data file 2 All accessory protein families found in 2-10 Synechococcus strains, including the 61 families shared only by the euryhaline Synechococcus spp. strains WH5701 and RS9917. Click here for file(77K, pdf) Additional data file 3 Genomes have been re-aligned so that they all start at dnaN. For other details, see the legend of Figure Figure33 Click here for file(7.1M, pdf) Additional data file 4 Core genome segments surrounding the islands are connected by yellow shading. Genes shared specifically by Synechococcus spp. WH7803 and CC9902 are connected by gray shading. Click here for file(220K, pdf) Additional data file 5 Island coordinates and island gene composition in the 14 genomes of marine picocyanobacteria used in this study. Click here for file(122K, pdf) Additional data file 6 NJ tree based on concatenated alignment of the core genome rooted with the freshwater cyanobacterium Synechocystis sp. PCC6803 (863 proteins, 263,424 amino acid positions, gene families with paralogs excluded). Click here for file(171K, pdf) Additional data file 7 The 122 core protein families showing a phylogeny divergent from the consensus core protein distance tree shown in Figure Figure4a4a Click here for file(13K, pdf) Additional data file 8 This enzyme is part of the GS/GOGAT pathway, which is involved in the assimilation of NH4+. This tree suggests at least two transfers between clades III and V (represented by WH7803 and WH8102, respectively) and between clades II and X (represented by RS9916 and CC9605, respectively). Click here for file(20K, pdf) Acknowledgements This work was supported by the European Network of Excellence Marine Genomics Europe (AD, DJS, LG, WRH, AFP and FP), the French ANR program 'PhycoSyn' ANR-05-BLAN-0122-01 (FP, LG), the 'Consortium National de Recherche en Génomique' (PW, CD), NERC grants NE/C000536/1 and NE/D003385/1 (DJS), ISF grant 135/05 and the Gruss-Lipper Fund, MBL Woods Hole (AFP), NSF grants EF0333162 and MCB0731771 (BP, ITP) and the BMBF-Freiburg Initiative in Systems Biology (WRH). We acknowledge support from the Gordon and Betty Moore Foundation, as part of its Marine Microbial Sequencing Project (leader, Robert Friedman). We also thank the JCVI software team (leader, Saul A Kravitz) and the JCVI Joint Technology Center (leader, Yu-Hui Rogers) and the sequencing and bioinformatics teams of the JGI. We thank Ouest-Genopole for use of its bioinformatics platform. Bernard Henrissat is kindly acknowledged for checking annotation of genes encoding carbohydrate-active enzymes, Erwan Corre for help with bioinformatics and Priscillia Gourvil and Florence Le Gall for help with culturing and taking care of the Roscoff Culture Collection. References
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