Brown algae (Phaeophyceae) are complex photosynthetic organisms with a very different evolutionary history to green plants, to which they are only distantly related¹. These seaweeds are the dominant species in rocky coastal ecosystems and they exhibit many interesting adaptations to these, often harsh, environments. Brown algae are also one of only a small number of eukaryotic lineages that have evolved complex multicellularity (Fig. 1). We report the 214 million base pair (Mbp) genome sequence of the filamentous seaweed Ectocarpus siliculosus (Dillwyn) Lyngbye, a model organism for brown algae^2,3,4,5, closely related to the kelps^6,7 (Fig. 1). Genome features such as the presence of an extended set of light-harvesting and pigment biosynthesis genes and new metabolic processes such as halide metabolism help explain the ability of this organism to cope with the highly variable tidal environment. The evolution of multicellularity in this lineage is correlated with the presence of a rich array of signal transduction genes. Of particular interest is the presence of a family of receptor kinases, as the independent evolution of related molecules has been linked with the emergence of multicellularity in both the animal and green plant lineages. The Ectocarpus genome sequence represents an important step towards developing this organism as a model species, providing the possibility to combine genomic and genetic² approaches to explore these and other^4,5 aspects of brown algal biology further.

• Brown algal cell walls share some components with plants (cellulose) and animals (sulfated fucans), but they also contain some unique polysaccharides (alginates). Analysis of the Ectocarpus genome provides a unique opportunity to decipher the molecular bases of these crucial metabolisms. • An extensive bioinformatic census of the enzymes potentially involved in the biogenesis and remodeling of cellulose, alginate and fucans was performed, and completed by phylogenetic analyses of key enzymes. • The routes for the biosynthesis of cellulose, alginates and sulfated fucans were reconstructed. Surprisingly, known families of cellulases, expansins and alginate lyases are absent in Ectocarpus, suggesting the existence of novel mechanisms and/or proteins for cell wall expansion in brown algae. • Altogether, our data depict a complex evolutionary history for the main components of brown algal cell walls. Cellulose synthesis was inherited from the ancestral red algal endosymbiont, whereas the terminal steps for alginate biosynthesis were acquired by horizontal gene transfer from an Actinobacterium. This horizontal gene transfer event also contributed genes for hemicellulose biosynthesis. By contrast, the biosynthetic route for sulfated fucans is an ancestral pathway, conserved with animals. These findings shine a new light on the origin and evolution of cell wall polysaccharides in other Eukaryotes.

Red seaweeds are key components of coastal ecosystems and are economically important as food and as a source of gelling agents, but their genes and genomes have received little attention. Here we report the sequencing of the 105-Mbp genome of the florideophyte Chondrus crispus (Irish moss) and the annotation of the 9,606 genes. The genome features an unusual structure characterized by gene-dense regions surrounded by repeat-rich regions dominated by transposable elements. Despite its fairly large size, this genome shows features typical of compact genomes, e.g., on average only 0.3 introns per gene, short introns, low median distance between genes, small gene families, and no indication of large-scale genome duplication. The genome also gives insights into the metabolism of marine red algae and adaptations to the marine environment, including genes related to halogen metabolism, oxylipins, and multicellularity (microRNA processing and transcription factors). Particularly interesting are features related to carbohydrate metabolism, which include a minimalistic gene set for starch biosynthesis, the presence of cellulose synthases acquired before the primary endosymbiosis showing the polyphyly of cellulose synthesis in Archaeplastida, and cellulases absent in terrestrial plants as well as the occurrence of a mannosylglycerate synthase potentially originating from a marine bacterium. To explain the observations on genome structure and gene content, we propose an evolutionary scenario involving an ancestral red alga that was driven by early ecological forces to lose genes, introns, and intergenetic DNA; this loss was followed by an expansion of genome size as a consequence of activity of transposable elements.

Background: The heterokonts are a particularly interesting group of eukaryotic organisms; they include many key species of planktonic and coastal algae and several important pathogens. To understand the biology of these organisms, it is necessary to be able to predict the subcellular localisation of their proteins but this is not straightforward, particularly in photosynthetic heterokonts which possess a complex chloroplast, acquired as the result of a secondary endosymbiosis. This is because the bipartite target peptides that deliver proteins to these chloroplasts can be easily confused with the signal peptides of secreted proteins, causing currently available algorithms to make erroneous predictions. HECTAR, a subcellular targeting prediction method which takes into account the specific properties of heterokont proteins, has been developed to address this problem. Results: HECTAR is a statistical prediction method designed to assign proteins to five different categories of subcellular targeting: Signal peptides, type II signal anchors, chloroplast transit peptides, mitochondrion transit peptides and proteins which do not possess any N-terminal target peptide. The recognition rate of HECTAR is 96.3%, with Matthews correlation coefficients ranging from 0.67 to 0.95. The method is based on a hierarchical architecture which implements the divide and conquer approach to identify the different possible target peptides one at a time. At each node of the hierarchy, the most relevant outputs of various existing subcellular prediction methods are combined by a Support Vector Machine. Conclusion: The HECTAR method is able to predict the subcellular localisation of heterokont proteins with high accuracy. It also efficiently predicts the subcellular localisation of proteins from cryptophytes, a group that is phylogenetically close to the heterokonts. A variant of HECTAR, called HECTAR ^SEC , can be used to identify signal peptide and type II signal anchor sequences in proteins from any eukaryotic organism. Both HECTAR and HECTAR ^SEC are available as a web application at the following address: http://www.sb-roscoff.fr/hectar/.