Background: Brown algae belong to the Stramenopiles phylum and are phylogenetically distant from plants and other multicellular organisms. This independent evolutionary history has shaped brown algae with numerous metabolic characteristics specific to this group, including the synthesis of peculiar polysaccharides contained in their extracellular matrix (ECM). Alginates and fucose-containing sulphated polysaccharides (FCSP), the latter including fucans, are the main components of ECMs. However, the metabolic pathways of these polysaccharides remain poorly described due to a lack of genomic data. Results: An extensive genomic dataset has been recently released for brown algae and their close sister species. We performed an expert annotation of key genes involved in ECM-carbohydrate metabolisms, combined with comparative genomics, phylogenetics analyses, and protein modelling. Our analysis indicates that the gene families involved in both the synthesis and degradation of alginate were acquired by the common ancestor of brown algae and their closest sister species Schizocladia ischiensis, and subsequently expanded in brown algae. The pathway for the biosynthesis of fucans still remains biochemically unresolved and we also identify the most likely fucosyltransferase genes that may harbour a fucan synthase activity in brown algae. Conclusions: The expansion of specific families related to alginate metabolism may have represented an important prerequisite for the evolution of developmental complexity in brown algae. Our analysis questions the possible occurrence of FCSPs outside brown algae, notably within their closest sister taxon and in other Stramenopiles such as diatoms. Filling this knowledge gap in the future will help determine the origin and evolutionary history of fucan synthesis in eukaryotes. Access to the present large genomic resource allowed us to identify putative glycosyltransferases (GTs) involved in fucan synthesis and elongation, and members of the GT23 family appear to be very interesting candidates for functional validation.