Background: To fully exploit the potential of microalgae as commercial green hosts, the scientific
community has to improve their understanding of these organisms from a systems biology perspective.
Compared to other model organisms, our genomic knowledge of the microalgae model species
Chlamydomonas reinhardtii is very limited. Currently, almost 90% of the functional annotated
proteins of C. reinhardtii and of other microalgal proteins are homologs of Arabidopsis thaliana
proteins, which suggests that for the most part only the metabolic core conserved between these
species is properly annotated.
Objective: This review highlights how proteins outside of this core can be annotated by applying
publically available tools and methods. These include the use of novel state-of-the-art prediction tools,
combinations of these tools, and the use of metabolic modeling-assisted functional annotation. Furthermore, we discuss
the need for data on the subcellular location of microalgal proteins. Finally, some remaining bottlenecks regarding
functional annotation of microalgal proteins are discussed.
Conclusion: We conclude that both large dry-lab and wet-lab efforts are required to generate reliable functional
annotations of microalgae.