Lachlan McKinnie1, Scott Cummins1, Min Zhao1
1Seaweed Research Group, University of the Sunshine Coast, Maroochydore DC, 4558, Queensland, Australia
Red seaweed natural products and secondary metabolites are quickly becoming highly sought after materials. However, there is a dearth of knowledge on red algal metabolic pathways, and very few functionally annotated red algal genomes or transcriptomes compared to other organisms. To remedy this, a “multi-omics” database consisting of 29 genomes and 29 transcriptomes was created with organisms from 32 species over all 7 classes of red algae. This database contains genome and transcriptome assemblies, BUSCO analyses, custom repeat libraries, deduced protein sequences, orthogroups, phylogenetic trees, gene duplication predictions, and functional annotation.
Using this database, over 200 metabolic pathways were investigated. Core metabolic pathways such as the MEP, C10-C20 isoprenoid biosynthesis, and C3 photosynthetic pathways were conserved across all algae, while known fungal and bacterial secondary metabolite biosynthesis pathways were absent. Notably, complete CAM and C4 photosynthetic pathways were detected in 74.2 and 51.6% of macroalgal sequences, respectively, but only in 3.7% for both pathways in microalgae, implying a potential reduction of genes across microalgae relative to macroalgae. These results suggest the conserved evolution of core metabolic pathways, but missing genes across microalgae, corresponding with different evolutionary paths.
In summary, we created a database of functionally annotated red algal genomes and transcriptomes, larger and more comprehensive than any database currently publicly available. Using this database, we were able to perform a comprehensive in silico investigation of red algal metabolic pathways. We envision that this database and metabolic pathway data will be a strong and comprehensive resource for future algal research.
Biography
ORCiD: Lachlan McKinnie 0000-0002-4996-5941, Scott Cummins 0000-0002-1454-2076, Min Zhao 0000-0001-5498-3434