Learning From Genomes: Comparative Genomic Approaches to Investigate Thylakoid Emergence in Cyanobacteria

The increasing availability of cyanobacterial genomes and metagenome-assembled genomes provides new opportunities to investigate the evolutionary history of cellular processes. However, reconstructing these events requires integrating complementary comparative genomic approaches while carefully balancing genome quality, phylogenetic diversity, dataset size, and computational constraints. In particular, dataset composition influences the types of evolutionary patterns that can be detected: dense sampling of closely related cyanobacteria improves within-group resolution, whereas broader phylogenetic sampling is important to identify deeper evolutionary signals and potential horizontal gene transfers.
Here, we describe a comparative genomic workflow combining curated genome selection, orthologous group inference, phylogenomics, taxonomic distribution analyses, and structural prediction. Orthologous groups were first inferred from a representative set of high-quality genomes selected to capture Terrabacteria diversity while maintaining computational tractability. The orthologous sequences of Cyanobacteria present in these groups were then used to build profile Hidden Markov Models with HMMER to identify orthologous proteins in a broader cyanobacteria-enriched genomic dataset.
We illustrate this approach through two examples related to the emergence of thylakoid-associated traits: photosystem II assembly factors and proteins involved in membrane dynamics (Hambücken et al., 2026b). These examples show how complementary bioinformatic analyses can be used to explore the conservation of photosynthetic processes, lineage-specific innovations, and candidate proteins potentially associated with thylakoid membrane evolution. Overall, this presentation provides an overview of the methodological choices, practical limitations, and evolutionary questions that can be addressed using comparative genomics in cyanobacteria.