PARENT SESSION
Posters P3D Genomic, proteomic and related technologies. Abstracts (720-730)

Co-evolution of photosynthetic genes in cyanobacteria. Tuo Shi^*,1, Thomas Bibby¹, Lin Jiang¹, Andrew Irwin¹, Paul Falkowski^{1, 2}, ¹ Environmental Biophysics and Molecular Ecology Program, Institute of Marine and Coastal Sciences, New Brunswick, New Jersey, USA² Department of Geological Sciences, Piscataway, New Jersey, USA

ABSTRACT- Unlike purple bacteria and heliobacteria, both of which have large and tightly linked photosynthesis gene clusters (superoperons) that are subject to co-transcription, most of the genes coding for photosynthetic components in cyanobacteria are distributed across the entire genome and constitutively expressed. The genomic organization in cyanobacteria exhibits characteristics similar to those of green sulfur and non-sulfur bacteria, whose photosynthetic genes are interspersed along the chromosome as a result of operon splitting. To explore the evolutionary constraints that might explain the differences in gene organization in photosynthetic prokaryotes, we analyzed 11 genomes of cyanobacteria for conservation in the linkage of photosynthetic genes. Based on a bioinformatic approach of co-evolutionary analysis, we detected significant correlations in the genetic distance matrices between proteins linked in conserved gene order, and interacting partners coordinating the cofactors involved in photosynthetic electron transport. Our results suggest the tempo of evolution of photosynthetic genes is constrained by protein interactions that are critical for energy transduction, primary charge separation, and electron transport. This analysis leads to a very conservative mutation rate of photosynthetic genes retained in the chloroplasts. We hypothesize that physical constraints reduce the tempo of evolution for interacting proteins, and hence act as a selection pressure governing the conservation of genome landscape in oxygenic photosynthesis.

KEY WORDS: co-evolution, photosynthesis, protein interactions, bioinformatics