Classifying and Predicting Photosynthetic Gene Fragments from the Environment

Cyanobacteria of the genera Synechococcus and Prochlorococcus play a key role in marine photosynthesis that contributes to the global carbon cycle and to the world oxygen supply. Recently, genes (psbA-encoding the D1 protein, psbDencoding the D2 protein and others) that encode the photosystem II (PSII) reaction centre were found in cyanophage genomes. This phenomenon suggested that horizontal transfer and possible recombination of psbA genes between Prochlorococcus and Synechococcus was achieved via phage intermediates. Gaining of the psbA gene could be very valuable for the phage survival. The transcription and activation of phage psbA gene during the infection period helps to maintain photosynthetic activity in the host after the shutdown of host protein synthesis. Coupling genomic data extracted directly from the environment to its species origin is necessary for better understanding of phage-host relationship and coevolution. Looking for a prediction solution, we developed a computational approach, combining Support Vector Machine (SVM) with position specific scoring matrix (PSSM), which successfully classifies different psbA fragments coming directly from the ocean. The method combines two basic feature levels: the DNA oligonucleotide composition and the amino acid codon usage. Finally, we confirm our results applying an unsupervised PCA (Principal Component Analysis) method.