Bioinformatic inference of specific and general transcription factor binding sites in the plant pathogen Phytophthora infestans. - Michael F Seidl (Public Library of Science (PLoS), 2012)
Plant infection by oomycete pathogens is a complex process. It requires precise expression of a plethora of genes in the pathogen that contribute to a successful interaction with the host. Whereas much effort has been made to uncover the molecular systems underlying this infection process, mechanisms of transcriptional regulation of the genes involved remain largely unknown. We performed the first systematic de-novo DNA motif discovery analysis in Phytophthora. To this end, we utilized the genome sequence of the late blight pathogen Phytophthora infestans and two related Phytophthora species (P. ramorum and P. sojae), as well as genome-wide in planta gene expression data to systematically predict 19 conserved DNA motifs. This catalog describes common eukaryotic promoter elements whose functionality is supported by the presence of orthologs of known general transcription factors. Together with strong functional enrichment of the common promoter elements towards effector genes involved in pathogenicity, we obtained a new and expanded picture of the promoter structure in P. infestans. More intriguingly, we identified specific DNA motifs that are either highly abundant or whose presence is significantly correlated with gene expression levels during infection. Several of these motifs are observed upstream of genes encoding transporters, RXLR effectors, but also transcriptional regulators. Motifs that are observed upstream of known pathogenicity-related genes are potentially important binding sites for transcription factors. Our analyses add substantial knowledge to the as of yet virtually unexplored question regarding general and specific gene regulation in this important class of pathogens. We propose hypotheses on the effects of cis-regulatory motifs on the gene regulation of pathogenicity-related genes and pinpoint motifs that are prime targets for further experimental validation.