PNNL

Abstract

The ability to detect regulatory elements within genome sequences is important in understanding how gene expression is controlled in biological systems. In this work, we combine microarray data analysis with genome sequence analysis to predict DNA sequences in the photosynthetic bacterium Rhodobacter sphaeroides that bind the regulators PrrA, PpsR and FnrL. These predictions were made by using hierarchical clustering to detect genes that share similar expression patterns. The DNA sequences upstream of these genes were then searched for possible transcription factor recognition motifs that may be involved in their co-regulation. The approach used promises to be widely applicable for the prediction of cis-acting DNA binding elements. Using this method we were independently able to detect and extend the previously described consensus sequences that have been suggested to bind FnrL and PpsR. In addition we have predicted sequences that may be recognized by the global regulator PrrA. Our results support the earlier suggestions that the DNA binding sequence of PrrA may have a variable sized gap between its conserved block elements. Using the predicted DNA binding sequences, we have performed a whole genome scale analysis to determine the relative importance of the interplay between these three regulators PpsR, FnrL and PrrA. Results of this analysis showed that, compared to the regulation by PpsR and FnrL, a much larger number of genes are candidates to be regulated by PrrA. Our study demonstrates by example that integration of multiple data types can be a powerful approach for inferring transcriptional regulatory patterns in microbial systems, and it allowed us to detect the photosynthesis related regulatory patterns in R. sphaeroides.