Identification of putative transcriptional regulatory networks in Entamoeba histolytica using Bayesian inference.

ABSTRACT: Few transcriptional regulatory networks have been described in non-model organisms. In Entamoeba histolytica seminal aspects of pathogenesis are transcriptionally controlled, however, little is known about transcriptional regulatory networks that effect gene expression in this parasite. We used expression data from two microarray experiments, cis-regulatory motif elucidation, and a naïve Bayesian classifier to identify genome-wide transcriptional regulatory patterns in E. histolytica. Our algorithm identified promoter motifs that accurately predicted the gene expression level of 68% of genes under trophozoite conditions. We identified a promoter motif ((A)/(T)AAACCCT) associated with high gene expression, which is highly enriched in promoters of ribosomal protein genes and tRNA synthetases

SUBMITTER: Hackney JA 

PROVIDER: S-EPMC1874630 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature