Reliable prediction of specific transcription factor target genes is a major challenge in functional genomics. Current sequence-based methods yield many false predictions due to the short and degenerated DNA-binding motifs.

Here, we describe a new systematic genome-wide approach, the seed-distribution-distance method that searches large scale genome wide expression data for genes that are similarly expressed as known targets. This method is used to identify genes that are likely targets and thereby sequence-based methods can focus on a subset of genes, giving rise to fewer false positive predictions. We show by cross-validation that this method is robust in recovering specific target genes. Further, this method identifies genes with typical functions and binding motifs of the seed. The method is illustrated by predicting novel targets of the transcription factor NFkB. Among the new targets is optineurin, which plays a key role in the pathogenesis of acquired blindness caused by adult-onset primary open-angle glaucoma. We show experimentally that optineurin as well as other predicted genes are targets of NFkB.

We present a robust and reliable method to enhance the genome-wide prediction of specific transcription factor target genes that exploits the vast expression information available in public databases today. A public web interface for customized searches will be available.