Combining genome and mouse knockout expression data to highlight binding sites for the transcription factor HNF1alpha

The identification of regulatory elements in silico is an important method for inferring function from sequence data, but it is uncertain which methods are best. We used a novel combination of expression data from a TCF1 knockout mouse (TCF1 codes for the transcription factor HNF1a), and human and mouse genome sequences, to search 2kb upstream of 28 genes downregulated in TCF1 null mice compared to wild type mice. We wrote software (http://www.BindGene.org) to search for and assign p-values to potential binding sites. This identified 8 genes as candidates for being directly regulated by HNF1a: LIPC, CRP, F13B, PRODH2, HSD17B2, SCL7A9, SLC16A7, PAH. There was evidence for conservation between human and mouse for all these regions identified as containing putative binding sites. For three of the genes identified there was experimental evidence for an HNF1a binding site. For comparison we also examined 25 genes up-regulated in TCF1 null mice; only one gene was selected and there was little evidence for conservation of this putative binding site between human and mouse. This result was consistent with HNF1a being a gene transcription activator. Another 6 up-regulated genes had unexpectedly high p-values, suggesting that possibly HNF1a sites have been suppressed from these genes. In conclusion, gene expression data from transgenic animals lacking a transcription factor can be used to identify DNA binding sites for that factor.