Hu and Gallo BMC Genomics 2010, 11:49 http://www.biomedcentral.com/1471-2164/11/49 coordinating and controlling tissue gene expression across a variety of conditions. In summary, our findings have shown that tissue gene expression is regulated by large sets of interacting TFs either on the same promo- ter of a gene or through TF-TF interaction networks. Methods Promoter sequences for housekeeping and tissue- expressed genes The GNF Atlas2 gene expression database (gnfAtlas2) [34], which contains gene expression data from 79 human tissues, was used for the selection of genes. Based on the report of Pennacchio et al [18] we selected in each tissue the top 300 expressed genes (referred to tissue-expressed genes), which have been used and pro- ven to successfully predict tissue-specific enhancers. Housekeeping genes are the 1018 genes defined by Farre et al [24]. Redundant genes in each group were first removed. Although regulatory elements can exist anywhere in the genome, they are more concentrated around the transcriptional start sites [35]. To reduce false predictions we focused on the proximal promoters which have been proven to successfully predict tissue- specific regulatory elements [21,36]. It is however worthy to note that the use of 1 kb promoter sequences has limitation for the prediction of tissue TF pairs when compared to the experimental approaches such as ChIP- chip experiment, in which TF pairs can be detected any- where in the genome. Considering no benchmark pro- moter sequence dataset is currently available for computational prediction of functional TF pairs, the use of 1 kb promoter sequences and our computational approach nevertheless provide an alternative way for tis- sue interacting TF discovery. Promoter sequences within 1 kb upstream of transcriptional starting sites for both human and corresponding mouse orthologous genes were extracted from the UCSC genome browser (hg18 March 2006 assembly, mm9 July 2007 assembly). Ortho- logous genes with promoter sequences from both human and mouse were selected for further analysis. This procedure resulted in 208 to 278 orthologous pro- moter sequences for tissue-expressed genes and 986 orthologous promoter sequences for housekeeping genes. Prediction of TF pairs and tissue TF pairs The procedures for predicting TF pair are basically the same as previously described [22] (Additional File 1). Briefly, background sequences were created by shuffling the DNA sequences within each promoter by either mixing completely or keeping dinucleotides together. These background sequences are preferable to using intergenic sequences which usually are AT-rich or exo- nic sequences whose nucleotide distributions tend to be biased, when compared to the test promoter sequences. Page 12 of 15 The resulting shuffled sequences from human and mouse, together with the original promoter sequences, were employed for TFBS detection using the Match® program [37], for which the profile parameter was set to “minimize the sum of false positives and negatives”, and the 214 non-redundant vertebrate PWMs from the pro- fessional TRANSFAC11.4 database [25]. To detect enriched TF pairs out of 23,005 (214*215/2) possible combinations of 2 TFs, distance constraints were first applied for the selection of co-occurring TFBSs with a defined maximum distance between 2 TFBSs. A total of 10 distances were defined, ranging from the smallest 20 bp to the largest 200 bp with a 20 bp increment. The assumption behind the distance constraint is that func- tional TFBS pairs are more distance-restricted than ran- dom co-occurrence of TFBSs [19,38]. This is true not only in human, for which we found that functional TF pairs were enriched within 200 bp distance ranges [22], but also in Drosophila, in which short-range linkages (< 50 bp) between TFs was overrepresented but mid-range distances (100-500 bp) between TFs was depleted [39]. Enrichment of TFBS pairs for each distance constraint was achieved by computing the ratio of counts for a particular TFBS pair in real promoter sequences vs. the counts of the same TFBS pair in background sequences. To reduce noise while keeping as many as TFBS pairs for the integration of function conservation analysis described below, TFBS pairs with ratio > 1 in more than 5 distance constraints were selected. A two-step analysis procedure was employed to com- pute the enrichment of overlapping orthologous genes for a particular TFBS pair. First, a cutoff threshold of at least 10% overlapping orthologous genes between mouse and human was set up for selecting genes whose pro- moters contained the TFBS pair. The enrichment of overlapping orthologous genes was then estimated by computing the ratio of overlapping orthologous genes from real promoter sequences against those from shuffled sequences. This analysis was performed for each distance constraint. The integration of function conservation for each TF pair was achieved by estimat- ing the correlation (Pearson correlation coefficients) between the 10 enriched TFBS pairs and 10 correspond- ing enriched overlapping orthologous genes from the same distance constraint. Permutation tests were employed to estimate the statistical significance of corre- lation by randomly matching the 10 TFBS pair ratios with the 10 overlapping orthologous gene ratios. For multiple test correction, a cutoff threshold of q-value < 0.05 was applied. TF pairs are those passing the cutoff and common between human and mouse. We next filtered TF pairs of housekeeping genes from those in each tissue (Figure 1a). This was done by removing TF pairs in a particular tissue common to