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Cross-hybridization of repetitive sequences in genomic and expression arrays is reported to be suppressed with repeat-blocking nucleic acids (C(o)t-1 DNA). Contrary to expectation, we demonstrated that C(o)t-1 also enhanced non-specific hybridization between probes and genomic targets. When added to target DNA, C(o)t-1 enhanced hybridization (2.2- to 3-fold) to genomic probes containing conserved repetitive elements. In addition to repetitive sequences, C(o)t-1 was found to be enriched for linked single copy (sc) sequences. Adventitious association between these sequences and probes distort quantitative measurements of the probes hybridized to desired genomic targets. Quantitative microarray hybridization studies using C(o)t-1 DNA are also susceptible to these effects, especially for probes that map to genomic regions containing conserved repetitive sequences. Hybridization measurements with such probes are less reproducible in the presence of C(o)t-1 than for probes derived from sc regions or regions containing divergent repeat elements, a finding with significant ramifications for genomic and expression microarray studies. We mitigated the requirement for C(o)t-1 either by hybridizing with computationally defined sc probes lacking repeats or by substituting synthetic repetitive elements complementary to sequences in genomic probes.

The pregnane X receptor (PXR) acts as a receptor to induce gene expression in response to structurally diverse xenobiotics through binding as a heterodimer with the 9-cis retinoic acid receptor (RXR) to enhancers in target gene promoters. We identified and estimated the affinities of novel PXR/RXR binding sites in regulated genes and additional genomic targets of PXR with an information theory-based model of the PXR/RXR binding site. Our initial PXR/RXR model, the result of the alignment of 15 previously characterized binding sites, was used to scan the promoters of known PXR target genes. Sites from these genes, with information contents of >8 bits bound by PXR/RXR in vitro, were used to revise the information weight matrix; this procedure was repeated by screening for progressively weaker binding sites. After three iterations of refinement, the model was based on 48 validated PXR/RXR binding sites and has an average information content (Rsequence) of 14.43 +/- 3.21 bits. A scan of the human genome predicted novel PXR/RXR binding sites in the promoters of UGT1A3 (19.78 bits at -8040 and 16.37 bits at -6930) and UGT1A6 (12.74 bits at -9216), both of which were identified previously as targets for PXR. These sites were subsequently demonstrated to specifically bind PXR/RXR in competition electrophoretic mobility shift assays. A strong PXR site was also predicted upstream of the CASP10 gene (18.69 bits at -7872) and was validated by binding studies and reporter assays as a PXR responsive element. This suggests that the PXR-mediated response extends beyond genes involved in drug biotransformation and transport.

Many multimeric transcription factors recognize DNA sequence patterns by cooperatively binding to bipartite elements composed of half sites separated by a flexible spacer. We developed a novel bipartite algorithm, bipartite pattern discovery (Bipad), which produces a mathematical model based on information maximization or Shannon's entropy minimization principle, for discovery of bipartite sequence patterns. Bipad is a C++ program that applies greedy methods to search the bipartite alignment space and examines the upstream or downstream regions of co-regulated genes, looking for cis-regulatory bipartite patterns. An input sequence file with zero or one site per locus is required, and the left and right motif widths and a range of possible gap lengths must be specified. Bipad can run in either single-block or bipartite pattern search modes, and it is capable of comprehensively searching all four orientations of half-site patterns. Simulation studies showed that the accuracy of this motif discovery algorithm depends on sample size and motif conservation level, but results were independent of background composition. Bipad performed equivalent with or better than other pattern search algorithms in correctly identifying Escherichia coli cyclic AMP receptor protein and Bacillus subtilis sigma factor binding site sequences based on experimentally defined benchmarks. Finally, a new bipartite information weight matrix for vitamin D3 receptor/retinoid X receptor alpha (VDR/RXRalpha) binding sites was derived that comprehensively models the natural variability inherent in these sequence elements.