Abstract
BackgroundTranscriptional networks of higher eukaryotes are difficult to obtain. Available experimental data from conventional approaches are sporadic, while those generated with modern high-throughput technologies are biased. Computational predictions are generally perceived as being flooded with high rates of false positives. New concepts about the structure of regulatory regions and the function of master regulator sites may provide a way out of this dilemma.MethodsWe combined promoter scanning with positional weight matrices with a 4-genome conservativity analysis to predict high-affinity, highly conserved transcription factor (TF) binding sites and to infer TF-target gene relations. They were expanded to paralogous TFs and filtered for tissue-specific expression patterns to obtain a reference transcriptional network (RTN) as well as tissue-specific transcriptional networks (TTNs).ResultsWhen validated with experimental data sets, the predictions done showed the expected trends of true positive and true negative predictions, resulting in satisfying sensitivity and specificity characteristics. This also proved that confining the network reconstruction to the 1% top-ranking TF-target predictions gives rise to networks with expected degree distributions. Their expansion to paralogous TFs enriches them by tissue-specific regulators, providing a reasonable basis to reconstruct tissue-specific transcriptional networks.ConclusionsThe concept of master regulator or seed sites provides a reasonable starting point to select predicted TF-target relations, which, together with a paralogous expansion, allow for reconstruction of tissue-specific transcriptional networks.
Highlights
Transcriptional networks of higher eukaryotes are difficult to obtain
We applied all vertebrate matrices using default minFN ("minimize false negatives”) thresholds in order to retrieve almost all potential transcription factor binding sites that have at least the quality of the used TFBS which are given in the corresponding matrix [8]
We combined standard PWM scanning with a four species conservation filtering to identify potential TFBSs and, on this basis, to infer TF-target gene relations for a comprehensive reference transcriptional network (RTN). With this strategy, we predicted 4,3*10e7 TFBS which are conserved among these four species
Summary
Available experimental data from conventional approaches are sporadic, while those generated with modern high-throughput technologies are biased. New concepts about the structure of regulatory regions and the function of master regulator sites may provide a way out of this dilemma. Regulation of transcription is mediated through complex arrays of transcription factor binding sites (TFBSs), which constitute promoter and enhancer regions. In spite of the advent of high-throughput approaches to identify TFBSs in a given cellular context, the available information, most comprehensively collected in the TRANSFAC® database [1], is still fragmented and biased with regard to the systems selected. Any transcriptional network reconstructed from the available experimental data is highly incomplete. This situation structures of TF-DNA complexes are known for only a minority of factors. The recently published concepts about master transcription factors [5] or pioneer transcription factors [6] may provide a clue to this problem
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
