Determining how cells regulate their transcriptional response toextracellular signals is key to the understanding of complex eukaryotic systems. This study wasinitiated with the goals of furthering the study of mammal...Determining how cells regulate their transcriptional response toextracellular signals is key to the understanding of complex eukaryotic systems. This study wasinitiated with the goals of furthering the study of mammalian transcriptional regulation andanalyzing the relative benefits of related computational methodologies. One dataset available forsuch an analysis involved gene expression profiling of the early growth factor response to plateletderived growth factor (PDGF) in a human glioblastoma cell line; this study differentiated geneswhose expression was regulated by signaling through the phosphoinositide-3-kinase (PI3K) versus theextracellular-signal regulated kinase (ERK) pathways. We have compared the inferred transcriptionfactors from this previous study with additional predictions of regulatory transcription factorsusing two alternative promoter sequence analysis techniques. This comparative analysis, in which thealgorithms predict overlapping, although not identical, sets of factors, argues for meticulousbenchmarking of promoter sequence analysis methods to determine the positive and negative attributesthat contribute to their varying results. Finally, we inferred transcriptional regulatory networksderiving from various signaling pathways using the CARRIE program suite. These networks not onlyincluded previously described transcriptional features of the response to growth signals, but alsopredicted new regulatory features for the propagation and modulation of the growth signal.展开更多
文摘Determining how cells regulate their transcriptional response toextracellular signals is key to the understanding of complex eukaryotic systems. This study wasinitiated with the goals of furthering the study of mammalian transcriptional regulation andanalyzing the relative benefits of related computational methodologies. One dataset available forsuch an analysis involved gene expression profiling of the early growth factor response to plateletderived growth factor (PDGF) in a human glioblastoma cell line; this study differentiated geneswhose expression was regulated by signaling through the phosphoinositide-3-kinase (PI3K) versus theextracellular-signal regulated kinase (ERK) pathways. We have compared the inferred transcriptionfactors from this previous study with additional predictions of regulatory transcription factorsusing two alternative promoter sequence analysis techniques. This comparative analysis, in which thealgorithms predict overlapping, although not identical, sets of factors, argues for meticulousbenchmarking of promoter sequence analysis methods to determine the positive and negative attributesthat contribute to their varying results. Finally, we inferred transcriptional regulatory networksderiving from various signaling pathways using the CARRIE program suite. These networks not onlyincluded previously described transcriptional features of the response to growth signals, but alsopredicted new regulatory features for the propagation and modulation of the growth signal.
