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A computational study of bacterial gene regulation and adaptation ...

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Chapter 1: Global regulators <strong>of</strong> <strong>bacterial</strong> transcription initiationbinding intensities than H <strong>and</strong> C together (PW = 4.5 x 10 -9 ) indicating a preference againstbinding to low-AT <strong>gene</strong>s. These data clearly indicate differential binding <strong>of</strong> these three factorsto the three sets <strong>of</strong> <strong>gene</strong>s.In sum, it is notable that the greatest selective preference towards binding to H <strong>gene</strong>s is shownby H-NS, which is recognised as a major global repressor <strong>of</strong> transcription (McGovern et al.1994): among all H-NS targets in RegulonDB, 70% are repressed by this factor. Comparison(A)Stationary phase response(B)gyrAB coexpression!log pvalue x direction <strong>of</strong> response!15 !10 !5 0 5 10 15Pearson correlation coefficientwith gyrA <strong>and</strong> gyrB!1.0 !0.5 0.0 0.5 1.0L C HL C H(C)hupAB coexpression(D)Gyrase bindingPearson correlation coefficientwith hupA <strong>and</strong> hupB!1.0 !0.5 0.0 0.5 1.0Gyrase ChIP!chip intensity ratio(log scale)!1.0 !0.5 0.0 0.5 1.0L C HL C HFigure 1.5. Supercoiling <strong>and</strong> AT content. For each <strong>of</strong> the three classes <strong>of</strong> lead <strong>gene</strong>s in our <strong>study</strong>, (A)Distribution <strong>of</strong> the p-value for differential <strong>gene</strong> expression in stationary phase against mid-log phase.Each p-value is represented as its negative logarithm (base 10), multiplied by +1 if the <strong>gene</strong> isupregulated in stationary phase <strong>and</strong> -1 if it is downregulated. (B) Distribution <strong>of</strong> Pearson correlationcoefficients with gyrA <strong>and</strong> gyrB. (C) Distribution <strong>of</strong> Pearson correlation coefficients with hupA <strong>and</strong>hupB. (D) Distribution <strong>of</strong> ChIP-chip binding intensities for DNA gyrase from Jeong et al. 2004.39

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