Analyzing stochastic transcription to elucidate the nucleoid's organization-2

curve) when the plasmid is actively transcribed (and translated; data set A). The red curve shows the autocorrelation function when the genes' positions were randomly assigned. The Y-axis has been cropped at an autocorrelation of 0.15 for a clearer visual interpretation; the blue curve starts at an autocorrelation of 0.27 for a gene distance of one. Maxima (positive correlation) and minima (negative or anti-correlation) can be clearly distinguished, with a strong anti-correlation for genes that lie opposite of each other on the chromosome (a gene distance of around 650). Similarly, Figures 1b and 1c show the results for the chromosome and the megaplasmid pSymB, respectively, when both are actively transcribed (and translated; data set A). As can be seen, the autocorrelation functions for the three replicons are similar. Note: The figures are all at the same scale to better illustrate the different sizes of the three replicons. All Y-axes have been cropped at a value of 0.15 for (visual) clarity's sake.<p><b>Copyright information:</b></p><p>Taken from "Analyzing stochastic transcription to elucidate the nucleoid's organization"</p><p>http://www.biomedcentral.com/1471-2164/9/125</p><p>BMC Genomics 2008;9():125-125.</p><p>Published online 10 Mar 2008</p><p>PMCID:PMC2270832.</p><p></p

Analyzing stochastic transcription to elucidate the nucleoid's organization-0

curve) when the plasmid is actively transcribed (and translated; data set A). The red curve shows the autocorrelation function when the genes' positions were randomly assigned. The Y-axis has been cropped at an autocorrelation of 0.15 for a clearer visual interpretation; the blue curve starts at an autocorrelation of 0.27 for a gene distance of one. Maxima (positive correlation) and minima (negative or anti-correlation) can be clearly distinguished, with a strong anti-correlation for genes that lie opposite of each other on the chromosome (a gene distance of around 650). Similarly, Figures 1b and 1c show the results for the chromosome and the megaplasmid pSymB, respectively, when both are actively transcribed (and translated; data set A). As can be seen, the autocorrelation functions for the three replicons are similar. Note: The figures are all at the same scale to better illustrate the different sizes of the three replicons. All Y-axes have been cropped at a value of 0.15 for (visual) clarity's sake.<p><b>Copyright information:</b></p><p>Taken from "Analyzing stochastic transcription to elucidate the nucleoid's organization"</p><p>http://www.biomedcentral.com/1471-2164/9/125</p><p>BMC Genomics 2008;9():125-125.</p><p>Published online 10 Mar 2008</p><p>PMCID:PMC2270832.</p><p></p

Analyzing stochastic transcription to elucidate the nucleoid's organization-1

curve) when only stochastic transcription takes place (data set B). The red curve shows the autocorrelation function when the genes' positions were randomly assigned. The Y-axis has been cropped at an autocorrelation of 0.15 for a clearer visual interpretation; the blue curve starts at an autocorrelation of 0.15 for a gene distance of one. The signal becomes quickly confounded with the noise (red curve). There are minima and maxima that stand out, but only a spectral analysis can tell, whether these are significant or not. Again to serve as comparison, Figures 2b and 2c show the autocorrelation functions for the chromosome and the megaplasmid psymB, respectively, for data set B. Both replicons are actively transcribed and translated, unlike psymA, and their autocorrelation functions are comparable to those in data set A (as confirmed by the spectral and statistical analyses, see additional file ). Note: The figures are all at the same scale to better illustrate the different sizes of the three replicons. All Y-axes have been cropped at a value of 0.15 for (visual) clarity's sake.<p><b>Copyright information:</b></p><p>Taken from "Analyzing stochastic transcription to elucidate the nucleoid's organization"</p><p>http://www.biomedcentral.com/1471-2164/9/125</p><p>BMC Genomics 2008;9():125-125.</p><p>Published online 10 Mar 2008</p><p>PMCID:PMC2270832.</p><p></p