Stress response regulators identified through genome-wide transcriptome analysis of the (p)ppGpp-dependent response in Rhizobium etli

Additional file 1:

Figure S1. Growth curve of R. etli CFN42 in AMS medium. (a) Optical density (OD) readings during growth of the wild type and rsh mutant shown in green and red, respectively. The arrows indicate the time points of sampling. (b) Colony forming units (CFU) during growth of the wild type and rsh mutant.

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Additional file 2:

Figure S2. MA plots comparing transcriptome data. Scatter plots of the microarray data that plot the distribution of the log₂ intensity ratio (M-value) versus the log₂ average intensity (A-value). Differentially expressed genes that are upregulated or downregulated are shown in red or green, respectively. The number of genes with a growth phase or (p)ppGpp-dependent expression profile are indicated by histogram bars at the right of the MA plot. (a) Wild type compared to rsh mutant in stationary phase. (b) Wild type compared to rsh mutant in exponential phase.

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Additional file 3:

Table S1. The differentially expressed genes during stationary phase and exponential phase in the wild type compared to the rsh mutant.

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Additional file 4:

Table S2. The RpoE4-regulated genes according to Martinez-Salazar et al. (2009) that were found to be alarmone-dependent in this study [42].

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Additional file 5:

Table S3. The alarmone-dependent ncRNAs.

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Additional file 6:

Table S4. The RT-qPCR fold changes compared to array fold changes and qPCR primers.

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Additional file 7:

Table S5. The bacterial strains and plasmids used in this study.

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Additional file 8:

Figure S3. RT-qPCR identification of stable endogenous genes. (a) Determining the most stable reference genes using the average expression stability value M of the remaining reference genes during a stepwise exclusion of the least stable internal control gene. The genes are ranked according to increasing expression stability. At the left are the least stable genes and at the right are the most stable ones. (b) Determining the optimal number of reference genes using the pairwise variation V between two sequential normalization factors containing an increasing number of genes with 0.15 as a proposed cutoff value by Vandesompele et al. [90].

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