Dataset Information

Comparative analysis of regulatory elements between Escherichia coli and Klebsiella pneumoniae by genome-wide transcription start site profiling [TSS-Seq]

ABSTRACT: We report the application of single-molecule-based sequencing technology for high-throughput profiling of transcription start sites for two enterobacteria: Escherichia coli and Klebsiella pneumoniae.By obtaining over fourteen billion bases of sequence from 5' RACE (rapid amplification of cDNA ends) followed by deep sequencing, we generated genome-wide TSS (transcription start site) maps for those two species. With experimentally derived TSS datasets, we examined usage of multiple TSSs, length of 5' UTR (untranslated region), SD (Shine-Dalgarno) sequence motif, promoter sequence motif, and dinucleotide preference near TSS site. In addition, we used the TSS datasets to identify sRNAs (small RNAs) in E. coli and K. pneumoniae. Based on these analysis, we compared regulatory elements including promoter, 5' UTR and sRNAs between two species, and investigated similarities and differences of upstream regulatory regions. Moreover, sRNAs were also compared and analyzed in terms of their sequences and target sequences, presenting possible working mechanisms of K. pneumoniae sRNAs by transferring prior knowledge from E. coli sRNAs.

ORGANISM(S): Escherichia coli K-12 Klebsiella pneumoniae

PROVIDER: GSE35821 | GEO | 2012/07/30

SECONDARY ACCESSION(S): PRJNA155893

REPOSITORIES: GEO

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Project description:Background: In prokaryotes, sigma factors are essential for the targeting of the transcription machinery to promoters. Various sigma factors have been described that recognize and bind to specific DNA sequence motifs in promoter sequences. The canonical sigma factor M-OM-^C70 is commonly involved in transcription of the cell's general housekeeping genes, which is mediated by the conserved M-OM-^C70 promoter sequence motifs. This study detects and predicts the general M-OM-^C70-promoter sequences in Lactobacillus plantarum WCFS1 using genome-wide analysis. The accuracy of the transcriptionally-active part of this promoter prediction was subsequently evaluated by correlating locations of predicted promoters with experimentally detected transcription starts sites (TSSs) using high-resolution tiling array transcriptome datasets. Results: To identify M-OM-^C70-related promoter sequences, we performed a genome-wide sequence motif scan of the L. plantarum WCFS1 genome focusing on the regions upstream of protein-encoding genes. We obtained several highly conserved motifs including those resembling the conserved M-OM-^C70-promoter consensus. Position weight matrices-based models of the recovered M-OM-^C70-promoter sequence motif were employed to identify 4746 motifs with significant similarity (p-value < 10-4) to the model-motif in the L. plantarum genome. Genome-wide transcription start site information deduced from whole genome tiling-array transcriptome datasets revealed 936 TSSs that were employed to validate the transcriptionally active fraction of these predicted promoters. In total, 578 predicted promoters were found in proximity (M-bM-^IM-$ 100 nucleotides) of the identified TSSs, showing a highly significant co-occurrence of predicted promoter and measured TSS (p-value < 10-23). An additional 224 predicted promoters was validated when the significant similarity to the model-motif was applied less strictly (10-4 M-bM-^IM-$ p-value < 10-3). Conclusions: High-resolution tiling arrays provide a suitable source for TSS detection at a genome-wide level, and allow experimental verification of in silico-predicted promoter sequence motifs. Triplicate hybridizations (technical replicates) of two L. plantarum WCFS1 samples (biological replicates) gathered from a fermentation run at OD600 of 1. Dye swap applied to one of the three technical replicates.

Project description:Background: In prokaryotes, sigma factors are essential for the targeting of the transcription machinery to promoters. Various sigma factors have been described that recognize and bind to specific DNA sequence motifs in promoter sequences. The canonical sigma factor σ70 is commonly involved in transcription of the cell's general housekeeping genes, which is mediated by the conserved σ70 promoter sequence motifs. This study detects and predicts the general σ70-promoter sequences in Lactobacillus plantarum WCFS1 using genome-wide analysis. The accuracy of the transcriptionally-active part of this promoter prediction was subsequently evaluated by correlating locations of predicted promoters with experimentally detected transcription starts sites (TSSs) using high-resolution tiling array transcriptome datasets. Results: To identify σ70-related promoter sequences, we performed a genome-wide sequence motif scan of the L. plantarum WCFS1 genome focusing on the regions upstream of protein-encoding genes. We obtained several highly conserved motifs including those resembling the conserved σ70-promoter consensus. Position weight matrices-based models of the recovered σ70-promoter sequence motif were employed to identify 4746 motifs with significant similarity (p-value < 10-4) to the model-motif in the L. plantarum genome. Genome-wide transcription start site information deduced from whole genome tiling-array transcriptome datasets revealed 936 TSSs that were employed to validate the transcriptionally active fraction of these predicted promoters. In total, 578 predicted promoters were found in proximity (≤ 100 nucleotides) of the identified TSSs, showing a highly significant co-occurrence of predicted promoter and measured TSS (p-value < 10-23). An additional 224 predicted promoters was validated when the significant similarity to the model-motif was applied less strictly (10-4 ≤ p-value < 10-3). Conclusions: High-resolution tiling arrays provide a suitable source for TSS detection at a genome-wide level, and allow experimental verification of in silico-predicted promoter sequence motifs.

Dataset Information

Comparative analysis of regulatory elements between Escherichia coli and Klebsiella pneumoniae by genome-wide transcription start site profiling [TSS-Seq]

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