() β-Galactosidase assay of the different loop–loop interactions investigated

<p><b>Copyright information:</b></p><p>Taken from "Stabilities of HIV-1 DIS type RNA loop–loop interactions and "</p><p>Nucleic Acids Research 2006;34(1):334-342.</p><p>Published online 12 Jan 2006</p><p>PMCID:PMC1331993.</p><p>© The Author 2006. Published by Oxford University Press. All rights reserved</p> β-Galactosidase activity is expressed in Miller Units and was normalized relative to the activity of the XYLAI interaction. All hairpins were tested together with their cognate interaction partner (closed bars). As control all RNAs X and Y were assayed against non-cognate interaction partners, namely YΘ for RNAs X (light gray bars) and XΘ for RNAs Y (open bars). Furthermore transformants expressing only either XLAI-MS2 or m26-YLAI or no hairpin RNA at all are shown. s for the cognate kissing complexes at a concentration of 2 × 10 M are indicated. Error bars show the SD of two independent triplicate experiments. () Correlation between the and the β-galactosidase activity determined for kissing interactions containing 9 nt in the loop. (XYAA and YX0 contain 8 and 6 nt, respectively, and are not included.) () Schematic representation of cognate and non-cognate interactions considering XYLAI as example

Trends in nucleotide frequencies of the Neutral SELEX and Hfq SELEX pools.

<p>Each group in the bar charts shows the difference in mononucleotide frequency (<i>A</i>) and dinucleotide frequency (<i>B</i>) from the averages of the <i>E. coli</i> K-12 genome. The groups begin on the left with the sequenced library in brown, then ten rounds of Neutral SELEX in green, and finally the Hfq Genomic SELEX content in grey.</p

Effects of Neutral SELEX on length and distance to genomic sequence.

<p>The average lengths of the sequences in each Neutral SELEX pool, shown in bars, decreased dramatically after the library was transcribed and reverse transcribed into the first round of Neutral SELEX (left two bars), but only steadily thereafter. The average nucleotide became slightly more distant from the genomic sequence, shown in points and lines. The grey bar and the last point to the right indicate the average length and distance from the genome in the 9th round of the Hfq Genomic SELEX experiment.</p

Additional file 10: Table S3. of Temperature-dependent sRNA transcriptome of the Lyme disease spirochete

Genes with antisense and 5′ UTR sRNAs. The table contains information about all of the genes with antisense and 5′ UTR sRNAs associated with them. Gene ontology terms (GO terms) for biological processes (BP) are also given for each gene. The column titled, “Norgard FoldChange” contains the fold-change of that particular gene as reported by Revel et al. [52] via microarray after a temperature shift. (XLSX 221 kb

Additional file 12: Figure S8. of Temperature-dependent sRNA transcriptome of the Lyme disease spirochete

Manual curation of peaks. Intragenic RNA peaks called in genes bb0311 and bb0312 were manually curated based on the coverage patterns. The deep-sequencing results are displayed as described in the caption of Additional file 4: Figure S2. The - strand coverage is shown in blue. Note that the y-axis scale is different between the peak calling libraries (peak) and the biological replicates used for differential expression analyses (23 °C and 37 °C). The genomic context is illustrated below the coverage maps: black arrows indicate the annotated genes; the yellow box indicates the region called as a small intraRNA by our peak caller. The peaks appear to be broad and similar in height across the gene, suggesting they are degradation products of the mRNA, not stable sRNAs. (PDF 2229 kb

Enrichment effects on positively selected sequences.

<p>(<i>A</i>) Enrichment level plotted against <i>Z</i>-scores. Sequences selected by Genomic SELEX for Hfq were clustered if the best alignment shows mutual identity ≥85%. The cluster size is shown along the <i>x</i>-axis, and the <i>Z</i>-score of the sequence along the <i>y</i>-axis. The sequences were binned into cluster size ranges of 10, and the boxes represent the distribution of <i>Z</i>-scores within the range of cluster sizes. The boxes cover the 25%–75% range of the data, the line within the box is the median and the whiskers indicate 1.5× the interquartile range. If enrichment were dependent on a high <i>Z</i>-score, we would expect to see an increase in the median <i>Z</i>-score as cluster sizes increase, however this is not the case. In fact, the <i>Z</i>-score of any given sequence appears to vary nearly as much with enriched sequences as with unenriched sequences. (<i>B</i>) As a control, we plotted the same analysis with round 9 of Neutral SELEX, showing that enrichment is a signal of the positive selection of sequences.</p

Effects of SELEX on structural stability of RNA sequences.

<p>(<i>A</i>) Average <i>Z</i>-score of sequences in the initial library (brown bar), each pool of Neutral SELEX (green bars) and the sequences from the Hfq Genomic SELEX experiment after 9 rounds of selection (grey bar). Numbers indicate the SELEX cycle. (<i>B</i>) Comparison of the distributions of <i>Z</i>-scores of the 9th round of Neutral SELEX, the 9th round of Hfq Genomic SELEX and the genomic library. These are all plotted next to the normal distribution (expected from random sequence), shown with the black line.</p

Nascent RNA signaling to yeast RNA Pol II during transcription elongation

<div><p>Transcription as the key step in gene expression is a highly regulated process. The speed of transcription elongation depends on the underlying gene sequence and varies on a gene by gene basis. The reason for this sequence dependence is not known in detail. Recently, our group studied the cross talk between the nascent RNA and the transcribing RNA polymerase by screening the <i>Escherichia coli</i> genome for RNA sequences with high affinity to RNA Pol by performing genomic SELEX. This approach led to the identification of <u>R</u>NA polymerase-binding <u>AP</u>tamers termed “RAPs”. RAPs can have positive and negative effects on gene expression. A subgroup is able to downregulate transcription via the activity of the termination factor Rho. In this study, we used a similar SELEX setup using yeast genomic DNA as source of RNA sequences and highly purified yeast RNA Pol II as bait and obtained almost 1300 yeast-derived RAPs. Yeast RAPs are found throughout the genome within genes and antisense to genes, they are overrepresented in the non-transcribed strand of yeast telomeres and underrepresented in intergenic regions. Genes harbouring a RAP are more likely to show lower mRNA levels. By determining the endogenous expression levels as well as using a reporter system, we show that RAPs located within coding regions can reduce the transcript level downstream of the RAP. Here we demonstrate that RAPs represent a novel type of regulatory RNA signal in <i>Saccharomyces cerevisiae</i> that act in <i>cis</i> and interfere with the elongating transcription machinery to reduce the transcriptional output.</p></div

Expression profiles of RAP-containing genes.

<p>(A) to (J) Transcript levels of 10 selected target genes (<i>MOT3</i>, <i>CYC8</i>, <i>CBK1</i>, <i>SSL2</i>, <i>PUF3</i>, <i>TOP3</i>, <i>TUP1</i>, <i>BUD8</i>, <i>MSI1</i> and <i>SSM4</i> respectively). Yeast cells were grown to exponential phase, total RNA was extracted and DNAseI digested. Reverse transcription was performed, and expression levels were quantified by qRT-PCR using amplicons upstream and downstream of RAPs as indicated in the respective figures. Values were normalized to the first 5’ amplicon and represent means ° SD n ≤ 3; ***p<0.001; **p<0.01; *p≤0.05; ns, not significant (tested by t-test).</p

RAP host genes display intragenic termination.

<p>(A) and (C) show a gene centered view on RNA Pol II occupancy at RAP-containing genes and genes without RAPs determined by available NET-Seq (A) and CRAC-Seq (C) data sets. To avoid signal distortion by the RNA Pol II 5’ peak, the first 200nts (and for symmetry reasons also the last 200nts) were excluded from the analysis. The remaining gene body was binned into ten equally spaced segments (deciles) and the upstream/downstream ratio of RNA Pol II occupancy was calculated for each segment. Distribution of ratios from segments harboring a RAP are separately visualized (blue bars) and show a consistently higher upstream RNA Pol II density. (B) and (D) Ratio of RNA Pol II occupancy between genic regions upstream and downstream of RAPs tested by NET-seq (B) and CRAC-seq (D). For each gene position upstream and downstream of a RAP the number of reads per position from each experiment was deduced and tested for a significant increase, decrease, or no significant change between the upstream and downstream region coverage (Poisson test; p-value threshold < 0.01). To estimate an expected background distribution accounting for the general decrease of Pol II occupancy along the gene body, the analysis was repeated with 100 randomized positions, conserving the relative RAP positions within the harboring gene. Both data sets, NET-Seq (B) and CRAC-Seq (D), show that RAP containing genes more often display a significant decrease downstream of the RAP compared to the randomized background.</p