CopraRNA and IntaRNA: predicting small RNA targets, networks and interaction domains

Abstract

CopraRNA (Comparative prediction algorithm for small RNA targets) is the most recent asset to the Freiburg RNA Tools webserver. It incorporates and extends the functionality of the existing tool IntaRNA (Interacting RNAs) in order to predict targets, interaction domains and consequently the regulatory networks of bacterial small RNA molecules. The CopraRNA prediction results are accompanied by extensive postprocessing methods such as functional enrichment analysis and visualization of interacting regions. Here, we introduce the functionality of the CopraRNA and IntaRNA webservers and give detailed explanations on their postprocessing functionalities. Both tools are freely accessible at http://rna.informatik.uni-freiburg.de.

Figure 1.

sRNA identification and classification workflow incorporating CopraRNA or IntaRNA. The first box mentions selected experiments that have aided in sRNA identification, i.e. RNAseq (8), dRNAseq (6) or Hfq co-immunoprecipitation (CoIP) (9). The cylinder represents databases that can be queried while looking for sRNA homologs. Examples are NCBI (BLAST) (26) or Rfam (27). The next step is the execution of the actual sRNA target prediction depending on presence of sRNA homologs (CopraRNA) or absence of sRNA homologs (IntaRNA). The final two stages consist of postprocessing and selection of candidates for experimental verification, e.g. by a GFP reporter system (32).

Figure 2.

The CopraRNA heatmap shows the targets with a p-value ≤ 0.01 (for IntaRNA the top 50 predicted targets are subjected to the initial functional enrichment), which have homologs in the organism of interest and are functionally enriched. All members of clusters with a DAVID enrichment score ≥ 1.0 are shown in a specific color. Each row represents a gene and each column a specific functional term. If the gene can be assigned to a term, the corresponding square is colored. If no assignment was made, the square remains white. Closely related terms are assigned to a cluster and have the same color. The opacity of the color depends on the p-value of the CopraRNA prediction. A more intense color represents a more significant p-value. The ‘fold enrichment’ is given in front of the term descriptions. It represents the enrichment of a term in the prediction group in relation to the whole prediction background (e.g. a term with an enrichment of 10 contains 10 times more genes belonging to the respective term than the background). The enrichment scores give a measure of the biological significance of the cluster. The DAVID enrichment score for a cluster is the log transformed geometric mean of all enrichment p-values from the terms belonging to the respective cluster. A higher score represents a more statistically significant enrichment. The individual p-values for the terms are calculated by a modified Fisher's exact test. The length of the bars next to the groups of enriched genes corresponds to the size of the enrichment score. The publication on the DAVID webserver suggests to investigate clusters with an enrichment score of ≥ 1.3 while also pointing out that clusters with lower enrichment scores must not necessarily be discarded and may also contain useful information (33). This specific heatmap represents the enrichment output for the enterobacterial (here Escherichia coli) sRNA FnrS. Due to space reasons only one term for each cluster is shown.

Figure 3.

CopraRNA webserver input (A) and output (B) page for the sRNA GcvB. The FASTA file may be pasted or uploaded to the webserver. Upon insertion of the sequences, the webserver automatically displays the RefSeq IDs’ organism affiliations (blue text in (A)). The output page contains a visualization of the primary result table, the interaction as predicted by IntaRNA and the interacting region plots within the sRNA and mRNA. Furthermore, the functional enrichment is visualized as interactive heatmap.