IntaRNA 2.0: enhanced and customizable prediction of RNA-RNA interactions

Abstract

The IntaRNA algorithm enables fast and accurate prediction of RNA-RNA hybrids by incorporating seed constraints and interaction site accessibility. Here, we introduce IntaRNAv2, which enables enhanced parameterization as well as fully customizable control over the prediction modes and output formats. Based on up to date benchmark data, the enhanced predictive quality is shown and further improvements due to more restrictive seed constraints are highlighted. The extended web interface provides visualizations of the new minimal energy profiles for RNA-RNA interactions. These allow a detailed investigation of interaction alternatives and can reveal potential interaction site multiplicity. IntaRNAv2 is freely available (source and binary), and distributed via the conda package manager. Furthermore, it has been included into the Galaxy workflow framework and its already established web interface enables ad hoc usage.

Figure 1.

The figure shows the whole genome target prediction performance of IntaRNAv1 (orange) and IntaRNAv2 (blue) on a benchmark set of 160 experimentally verified enterobacterial (E. coli, Salmonella) RNA–RNA interactions including 28 different sRNAs (see Supplementary Table S1 and Supplementary FASTA). Furthermore, the performance of IntaRNAv2 was assessed with the same data set under enforcement of a seed energy E ≤ –4.8 kcal/mol (dashed blue). The x-axis represents the amount of predictions per sRNA at a given rank and the y-axis shows the cumulated number of true positives for all sRNA whole genome target predictions.

Figure 2.

Minimal energy profile for all intermolecular index pairs covered by any predicted interaction of Spot42 with the sthA mRNA (with E < 0). Conserved accessible regions I, II and III of Spot42 known to interact are tagged on the right.