Abstract
BackgroundSeed and accessibility constraints are core features to enable highly accurate sRNA target screens based on RNA-RNA interaction prediction. Currently, available tools provide different (sets of) constraints and default parameter sets. Thus, it is hard to impossible for users to estimate the influence of individual restrictions on the prediction results.ResultsHere, we present a systematic assessment of the impact of established and new constraints on sRNA target prediction both on a qualitative as well as computational level. This is done exemplarily based on the performance of IntaRNA, one of the most exact sRNA target prediction tools. IntaRNA provides various ways to constrain considered seed interactions, e.g. based on seed length, its accessibility, minimal unpaired probabilities, or energy thresholds, beside analogous constraints for the overall interaction. Thus, our results reveal the impact of individual constraints and their combinations.ConclusionsThis provides both a guide for users what is important and recommendations for existing and upcoming sRNA target prediction approaches.We show on a large sRNA target screen benchmark data set that only by altering the parameter set, IntaRNA recovers 30% more verified interactions while becoming 5-times faster. This exemplifies the potential of seed, accessibility and interaction constraints for sRNA target prediction.
Highlights
Seed and accessibility constraints are core features to enable highly accurate sRNA target screens based on RNA-RNA interaction prediction
The runtime normalization is done using the default parameter setup of IntaRNA v2.3.1, which we extended with additional constraints tested here
Abbreviations in figures and text are based on respective IntaRNA parameter names
Summary
Seed and accessibility constraints are core features to enable highly accurate sRNA target screens based on RNA-RNA interaction prediction. Accessibility-based approaches combine the prediction of a most stable interaction duplex with an energy penalty for making the interaction regions accessible, i.e. free of intra-molecular structure They are very good compromise between the computational complex prediction of joint structures and a simple detection of stable duplexes. The site-based approaches, like RNAup [5], IntaRNA [6, 7] or RIsearch2 [8], compute and use explicit unpaired probabilities for the interacting subregions. While this is exact, the precomputation time and space consumption grows with the maximal length of considered interactions. Position-based approaches, like RNAplex [9], AccessFold [10] or RIblast [11], estimate the
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