Using structural and evolutionary information to detect and correct pyrosequencing errors in non-coding RNAs

TL;DR

This paper introduces RNApyro, an efficient algorithm that calculates mutation probabilities in RNA sequences considering structure and evolution, aiding in error correction for sequencing data.

Contribution

The paper presents RNApyro, a novel linear-time algorithm for exact mutational probability computation under structural and evolutionary constraints in RNA.

Findings

RNApyro effectively corrects errors in rRNA sequences.

The algorithm integrates stacking energies and isostericity scales.

RNApyro complements existing NGS error correction tools.

Abstract

Analysis of the sequence-structure relationship in RNA molecules are essential to evolutionary studies but also to concrete applications such as error-correction methodologies in sequencing technologies. The prohibitive sizes of the mutational and conformational landscapes combined with the volume of data to proceed require efficient algorithms to compute sequence-structure properties. More specifically, here we aim to calculate which mutations increase the most the likelihood of a sequence to a given structure and RNA family. In this paper, we introduce RNApyro, an efficient linear-time and space inside-outside algorithm that computes exact mutational probabilities under secondary structure and evolutionary constraints given as a multiple sequence alignment with a consensus structure. We develop a scoring scheme combining classical stacking base pair energies to novel isostericity scales, and apply our techniques to correct point-wise errors in 5s and 16s rRNA sequences. Our results suggest that RNApyro is a promising algorithm to complement existing tools in the NGS error-correction pipeline.