The energy-spectrum of bicompatible sequences

TL;DR

This paper introduces a novel dynamic programming algorithm and Boltzmann sampler to analyze the energy spectra and properties of bicompatible RNA sequences, revealing insights into their role in evolution and riboswitch function.

Contribution

It presents a new energy model and algorithm for sampling bicompatible sequences, advancing understanding of their energy landscapes and evolutionary significance.

Findings

Bicompatible sequences vary with structure pairs.

Native riboswitches show distinct energy ranking signatures.

Random structure pairs have fewer transitions.

Abstract

Background: Genotype-phenotype maps provide a meaningful filtration of sequence space and RNA secondary structures are particular such phenotypes. Compatible sequences i.e.~sequences that satisfy the base pairing constraints of a given RNA structure play an important role in the context of neutral networks and inverse folding. Sequences satisfying the constraints of two structures simultaneously are called bicompatible and phenotypic change, induced by erroneously replicating populations of RNA sequences, is closely connected to bicompatibility. Furthermore, bicompatible sequences are relevant for riboswitch sequences, beacons of evolution, realizing two distinct phenotypes. Results: We present a full loop energy model Boltzmann sampler of bicompatible sequences for pairs of structures. The novel dynamic programming algorithm is based on a topological framework encapsulating the relations between loops. We utilize our sequence sampler to study the energy spectra and density of bicompatible sequences, the rankings of the structures and key properties for evolutionary transitions. Conclusion: Our analysis of riboswitch sequences shows that key properties of bicompatible sequences depend on the particular pair of structures. While there always exist bicompatible sequences for random structure pairs, they are less suited to facilitate transitions. We show that native riboswitch sequences exhibit a distinct signature with regards to the ranking of their two phenotypes relative to the minimum free energy, suggesting a new criterion for identifying native sequences and sequences subjected to evolutionary pressure.