Biology subjects

Garcia-Galindo, P.

Publications and source records attributed to Garcia-Galindo, P..

4 recordsLinked to original sources

bioRxiv2026

Comparing Random and Natural RNA Boltzmann Ensembles

A morphospace is an abstract space of theoretically possible biological traits, shapes, or property values. It is interesting to explore which parts of a morphospace life occupies, as compared to those parts which could be occupied, but are not. Comparing random and natural non-coding (nc) RNA secondary structures is an established approach to studying morphospace occupation for RNA structures. Most earlier studies have focused on the minimum free energy (MFE) structure, while relatively few have looked at the Boltzmann distribution, describing the ensemble of energetically suboptimal RNA folds. These suboptimal structures may have important roles and functions, and hence should be examined carefully. Here we compare random and natural ncRNA in terms of their Boltzmann distributions, finding that natural RNA tend to have very similar profiles to random RNA, with the main difference being that natural RNA are slightly more energetically stable, except for very short sequences (20 to 30 nucleotides) which appear to be equally or slightly less stable. We infer that natural ncRNA and random RNA occupy similar parts of the morphospace, indicating that the biophysics of the genotype-phenotype map largely determines the ensemble properties of ncRNA.

biophysics↗

bioRxiv2025

Phenotypic cliffs in the RNA genotype-phenotype map

Point mutations of a genotype can leave the phenotype unchanged, or change it, in some cases radically. The extent of this phenotypic change can critically impact fitness. To investigate the range of possible phenotypic changes that result from point mutations, we analyse the structure of the well-established RNA genotype-phenotype (GP) map for sequences of length 12 by developing a general phenotypic distance framework. Our analysis reveals that phenotypes are more likely to be surrounded by similar phenotypes than would be expected by chance. Furthermore, we see that generalised versions of the GP map metrics of frequency, robustness, and evolvability that take phenotypic distance into account still exhibit the same fundamental structural relationships that are observed in many GP maps. We also develop site-specific quantities for robustness, evolvability, and accessible phenotypic distance, which reveal a key insight: RNA secondary structure (SS) sites that are more likely to be neutral and access fewer new phenotypes tend to produce larger changes in phenotype when a change does occur. Robust sites therefore produce cliffs in the landscape (flat in some directions, steep in others) whereas non-robust sites give rise to more gently undulating landscapes.

biophysics↗

bioRxiv2024

Phenotypic plasticity can be an evolutionary response to fluctuating environments

Phenotypic plasticity refers to the ability of a single genotype to produce multiple distinct phenotypes. Using the computationally tractable genotype-phenotype (GP) map of RNA secondary structures, we model RNA phenotypic plasticity using the Boltzmann distribution of secondary structures for each genotype. Through evolutionary simulations that involve periodic environmental switching on the GP map, we reveal that RNA phenotypes can adapt to these fluctuations towards an optimal plasticity. The optimal phenotypes exhibit dominant near-equal Boltzmann probabilities of distinct structures, each representing the fittest structure for each alternating environment. Our findings demonstrate that phenotypic plasticity, a widespread biological phenomenon, is a fundamental evolutionary response to changing environments for RNA secondary structure. We also find naturally evolved functional RNAs that exhibit optimal plasticity unlikely to arise by neutral drift alone, suggesting functional relevance in fluctuating environments.

biophysics↗

bioRxiv2023

The non-deterministic genotype-phenotype map of RNA secondary structure

Selection and variation are both key aspects in the evolutionary process. Previous research on the mapping between molecular sequence (genotype) and molecular fold (phenotype) has shown the presence of several structural properties in different biological contexts, implying that these might be universal in evolutionary spaces. The deterministic genotype-phenotype (GP) map that links short RNA sequences to minimum free energy secondary structures has been studied extensively because of its computational tractability and biologically realistic nature. However, this mapping ignores the phenotypic plasticity of RNA. We define a GP map that incorporates non-deterministic phenotypes, and take RNA as a case study; we use the Boltzmann probability distribution of folded structures and examine the structural properties of non-deterministic (ND) GP maps for RNA sequences of length 12 and coarse-grained RNA structures of length 30 (RNAshapes30). A framework is presented to study robustness, evolvability and neutral spaces in the non-deterministic map. This framework is validated by demonstrating close correspondence between the non-deterministic quantities and sample averages of their deterministic counterparts. When using the non-deterministic framework we observe the same structural properties as in the deterministic GP map, such as bias, negative correlation between genotypic robustness and evolvability, and positive correlation between phenotypic robustness and evolvability.

biophysics↗