The effect of recombination on the neutral evolution of genetic robustness

Conventional population genetics considers the evolution of a limited number of genotypes corresponding to phenotypes with different fitness. As model phenotypes, in particular RNA secondary structure, have become computationally tractable, however, it has become apparent that the context dependent effect of mutations and the many-to-one nature inherent in these genotype-phenotype maps can have fundamental evolutionary consequences. It has previously been demonstrated that populations of genotypes evolving on the neutral networks corresponding to all genotypes with the same secondary structure only through neutral mutations can evolve mutational robustness [E. van Nimwegen, J.P. Crutchfield, M. Huynen, Neutral evolution of mutational robustness, Proc. Natl. Acad. Sci. USA 96(17), 9716-9720 (1999)], by concentrating the population on regions of high neutrality. Introducing recombination we demonstrate, through numerically calculating the stationary distribution of an infinite population on ensembles of random neutral networks that mutational robustness is significantly enhanced and further that the magnitude of this enhancement is sensitive to details of the neutral network topology. Through the simulation of finite populations of genotypes evolving on random neutral networks and a scaled down microRNA neutral network, we show that even in finite populations recombination will still act to focus the population on regions of locally high neutrality.     

Degeneracy: A design principle for achieving robustness and evolvability

Robustness, the insensitivity of some of a biological system's functionalities to a set of distinct conditions, is intimately linked to fitness. Recent studies suggest that it may also play a vital role in enabling the evolution of species. Increasing robustness, so is proposed, can lead to the emergence of evolvability if evolution proceeds over a neutral network that extends far throughout the fitness landscape. Here, we show that the design principles used to achieve robustness dramatically influence whether robustness leads to evolvability. In simulation experiments, we find that purely redundant systems have remarkably low evolvability while degenerate, i.e. partially redundant, systems tend to be orders of magnitude more evolvable. Surprisingly, the magnitude of observed variation in evolvability can neither be explained by differences in the size nor the topology of the neutral networks. This suggests that degeneracy, a ubiquitous characteristic in biological systems, may be an important enabler of natural evolution. More generally, our study provides valuable new clues about the origin of innovations in complex adaptive systems.     

Selection for thermostability can lead to the emergence of mutational robustness in an RNA virus

Mutational robustness has important evolutionary implications, yet the mechanisms leading to its emergence remain poorly understood. One possibility is selection acting on a correlated trait, as for instance thermostability (plastogenetic congruence). Here, we examine the correlation between mutational robustness and thermostability in experimental populations of the RNA bacteriophage Qβ. Thermostable viruses evolved after only six serial passages in the presence of heat shocks, and genome sequencing suggested that thermostability can be conferred by several alternative mutations. To test whether thermostable viruses have increased mutational robustness, we performed additional passages in the presence of nitrous acid. Whereas in control lines this treatment produced the expected reduction in growth rate caused by the accumulation of deleterious mutations, thermostable viruses showed no such reduction, indicating that they are more resistant to mutagenesis. Our results suggest that selection for thermostability can lead to the emergence of mutational robustness driven by plastogenetic congruence. As temperature is a widespread selective pressure in nature, the mechanism described here may be relevant to the evolution of mutational robustness.     

ARDesigner: a web-based system for allosteric RNA design

RNA molecules play vital informational, structural, and functional roles in molecular biology, making them ideal targets for synthetic biology. However, several challenges remain for engineering novel allosteric RNA molecules, and the development of efficient computational design techniques is vitally needed. Here we describe the development of Allosteric RNA Designer (ARDesigner), a user-friendly and freely available web-based system for allosteric RNA design that incorporates mutational robustness in the design process. The system output includes detailed design information in a graphical HTML format. We used ARDesigner to engineer a temperature-sensitive AR, and found that the resulting design satisfied the prescribed properties/input. ARDesigner provides a simple means for researchers to design allosteric RNAs with specific properties. With its versatile framework and possibilities for further enhancement, ARDesigner may serve as a useful tool for synthetic biologists and therapeutic design. ARDesigner and its executable version are freely available at http://biotech.bmi.ac.cn/ARDesigner.     

In silico predicted robustness of viroid RNA secondary structures. II. Interaction between mutation pairs

Viroids are plant subviral pathogens whose genomes are constituted by a single-stranded and covalently closed small RNA molecule that does not encode for any protein. Most of the 29 described viroid species fold into a rodlike or quasi-rodlike structure, whereas a few of them fold as highly branched structures. In a previous study, we used RNA thermodynamic secondary structure prediction algorithms to compare the mutational robustness of all viroid species. Here we used the same approach to explore the sign and strength of epistasis among pairs of random mutations. We found that antagonistic interactions were more abundant than synergistic ones. However, despite their lower frequency, synergistic interactions tended to be more intense. Mutational robustness and the intensity of epistasis were correlated such that viroid species with large average mutational effects showed stronger antagonistic epistasis, whereas viroids with mild average mutational effects showed weaker antagonistic interactions. The strength of antagonistic epistasis decreased with genome complexity as a consequence of the gained robustness of duplicated genomes. In good agreement with our previous finding of an evolutionary trend toward increased robustness, we now found a trend toward reduced antagonistic epistasis.     

In silico predicted robustness of viroids RNA secondary structures. I. The effect of single mutations

Viroids are plant subviral pathogens whose genomes are constituted by a single-stranded and covalently closed small RNA molecule that does not encode for any protein. Despite this genomic simplicity, they are able of inducing devastating symptoms in susceptible plants. Most of the 29 described viroid species fold into a rodlike or quasi-rodlike structure, whereas a few of them fold as branched structures. The shape of these RNA structures is perhaps one of the most characteristic properties of viroids and sometimes is considered their only phenotype. Here we use RNA thermodynamic secondary structure prediction algorithms to compare the mutational robustness of all viroid species. After characterizing the statistical properties of the distribution of mutational effects on structure stability and the wideness of neutral neighborhood for each viroid species, we show an evolutionary trend toward increased structural robustness during viroid radiation, giving support to the adaptive value of robustness. Differences in robustness among the 2 viroid families can be explained by the larger fragility of branched structures compared with the rodlike ones. We also show that genomic redundancy can contribute to the robustness of these simple RNA genomes.     

A genetic background with low mutational robustness is associated with increased adaptability to a novel host in an RNA virus

Although mutational robustness is central to many evolutionary processes, its relationship to evolvability remains poorly understood and has been very rarely tested experimentally. Here, we measure the evolvability of Vesicular stomatitis virus in two genetic backgrounds with different levels of mutational robustness. We passaged the viruses into a novel cell type to model a host‐jump episode, quantified changes in infectivity and fitness in the new host, evaluated the cost of adaptation in the original host and analyzed the genetic basis of this adaptation. Lineages evolved from the less robust genetic background demonstrated increased adaptability, paid similar costs of adaptation to the new host and fixed approximately the same number of mutations as their more robust counterparts. Theory predicts that robustness can promote evolvability only in systems where large sets of genotypes are connected by effectively neutral mutations. We argue that this condition might not be fulfilled generally in RNA viruses.     

Pattern generation in molecular evolution: Exploitation of the variation in RNA landscapes

Evolution of RNA secondary structure is studied using simulation techniques and statistical analysis of fitness landscapes. The transition from RNA sequence to RNA secondary structure leads to fitness landscapes that have local variations in their ruggedness. Evolution exploits these variations. In stable environments it moves the quasispecies toward relatively flat peaks, where not only the master sequence but also its mutants have a high fitness. In a rapidly changing environment, the situation is reversed; evolution moves the quasispecies to a region where the correlation between secondary structures of neighboring RNA sequences is relatively low. In selection for simple secondary structures the movement toward flat peaks leads to pattern generation in the RNA sequences. Patterns are generated at the level of polynucleotide frequencies and the distribution of purines and pyrimidines. The patterns increase the modularity of the sequence. They thereby prevent the formation of alternative secondary structures after mutations. The movement of the quasispecies toward relatively rugged parts of the landscape results in pattern generation at the level of the RNA secondary structure. The base-pairing frequency of the sequences increases. The patterns that are generated in the RNA sequences and the RNA secondary structures are not directly selected for and can be regarded as a side effect of the evolutionary dynamics of the system. Correspondence to: M.A. Huynen     

Statistics of RNA melting kinetics

We present and study the behavior of a simple kinetic model for the melting of RNA secondary structures, given that those structures are known. The model is then used as a map that. assigns structure dependent overall rate constants of melting (or refolding) to a sequence. This induces a landscape of reaction rates, or activation energies, over the space of sequences with fixed length. We study the distribution and the correlation structure of these activation energies. Correspondence to: P. Schuster     

Motif frequency and evolutionary search times in RNA populations

RNA molecules, through their dual identity as sequence and structure, are an appropriate experimental and theoretical model to study the genotype-phenotype map and evolutionary processes taking place in simple replicator populations. In this computational study, we relate properties of the sequence-structure map, in particular the abundance of a given secondary structure in a random pool, with the number of replicative events that an initially random population of sequences needs to find that structure through mutation and selection. For common structures, this search process turns out to be much faster than for rare structures. Furthermore, search and fixation processes are more efficient in a wider range of mutation rates for common structures, thus indicating that evolvability of RNA populations is not simply determined by abundance. We also find significant differences in the search and fixation processes for structures of same abundance, and relate them with the number of base pairs forming the structure. Moreover, the influence of the nucleotide content of the RNA sequences on the search process is studied. Our results advance in the understanding of the distribution and attainability of RNA secondary structures. They hint at the fact that, beyond sequence length and sequence-to-function redundancy, the mutation rate that permits localization and fixation of a given phenotype strongly depends on its relative abundance and global, in general non-uniform, distribution in sequence space.     

Functional links and robustness in food webs

The robustness of ecosystems to species losses is a central question in ecology, given the current pace of extinctions and the many species threatened by human impacts, including habitat destruction and climate change. Robustness from the perspective of secondary extinctions has been addressed in the context of food webs to consider the complex network of species interactions that underlie responses to perturbations. In-silico removal experiments have examined the structural properties of food webs that enhance or hamper the robustness of ecosystems to species losses, with a focus on the role of hubs, the most connected species. Here we take a different approach and focus on the role of the connections themselves. We show that trophic links can be divided into functional and redundant based on their contribution to robustness. The analysis of empirical webs shows that hubs are not necessarily the most important species as they may hold many redundant links. Furthermore, the fraction of functional connections is high and constant across systems regardless of size and interconnectedness. The main consequence of this scaling pattern is that ecosystem robustness can be considerably reduced by species extinctions even when these do not result in any secondary extinctions. This introduces the possibility of tipping points in the collapse of ecosystems.     

The Robustness of Naturally and Artificially Selected Nucleic Acid Secondary Structures

Thermodynamic stability and mutational robustness of secondary structure are critical to the function and evolutionary longevity of RNA molecules. We hypothesize that natural and artificial selection for functional molecules favors the formation of structures that are stable to both thermal and mutational perturbation. There is little direct evidence, however, that functional RNA molecules have been selected for their stability. Here we use thermodynamic secondary structure prediction algorithms to compare the thermal and mutational robustness of over 1000 naturally and artificially evolved molecules. Although we find evidence for the evolution of both types of stability in both sets of molecules, the naturally evolved functional RNA molecules were significantly more stable than those selected in vitro, and artificially evolved catalysts (ribozymes) were more stable than artificially evolved binding species (aptamers). The thermostability of RNA molecules bred in the laboratory is probably not constrained by a lack of suitable variation in the sequence pool but, rather, by intrinsic biases in the selection process.     

Simulating the Folding Pathway of RNA Secondary Structure Using the Modified Ant Colony Algorithm

<正> A new method for simulating the folding pathway of RNA secondary structure using the modified ant colony algorithmis proposed.For a given RNA sequence,the set of all possible stems is obtained and the energy of each stem iscalculated and stored at the initial stage.Furthermore,a more realistic formula is used to compute the energy ofmulti-branch loop in the following iteration.Then a folding pathway is simulated,including such processes as constructionof the heuristic information,the rule of initializing the pheromone,the mechanism of choosing the initial andnext stem and the strategy of updating the pheromone between two different stems.Finally by testing RNA sequences withknown secondary structures from the public databases,we analyze the experimental data to select appropriate values forparameters.The measure indexes show that our procedure is more consistent with phylogenetically proven structures thansoftware RNAstructure sometimes and more effective than the standard Genetic Algorithm.