Why are phenotypic mutation rates much higher than genotypic mutation rates?

The evolution of genotypic mutation rates has been investigated in numerous theoretical and experimental studies. Mutations, however, occur not only when copying DNA, but also when building the phenotype, especially when translating and transcribing DNA to RNA and protein. Here we study the effect of such phenotypic mutations. We find a maximum phenotypic mutation rate, umax, that is compatible with maintaining a certain function of the organism. This may be called a phenotypic error threshold. In particular, we find a minimum phenotypic mutation rate, umin, with the property that there is (nearly) no selection pressure to reduce the rate of phenotypic mutations below this value. If there is a cost for lowering the phenotypic mutation rate, then umin is close to the optimum phenotypic mutation rate that maximizes the fitness of the organism. In our model, there is selective pressure to decrease the rate of genotypic mutations to zero, but to decrease the rate of phenotypic mutations only to a positive value. Despite its simplicity, our model can explain part of the huge difference between genotypic and phenotypic mutation rates that is observed in nature. The relevant data are summarized.     

Replication and mutation on neutral networks

Folding of RNA sequences into secondary structures is viewed as a map that assigns a uniquely defined base pairing pattern to every sequence. The mapping is non-invertible since many sequences fold into the same minimum free energy (secondary) structure or shape. The pre-images of this map, called neutral networks, are uniquely associated with the shapes and vice versa. Random graph theory is used to construct networks in sequence space which are suitable models for neutral networks. The theory of molecular quasispecies has been applied to replication and mutation on single-peak fitness landscapes. This concept is extended by considering evolution on degenerate multi-peak landscapes which originate from neutral networks by assuming that one particular shape is fitter than all the others. On such a single-shape landscape the superior fitness value is assigned to all sequences belonging to the master shape. All other shapes are lumped together and their fitness values are averaged in a way that is reminiscent of mean field theory. Replication and mutation on neutral networks are modeled by phenomenological rate equations as well as by a stochastic birth-and-death model. In analogy to the error threshold in sequence space the phenotypic error threshold separates two scenarios: (i) a stationary (fittest) master shape surrounded by closely related shapes and (ii) populations drifting through shape space by a diffusion-like process. The error classes of the quasispecies model are replaced by distance classes between the master shape and the other structures. Analytical results are derived for single-shape landscapes, in particular, simple expressions are obtained for the mean fraction of master shapes in a population and for phenotypic error thresholds. The analytical results are complemented by data obtained from computer simulation of the underlying stochastic processes. The predictions of the phenomenological approach on the single-shape landscape are very well reproduced by replication and mutation kinetics of tRNA(phe). Simulation of the stochastic process at a resolution of individual distance classes yields data which are in excellent agreement with the results derived from the birth-and-death model.     

A computer model of evolutionary optimization

Molecular evolution is viewed as a typical combinatorial optimization problem. We analyse a chemical reaction model which considers RNA replication including correct copying and point mutations together with hydrolytic degradation and the dilution flux of a flow reactor. The corresponding stochastic reaction network is implemented on a computer in order to investigate some basic features of evolutionary optimization dynamics. Characteristic features of real molecular systems are mimicked by folding binary sequences into unknotted two-dimensional structures. Selective values are derived from these molecular 'phenotypes' by an evaluation procedure which assigns numerical values to different elements of the secondary structure. The fitness function obtained thereby contains nontrivial long-range interactions which are typical for real systems. The fitness landscape also reveals quite involved and bizarre local topologies which we consider also representative of polynucleotide replication in actually occurring systems. Optimization operates on an ensemble of sequences via mutation and natural selection. The strategy observed in the simulation experiments is fairly general and resembles closely a heuristic widely applied in operations research areas. Despite the relative smallness of the system--we study 2000 molecules of chain length v = 70 in a typical simulation experiment--features typical for the evolution of real populations are observed as there are error thresholds for replication, evolutionary steps and quasistationary sequence distributions. The relative importance of selectively neutral or almost neutral variants is discussed quantitatively. Four characteristic ensemble properties, entropy of the distribution, ensemble correlation, mean Hamming distance and diversity of the population, are computed and checked for their sensitivity in recording major optimization events during the simulation.     

Revisiting Robustness and Evolvability: Evolution in Weighted Genotype Spaces

Robustness and evolvability are highly intertwined properties of biological systems. The relationship between these properties determines how biological systems are able to withstand mutations and show variation in response to them. Computational studies have explored the relationship between these two properties using neutral networks of RNA sequences (genotype) and their secondary structures (phenotype) as a model system. However, these studies have assumed every mutation to a sequence to be equally likely; the differences in the likelihood of the occurrence of various mutations, and the consequence of probabilistic nature of the mutations in such a system have previously been ignored. Associating probabilities to mutations essentially results in the weighting of genotype space. We here perform a comparative analysis of weighted and unweighted neutral networks of RNA sequences, and subsequently explore the relationship between robustness and evolvability. We show that assuming an equal likelihood for all mutations (as in an unweighted network), underestimates robustness and overestimates evolvability of a system. In spite of discarding this assumption, we observe that a negative correlation between sequence (genotype) robustness and sequence evolvability persists, and also that structure (phenotype) robustness promotes structure evolvability, as observed in earlier studies using unweighted networks. We also study the effects of base composition bias on robustness and evolvability. Particularly, we explore the association between robustness and evolvability in a sequence space that is AU-rich – sequences with an AU content of 80% or higher, compared to a normal (unbiased) sequence space. We find that evolvability of both sequences and structures in an AU-rich space is lesser compared to the normal space, and robustness higher. We also observe that AU-rich populations evolving on neutral networks of phenotypes, can access less phenotypic variation compared to normal populations evolving on neutral networks.     

In silico identification of functional divergence between the multiple groEL gene paralogs in Chlamydiae

Background

RNA molecules, through their dual appearance as sequence and structure, represent a suitable model to study evolutionary properties of quasispecies. The essential ingredient in this model is the differentiation between genotype (molecular sequences which are affected by mutation) and phenotype (molecular structure, affected by selection). This framework allows a quantitative analysis of organizational properties of quasispecies as they adapt to different environments, such as their robustness, the effect of the degeneration of the sequence space, or the adaptation under different mutation rates and the error threshold associated.

Results

We describe and analyze the structural properties of molecular quasispecies adapting to different environments both during the transient time before adaptation takes place and in the asymptotic state, once optimization has occurred. We observe a minimum in the adaptation time at values of the mutation rate relatively far from the phenotypic error threshold. Through the definition of a consensus structure, it is shown that the quasispecies retains relevant structural information in a distributed fashion even above the error threshold. This structural robustness depends on the precise shape of the secondary structure used as target of selection. Experimental results available for natural RNA populations are in qualitative agreement with our observations.

Conclusion

Adaptation time of molecular quasispecies to a given environment is optimized at values of the mutation rate well below the phenotypic error threshold. The optimal value results from a trade-off between diversity generation and fixation of advantageous mutants. The critical value of the mutation rate is a function not only of the sequence length, but also of the specific properties of the environment, in this case the selection pressure and the shape of the secondary structure used as target phenotype. Certain functional motifs of RNA secondary structure that withstand high mutation rates (as the ubiquitous hairpin motif) might appear early in evolution and be actually frozen evolutionary accidents.     

Evolution of mutational robustness in an RNA virus

Mutational (genetic) robustness is phenotypic constancy in the face of mutational changes to the genome. Robustness is critical to the understanding of evolution because phenotypically expressed genetic variation is the fuel of natural selection. Nonetheless, the evidence for adaptive evolution of mutational robustness in biological populations is controversial. Robustness should be selectively favored when mutation rates are high, a common feature of RNA viruses. However, selection for robustness may be relaxed under virus co-infection because complementation between virus genotypes can buffer mutational effects. We therefore hypothesized that selection for genetic robustness in viruses will be weakened with increasing frequency of co-infection. To test this idea, we used populations of RNA phage φ6 that were experimentally evolved at low and high levels of co-infection and subjected lineages of these viruses to mutation accumulation through population bottlenecking. The data demonstrate that viruses evolved under high co-infection show relatively greater mean magnitude and variance in the fitness changes generated by addition of random mutations, confirming our hypothesis that they experience weakened selection for robustness. Our study further suggests that co-infection of host cells may be advantageous to RNA viruses only in the short term. In addition, we observed higher mutation frequencies in the more robust viruses, indicating that evolution of robustness might foster less-accurate genome replication in RNA viruses.     

Evolution of phenotypic drug susceptibility and viral replication capacity during long-term virologic failure of protease inhibitor therapy in human immunodeficiency virus-infected adults

Continued use of antiretroviral therapy despite the emergence of drug-resistant human immunodeficiency virus (HIV) has been associated with the durable maintenance of plasma HIV RNA levels below pretherapy levels. The factors that may account for this partial control of viral replication were assessed in a longitudinal observational study of 20 HIV-infected adults who remained on a stable protease inhibitor-based regimen despite ongoing viral replication (plasma HIV RNA levels consistently >500 copies/ml). Longitudinal plasma samples (n = 248) were assayed for drug susceptibility and viral replication capacity (measured by using a single-cycle recombinant-virus assay). The initial treatment-mediated decrease in plasma viremia was directly proportional to the reduction in replicative capacity (P = 0.01). Early virologic rebound was associated the emergence of a virus population exhibiting increased protease inhibitor phenotypic resistance, while replicative capacity remained low. During long-term virologic failure, plasma HIV RNA levels often remained stable or increased slowly, while phenotypic resistance continued to increase and replicative capacity decreased slowly. The emergence of primary genotypic mutations within protease (particularly V82A, I84V, and L90M) was temporally associated with increasing phenotypic resistance and decreasing replicative capacity, while the emergence of secondary mutations within protease was associated with more-gradual changes in both phenotypic resistance and replicative capacity. We conclude that HIV may be constrained in its ability to become both highly resistant and highly fit and that this may contribute to the continued partial suppression of plasma HIV RNA levels that is observed in some patients with drug-resistant viremia.     

Evolution in vitro: analysis of a lineage of ribozymes

Background: Catalytic RNAs, or ribozymes, possessing both a genotype and a phenotype, are ideal molecules for evolution experiments in vitro. A large, heterogeneous pool of RNAs can be subjected to multiple rounds of selection, amplification and mutation, leading to the development of variants that have some desired phenotype. Such experiments allow the investigator to correlate specific genetic changes with quantifiable alterations of the catalytic properties of the RNA. In addition, patterns of evolutionary change can be discerned through a detailed examination of the genotypic composition of the evolving RNA population. Results: Beginning with a pool of 10(13) variants of the Tetrahymena ribozyme, we carried out in vitro evolution experiments that led to the generation of ribozymes with the ability to cleave an RNA substrate in the presence of Ca2+ ions, an activity that does not exist for the wild-type molecule. Over the course of 12 generations, a seven-error variant emerged that has substantial Ca(2+)-dependent RNA-cleavage activity. Advantageous mutations increased in frequency in the population according to three distinct dynamics--logarithmic, linear and transient. Through a comparative analysis of 31 individual variants, we infer how certain mutations influence the catalytic properties of the ribozyme. Conclusions: In vitro evolution experiments make it possible to elucidate important aspects of both evolutionary biology and structural biochemistry on a reasonable short time scale.     

Effective Population Size Predicts Local Rates but Not Local Mitigation of Read-through Errors

In correctly predicting that selection efficiency is positively correlated with the effective population size (N_e), the nearly neutral theory provides a coherent understanding of between-species variation in numerous genomic parameters, including heritable error (germline mutation) rates. Does the same theory also explain variation in phenotypic error rates and in abundance of error mitigation mechanisms? Translational read-through provides a model to investigate both issues as it is common, mostly nonadaptive, and has good proxy for rate (TAA being the least leaky stop codon) and potential error mitigation via “fail-safe” 3′ additional stop codons (ASCs). Prior theory of translational read-through has suggested that when population sizes are high, weak selection for local mitigation can be effective thus predicting a positive correlation between ASC enrichment and N_e. Contra to prediction, we find that ASC enrichment is not correlated with N_e. ASC enrichment, although highly phylogenetically patchy, is, however, more common both in unicellular species and in genes expressed in unicellular modes in multicellular species. By contrast, N_e does positively correlate with TAA enrichment. These results imply that local phenotypic error rates, not local mitigation rates, are consistent with a drift barrier/nearly neutral model.     

Functional Analysis of the Core Human Immunodeficiency Virus Type 1 Packaging Signal in a Permissive Cell Line

Packaging of type C retrovirus genomic RNAs into budding virions requires a highly specific interaction between the viral Gag precursor and unique cis-acting packaging signals on the full-length RNA genome, allowing the selection of this RNA species from among a pool of spliced viral RNAs and similar cellular RNAs. This process is thought to involve RNA secondary and tertiary structural motifs since there is little conservation of the primary sequence of this region between retroviruses. To confirm RNA secondary structures, which we and others have predicted for this region, disruptive, compensatory, and deletion mutations were introduced into proviral constructs, which were then assayed in a permissive cell line. Disruption of either of two predicted stem-loops was found to greatly reduce RNA encapsidation and replication, whereas compensatory mutations restoring base pairing to these stem-loops had a wild-type phenotype. A GGNGR motif was identified in the loops of three hairpins in this region. Results were consistent with the hypothesis that the process of efficient RNA encapsidation is linked to dimerization. Replication and encapsidation were shown to occur at a reduced rate in the absence of the previously described kissing hairpin motif.     

An in vivo selection method to optimize trans-splicing ribozymes

Group I intron ribozymes can repair mutated mRNAs by replacing the 3′-terminal portion of the mRNA with their own 3′-exon. This trans-splicing reaction has the potential to treat genetic disorders and to selectively kill cancer cells or virus-infected cells. However, these ribozymes have not yet been used in therapy, partially due to a low in vivo trans-splicing efficiency. Previous strategies to improve the trans-splicing efficiencies focused on designing and testing individual ribozyme constructs. Here we describe a method that selects the most efficient ribozymes from millions of ribozyme variants. This method uses an in vivo rescue assay where the mRNA of an inactivated antibiotic resistance gene is repaired by trans-splicing group I intron ribozymes. Bacterial cells that express efficient trans-splicing ribozymes are able to grow on medium containing the antibiotic chloramphenicol. We randomized a 5′-terminal sequence of the Tetrahymena thermophila group I intron and screened a library with 9 × 10⁶ ribozyme variants for the best trans-splicing activity. The resulting ribozymes showed increased trans-splicing efficiency and help the design of efficient trans-splicing ribozymes for different sequence contexts. This in vivo selection method can now be used to optimize any sequence in trans-splicing ribozymes.     

Natural and Unanticipated Modifiers of RNAi Activity in Caenorhabditis elegans

Organisms used as model genomics systems are maintained as isogenic strains, yet evidence of sequence differences between independently maintained wild-type stocks has been substantiated by whole-genome resequencing data and strain-specific phenotypes. Sequence differences may arise from replication errors, transposon mobilization, meiotic gene conversion, or environmental or chemical assault on the genome. Low frequency alleles or mutations with modest effects on phenotypes can contribute to natural variation, and it has proven possible for such sequences to become fixed by adapted evolutionary enrichment and identified by resequencing. Our objective was to identify and analyze single locus genetic defects leading to RNAi resistance in isogenic strains of Caenorhabditis elegans. In so doing, we uncovered a mutation that arose de novo in an existing strain, which initially frustrated our phenotypic analysis. We also report experimental, environmental, and genetic conditions that can complicate phenotypic analysis of RNAi pathway defects. These observations highlight the potential for unanticipated mutations, coupled with genetic and environmental phenomena, to enhance or suppress the effects of known mutations and cause variation between wild-type strains.     

Sequence-Specific Fidelity Alterations Associated with West Nile Virus Attenuation in Mosquitoes

High rates of error-prone replication result in the rapid accumulation of genetic diversity of RNA viruses. Recent studies suggest that mutation rates are selected for optimal viral fitness and that modest variations in replicase fidelity may be associated with viral attenuation. Arthropod-borne viruses (arboviruses) are unique in their requirement for host cycling and may necessitate substantial genetic and phenotypic plasticity. In order to more thoroughly investigate the correlates, mechanisms and consequences of arbovirus fidelity, we selected fidelity variants of West Nile virus (WNV; Flaviviridae, Flavivirus) utilizing selection in the presence of a mutagen. We identified two mutations in the WNV RNA-dependent RNA polymerase associated with increased fidelity, V793I and G806R, and a single mutation in the WNV methyltransferase, T248I, associated with decreased fidelity. Both deep-sequencing and in vitro biochemical assays confirmed strain-specific differences in both fidelity and mutational bias. WNV fidelity variants demonstrated host-specific alterations to replicative fitness in vitro, with modest attenuation in mosquito but not vertebrate cell culture. Experimental infections of colonized and field populations of Cx. quinquefaciatus demonstrated that WNV fidelity alterations are associated with a significantly impaired capacity to establish viable infections in mosquitoes. Taken together, these studies (i) demonstrate the importance of allosteric interactions in regulating mutation rates, (ii) establish that mutational spectra can be both sequence and strain-dependent, and (iii) display the profound phenotypic consequences associated with altered replication complex function of flaviviruses.     

Polymerase ribozyme efficiency increased by G/T-rich DNA oligonucleotides

The RNA world hypothesis states that the early evolution of life went through a stage where RNA served as genome and as catalyst. The replication of RNA world organisms would have been facilitated by ribozymes that catalyze RNA polymerization. To recapitulate an RNA world in the laboratory, a series of RNA polymerase ribozymes was developed previously. However, these ribozymes have a polymerization efficiency that is too low for self-replication, and the most efficient ribozymes prefer one specific template sequence. The limiting factor for polymerization efficiency is the weak sequence-independent binding to its primer/template substrate. Most of the known polymerase ribozymes bind an RNA heptanucleotide to form the P2 duplex on the ribozyme. By modifying this heptanucleotide, we were able to significantly increase polymerization efficiency. Truncations at the 3'-terminus of this heptanucleotide increased full-length primer extension by 10-fold, on a specific template sequence. In contrast, polymerization on several different template sequences was improved dramatically by replacing the RNA heptanucleotide with DNA oligomers containing randomized sequences of 15 nt. The presence of G and T in the random sequences was sufficient for this effect, with an optimal composition of 60% G and 40% T. Our results indicate that these DNA sequences function by establishing many weak and nonspecific base-pairing interactions to the single-stranded portion of the template. Such low-specificity interactions could have had important functions in an RNA world.     

Topological structure of the space of phenotypes: the case of RNA neutral networks

The evolution and adaptation of molecular populations is constrained by the diversity accessible through mutational processes. RNA is a paradigmatic example of biopolymer where genotype (sequence) and phenotype (approximated by the secondary structure fold) are identified in a single molecule. The extreme redundancy of the genotype-phenotype map leads to large ensembles of RNA sequences that fold into the same secondary structure and can be connected through single-point mutations. These ensembles define neutral networks of phenotypes in sequence space. Here we analyze the topological properties of neutral networks formed by 12-nucleotides RNA sequences, obtained through the exhaustive folding of sequence space. A total of 4(12) sequences fragments into 645 subnetworks that correspond to 57 different secondary structures. The topological analysis reveals that each subnetwork is far from being random: it has a degree distribution with a well-defined average and a small dispersion, a high clustering coefficient, and an average shortest path between nodes close to its minimum possible value, i.e. the Hamming distance between sequences. RNA neutral networks are assortative due to the correlation in the composition of neighboring sequences, a feature that together with the symmetries inherent to the folding process explains the existence of communities. Several topological relationships can be analytically derived attending to structural restrictions and generic properties of the folding process. The average degree of these phenotypic networks grows logarithmically with their size, such that abundant phenotypes have the additional advantage of being more robust to mutations. This property prevents fragmentation of neutral networks and thus enhances the navigability of sequence space. In summary, RNA neutral networks show unique topological properties, unknown to other networks previously described.