Comparative RNA Genomics

Over the last quarter of a century it has become clear that RNA is much more than just a boring intermediate in protein expression. Ancient RNAs still appear in the core information metabolism and comprise a surprisingly large component in bacterial gene regulation. A common theme with these types of mostly small RNAs is their reliance of conserved secondary structures. Large-scale sequencing projects, on the other hand, have profoundly changed our understanding of eukaryotic genomes. Pervasively transcribed, they give rise to a plethora of large and evolutionarily extremely flexible non-coding RNAs that exert a vastly diverse array of molecule functions. In this chapter we provide a-necessarily incomplete-overview of the current state of comparative analysis of non-coding RNAs, emphasizing computational approaches as a means to gain a global picture of the modern RNA world.

Why are viral genomes so fragile? The bottleneck hypothesis

If they undergo new mutations at each replication cycle, why are RNA viral genomes so fragile, with most mutations being either strongly deleterious or lethal? Here we provide theoretical and numerical evidence for the hypothesis that genetic fragility is partly an evolutionary response to the multiple population bottlenecks experienced by viral populations at various stages of their life cycles. Modelling within-host viral populations as multi-type branching processes, we show that mutational fragility lowers the rate at which Muller’s ratchet clicks and increases the survival probability through multiple bottlenecks. In the context of a susceptible-exposed-infectious-recovered epidemiological model, we find that the attack rate of fragile viral strains can exceed that of more robust strains, particularly at low infectivities and high mutation rates. Our findings highlight the importance of demographic events such as transmission bottlenecks in shaping the genetic architecture of viral pathogens.

Given that most mutations are deleterious, high mutation rates carry a significant evolutionary cost. To reduce this burden, an obvious evolutionary solution would be to reduce the fitness cost of mutations by becoming more robust; this solution is indeed selected in populations of constantly large size. Here, we show that when populations regularly experience bottlenecks, as viruses do upon transmission to a new host, a less obvious solution becomes more viable: namely, to increase the fitness cost of mutations so that unfit mutants are less likely to fix at each passage. This could explain why viruses—especially RNA viruses—do in fact have very fragile genomes.

Emergency Services of Viral RNAs: Repair and Remodeling

Reproduction of RNA viruses is typically error-prone due to the infidelity of their replicative machinery and the usual lack of proofreading mechanisms. The error rates may be close to those that kill the virus. Consequently, populations of RNA viruses are represented by heterogeneous sets of genomes with various levels of fitness. This is especially consequential when viruses encounter various bottlenecks and new infections are initiated by a single or few deviating genomes. Nevertheless, RNA viruses are able to maintain their identity by conservation of major functional elements. This conservatism stems from genetic robustness or mutational tolerance, which is largely due to the functional degeneracy of many protein and RNA elements as well as to negative selection. Another relevant mechanism is the capacity to restore fitness after genetic damages, also based on replicative infidelity. Conversely, error-prone replication is a major tool that ensures viral evolvability. The potential for changes in debilitated genomes is much higher in small populations, because in the absence of stronger competitors low-fit genomes have a choice of various trajectories to wander along fitness landscapes. Thus, low-fit populations are inherently unstable, and it may be said that to run ahead it is useful to stumble. In this report, focusing on picornaviruses and also considering data from other RNA viruses, we review the biological relevance and mechanisms of various alterations of viral RNA genomes as well as pathways and mechanisms of rehabilitation after loss of fitness. The relationships among mutational robustness, resilience, and evolvability of viral RNA genomes are discussed.

Comparative RNA Genomics

Over the last two decades it has become clear that RNA is much more than just a boring intermediate in protein expression. Ancient RNAs still appear in the core information metabolism and comprise a surprisingly large component in bacterial gene regulation. A common theme with these types of mostly small RNAs is their reliance of conserved secondary structures. Large scale sequencing projects, on the other hand, have profoundly changed our understanding of eukaryotic genomes. Pervasively transcribed, they give rise to a plethora of large and evolutionarily extremely flexible noncoding RNAs that exert a vastly diverse array of molecule functions. In this chapter we provide a-necessarily incomplete-overview of the current state of comparative analysis of noncoding RNAs, emphasizing computational approaches as a means to gain a global picture of the modern RNA world.

Independent evolution of tetraloop in enterovirus oriL replicative element and its putative binding partners in virus protein 3C

Background

Enteroviruses are small non-enveloped viruses with a (+) ssRNA genome with one open reading frame. Enterovirus protein 3C (or 3CD for some species) binds the replicative element oriL to initiate replication. The replication of enteroviruses features a low-fidelity process, which allows the virus to adapt to the changing environment on the one hand, and requires additional mechanisms to maintain the genome stability on the other. Structural disturbances in the apical region of oriL domain d can be compensated by amino acid substitutions in positions 154 or 156 of 3C (amino acid numeration corresponds to poliovirus 3C), thus suggesting the co-evolution of these interacting sequences in nature. The aim of this work was to understand co-evolution patterns of two interacting replication machinery elements in enteroviruses, the apical region of oriL domain d and its putative binding partners in the 3C protein.

Methods

To evaluate the variability of the domain d loop sequence we retrieved all available full enterovirus sequences (>6, 400 nucleotides), which were present in the NCBI database on February 2017 and analysed the variety and abundance of sequences in domain d of the replicative element oriL and in the protein 3C.

Results

A total of 2,842 full genome sequences was analysed. The majority of domain d apical loops were tetraloops, which belonged to consensus YNHG (Y = U/C, N = any nucleotide, H = A/C/U). The putative RNA-binding tripeptide 154–156 (Enterovirus C 3C protein numeration) was less diverse than the apical domain d loop region and, in contrast to it, was species-specific.

Discussion

Despite the suggestion that the RNA-binding tripeptide interacts with the apical region of domain d, they evolve independently in nature. Together, our data indicate the plastic evolution of both interplayers of 3C-oriL recognition.

Evidence of a Direct Evolutionary Selection for Strong Folding and Mutational Robustness Within HIV Coding Regions

A large number of studies demonstrated the importance of different HIV RNA structural elements at all stages of the viral life cycle. Nevertheless, the significance of many of these structures is unknown, and plausibly new regions containing RNA structure-mediated regulatory signals remain to be identified. An important characteristic of genomic regions carrying functionally significant secondary structures is their mutational robustness, that is, the extent to which a sequence remains constant in spite of despite mutations in terms of its underlying secondary structure. Structural robustness to mutations is expected to be important in the case of functional RNA structures in viruses with high mutation rate; it may prevent fitness loss due to disruption of possibly functional conformations, pointing to the specific significance of the corresponding genomic region. In the current work, we perform a genome-wide computational analysis to detect signals of a direct evolutionary selection for strong folding and RNA structure-based mutational robustness within HIV coding sequences. We provide evidence that specific regions of HIV structural genes undergo an evolutionary selection for strong folding; in addition, we demonstrate that HIV Rev responsive element seems to undergo a direct evolutionary selection for increased secondary structure robustness to point mutations. We believe that our analysis may enable a better understanding of viral evolutionary dynamics at the RNA structural level and may benefit to practical efforts of engineering antiviral vaccines and novel therapeutic approaches.

Distribution of mutational fitness effects and of epistasis in the 5' untranslated region of a plant RNA virus

BACKGROUND

Understanding the causes and consequences of phenotypic variability is a central topic of evolutionary biology. Mutations within non-coding cis-regulatory regions are thought to be of major effect since they affect the expression of downstream genes. To address the evolutionary potential of mutations affecting such regions in RNA viruses, we explored the fitness properties of mutations affecting the 5'-untranslated region (UTR) of a prototypical member of the picorna-like superfamily, Tobacco etch virus (TEV). This 5' UTR acts as an internal ribosomal entry site (IRES) and is essential for expression of all viral genes.

RESULTS

We determined in vitro the folding of 5' UTR using the selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) technique. Then, we created a collection of single-nucleotide substitutions on this region and evaluated the statistical properties of their fitness effects in vivo. We found that, compared to random mutations affecting coding sequences, mutations at the 5' UTR were of weaker effect. We also created double mutants by combining pairs of these single mutations and found variation in the magnitude and sign of epistatic interactions, with an enrichment of cases of positive epistasis. A correlation exists between the magnitude of fitness effects and the size of the perturbation made in the RNA folding structure, suggesting that the larger the departure from the predicted fold, the more negative impact in viral fitness.

CONCLUSIONS

Evidence that mutational fitness effects on the short 5' UTR regulatory sequence of TEV are weaker than those affecting its coding sequences have been found. Epistasis among pairs of mutations on the 5' UTR ranged between the extreme cases of synthetic lethal and compensatory. A plausible hypothesis to explain all these observations is that the interaction between the 5' UTR and the host translational machinery was shaped by natural selection to be robust to mutations, thus ensuring the homeostatic expression of viral genes even at high mutation rates.

Unmasking the information encoded as structural motifs of viral RNA genomes: a potential antiviral target

RNA viruses show enormous capacity to evolve and adapt to new cellular and molecular contexts, a consequence of mutations arising from errors made by viral RNA-dependent RNA polymerase during replication. Sequence variation must occur, however, without compromising functions essential for the completion of the viral cycle. RNA viruses are safeguarded in this respect by their genome carrying conserved information that does not code only for proteins but also for the formation of structurally conserved RNA domains that directly perform these critical functions. Functional RNA domains can interact with other regions of the viral genome and/or proteins to direct viral translation, replication and encapsidation. They are therefore potential targets for novel therapeutic strategies. This review summarises our knowledge of the functional RNA domains of human RNA viruses and examines the achievements made in the design of antiviral compounds that interfere with their folding and therefore their function.

MicroRNA precursors are not structurally robust but plastic

Robustness is considered a ubiquitous property of living systems at all levels of organization, and small noncoding RNA (sncRNA) is a genuine model for its study at the molecular level. In this communication, we question whether microRNA precursors (pre-miRNAs) are actually structurally robust, as previously suggested. We found that natural pre-miRNAs are not more robust than expected under an appropriate null model. On the contrary, we found that eukaryotic pre-miRNAs show a significant enrichment in conformational flexibility at the thermal equilibrium of the molecule, that is, in their plasticity. Our results further support the selection for functional diversification and evolvability in sncRNAs.

Codon usage determines the mutational robustness, evolutionary capacity, and virulence of an RNA virus

RNA viruses exist as dynamic and diverse populations shaped by constant mutation and selection. Yet little is known about how the mutant spectrum contributes to virus evolvability and pathogenesis. Because several codon choices are available for a given amino acid, a central question concerns whether viral sequences have evolved to optimize not only the protein coding consensus, but also the DNA/RNA sequences accessible through mutation. Here we directly test this hypothesis by comparing wild-type poliovirus to synthetic viruses carrying re-engineered capsid sequences with hundreds of synonymous mutations. Strikingly, such rewiring of the population's mutant network reduced its robustness and attenuated the virus in an animal model of infection. We conclude that the position of a virus in sequence space defines its mutant spectrum, evolutionary trajectory, and pathogenicity. This organizing principle for RNA virus populations confers tolerance to mutations and facilitates replication and spread within the dynamic host environment.

The role of mutational robustness in RNA virus evolution

RNA viruses face dynamic environments and are masters at adaptation. During their short 'lifespans', they must surmount multiple physical, anatomical and immunological challenges. Central to their adaptative capacity is the enormous genetic diversity that characterizes RNA virus populations. Although genetic diversity increases the rate of adaptive evolution, low replication fidelity can present a risk because excess mutations can lead to population extinction. In this Review, we discuss the strategies used by RNA viruses to deal with the increased mutational load and consider how this mutational robustness might influence viral evolution and pathogenesis.

RNA virus genetic robustness: possible causes and some consequences

In general terms, robustness is the capacity of biological systems to function in spite of genetic or environmental perturbations. The small and compacted genomes and high mutation rates of RNA viruses, as well as the ever-changing environments wherein they replicate, create the conditions for robustness to be advantageous. In this review, I will enumerate possible mechanisms by which viral populations may acquire robustness, distinguishing between mechanisms that are inherent to virus replication and population dynamics and those that result from the interaction with host factors. Then, I will move to review some evidences that RNA virus populations are robust indeed. Finally, I will comment on the implications of robustness for virus evolvability, the emergence of new viruses and the efficiency of lethal mutagenesis as an antiviral strategy.

The role of robustness in phenotypic adaptation and innovation

Phenotypes that vary in response to DNA mutations are essential for evolutionary adaptation and innovation. Therefore, it seems that robustness, a lack of phenotypic variability, must hinder adaptation. The main purpose of this review is to show why this is not necessarily correct. There are two reasons. The first is that robustness causes the existence of genotype networks--large connected sets of genotypes with the same phenotype. I discuss why genotype networks facilitate phenotypic variability. The second reason emerges from the evolutionary dynamics of evolving populations on genotype networks. I discuss how these dynamics can render highly robust phenotypes more variable, using examples from protein and RNA macromolecules. In addition, robustness can help avoid an important evolutionary conflict between the interests of individuals and populations-a conflict that can impede evolutionary adaptation.

A distinct class of internal ribosomal entry site in members of the Kobuvirus and proposed Salivirus and Paraturdivirus genera of the Picornaviridae

The 5'-untranslated regions (5' UTRs) of picornavirus genomes contain an internal ribosomal entry site (IRES) that promotes the end-independent initiation of translation. Picornavirus IRESs are classified into four structurally distinct groups, each with different initiation factor requirements. Here, we identify a fifth IRES class in members of Kobuvirus, Salivirus, and Paraturdivirus genera of Picornaviridae: Aichi virus (AV), bovine kobuvirus (BKV), canine kobuvirus (CKoV), mouse kobuvirus (MKoV), sheep kobuvirus (SKV), salivirus A (SV-A), turdivirus 2 (TV2), and TV3. The 410-nucleotide (nt)-long AV IRES comprises four domains (I to L), including a hairpin (L) that overlaps a Yn-Xm-AUG (pyrimidine tract/spacer/initiation codon) motif. SV-A, CKoV, and MKoV also contain these four domains, whereas BKV, SKV, and TV2/TV3 5' UTRs contain domains that are related to domain I and equivalent to domains J and K but lack an AV-like domain L. These IRESs are located at different relative positions between a conserved 5'-terminal origin of replication and divergent coding sequences. Elements in these IRESs also occur elsewhere: domain J's apical subdomain, which contains a GNRA tetraloop, matches an element in type 1 IRESs, and eIF4G-binding motifs in domain K and in type 2 IRESs are identical. Other elements are unique, and their presence leads to unique initiation factor requirements. In vitro reconstitution experiments showed that like AV, but in contrast to other currently characterized IRESs, SV-A requires the DExH-box protein DHX29 during initiation, which likely ensures that the initiation codon sequestered in domain L is properly accommodated in the ribosomal mRNA-binding cleft.

Bioinformatic analysis of the neutrality of RNA secondary structure elements across genotypes reveals evidence for direct evolution of genetic robustness in HCV

The properties and origin of genetic robustness have recently been investigated in several works that examined microRNA stem-loop structures, and a variety of conclusions have been reached without agreement. Considering that this is a universal phenomenon that is not restricted to miRNAs, we recall the original work on this topic that began from looking at viral RNAs of several types. We provide a link to this work by examining the neutrality of HCV structural elements, performing a detailed bioinformatic analysis using RNA secondary structure predictions across genotypes. This study provides supporting evidence for direct evolution of genetic robustness that is not limited to noncoding RNAs participating in gene regulation, but includes functionally important structural elements of the hepatitis C virus (HCV) that show excess of robustness beyond the intrinsic robustness of their stem-loop structure. These findings further support the adaptive behavior of genetic robustness in functional RNAs of various types that seem to have evolved with selection pressure towards increased robustness.

Neutral evolution of robustness in Drosophila microRNA precursors

Mutational robustness describes the extent to which a phenotype remains unchanged in the face of mutations. Theory predicts that the strength of direct selection for mutational robustness is at most the magnitude of the rate of deleterious mutation. As far as nucleic acid sequences are concerned, only long sequences in organisms with high deleterious mutation rates and large population sizes are expected to evolve mutational robustness. Surprisingly, recent studies have concluded that molecules that meet none of these conditions--the microRNA precursors (pre-miRNAs) of multicellular eukaryotes--show signs of selection for mutational and/or environmental robustness. To resolve the apparent disagreement between theory and these studies, we have reconstructed the evolutionary history of Drosophila pre-miRNAs and compared the robustness of each sequence to that of its reconstructed ancestor. In addition, we "replayed the tape" of pre-miRNA evolution via simulation under different evolutionary assumptions and compared these alternative histories with the actual one. We found that Drosophila pre-miRNAs have evolved under strong purifying selection against changes in secondary structure. Contrary to earlier claims, there is no evidence that these RNAs have been shaped by either direct or congruent selection for any kind of robustness. Instead, the high robustness of Drosophila pre-miRNAs appears to be mostly intrinsic and likely a consequence of selection for functional structures.

On the possible role of robustness in the evolution of infectious diseases

Robustness describes the capacity for a biological system to remain canalized despite perturbation. Genetic robustness affords maintenance of phenotype despite mutational input, necessarily involving the role of epistasis. Environmental robustness is phenotypic constancy in the face of environmental variation, where epistasis may be uninvolved. Here we discuss genetic and environmental robustness, from the standpoint of infectious disease evolution, and suggest that robustness may be a unifying principle for understanding how different disease agents evolve. We focus especially on viruses with RNA genomes due to their importance in the evolution of emerging diseases and as model systems to test robustness theory. We present new data on adaptive constraints for a model RNA virus challenged to evolve in response to UV radiation. We also draw attention to other infectious disease systems where robustness theory may prove useful for bridging evolutionary biology and biomedicine, especially the evolution of antibiotic resistance in bacteria, immune evasion by influenza, and malaria parasite infections.

Replication mode and landscape topology differentially affect RNA virus mutational load and robustness

Regardless of genome polarity, intermediaries of complementary sense must be synthesized and used as templates for the production of new genomic strands. Depending on whether these new genomic strands become themselves templates for producing extra antigenomic ones, thus giving rise to geometric growth, or only the firstly synthesized antigenomic strands can be used to this end, thus following Luria's stamping machine model, the abundances and distributions of mutant genomes will be different. Here we propose mathematical and bit string models that allow distinguishing between stamping machine and geometric replication. We have observed that, regardless the topology of the fitness landscape, the critical mutation rate at which the master sequence disappears increases as the mechanism of replication switches from purely geometric to stamping machine. We also found that, for a wide range of mutation rates, large-effect mutations do not accumulate regardless the scheme of replication. However, mild mutations accumulate more in the geometric model. Furthermore, at high mutation rates, geometric growth leads to a population collapse for intermediate values of mutational effects at which the stamping machine still produces master genomes. We observed that the critical mutation rate was weakly dependent on the strength of antagonistic epistasis but strongly dependent on synergistic epistasis. In conclusion, we have shown that RNA viruses may increase their robustness against the accumulation of deleterious mutations by replicating as stamping machines and that the magnitude of this benefit depends on the topology of the fitness landscape assumed.

EvoRSR: an integrated system for exploring evolution of RNA structural robustness

Background

Robustness, maintaining a constant phenotype despite perturbations, is a fundamental property of biological systems that is incorporated at various levels of biological complexity. Although robustness has been frequently observed in nature, its evolutionary origin remains unknown. Current hypotheses suggest that robustness originated as a direct consequence of natural selection, as an intrinsic property of adaptations, or as a congruent correlate of environment robustness. To elucidate the evolutionary origins of robustness, a convenient computational package is strongly needed.

Results

In this study, we developed the open-source integrated system EvoRSR (Evolution of RNA Structural Robustness) to explore the evolution of robustness based on biologically important landscapes induced by RNA folding. EvoRSR is object-oriented, modular, and freely available at under the GNU/GPL license. We present an overview of EvoRSR package and illustrate its features with the miRNA gene cel-mir-357.

Conclusion

EvoRSR is a novel and flexible package for exploring the evolution of robustness. Accordingly, EvoRSR can be used for future studies to investigate the evolution and origin of robustness and to address other common questions about robustness. While the current EvoRSR environment is a versatile analysis framework, future versions can include features to enhance evolutionary studies of robustness.

Reconstruction of natural RNA sequences from RNA shape, thermodynamic stability, mutational robustness, and linguistic complexity by evolutionary computation

The process of designing novel RNA sequences by inverse RNA folding, available in tools such as RNAinverse and InfoRNA, can be thought of as a reconstruction of RNAs from secondary structure. In this reconstruction problem, no physical measures are considered as additional constraints that are independent of structure, aside of the goal to reach the same secondary structure as the input using energy minimization methods. An extension of the reconstruction problem can be formulated since in many cases of natural RNAs, it is desired to analyze the sequence and structure of RNA molecules using various physical quantifiable measures. In prior works that used secondary structure predictions, it has been shown that natural RNAs differ significantly from random RNAs in some of these measures. Thus, we relax the problem of reconstructing RNAs from secondary structure into reconstructing RNAs from shapes, and in turn incorporate physical quantities as constraints. This allows for the design of novel RNA sequences by inverse folding while considering various physical quantities of interest such as thermodynamic stability, mutational robustness, and linguistic complexity. At the expense of altering the number of nucleotides in stems and loops, for example, physical measures can be taken into account. We use evolutionary computation for the new reconstruction problem and illustrate the procedure on various natural RNAs.

Self containment, a property of modular RNA structures, distinguishes microRNAs

RNA molecules will tend to adopt a folded conformation through the pairing of bases on a single strand; the resulting so-called secondary structure is critical to the function of many types of RNA. The secondary structure of a particular substring of functional RNA may depend on its surrounding sequence. Yet, some RNAs such as microRNAs retain their specific structures during biogenesis, which involves extraction of the substructure from a larger structural context, while other functional RNAs may be composed of a fusion of independent substructures. Such observations raise the question of whether particular functional RNA substructures may be selected for invariance of secondary structure to their surrounding nucleotide context. We define the property of self containment to be the tendency for an RNA sequence to robustly adopt the same optimal secondary structure regardless of whether it exists in isolation or is a substring of a longer sequence of arbitrary nucleotide content. We measured degree of self containment using a scoring method we call the self-containment index and found that miRNA stem loops exhibit high self containment, consistent with the requirement for structural invariance imposed by the miRNA biogenesis pathway, while most other structured RNAs do not. Further analysis revealed a trend toward higher self containment among clustered and conserved miRNAs, suggesting that high self containment may be a characteristic of novel miRNAs acquiring new genomic contexts. We found that miRNAs display significantly enhanced self containment compared to other functional RNAs, but we also found a trend toward natural selection for self containment in most functional RNA classes. We suggest that self containment arises out of selection for robustness against perturbations, invariance during biogenesis, and modular composition of structural function. Analysis of self containment will be important for both annotation and design of functional RNAs. A Python implementation and Web interface to calculate the self-containment index are available at http://kim.bio.upenn.edu/software/.

An RNA molecule is made up of a linear sequence of nucleotides, which form pairwise interactions that define its folded three-dimensional structure; the particular structure largely depends on the specific sequence. These base-pairing interactions are stabilizing, and the RNA will tend to fold in a particular way to maximize stability. Consider some nucleotide sequence that optimally folds into some structure in isolation; if this sequence is now embedded inside a larger sequence, then either the original structure will be a robust subcomponent of the larger folded structure, or it will be disrupted due to new interactions between the original sequence and the surrounding sequence. We explore this property of context robustness of structure and in particular define the property of “self containment” to describe intrinsic context robustness—i.e., the tendency for certain sequences to be structurally robust in many different sequence contexts. Self containment turns out to be a strong characteristic of a class of RNAs called microRNAs, whose biogenesis process depends on the maintenance of structural robustness. This finding will be useful in future efforts to characterize novel miRNAs, as well as in understanding the regulation and evolution of noncoding functional RNAs as modular units.

Robustness and evolvability: a paradox resolved

Understanding the relationship between robustness and evolvability is key to understand how living things can withstand mutations, while producing ample variation that leads to evolutionary innovations. Mutational robustness and evolvability, a system's ability to produce heritable variation, harbour a paradoxical tension. On one hand, high robustness implies low production of heritable phenotypic variation. On the other hand, both experimental and computational analyses of neutral networks indicate that robustness enhances evolvability. I here resolve this tension using RNA genotypes and their secondary structure phenotypes as a study system. To resolve the tension, one must distinguish between robustness of a genotype and a phenotype. I confirm that genotype (sequence) robustness and evolvability share an antagonistic relationship. In stark contrast, phenotype (structure) robustness promotes structure evolvability. A consequence is that finite populations of sequences with a robust phenotype can access large amounts of phenotypic variation while spreading through a neutral network. Population-level processes and phenotypes rather than individual sequences are key to understand the relationship between robustness and evolvability. My observations may apply to other genetic systems where many connected genotypes produce the same phenotypes.

The road to modularity

A network of interactions is called modular if it is subdivided into relatively autonomous, internally highly connected components. Modularity has emerged as a rallying point for research in developmental and evolutionary biology (and specifically evo-devo), as well as in molecular systems biology. Here we review the evidence for modularity and models about its origin. Although there is an emerging agreement that organisms have a modular organization, the main open problem is the question of whether modules arise through the action of natural selection or because of biased mutational mechanisms.

How Mutational Networks Shape Evolution: Lessons from RNA Models

Recent advances in molecular biology and computation have enabled evolutionary biologists to develop models that explicitly capture molecular structure. By including complex and realistic maps from genotypes to phenotypes, such models are yielding important new insights into evolutionary processes. In particular, computer simulations of evolving RNA structure have inspired a new conceptual framework for thinking about patterns of mutational connectivity and general theories about the nature of evolutionary transitions, the evolutionary ascent of nonoptimal phenotypes, and the origins of mutational robustness and modular structures. Here, we describe this class of RNA models and review the major conceptual contributions they have made to evolutionary biology.

In silico genetic robustness analysis of microRNA secondary structures: potential evidence of congruent evolution in microRNA

Background

Robustness is a fundamental property of biological systems and is defined as the ability to maintain stable functioning in the face of various perturbations. Understanding how robustness has evolved has become one of the most attractive areas of research for evolutionary biologists, as it is still unclear whether genetic robustness evolved as a direct consequence of natural selection, as an intrinsic property of adaptations, or as congruent correlate of environment robustness. Recent studies have demonstrated that the stem-loop structures of microRNA (miRNA) are tolerant to some structural changes and show thermodynamic stability. We therefore hypothesize that genetic robustness may evolve as a correlated side effect of the evolution for environmental robustness.

Results

We examine the robustness of 1,082 miRNA genes covering six species. Our data suggest the stem-loop structures of miRNA precursors exhibit a significantly higher level of genetic robustness, which goes beyond the intrinsic robustness of the stem-loop structure and is not a byproduct of the base composition bias. Furthermore, we demonstrate that the phenotype of miRNA buffers against genetic perturbations, and at the same time is also insensitive to environmental perturbations.

Conclusion

The results suggest that the increased robustness of miRNA stem-loops may result from congruent evolution for environment robustness. Potential applications of our findings are also discussed.

Direct selection on genetic robustness revealed in the yeast transcriptome

BACKGROUND

Evolutionary theory predicts that organisms should evolve the ability to produce high fitness phenotypes in the face of environmental disturbances (environmental robustness) or genetic mutations (genetic robustness). While several studies have uncovered mechanisms that lead to both environmental and genetic robustness, we have yet to understand why some components of the genome are more robust than others. According to evolutionary theory, environmental and genetic robustness will have different responses to selective forces. Selection on environmental robustness for a trait is expected to be strong and related to the fitness costs of altering that trait. In contrast to environmental robustness, selection on genetic robustness for a trait is expected to be largely independent of the fitness cost of altering the trait and instead should correlate with the standing genetic variation for the trait that can potentially be buffered. Several mechanisms that provide both environmental and genetic robustness have been described, and this correlation could be explained by direct selection on both forms of robustness (direct selection hypothesis), or through selection on environmental robustness and a correlated response in genetic robustness (congruence hypothesis).

METHODOLOGY/PRINCIPAL FINDINGS

Using both published and novel data on gene expression in the yeast Saccharomyces cerevisiae, we find that genetic robustness is correlated with environmental robustness across the yeast genome as predicted by the congruence hypothesis. However, we also show that environmental robustness, but not genetic robustness, is related to per-gene fitness effects. In contrast, genetic robustness is significantly correlated with network position, suggesting that genetic robustness has been under direct selection.

CONCLUSIONS/SIGNIFICANCE

We observed a significant correlation between our measures of genetic and environmental robustness, in agreement with the congruence hypothesis. However, this correlation alone cannot explain the co-variance of genetic robustness with position in the protein interaction network. We therefore conclude that direct selection on robustness has played a role in the evolution of genetic robustness in the transcriptome.

Robustness can evolve gradually in complex regulatory gene networks with varying topology

The topology of cellular circuits (the who-interacts-with-whom) is key to understand their robustness to both mutations and noise. The reason is that many biochemical parameters driving circuit behavior vary extensively and are thus not fine-tuned. Existing work in this area asks to what extent the function of any one given circuit is robust. But is high robustness truly remarkable, or would it be expected for many circuits of similar topology? And how can high robustness come about through gradual Darwinian evolution that changes circuit topology gradually, one interaction at a time? We here ask these questions for a model of transcriptional regulation networks, in which we explore millions of different network topologies. Robustness to mutations and noise are correlated in these networks. They show a skewed distribution, with a very small number of networks being vastly more robust than the rest. All networks that attain a given gene expression state can be organized into a graph whose nodes are networks that differ in their topology. Remarkably, this graph is connected and can be easily traversed by gradual changes of network topologies. Thus, robustness is an evolvable property. This connectedness and evolvability of robust networks may be a general organizational principle of biological networks. In addition, it exists also for RNA and protein structures, and may thus be a general organizational principle of all biological systems.

RSRE: RNA structural robustness evaluator

Biological robustness, defined as the ability to maintain stable functioning in the face of various perturbations, is an important and fundamental topic in current biology, and has become a focus of numerous studies in recent years. Although structural robustness has been explored in several types of RNA molecules, the origins of robustness are still controversial. Computational analysis results are needed to make up for the lack of evidence of robustness in natural biological systems. The RNA structural robustness evaluator (RSRE) web server presented here provides a freely available online tool to quantitatively evaluate the structural robustness of RNA based on the widely accepted definition of neutrality. Several classical structure comparison methods are employed; five randomization methods are implemented to generate control sequences; sub-optimal predicted structures can be optionally utilized to mitigate the uncertainty of secondary structure prediction. With a user-friendly interface, the web application is easy to use. Intuitive illustrations are provided along with the original computational results to facilitate analysis. The RSRE will be helpful in the wide exploration of RNA structural robustness and will catalyze our understanding of RNA evolution. The RSRE web server is freely available at http://biosrv1.bmi.ac.cn/RSRE/ or http://biotech.bmi.ac.cn/RSRE/.

Effects of population size and mutation rate on the evolution of mutational robustness

It is often assumed that the efficiency of selection for mutational robustness would be proportional to mutation rate and population size, thus being inefficient in small populations. However, Krakauer and Plotkin (2002) hypothesized that selection in small populations would favor robustness mechanisms, such as redundancy, that mask the effect of deleterious mutations. In large populations, by contrast, selection is more effective at removing deleterious mutants and fitness would be improved by eliminating mechanisms that mask the effect of deleterious mutations and thus impede their removal. Here, we test whether these predictions are supported in experiments with evolving populations of digital organisms. Digital organisms are self-replicating programs that inhabit a virtual world inside a computer. Like their organic counterparts, digital organisms mutate, compete, evolve, and adapt by natural selection to their environment. In this study, 160 populations evolved at different combinations of mutation rate and population size. After 10(4) generations, we measured the mutational robustness of the most abundant genotype in each population. Mutational robustness tended to increase with mutation rate and to decline with population size, although the dependence with population size was in part mediated by a negative relationship between fitness and robustness. These results are independent of whether genomes were constrained to their original length or allowed to change in size.

Modular evolution and increase of functional complexity in replicating RNA molecules

At early stages of biochemical evolution, the complexity of replicating molecules was limited by unavoidably high mutation rates. In an RNA world, prior to the appearance of cellular life, an increase in molecular length, and thus in functional complexity, could have been mediated by modular evolution. We describe here a scenario in which short, replicating RNA sequences are selected to perform a simple function. Molecular function is represented through the secondary structure corresponding to each sequence, and a given target secondary structure yields the optimal function in the environment where the population evolves. The combination of independently evolved populations may have facilitated the emergence of larger molecules able to perform more complex functions (including RNA replication) that could arise as a combination of simpler ones. We quantitatively show that modular evolution has relevant advantages with respect to the direct evolution of large functional molecules, among them the allowance of higher mutation rates, the shortening of evolutionary times, and the very possibility of finding complex structures that could not be otherwise directly selected.

Prediction of structured non-coding RNAs in the genomes of the nematodesCaenorhabditis elegans andCaenorhabditis briggsae

We present a survey for non-coding RNAs and other structured RNA motifs in the genomes of Caenorhabditis elegans and Caenorhabditis briggsae using the RNAz program. This approach explicitly evaluates comparative sequence information to detect stabilizing selection acting on RNA secondary structure. We detect 3,672 structured RNA motifs, of which only 678 are known non-translated RNAs (ncRNAs) or clear homologs of known C. elegans ncRNAs. Most of these signals are located in introns or at a distance from known protein-coding genes. With an estimated false positive rate of about 50% and a sensitivity on the order of 50%, we estimate that the nematode genomes contain between 3,000 and 4,000 RNAs with evolutionary conserved secondary structures. Only a small fraction of these belongs to the known RNA classes, including tRNAs, snoRNAs, snRNAs, or microRNAs. A relatively small class of ncRNA candidates is associated with previously observed RNA-specific upstream elements.

Direct evolution of genetic robustness in microRNA

Genetic robustness, the invariance of the phenotype in the face of genetic perturbations, can endow the organism with reduced susceptibility to mutations. A large body of work in recent years has focused on the origins, mechanisms, and consequences of robustness in a wide range of biological systems. Despite the apparent prevalence of mutational robustness in nature, however, its evolutionary origins are still unclear. Does robustness evolve directly by natural selection or is it merely a correlated byproduct of other phenotypic traits? By examining microRNA (miRNA) genes of several eukaryotic species, we show that the structure of miRNA precursor stem-loops exhibits a significantly high level of mutational robustness in comparison with random RNA sequences with similar stem-loop structures. Hence, this excess robustness of miRNA goes beyond the intrinsic robustness of the stem-loop hairpin structure. Furthermore, we show that it is not the byproduct of a base composition bias or of thermodynamic stability. These findings suggest that the excess robustness of miRNA stem-loops is the result of direct evolutionary pressure toward increased robustness. We further demonstrate that this adaptive robustness evolves to compensate for structures with low intrinsic robustness.

Identification of clustered microRNAs using an ab initio prediction method

Background

MicroRNAs (miRNAs) are endogenous 21 to 23-nucleotide RNA molecules that regulate protein-coding gene expression in plants and animals via the RNA interference pathway. Hundreds of them have been identified in the last five years and very recent works indicate that their total number is still larger. Therefore miRNAs gene discovery remains an important aspect of understanding this new and still widely unknown regulation mechanism. Bioinformatics approaches have proved to be very useful toward this goal by guiding the experimental investigations.

Results

In this work we describe our computational method for miRNA prediction and the results of its application to the discovery of novel mammalian miRNAs. We focus on genomic regions around already known miRNAs, in order to exploit the property that miRNAs are occasionally found in clusters. Starting with the known human, mouse and rat miRNAs we analyze 20 kb of flanking genomic regions for the presence of putative precursor miRNAs (pre-miRNAs). Each genome is analyzed separately, allowing us to study the species-specific identity and genome organization of miRNA loci. We only use cross-species comparisons to make conservative estimates of the number of novel miRNAs. Our ab initio method predicts between fifty and hundred novel pre-miRNAs for each of the considered species. Around 30% of these already have experimental support in a large set of cloned mammalian small RNAs. The validation rate among predicted cases that are conserved in at least one other species is higher, about 60%, and many of them have not been detected by prediction methods that used cross-species comparisons. A large fraction of the experimentally confirmed predictions correspond to an imprinted locus residing on chromosome 14 in human, 12 in mouse and 6 in rat. Our computational tool can be accessed on the world-wide-web.

Conclusion

Our results show that the assumption that many miRNAs occur in clusters is fruitful for the discovery of novel miRNAs. Additionally we show that although the overall miRNA content in the observed clusters is very similar across the three considered species, the internal organization of the clusters changes in evolution.

The Evolutionary Genetics of Canalization

Evolutionary genetics has recently made enormous progress in understanding how genetic variation maps into phenotypic variation. However why some traits are phenotypically invariant despite apparent genetic and environmental changes has remained a major puzzle. In the 1940s, Conrad Hal Waddington coined the concept and term "canalization" to describe the robustness of phenotypes to perturbation; a similar concept was proposed by Waddington's contemporary Ivan Ivanovich Schmalhausen. This paper reviews what has been learned about canalization since Waddington. Canalization implies that a genotype's phenotype remains relatively invariant when individuals of a particular genotype are exposed to different environments (environmental canalization) or when individuals of the same single- or multilocus genotype differ in their genetic background (genetic canalization). Consequently, genetic canalization can be viewed as a particular kind of epistasis, and environmental canalization and phenotypic plasticity are two aspects of the same phenomenon. Canalization results in the accumulation of phenotypically cryptic genetic variation, which can be released after a "decanalizing" event. Thus, canalized genotypes maintain a cryptic potential for expressing particular phenotypes, which are only uncovered under particular decanalizing environmental or genetic conditions. Selection may then act on this newly released genetic variation. The accumulation of cryptic genetic variation by canalization may therefore increase evolvability at the population level by leading to phenotypic diversification under decanalizing conditions. On the other hand, under canalizing conditions, a major part of the segregating genetic variation may remain phenotypically cryptic; canalization may therefore, at least temporarily, constrain phenotypic evolution. Mechanistically, canalization can be understood in terms of transmission patterns, such as epistasis, pleiotropy, and genotype by environment interactions, and in terms of genetic redundancy, modularity, and emergent properties of gene networks and biochemical pathways. While different forms of selection can favor canalization, the requirements for its evolution are typically rather restrictive. Although there are several methods to detect canalization, there are still serious problems with unambiguously demonstrating canalization, particularly its adaptive value.

Evolution of genetic potential

Organisms employ a multitude of strategies to cope with the dynamical environments in which they live. Homeostasis and physiological plasticity buffer changes within the lifetime of an organism, while stochastic developmental programs and hypermutability track changes on longer time-scales. An alternative long-term mechanism is "genetic potential"--a heightened sensitivity to the effects of mutation that facilitates rapid evolution to novel states. Using a transparent mathematical model, we illustrate the concept of genetic potential and show that as environmental variability decreases, the evolving population reaches three distinct steady state conditions: (1) organismal flexibility, (2) genetic potential, and (3) genetic robustness. As a specific example of this concept we examine fluctuating selection for hydrophobicity in a single amino acid. We see the same three stages, suggesting that environmental fluctuations can produce allele distributions that are distinct not only from those found under constant conditions, but also from the transient allele distributions that arise under isolated selective sweeps.

Epistasis and its relationship to canalization in the RNA virus phi 6

Although deleterious mutations are believed to play a critical role in evolution, assessing their realized effect has been difficult. A key parameter governing the effect of deleterious mutations is the nature of epistasis, the interaction between the mutations. RNA viruses should provide one of the best systems for investigating the nature of epistasis because the high mutation rate allows a thorough investigation of mutational effects and interactions. Nonetheless, previous investigations of RNA viruses by S. Crotty and co-workers and by S. F. Elena have been unable to detect a significant effect of epistasis. Here we provide evidence that positive epistasis is characteristic of deleterious mutations in the RNA bacteriophage phi 6. We estimated the effects of deleterious mutations by performing mutation-accumulation experiments on five viral genotypes of decreasing fitness. We inferred positive epistasis because viral genotypes with low fitness were found to be less sensitive to deleterious mutations. We further examined environmental sensitivity in these genotypes and found that low-fitness genotypes were also less sensitive to environmental perturbations. Our results suggest that even random mutations impact the degree of canalization, the buffering of a phenotype against genetic and environmental perturbations. In addition, our results suggest that genetic and environmental canalization have the same developmental basis and finally that an understanding of the nature of epistasis may first require an understanding of the nature of canalization.

Overlapping messages and survivability

The phenomenon of overlapping of various sequence messages in genomes is a puzzle for evolutionary theoreticians, geneticists, and sequence researchers. The overlapping is possible due to degeneracy of the messages, in particular, degeneracy of codons. It is often observed in organisms with a limited size of genome, possessing polymerases of low fidelity. The most accepted view considers the overlapping as a mechanism to increase the amount of information per unit length. Here we present a model that suggests direct evolutionary advantage of the message overlapping. Two opposing drives are considered: (a) reduction in the amount of vulnerable points when the overlapping of two messages involves common critical points and (b) cumulative compromising cost of coexistence of messages at the same site. Over a broad range of conditions the reduction of the target size prevails, thus making the overlapping of messages advantageous.

Following the very initial growth of biological RNA viral clones

Due to their extremely high genetic diversity, which is a direct consequence of high mutation rates, RNA viruses are often described as molecular quasispecies. According to this theory, RNA virus populations cannot be understood in terms of individual viral clones, as they are clouds of interconnected mutants, but this prediction has not yet been demonstrated experimentally. The goal of this study was to determine the fitness of individual clones sampled from a given RNA virus population, a necessary previous step to test the above prediction. To do so, limiting dilutions of a vesicular stomatitis virus population were employed to isolate single viral clones and their initial growth dynamics were followed, corresponding to the release of the first few hundred viral particles. This technique is useful for estimating basic fitness parameters, such as intracellular growth rate, viral yield per cell, rate at which cells are infected and time spent in cell-to-cell transmission. A combination of these parameters allows estimation of the fitness of individual clones, which seems to be determined mainly by their ability to complete infection cycles more quickly. Interestingly, fitness was systematically higher for initial clones than for their derived populations. In addition to environmental changes, such as cellular defence mechanisms, these differences are attributable to high RNA virus mutation rates.

Evolution of mutational robustness

We review recent advances in the understanding of the mutation-selection balance of asexual replicators. For over 30 years, population geneticists thought that an expression derived by Kimura and Maruyama in 1966 fully solved this problem. However, Kimura and Maruyama's result is only correct in the absence of neutral mutations. The inclusion of neutral mutations leads to a wealth of interesting new effects, and, in particular, to a selective pressure to evolve robustness against mutations. We cover recent literature on the population dynamics of asexual replicators on networks of neutral genotypes, on the outcompetition of fast replicators by slower ones with better mutational support, and on the probability of fixation at high mutation rates. We discuss empirical evidence for the evolution of mutational robustness, and speculate on its relevance for higher organisms.

Epistasis between new mutations and genetic background and a test of genetic canalization

The importance for fitness of epistatic interactions among mutations is poorly known, yet epistasis can exert important effects on the dynamics of evolving populations. We showed previously that epistatic interactions are common between pairs of random insertion mutations in the bacterium Escherichia coli. In this paper, we examine interactions between these mutations and other mutations by transducing each of twelve insertion mutations into two genetic backgrounds, one ancestral and the other having evolved in, and adapted to, a defined laboratory environment for 10,000 generations. To assess the effect of the mutation on fitness, we allowed each mutant to compete against its unmutated counterpart in that same environment. Overall, there was a strong positive correlation between the mutational effects on the two genetic backgrounds. Nonetheless, three of the twelve mutations had significantly different effects on the two backgrounds, indicating epistasis. There was no significant tendency for the mutations to be less harmful on the derived background. Thus, there is no evidence supporting the hypothesis that the derived bacteria had adapted, in part, by becoming buffered against the harmful effects of mutations.

Rational evolutionary design: the theory of in vitro protein evolution

Directed evolution uses a combination of powerful search techniques to generate proteins with improved properties. Part of the success is due to the stochastic element of random mutagenesis; improvements can be made without a detailed description of the complex interactions that constitute function or stability. However, optimization is not a conglomeration of random processes. Rather, it requires both knowledge of the system that is being optimized and a logical series of techniques that best explores the pathways of evolution (Eigen et al., 1988). The weighing of parameters associated with mutation, recombination, and screening to achieve the maximum fitness improvement is the beginning of rational evolutionary design. The optimal mutation rate is strongly influenced by the finite number of mutants that can be screened. A smooth fitness landscape implies that many mutations can be accumulated without disrupting the fitness. This has the effect of lowering the required library size to sample a higher mutation rate. As the sequence ascends the fitness landscape, the optimal mutation rate decreases as the probability of discovering improved mutations also decreases. Highly coupled regions require that many mutations be simultaneously made to generate a positive mutant. Therefore, positive mutations are discovered at uncoupled positions as the fitness of the parent increases. The benefit of recombination is twofold: it combines good mutations and searches more sequence space in a meaningful way. Recombination is most beneficial when the number of mutants that can be screened is limited and the landscape is of an intermediate ruggedness. The structure of schema in proteins leads to the conclusion that many cut points are required. The number of parents and their sequence identity are determined by the balance between exploration and exploitation. Many disparate parents can explore more space, but at the risk of losing information. The required screening effort is related to the number of uphill paths, which decreases more rapidly for rugged landscapes. Noise in the fitness measurements causes a dramatic increase in the required mutant library size, thus implying a smaller optimal mutation rate. Because of strict limitations on the number of mutants that can be screened, there is motivation to optimize the content of the mutant library. By restricting mutations to regions of the gene that are expected to show improvement, a greater return can be made with the same number of mutants. Initial studies with subtilisin E have shown that structurally tolerant positions tend to be where positive activity mutants are made during directed evolution. Mutant fitness information is produced by the screening step that has the potential to provide insight into the structure of the fitness landscape, thus aiding the setting of experimental parameters. By analyzing the mutant fitness distribution and targeting specific regions of the sequence, in vitro evolution can be accelerated. However, when expediting the search, there is a trade-off between rapid improvement and the quality of the long-term solution. The benefit of neutrality has yet to be captured with in vitro protein evolution. Neutral theory predicts the punctuated emergence of novel structure and function, however, with current methods, the required time scale is not feasible. Utilizing neutral evolution to accelerate the discovery of new functional and structural solutions requires a theory that predicts the behavior of mutational pathways between networks. Because the transition from neutral to adaptive evolution requires a multi-mutational switch, increasing the mutation rate decreases the time required for a punctuated change to occur. By limiting the search to the less coupled region of the sequence (smooth portion of the fitness landscape), the required larger mutation rate can be tolerated. Advances in directed evolution will be achieved when the driving forces behind such proce

Modeling genetic architecture: a multilinear theory of gene interaction

The map from genotype to phenotype is an exceedingly complex function of central importance in biology. In this work we derive and analyze a mathematically tractable model of the genotype-phenotype map that allows for any order of gene interaction. By assuming that the alterations of the effect of a gene substitution due to changes in the genetic background can be described as a linear transformation, we show that the genotype-phenotype map is a sum of linear and multilinear terms of operationally defined "reference" effects at each locus. The "multilinear" model is used to study the effect of epistasis on quantitative genetic variation, on the response to selection, and on genetic canalization. It is shown how the model can be used to estimate the strength of "functional" epistasis from a variety of genetic experiments.