Evolution in silico and in vitro: the RNA model

On the emergence of structural complexity in RNA replicators

The RNA world hypothesis relies on the ability of ribonucleic acids to spontaneously acquire complex structures capable of supporting essential biological functions. Multiple sophisticated evolutionary models have been proposed for their emergence, but they often assume specific conditions. In this work, we explore a simple and parsimonious scenario describing the emergence of complex molecular structures at the early stages of life. We show that at specific GC content regimes, an undirected replication model is sufficient to explain the apparition of multibranched RNA secondary structures-a structural signature of many essential ribozymes. We ran a large-scale computational study to map energetically stable structures on complete mutational networks of 50-nt-long RNA sequences. Our results reveal that the sequence landscape with stable structures is enriched with multibranched structures at a length scale coinciding with the appearance of complex structures in RNA databases. A random replication mechanism preserving a 50% GC content may suffice to explain a natural enrichment of stable complex structures in populations of functional RNAs. In contrast, an evolutionary mechanism eliciting the most stable folds at each generation appears to help reaching multibranched structures at highest GC content.

Contingency, convergence and hyper-astronomical numbers in biological evolution

Counterfactual questions such as "what would happen if you re-run the tape of life?" turn on the nature of the landscape of biological possibilities. Since the number of potential sequences that store genetic information grows exponentially with length, genetic possibility spaces can be so unimaginably vast that commentators frequently reach of hyper-astronomical metaphors that compare their size to that of the universe. Re-run the tape of life and the likelihood of encountering the same sequences in such hyper-astronomically large spaces is infinitesimally small, suggesting that evolutionary outcomes are highly contingent. On the other hand, the wide-spread occurrence of evolutionary convergence implies that similar phenotypes can be found again with relative ease. How can this be? Part of the solution to this conundrum must lie in the manner that genotypes map to phenotypes. By studying simple genotype-phenotype maps, where the counterfactual space of all possible phenotypes can be enumerated, it is shown that strong bias in the arrival of variation may explain why certain phenotypes are (repeatedly) observed in nature, while others never appear. This biased variation provides a non-selective cause for certain types of convergence. It illustrates how the role of randomness and contingency may differ significantly between genetic and phenotype spaces.

Sequence Evolution Under Constraints: Lessons Learned from Sudoku

The complex structures of all proteins in nature are outcomes of a random walk driven by mutation and selection. Reconstructing the fitness landscape staging this process based on first-principle physical rules or experimental measurements is difficult. In this article we turn the popular Sudoku game into an artificial fitness landscape and use it as a model system to study sequence evolution under constraints. The Sudoku rules, which are human-mind friendly, intertwine a rugged landscape for sequences composed of digits, mimicking the functional constraints felt by a tightly folded protein. Simulated evolution reveals interesting properties of the valley-crossing dynamics on this complex landscape. It is found that (i) the mutation accumulation rate during valley-crossing is constant among different evolutionary pathways and depends on the ruggedness of the landscape; (ii) genetic drift and neutral networks play constructive roles during the process of searching for novel functions; and (iii) under strong selection, gene duplication can speed up the evolution by relaxing, but not completely liberating, the redundant copy from selective pressure. Insights gained from this prototype model may help us understand the evolution of real proteins.

Diverse mutants of HIV RRE IIB recognize wild-type Rev ARM or Rev ARM R35G-N40V

The binding of human immunodeficiency virus Rev protein via its arginine-rich motif (ARM) to an internal loop in the Rev-response element region IIB (RRE IIB) is necessary for viral replication. Many variant RNAs and ARMs that bind Rev and RRE IIB have been found. Despite the essential role of Rev asparagine 40 in recognition, the Rev ARM double-mutant R35G-N40V functions well in a Rev-RRE IIB reporter assay, indicating R35G-N40V uses a distinct recognition strategy. To examine how RRE IIB may evolve specificity to wild-type Rev ARM and R35G-N40V, 10 RRE IIB libraries, each completely randomized in overlapping regions, were screened with wild-type Rev ARM and R35G-N40V using a reporter system based on bacteriophage λ N antitermination. Consistent with previous studies, a core element of RRE IIB did not vary, and substitutions occurred at conserved residues only in the presence of other substitutions. Notably, the groove-widening, non-canonical base-pair G48:G71 was mutable to U48:G71 without strong loss of binding to wild-type Rev ARM, suggesting U48:G71 performs the same role by adopting the nearly isosteric, reverse wobble base pair. Originating from RRE IIB, as few as one or two substitutions are sufficient to confer specificity to wild-type Rev or Rev R35G-N40. The diversity of RRE IIB mutants that maintain binding to wild-type Rev ARM and R35G-N40V supports neutral theories of evolution and illustrates paths by which viral RNA-protein interactions can evolve new specificities. Rev-RRE offers an excellent model with which to study the fine structure of how specificity evolves.

Evolutionary dynamics of RNA-like replicator systems: A bioinformatic approach to the origin of life

We review computational studies on prebiotic evolution, focusing on informatic processes in RNA-like replicator systems. In particular, we consider the following processes: the maintenance of information by replicators with and without interactions, the acquisition of information by replicators having a complex genotype-phenotype map, the generation of information by replicators having a complex genotype-phenotype-interaction map, and the storage of information by replicators serving as dedicated templates. Focusing on these informatic aspects, we review studies on quasi-species, error threshold, RNA-folding genotype-phenotype map, hypercycle, multilevel selection (including spatial self-organization, classical group selection, and compartmentalization), and the origin of DNA-like replicators. In conclusion, we pose a future question for theoretical studies on the origin of life.

Clay minerals mediate folding and regioselective interactions of RNA: a large-scale atomistic simulation study

Since a mineral-mediated origin of life was first hypothesized over 60 years ago, clays have played a significant role in origins of life studies. Such studies have hitherto rarely used computer simulation to understand the possible chemical pathways to the formation of biomolecules. We use molecular dynamics techniques, performed on supercomputing grids, to carry out large-scale simulations of various 25-mer sequences of ribonucleic acid (RNA), in bulk water and with aqueous montmorillonite clay over many tens of nanoseconds. Hitherto, there has only been limited experimental data reported for these systems. Our simulations are found to be in agreement with various experimental observations pertaining to the relative adsorption of RNA on montmorillonite in the presence of charge balancing cations. Over time scales of only a few nanoseconds, specific RNA sequences fold to characteristic secondary structural motifs, which do not form in the corresponding bulk water simulations. Our simulations also show that, in aqueous Ca(2+) environments, RNA can tether to the clay surface through a nucleotide base, leaving the 3'-end of the strand exposed, providing a mechanism for the regiospecific adsorption and elongation of RNA oligomers on clay surfaces.

Rapid construction of empirical RNA fitness landscapes

Evolution is an adaptive walk through a hypothetical fitness landscape, which depicts the relationship between genotypes and the fitness of each corresponding phenotype. We constructed an empirical fitness landscape for a catalytic RNA by combining next-generation sequencing, computational analysis, and "serial depletion," an in vitro selection protocol. By determining the reaction rate constant for every point mutant of a catalytic RNA, we demonstrated that abundance in serially depleted pools correlates with biochemical activity (correlation coefficient r = 0.67, standard score Z = 7.4). Therefore, enumeration of each genotype by deep sequencing yielded a fitness landscape containing ~10(7) unique sequences, without requiring measurement of the phenotypic fitness for each sequence. High-throughput mapping between genotype and phenotype may apply to artificial selections, host-pathogen interactions, and other biomedically relevant evolutionary phenomena.

Folding and finding RNA secondary structure

Optimal exploitation of the expanding database of sequences requires rapid finding and folding of RNAs. Methods are reviewed that automate folding and discovery of RNAs with algorithms that couple thermodynamics with chemical mapping, NMR, and/or sequence comparison. New functional noncoding RNAs in genome sequences can be found by combining sequence comparison with the assumption that functional noncoding RNAs will have more favorable folding free energies than other RNAs. When a new RNA is discovered, experiments and sequence comparison can restrict folding space so that secondary structure can be rapidly determined with the help of predicted free energies. In turn, secondary structure restricts folding in three dimensions, which allows modeling of three-dimensional structure. An example from a domain of a retrotransposon is described. Discovery of new RNAs and their structures will provide insights into evolution, biology, and design of therapeutics. Applications to studies of evolution are also reviewed.

A minimal and self-consistent in silico cell model based on macromolecular interactions

A self-consistent minimal cell model with a physically motivated schema for molecular interaction is introduced and described. The genetic and metabolic reaction network of the cell is modelled by multidimensional nonlinear ordinary differential equations, which are derived from biochemical kinetics. The strategy behind this modelling approach is to keep the model sufficiently simple in order to be able to perform studies on evolutionary optimization in populations of cells. At the same time, the model should be complex enough to handle the basic features of genetic control of metabolism and coupling to environmental factors. Thereby, the model system will provide insight into the mechanisms leading to important biological phenomena, such as homeostasis, (circadian) rhythms, robustness and adaptation to a changing environment. One example of modelling a molecular regulatory mechanism, cooperative binding of transcription factors, is discussed in detail.

Varying environments can speed up evolution

Simulations of biological evolution, in which computers are used to evolve systems toward a goal, often require many generations to achieve even simple goals. It is therefore of interest to look for generic ways, compatible with natural conditions, in which evolution in simulations can be speeded. Here, we study the impact of temporally varying goals on the speed of evolution, defined as the number of generations needed for an initially random population to achieve a given goal. Using computer simulations, we find that evolution toward goals that change over time can, in certain cases, dramatically speed up evolution compared with evolution toward a fixed goal. The highest speedup is found under modularly varying goals, in which goals change over time such that each new goal shares some of the subproblems with the previous goal. The speedup increases with the complexity of the goal: the harder the problem, the larger the speedup. Modularly varying goals seem to push populations away from local fitness maxima, and guide them toward evolvable and modular solutions. This study suggests that varying environments might significantly contribute to the speed of natural evolution. In addition, it suggests a way to accelerate optimization algorithms and improve evolutionary approaches in engineering.

Structural differences within the loop E motif imply alternative mechanisms of viroid processing

Viroids replicate via a rolling circle mechanism, and cleavage/ligation requires extensive rearrangement of the highly base-paired native structure. For Potato spindle tuber viroid (PSTVd), the switch from cleavage to ligation is driven by the change from a multibranched tetraloop structure to a loop E conformation. Here we present evidence that processing of Citrus viroid III (CVd-III), a member of a related group of viroids that also replicate in the nucleus, may proceed via a distinct pathway. Chemical probing of PSTVd and CVd-III miniRNAs with DMS and CMCT revealed that the loop E motifs of these two viroids have quite different tertiary structures. As shown by temperature gradient gel electrophoresis, the presence of two likely Watson-Crick GC pairs results in a significant overall stabilization of the CVd-III loop E-like motif. Unlike PSTVd, the upper strand of the CVd-III loop E-like motif cannot fold into a GNRA tetraloop, and comparison of suboptimal structures indicates that the initial cleavage event could occur on the 5' side of the only GU wobble pair in a helix involving a nearby pair of inverted repeats. According to our model, rearrangement of 3' sequences into a hairpin stem containing an identical arrangement of GC, GU, and CG base pairs and a second cleavage event is followed by formation of loop E, which serves to align the 5' and 3' termini of the CVd-III monomer prior to ligation. Because ligation would occur within loop E itself, stabilization of this motif may be needed to hold the 5' and 3' termini of CVd-III in position for the host ligase.

Determinants of simulated RNA evolution

Models of RNA secondary structure folding are widely used to study evolution in theory and simulation. However, systematic studies of the parameters involved are rare. In this paper, we study by simulation how RNA evolution is influenced by three different factors, namely the mutation rate, scaling of the fitness function, and distance measure. We found that for low mutation rates the qualitative evolutionary behavior is robust with respect to the scaling of the fitness function. For efficient mutation rates, which are close to the error threshold, scaling and distance measure have a strong influence on the evolutionary behavior. A global distance measure that takes sequence information additively into account lowers the error threshold. When using a local sequence-structure alignment for the distance, we observed a smoother evolution of the fitness over time. Finally, in addition to the well known error threshold, we identify another threshold of the mutation rate, called divergence threshold, where the qualitative transient behavior changes from a localized to an exploratory search.

The modern theory of biological evolution: an expanded synthesis

In 1858, two naturalists, Charles Darwin and Alfred Russel Wallace, independently proposed natural selection as the basic mechanism responsible for the origin of new phenotypic variants and, ultimately, new species. A large body of evidence for this hypothesis was published in Darwin's Origin of Species one year later, the appearance of which provoked other leading scientists like August Weismann to adopt and amplify Darwin's perspective. Weismann's neo-Darwinian theory of evolution was further elaborated, most notably in a series of books by Theodosius Dobzhansky, Ernst Mayr, Julian Huxley and others. In this article we first summarize the history of life on Earth and provide recent evidence demonstrating that Darwin's dilemma (the apparent missing Precambrian record of life) has been resolved. Next, the historical development and structure of the "modern synthesis" is described within the context of the following topics: paleobiology and rates of evolution, mass extinctions and species selection, macroevolution and punctuated equilibrium, sexual reproduction and recombination, sexual selection and altruism, endosymbiosis and eukaryotic cell evolution, evolutionary developmental biology, phenotypic plasticity, epigenetic inheritance and molecular evolution, experimental bacterial evolution, and computer simulations (in silico evolution of digital organisms). In addition, we discuss the expansion of the modern synthesis, embracing all branches of scientific disciplines. It is concluded that the basic tenets of the synthetic theory have survived, but in modified form. These sub-theories require continued elaboration, particularly in light of molecular biology, to answer open-ended questions concerning the mechanisms of evolution in all five kingdoms of life.