Evolution of the aminoacyl-tRNA synthetases and the origin of the genetic code

The aminoacyl-tRNA synthetases exist as two enzyme families which were apparently generated by divergent evolution from two primordial synthetases. The two classes of enzymes exhibit intriguing familial relationships, in that they are distributed nonrandomly within the codon-amino acid matrix of the genetic code. For example, all XCX codons code for amino acids handled by class II synthetases, and all but one of the XUX codons code for amino acids handled by class I synthetases. One interpretation of these patterns is that the synthetases coevolved with the genetic code. The more likely explanation, however, is that the synthetases evolved in the context of an already-established genetic code—a code which developed earlier in an RNA world. The rules which governed the development of the genetic code, and led to certain patterns in the coding catalog between codons and amino acids, would also have governed the subsequent evolution of the synthetases in the context of a fixed code, leading to patterns in synthetase distribution such as those observed. These rules are (1) conservative evolution of amino acid and adapter binding sites and (2) minimization of the disruptive effects on protein structure caused by codon meaning changes.     

A simple model for the evolution of molecular codes driven by the interplay of accuracy, diversity and cost

Molecular codes translate information written in one type of molecule into another molecular language. We introduce a simple model that treats molecular codes as noisy information channels. An optimal code is a channel that conveys information accurately and efficiently while keeping down the impact of errors. The equipoise of the three conflicting needs, for minimal error load, minimal cost of resources and maximal diversity of vocabulary, defines the fitness of the code. The model suggests a mechanism for the emergence of a code when evolution varies the parameters that control this equipoise and the mapping between the two molecular languages becomes non-random. This mechanism is demonstrated by a simple toy model that is formally equivalent to a mean-field Ising magnet.     

On the Evolution of Redundancy in Genetic Codes

We simulate a deterministic population genetic model for the coevolution of genetic codes and protein-coding genes. We use very simple assumptions about translation, mutation, and protein fitness to calculate mutation-selection equilibria of codon frequencies and fitness in a large asexual population with a given genetic code. We then compute the fitnesses of altered genetic codes that compete to invade the population by translating its genes with higher fitness. Codes and genes coevolve in a succession of stages, alternating between genetic equilibration and code invasion, from an initial wholly ambiguous coding state to a diversified frozen coding state. Our simulations almost always resulted in partially redundant frozen genetic codes. Also, the range of simulated physicochemical properties among encoded amino acids in frozen codes was always less than maximal. These results did not require the assumption of historical constraints on the number and type of amino acids available to codes nor on the complexity of proteins, stereochemical constraints on the translational apparatus, nor mechanistic constraints on genetic code change. Both the extent and timing of amino-acid diversification in genetic codes were strongly affected by the message mutation rate and strength of missense selection. Our results suggest that various omnipresent phenomena that distribute codons over sites with different selective requirements—such as the persistence of nonsynonymous mutations at equilibrium, the positive selection of the same codon in different types of sites, and translational ambiguity—predispose the evolution of redundancy and of reduced amino acid diversity in genetic codes. Received: 21 December 2000 / Accepted: 12 March 2001     

Study of the genetic code adaptability by means of a genetic algorithm

We used simulated evolution to study the adaptability level of the canonical genetic code. An adapted genetic algorithm (GA) searches for optimal hypothetical codes. Adaptability is measured as the average variation of the hydrophobicity that the encoded amino acids undergo when errors or mutations are present in the codons of the hypothetical codes. Different types of mutations and point mutation rates that depend on codon base number are considered in this study. Previous works have used statistical approaches based on randomly generated alternative codes or have used local search techniques to determine an optimum value. In this work, we emphasize what can be concluded from the use of simulated evolution considering the results of previous works. The GA provides more information about the difficulty of the evolution of codes, without contradicting previous studies using statistical or engineering approaches. The GA also shows that, within the coevolution theory, the third base clearly improves the adaptability of the current genetic code.     

Genetic code development by stop codon takeover

A novel theoretical consideration of the origin and evolution of the genetic code is presented. Code development is viewed from the perspective of simultaneously evolving codons, anticodons and amino acids. Early code structure was determined primarily by thermodynamic stability considerations, requiring simplicity in primordial codes. More advanced coding stages could arise as biological systems became more complex and precise in their replication. To be consistent with these ideas, a model is described in which codons become permanently associated with amino acids only when a codon-anticodon pairing is strong enough to permit rapid translation. Hence all codons are essentially chain-termination or "stop" codons until tRNA adaptors evolve having the ability to bind tightly to them. This view, which draws support from several lines of evidence, differs from the prevalent thinking on code evolution which holds that codons specifying newer amino acids were derived from codons encoding older amino acids.     

Unassigned Codons, Nonsense Suppression, and Anticodon Modifications in the Evolution of the Genetic Code

The origin of the genetic code is a central open problem regarding the early evolution of life. Here, we consider two undeveloped but important aspects of possible scenarios for the evolutionary pathway of the translation machinery: the role of unassigned codons in early stages of the code and the incorporation of tRNA anticodon modifications. As the first codons started to encode amino acids, the translation machinery likely was faced with a large number of unassigned codons. Current molecular scenarios for the evolution of the code usually assume the very rapid assignment of all codons before all 20 amino acids became encoded. We show that the phenomenon of nonsense suppression as observed in current organisms allows for a scenario in which many unassigned codons persisted throughout most of the evolutionary development of the code. In addition, we demonstrate that incorporation of anticodon modifications at a late stage is feasible. The wobble rules allow a set of 20 tRNAs fully lacking anticodon modifications to encode all 20 canonical amino acids. These observations have implications for the biochemical plausibility of early stages in the evolution of the genetic code predating tRNA anticodon modifications and allow for effective translation by a relatively small and simple early tRNA set.     

A quantitative measure of error minimization in the genetic code

Summary We have calculated the average effect of changing a codon by a single base for all possible single-base changes in the genetic code and for changes in the first, second, and third codon positions separately. Such values were calculated for an amino acid's polar requirement, hydropathy, molecular volume, and isoelectric point. For each attribute the average effect of single-base changes was also calculated for a large number of randomly generated codes that retained the same level of redundancy as the natural code. Amino acids whose codons differed by a single base in the first and third codon positions were very similar with respect to polar requirement and hydropathy. The major differences between amino acids were specified by the second codon position. Codons with U in the second position are hydrophobic, whereas most codons with A in the second position are hydrophilic. This accounts for the observation of complementary hydropathy. Single-base changes in the natural code had a smaller average effect on polar requirement than all but 0.02% of random codes. This result is most easily explained by selection to minimize deleterious effects of translation errors during the early evolution of the code.     

Evolution of the Genetic Code by Incorporation of Amino Acids that Improved or Changed Protein Function

Fifty years have passed since the genetic code was deciphered, but how the genetic code came into being has not been satisfactorily addressed. It is now widely accepted that the earliest genetic code did not encode all 20 amino acids found in the universal genetic code as some amino acids have complex biosynthetic pathways and likely were not available from the environment. Therefore, the genetic code evolved as pathways for synthesis of new amino acids became available. One hypothesis proposes that early in the evolution of the genetic code four amino acids—valine, alanine, aspartic acid, and glycine—were coded by GNC codons (N = any base) with the remaining codons being nonsense codons. The other sixteen amino acids were subsequently added to the genetic code by changing nonsense codons into sense codons for these amino acids. Improvement in protein function is presumed to be the driving force behind the evolution of the code, but how improved function was achieved by adding amino acids has not been examined. Based on an analysis of amino acid function in proteins, an evolutionary mechanism for expansion of the genetic code is described in which individual coded amino acids were replaced by new amino acids that used nonsense codons differing by one base change from the sense codons previously used. The improved or altered protein function afforded by the changes in amino acid function provided the selective advantage underlying the expansion of the genetic code. Analysis of amino acid properties and functions explains why amino acids are found in their respective positions in the genetic code.     

Evolution of the genetic code: partial optimization of a random code for robustness to translation error in a rugged fitness landscape

Background  

The standard genetic code table has a distinctly non-random structure, with similar amino acids often encoded by codons series that differ by a single nucleotide substitution, typically, in the third or the first position of the codon. It has been repeatedly argued that this structure of the code results from selective optimization for robustness to translation errors such that translational misreading has the minimal adverse effect. Indeed, it has been shown in several studies that the standard code is more robust than a substantial majority of random codes. However, it remains unclear how much evolution the standard code underwent, what is the level of optimization, and what is the likely starting point.     

An Analysis of the Metabolic Theory of the Origin of the Genetic Code

A computer program was used to test Wong's coevolution theory of the genetic code. The codon correlations between the codons of biosynthetically related amino acids in the universal genetic code and in randomly generated genetic codes were compared. It was determined that many codon correlations are also present within random genetic codes and that among the random codes there are always several which have many more correlations than that found in the universal code. Although the number of correlations depends on the choice of biosynthetically related amino acids, the probability of choosing a random genetic code with the same or greater number of codon correlations as the universal genetic code was found to vary from 0.1% to 34% (with respect to a fairly complete listing of related amino acids). Thus, Wong's theory that the genetic code arose by coevolution with the biosynthetic pathways of amino acids, based on codon correlations between biosynthetically related amino acids, is statistical in nature. Received: 8 August 1996 / Accepted: 26 December 1996     

The triplet genetic code had a doublet predecessor

Information theoretic analysis of genetic languages indicates that the naturally occurring 20 amino acids and the triplet genetic code arose by duplication of 10 amino acids of class-II and a doublet genetic code having codons NNY and anticodons GNN. Evidence for this scenario is presented based on the properties of aminoacyl-tRNA synthetases, amino acids and nucleotide bases.     

Simplification of the genetic code: restricted diversity of genetically encoded amino acids

At earlier stages in the evolution of the universal genetic code, fewer than 20 amino acids were considered to be used. Although this notion is supported by a wide range of data, the actual existence and function of the genetic codes with a limited set of canonical amino acids have not been addressed experimentally, in contrast to the successful development of the expanded codes. Here, we constructed artificial genetic codes involving a reduced alphabet. In one of the codes, a tRNA^Ala variant with the Trp anticodon reassigns alanine to an unassigned UGG codon in the Escherichia coli S30 cell-free translation system lacking tryptophan. We confirmed that the efficiency and accuracy of protein synthesis by this Trp-lacking code were comparable to those by the universal genetic code, by an amino acid composition analysis, green fluorescent protein fluorescence measurements and the crystal structure determination. We also showed that another code, in which UGU/UGC codons are assigned to Ser, synthesizes an active enzyme. This method will provide not only new insights into primordial genetic codes, but also an essential protein engineering tool for the assessment of the early stages of protein evolution and for the improvement of pharmaceuticals.     

Possible evolutionary steps in the genetic code

In mammalian mitochondrial codes, fourfold codons wobble-pair with UNN anticodons so that U wobbles with U, C, A and G. Twofold pyrimidine-terminated codons pair with GNN and twofold purine-terminated codons pair with UNN. These properties enable a prediction to be made for evolution of the universal genetic code. It was postulated (1) that an archetypal code of 16 quartets coded for 15 amino acids. If this code used UNN anticodons, then duplication of tRNA genes, followed by mutations in the anticodons and aminoacylation sites, would give rise to the present universal code.     

A hardware interpretation of the evolution of the genetic code

A quantitative rationale for the evolution of the genetic code is developed considering the principle of minimal hardware. This principle defines an optimal code as one that minimizes for a given amount of information encoded, the product of the number of physical devices used by the average complexity of each device. By identifying the number of different amino acids, number of nucleotide positions per codon and number of base types that can occupy each such position with, respectively, the amount of information, number of devices and the complexity, we show that optimal codes occur for 3, 7 and 20 amino acids with codons having a single, two and three base positions per codon, respectively. The advantage of a code of exactly 4 symbols is deduced, as well as a plausible evolutionary pathway from a code of doublets to triplets. The present day code of 20 amino acids encoded by 64 codons is shown to be the most optimal in an absolute sense. Using a tetraplet code further evolution to a code in which there would be 55 amino acids is in principle possible, but such a code would deviate slightly more than the present day code from the minimal hardware configuration. The change from a triplet code to a tetraplet code would occur at about 32 amino acids. Our conclusions are independent of, but consistent with, the observed physico-chemical properties of the amino acids and codon structures. These correlations could have evolved within the constrains imposed by the minimal hardware principle.     

Local stability and evolution of the genetic code

The standard genetic code is known to be robust to translation errors and point mutations. We studied how small modifications of the standard code affect its robustness. The robustness was assessed in terms of a proper stability function, the negative variations of which correspond to a more robust code. The fraction of more robust codes obtained under small modifications appeared to be unexpectedly high, about 0.1-0.4 depending on the choice of stability function and code modifications, yet significantly lower than the corresponding fraction in the random codes (about a half). In this sense the standard code ought to be considered distinctly non-random in accordance with previous observations. The distribution of the negative variations of stability function revealed very abrupt drop beyond one standard deviation, much sharper than for Gaussian distribution or for the random codes with the same number of codons in the sets coding for amino acids or stop-codons. This behavior holds for both the standard code as a whole and its binary NRN-NYN, NWN-NSN, and NMN-NKN blocks. Previously, it has been proved that such binary block structure is necessary for the robustness of a code and is inherent to the standard genetic code. The modifications of the standard code corresponding to more robust coding may be related to the different variants of the code. These effects may also contribute to the rates of replacements of amino acids. The observed features demonstrate the joint impact of random factors and natural selection during evolution of the genetic code.     

Revisiting the Physico-Chemical Hypothesis of Code Origin: An Analysis Based on Code-Sequence Coevolution in a Finite Population

The origin of the genetic code marked a major transition from a plausible RNA world to the world of DNA and proteins and is an important milestone in our understanding of the origin of life. We examine the efficacy of the physico-chemical hypothesis of code origin by carrying out simulations of code-sequence coevolution in finite populations in stages, leading first to the emergence of ten amino acid code(s) and subsequently to 14 amino acid code(s). We explore two different scenarios of primordial code evolution. In one scenario, competition occurs between populations of equilibrated code-sequence sets while in another scenario; new codes compete with existing codes as they are gradually introduced into the population with a finite probability. In either case, we find that natural selection between competing codes distinguished by differences in the degree of physico-chemical optimization is unable to explain the structure of the standard genetic code. The code whose structure is most consistent with the standard genetic code is often not among the codes that have a high fixation probability. However, we find that the composition of the code population affects the code fixation probability. A physico-chemically optimized code gets fixed with a significantly higher probability if it competes against a set of randomly generated codes. Our results suggest that physico-chemical optimization may not be the sole driving force in ensuring the emergence of the standard genetic code.     

Codon Size Reduction as the Origin of the Triplet Genetic Code

The genetic code appears to be optimized in its robustness to missense errors and frameshift errors. In addition, the genetic code is near-optimal in terms of its ability to carry information in addition to the sequences of encoded proteins. As evolution has no foresight, optimality of the modern genetic code suggests that it evolved from less optimal code variants. The length of codons in the genetic code is also optimal, as three is the minimal nucleotide combination that can encode the twenty standard amino acids. The apparent impossibility of transitions between codon sizes in a discontinuous manner during evolution has resulted in an unbending view that the genetic code was always triplet. Yet, recent experimental evidence on quadruplet decoding, as well as the discovery of organisms with ambiguous and dual decoding, suggest that the possibility of the evolution of triplet decoding from living systems with non-triplet decoding merits reconsideration and further exploration. To explore this possibility we designed a mathematical model of the evolution of primitive digital coding systems which can decode nucleotide sequences into protein sequences. These coding systems can evolve their nucleotide sequences via genetic events of Darwinian evolution, such as point-mutations. The replication rates of such coding systems depend on the accuracy of the generated protein sequences. Computer simulations based on our model show that decoding systems with codons of length greater than three spontaneously evolve into predominantly triplet decoding systems. Our findings suggest a plausible scenario for the evolution of the triplet genetic code in a continuous manner. This scenario suggests an explanation of how protein synthesis could be accomplished by means of long RNA-RNA interactions prior to the emergence of the complex decoding machinery, such as the ribosome, that is required for stabilization and discrimination of otherwise weak triplet codon-anticodon interactions.     

The Genetic Code: What Is It Good For? An Analysis of the Effects of Selection Pressures on Genetic Codes

How did the ``universal' genetic code arise? Several hypotheses have been put forward, and the code has been analyzed extensively by authors looking for clues to selection pressures that might have acted during its evolution. But this approach has been ineffective. Although an impressive number of properties has been attributed to the universal code, it has been impossible to determine whether selection on any of these properties was important in the code's evolution or whether the observed properties arose as a consequence of selection on some other characteristic. Therefore we turned the question around and asked, what would a genetic code look like if it had evolved in response to various different selection pressures? To address this question, we constructed a genetic algorithm. We found first that selecting on a particular measure yields codes that are similar to each other. Second, we found that the universal code is far from minimized with respect to the effects of mutations (or translation errors) on the amino acid compositions of proteins. Finally, we found that the codes that most closely resembled real codes were those generated by selecting on aspects of the code's structure, not those generated by selecting to minimize the effects of amino acid substitutions on proteins. This suggests that the universal genetic code has been selected for a particular structure—a structure that confers an important flexibility on the evolution of genes and proteins—and that the particular assignments of amino acids to codons are secondary. Received: 29 December 1998 / Accepted: 8 July 1999     

Amino Acid Exchangeability and the Adaptive Code Hypothesis

Since the genetic code first was determined, many have claimed that it is organized adaptively, so as to assign similar codons to similar amino acids. This claim has proved difficult to establish due to the absence of relevant comparative data on alternative primordial codes and of objective measures of amino acid exchangeability. Here we use a recently developed measure of exchangeability to evaluate a null hypothesis and two alternative hypotheses about the adaptiveness of the genetic code. The null hypothesis that there is no tendency for exchangeable amino acids to be assigned to similar codons can be excluded here as expected from earlier work. The first alternative hypothesis is that any such correlation between codon distance and amino acid distance is due to incremental mechanisms of code evolution, and not to adaptation to reduce deleterious effects of future mutations. More specifically, new codon assignments that occur by ambiguity reduction or by codon capture will tend to give rise to correlations, whether due to the condition of amino acid ambiguity, or to the condition of similarity between a new tRNA synthetase (or tRNA) and its parent. The second alternative hypothesis, the adaptive hypothesis, then may be defined as an excess relative to what may be expected given the incremental nature of evolution, reflecting true adaptation for robustness rather than an incidental effect. The results reported here indicate that most of the nonrandomness in the amino acids to codon assignments can be explained by incremental code evolution, with a small residue of orderliness that may reflect code adaptation.