Parallel evolution of the genetic code in arthropod mitochondrial genomes

The genetic code provides the translation table necessary to transform the information contained in DNA into the language of proteins. In this table, a correspondence between each codon and each amino acid is established: tRNA is the main adaptor that links the two. Although the genetic code is nearly universal, several variants of this code have been described in a wide range of nuclear and organellar systems, especially in metazoan mitochondria. These variants are generally found by searching for conserved positions that consistently code for a specific alternative amino acid in a new species. We have devised an accurate computational method to automate these comparisons, and have tested it with 626 metazoan mitochondrial genomes. Our results indicate that several arthropods have a new genetic code and translate the codon AGG as lysine instead of serine (as in the invertebrate mitochondrial genetic code) or arginine (as in the standard genetic code). We have investigated the evolution of the genetic code in the arthropods and found several events of parallel evolution in which the AGG codon was reassigned between serine and lysine. Our analyses also revealed correlated evolution between the arthropod genetic codes and the tRNA-Lys/-Ser, which show specific point mutations at the anticodons. These rather simple mutations, together with a low usage of the AGG codon, might explain the recurrence of the AGG reassignments.     

Yeast as a model organism for studying the evolution of non-standard genetic codes.

During the last 30 years, a number of alterations to the standard genetic code have been uncovered both in prokaryotes and eukaryotic nuclear and mitochondrial genomes. But, the study of the evolutionary pathways and molecular mechanisms of codon identity redefinition has been largely ignored due to the assumption that non-standard genetic codes can only evolve through neutral evolutionary mechanisms and that they have no functional significance. The recent discovery of a genetic code change in the genus Candida that evolved through an ambiguous messenger RNA decoding mechanism is bringing that naive assumption to an abrupt end by showing, in a rather dramatic way, that genetic code changes have profound physiological and evolutionary consequences for the species that redefine codon identity. In this paper, the recent data on the evolution of the Candida genetic code are reviewed and an experimental framework based on forced evolution, molecular genetics and comparative and functional genomics methodologies is put forward for the study of non-standard genetic codes and genetic code ambiguity in general. Additionally, the importance of using Saccharomyces cerevisiae as a model organism for elucidating the evolutionary pathway of the Candida and other genetic code changes is emphasised.     

线粒体遗传密码及基因组遗传密码的对称分析

病毒、细菌和真核生物的氨基酸编码都使用相同的遗传密码,表明它们可能有共同的来源。但人和牛的线粒体的遗传密码和基因组的遗传密码相比,出现以下不同;（1）ATA编码甲硫氮酸M而不是异亮氨酸I。（2）TGA不再是终止密码子X而编码色氨酸W。（3）AGA和AGG不再是精氨酸R的密码子而变为终止密码子X。应用高维空间拓扑分析的方法,对线粒体遗传密码和基因组遗传密码的6维编码空间进行对称性分析,得到如下结果：（1）线粒体遗传密码的起始密码子是2个而不是1个。（2）线粒体遗传密码的终止密码子是4个而不是3个。（3）线粒体遗传密码空间只有2、4、6三种偶数简并度而没1、3两种奇数简并度,表明其对称度较高。（4）线粒体遗传密码空间除丝氨酸S分成两个平行的子空间之外,终止密码子X亦分成两个平行的子空间,表明其连通度较低。（5）线粒体遗传密码一基因组遗传密码相比,共有3个简并平面出现变异,即：1001λλ（M和I）,011λ1λ（W和X）,以及1011λλ（S和X或S和R）。（6）基因组遗传密码的1、3两种奇数简并度可能来源于线粒体遗传密码的1001λλ平面和011λ1λ平面的对称性破缺。对线粒体遗传密码变异的生物学意义及遗传密码的起源进行了分析和讨论。     

The standard genetic code enhances adaptive evolution of proteins

The standard genetic code, by which most organisms translate genetic material into protein metabolism, is non-randomly organized. The Error Minimization hypothesis interprets this non-randomness as an adaptation, proposing that natural selection produced a pattern of codon assignments that buffers genomes against the impact of mutations. Indeed, on the average any given point mutation has a lesser effect on the chemical properties of the utilized amino acid than expected by chance. Might it also, however, be the case that the non-random nature of the code effects the rate of adaptive evolution? To investigate this, here we develop population genetic simulations to test the rate of adaptive gene evolution under different genetic codes. We identify two independent properties of a genetic code that profoundly influence the speed of adaptive evolution. Noting that the standard genetic code exhibits both, we offer a new insight into the effects of the "error minimizing" code: such a code enhances the efficacy of adaptive sequence evolution.     

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.     

Comparison of translation loads for standard and alternative genetic codes

Background  

The (almost) universality of the genetic code is one of the most intriguing properties of cellular life. Nevertheless, several variants of the standard genetic code have been observed, which differ in one or several of 64 codon assignments and occur mainly in mitochondrial genomes and in nuclear genomes of some bacterial and eukaryotic parasites. These variants are usually considered to be the result of non-adaptive evolution. It has been shown that the standard genetic code is preferential to randomly assembled codes for its ability to reduce the effects of errors in protein translation.     

An Alternative Look at Code Evolution: Using Non-canonical Codes to Evaluate Adaptive and Historic Models for the Origin of the Genetic Code

The canonical code has been shown many times to be highly robust against point mutations; that is, mutations that change a single nucleotide tend to result in similar amino acids more often than expected by chance. There are two major types of models for the origin of the code, which explain how this sophisticated structure evolved. Adaptive models state that the primitive code was specifically selected for error minimization, while historic models hypothesize that the robustness of the code is an artifact or by-product of the mechanism of code evolution. In this paper, we evaluated the levels of robustness in existing non-canonical codes as well as codes that differ in only one codon assignment from the standard code. We found that the level of robustness of many of these codes is comparable or better than that of the standard code. Although these results do not preclude an adaptive origin of the genetic code, they suggest that the code was not selected for minimizing the effects of point mutations.     

The evolution of the mitochondrial genetic code in arthropods revisited

A variant of the invertebrate mitochondrial genetic code was previously identified in arthropods (Abascal et al. 2006a, PLoS Biol 4:e127) in which, instead of translating the AGG codon as serine, as in other invertebrates, some arthropods translate AGG as lysine. Here, we revisit the evolution of the genetic code in arthropods taking into account that (1) the number of arthropod mitochondrial genomes sequenced has triplicated since the original findings were published; (2) the phylogeny of arthropods has been recently resolved with confidence for many groups; and (3) sophisticated probabilistic methods can be applied to analyze the evolution of the genetic code in arthropod mitochondria. According to our analyses, evolutionary shifts in the genetic code have been more common than previously inferred, with many taxonomic groups displaying two alternative codes. Ancestral character-state reconstruction using probabilistic methods confirmed that the arthropod ancestor most likely translated AGG as lysine. Point mutations at tRNA-Lys and tRNA-Ser correlated with the meaning of the AGG codon. In addition, we identified three variables (GC content, number of AGG codons, and taxonomic information) that best explain the use of each of the two alternative genetic codes.     

Some mathematical refinements concerning error minimization in the genetic code

The genetic code is known to have a high level of error robustness and has been shown to be very error robust compared to randomly selected codes, but to be significantly less error robust than a certain code found by a heuristic algorithm. We formulate this optimization problem as a Quadratic Assignment Problem and use this to formally verify that the code found by the heuristic algorithm is the global optimum. We also argue that it is strongly misleading to compare the genetic code only with codes sampled from the fixed block model, because the real code space is orders of magnitude larger. We thus enlarge the space from which random codes can be sampled from approximately 2.433 × 10(18) codes to approximately 5.908 × 10(45) codes. We do this by leaving the fixed block model, and using the wobble rules to formulate the characteristics acceptable for a genetic code. By relaxing more constraints, three larger spaces are also constructed. Using a modified error function, the genetic code is found to be more error robust compared to a background of randomly generated codes with increasing space size. We point out that these results do not necessarily imply that the code was optimized during evolution for error minimization, but that other mechanisms could be the reason for this error robustness.     

Genetic codes as evolutionary filters: subtle differences in the structure of genetic codes result in significant differences in patterns of nucleotide substitution

The codon-degeneracy model (CDM) predicts that patterns of nucleotide substitution in protein-coding genes are largely determined by the relative frequencies of four-fold (4f), two-fold, and non-degenerate sites, the attributes of which are determined by the structure of the governing genetic code. The CDM thus further predicts that genetic codes with alternative structures will "filter" molecular evolution differentially. A method, therefore, is presented by which the CDM may be applied to the unique structure of any genetic code. The mathematical relationship between the proportion of transitions at 4f degenerate nucleotide sites and the transition-to-transversion ratio is described. Predictions for five individual genetic codes, relative to the relationship between code structure and expected patterns of nucleotide substitution, are clearly defined. To test this "filter" hypothesis of genetic codes, simulated DNA sequence data sets were generated with a variety of input parameter values to estimate the relationship between patterns of nucleotide substitution and best-fit estimates of transition bias at 4f degenerate sites for both the universal genetic code and the vertebrate mitochondrial genetic code. These analyses confirm the prediction of the CDM that, all else being equal, even small differences in the structure of alternative genetic codes may result in significant shifts in the overall pattern of nucleotide substitution.     

Evolutionary deviations from the universal genetic code in ciliates

The review surveys the information, including the most recent data, on the evolution of genetic code in ciliates, which is among the few codes deviating from the universal one. We discuss the cases of recurrent, independently arising deviations from the assignments of standard codons of polypeptide chain termination in the mitochondrial and nuclear genomes of ciliates and some other protozoans. Possible molecular mechanisms are considered, which underlie deviations from standard termination code to coding glutamine (codon UAA and UAG) and cystein or tryptophane (codon UGA) in the nuclear genome. Critical analysis of the main hypotheses on the evolution of secondary deviations from the universal code in ciliates is presented.     

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.     

The Coevolution of Genes and Genetic Codes: Crick’s Frozen Accident Revisited

The standard genetic code is the nearly universal system for the translation of genes into proteins. The code exhibits two salient structural characteristics: it possesses a distinct organization that makes it extremely robust to errors in replication and translation, and it is highly redundant. The origin of these properties has intrigued researchers since the code was first discovered. One suggestion, which is the subject of this review, is that the code’s organization is the outcome of the coevolution of genes and genetic codes. In 1968, Francis Crick explored the possible implications of coevolution at different stages of code evolution. Although he argues that coevolution was likely to influence the evolution of the code, he concludes that it falls short of explaining the organization of the code we see today. The recent application of mathematical modeling to study the effects of errors on the course of coevolution, suggests a different conclusion. It shows that coevolution readily generates genetic codes that are highly redundant and similar in their error-correcting organization to the standard code. We review this recent work and suggest that further affirmation of the role of coevolution can be attained by investigating the extent to which the outcome of coevolution is robust to other influences that were present during the evolution of the code. Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users. [Reviewing Editor: Dr. Martin Kreitman]     

Mitochondrial genome evolution in the social amoebae

Most mitochondria contain a core set of genes required for mitochondrial function, but beyond this base there are variable genomic features. The mitochondrial genome of the model species Dictyostelium discoideum demonstrated that the social amoebae mitochondrial genomes have a size between those of metazoans and plants, but no comparative study of social amoebae mitochondria has been performed. Here, we present a comparative analysis of social amoebae mitochondrial genomes using D. discoideum, Dictyostelium citrinum, Dictyostelium fasciculatum, and Polysphondylium pallidum. The social amoebae mitochondria have similar sizes, AT content, gene content and have a high level of synteny except for one segmental rearrangement and extensive displacement of tRNAs. From the species that contain the rearrangement, it can be concluded that the event occurred late in the evolution of social amoebae. A phylogeny using 36 mitochondrial genes produced a well-supported tree suggesting that the pairs of D. discoideum/D. citrinum and D. fasciculatum/P. pallidum are sister species although the position of the root is not certain. Group I introns and endonucleases are variable in number and location in the social amoebae. Phylogenies of the introns and endonucleases suggest that there have been multiple recent duplications or extinctions and confirm that endonucleases have the ability to insert into new areas. An analysis of dN/dS ratios in mitochondrial genes revealed that among groups of genes, adenosine triphosphate synthase complex genes have the highest ratio, whereas cytochrome oxidase and nicotinamide adenine dinucleotide (NADH) dehydrogenase genes had the lowest ratio. The genetic codes of D. citrinum, P. pallidum, and D. fasciculatum are the universal code although D. fasciculatum does not use the TGA stop codon. In D. fasciculatum, we demonstrate for the first time that a mitochondrial genome without the TGA stop codon still uses the release factor RF2 that recognizes TGA. Theories of how the genetic code can change and why RF2 may be a constraint against switching codes are discussed.     

Use of a deviant mitochondrial genetic code in yellow-green algae as a landmark for segregating members within the phylum

Several algae that were previously classified in the phylum Xanthophyta (yellow-green algae) were assigned in 1971 to a new phylum, Eustigmatophyta. It was anticipated that the number of algae reclassified to Eustigmatophyta would increase. However, due to the fact that the morphological characteristics that segregate eustigmatophytes from other closely related algae can be only obtained through laborious electron microscopic techniques, the number of members in this phylum have increased rather slowly. We attempted, therefore, to segregate two closely related groups of algae, eustigmatophytes and yellow-green algae, on the basis of a molecular phylogenetic tree as a means of providing an alternative method of distinguishing these phyla. We analyzed the mitochondrial cytochrome oxidase subunit I (COXI) gene sequences of eight algae classified as xanthophyceans and found that six manifested the expected deviant genetic code where AUA codes for methionine (AUA/Met), but not for isoleucine (AUA/Ile) as in the universal genetic code. The other two, Monodus sp. (CCMP 505) and Ophiocytium majus (CCAP 855/1), which were presumed to be yellow-green algae, and all the examined eustigmatophytes utilized AUA for Ile. In addition, the phylogenetic tree of COXI gene sequences showed that the six yellow-green algae bearing the AUA/Met deviant code composed a tight clade with a bootstrap value of 100%. The phylogenetic tree of the corresponding sequences from Monodus sp. and Ophiocytium majus and the eustigmatophytes also composed a tight cluster, but with a bootstrap value of 92%. These results strongly suggest that two previously classified members of yellow-green algae belong to the phylum Eustigmatophyta. Therefore, examination of the mitochondrial genetic code in algae appears to be a potentially very useful genetic marker for classifying these organisms, especially when it is considered with the results obtained through a molecular phylogenetic tree. Received: 14 December 1996 / Accepted: 3 April 1997     

Natural history and experimental evolution of the genetic code

The standard genetic code is a set of rules that relates the 20 canonical amino acids in proteins to groups of three bases in the mRNA. It evolved from a more primitive form and the attempts to reconstruct its natural history are based on its present-day features. Genetic code engineering as a new research field was developed independently in a few laboratories during the last 15 years. The main intention is to re-program protein synthesis by expanding the coding capacities of the genetic code via re-assignment of specific codons to un-natural amino acids. This article focuses on the question as to which extent hypothetical scenarios that led to codon re-assignments during the evolution of the genetic code are relevant for its further evolution in the laboratory. Current attempts to engineer the genetic code are reviewed with reference to theoretical works on its natural history. Integration of the theoretical considerations into experimental concepts will bring us closer to designer cells with target-engineered genetic codes that should open not only tremendous possibilities for the biotechnology of the twenty-first century but will also provide a basis for the design of novel life forms.     

No accident: genetic codes freeze in error-correcting patterns of the standard genetic code

The standard genetic code poses a challenge in understanding the evolution of information processing at a fundamental level of biological organization. Genetic codes are generally coadapted with, or 'frozen' by, the protein-coding genes that they translate, and so cannot easily change by natural selection. Yet the standard code has a significantly non-random pattern that corrects common errors in the transmission of information in protein-coding genes. Because of the freezing effect and for other reasons, this pattern has been proposed not to be due to selection but rather to be incidental to other evolutionary forces or even entirely accidental. We present results from a deterministic population genetic model of code-message coevolution. We explicitly represent the freezing effect of genes on genetic codes and the perturbative effect of changes in genetic codes on genes. We incorporate characteristic patterns of mutation and translational error, namely, transition bias and positional asymmetry, respectively. Repeated selection over small successive changes produces genetic codes that are substantially, but not optimally, error correcting. In particular, our model reproduces the error-correcting patterns of the standard genetic code. Aspects of our model and results may be applicable to the general problem of adaptation to error in other natural information-processing systems.     

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.     

The genetic code in bovine mitochondria: sequence of genes for the cytochrome oxidase subunit II and two tRNAs

Bovine-heart mitochondrial DNA from a single animal was isolated and fragments representative of the entire genome cloned into multicopy plasmid vectors to facilitate determination of its complete nucleotide sequence. We present here the sequence of the region covering the gene for cytochrome oxidase subunit II. Comparison of this sequence with the amino acid sequence of the homologous beef-heart protein has enabled the determination of most of the bovine mitochondrial genetic code. The code differs from the "universal" genetic code in that UGA codes for tryptophan and not termination, and AUA codes for methionine and not isoleucine. The only codon family not represented is the AGA/AGG pair normally used for arginine; evidence from other genes suggests that these code for termination in bovine mitochondria. The sequence presented also includes the adjacent tRNAAsp and tRNALys genes. The tRNAAsp gene is separated by one nucleotide from the 5' end of the COII gene and only three bases separate the 3' end of this gene and the adjacent tRNALys gene. This highly compact gene organisation is very similar to that found in the corresponding region of the human mitochondrial genome and the gene arrangement is identical. The structure of the respective bovine and human tRNAs vary primarily the "D-" and "T psi C-loops".     

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.