Genetic Code and its Variants

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.

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.

In animal mitochondria, six codons have been known as nonuniversal genetic codes, which vary in the course of animal evolution. They are UGA (termination codon in the universal genetic code changes to Trp codon in all animal mitochondria), AUA (Ile to Met in most metazoan mitochondria), AAA (Lys to Asn in echinoderm and some platyhelminth mitochondria), AGA/AGG (Arg to Ser in most invertebrate, Arg to Gly in tunicate, and Arg to termination in vertebrate mitochondria), and UAA (termination to Tyr in a planaria and a nematode mitochondria, but conclusive evidence is lacking in this case). We have elucidated that the anticodons of tRNAs deciphering these nonuniversal codons (tRNATrp for UGA, tRNAMet for AUA, tRNAAsn for AAA, and tRNASer and tRNAGly for AGA/AGG) are all modified; tRNATrp has 5-carboxymethylaminomethyluridine or 5-taurinomethyluridine, tRNAMet has 5-formylcytidine or 5-taurinomethyluridine, tRNASer has 7-methylguanosine and tRNAGly has 5-taurinomethyluridine in their anticodon wobble position, and tRNAAsn has pseudouridine in the anticodon second position. This review aims to clarify the structural relationship between these nonuniversal codons and the corresponding tRNA anticodons including modified nucleosides and to speculate on the possible mechanisms for explaining the evolutional changes of these nonuniversal codons in the course of animal evolution.

The standard genetic code is well known to be optimized for minimizing the phenotypic effects of single-nucleotide substitutions, a property that was likely selected for during the emergence of a universal code. Given the fitness advantage afforded by high standing genetic diversity in a population in a dynamic environment, it is possible that selection to explore a large fraction of the space of functional proteins also occurred. To determine whether selection for such a property played a role during the emergence of the nearly universalstandard genetic code, we investigated the number of functional variants of the Escherichia coli PhoQ protein explored at different time scales under translation using different genetic codes. We found that the standard genetic code is highly optimal for exploring a large fraction of the space of functional PhoQ variants at intermediate time scales as compared to random codes. Environmental changes, in response to which genetic diversity in a population provides a fitness advantage, are likely to have occurred at these intermediate time scales. Our results indicate that the ability of the standard code to explore a large fraction of the space of functional sequence variants arises from a balance between robustness and flexibility and is largely independent of the property of the standard code to minimize the phenotypic effects of mutations. We propose that selection to explore a large fraction of the functional sequence space while minimizing the phenotypic effects of mutations contributed toward the emergence of the standard code as the universal genetic code.

In this chapter, the genetic code seems to be a universal code. The universal code has a specific arrangement of the codons that is definitely not random. There are at least three major concepts of the origin and the evolution of the universal genetic code: Firstly, there is the stereochemical theory stating that the assignments of codons are determined by the physicochemical affinity of the amino acids and the cognate codons (synonymously referred to as anticodons); secondly, the co-evolution theory stating that the structure of the code structure coevolved with the biosynthesis process of amino acids; and thirdly, the error minimization theory stating that there is a selection pressure minimizing the negative effects of point mutations and errors in translation were the main factor of code development. These theories are not contradictory and are also in line with the frozen accident hypothesis, such as the idea that the standard code may not have any special properties, but is simply determined by the fact that all existing life forms have a common ancestor, whereby later alterations to the code are generally excluded by the detrimental effect of codon reallocation. The mathematical examination of the structure and potential evolutionary trajectories of the code reveals that the code is highly resistant to translation errors, although there are numerous more resistant codes, suggesting that the standard code could emerge from a random code through a short sequence of rearrangements of series of codons. A large proportion of the evolution leading to the standard code seems to be a mixture of a frozen collision with a selection for error minimization, even though it cannot be excluded that the code co-evolves along with metabolic pathways due to weak affinities between amino acids and nucleotide triplets. These scenarios for code evolution, nonetheless, are founded on formal patterns with uncertain relevance to real primordial evolution. A true comprehension of code origins and developments is probably only possible in connection with a plausible script for the development of the coding scheme and the translation tool itself.

The sequence of nucleotides in the genetic material, DNA, determines the amino-acid sequences of the cell proteins. This process is mediated by generally called messenger RNA, which moves from the nucleus to the cytoplasm where it specifies the amino-acid sequence of the proteins. If we could lay bare the entire DNA nucleotide of an organism and make assumptions about the size of genes, and further assume that all DNA is involved with protein synthesis, and use the code which equates nucleotide triplets with an amino acid, then we might predict the amino-acid sequences of all cell proteins. A comparison between the DNA sequences of different organisms might lead to an understanding of the evolutionary relationships between these, since it could be assumed that the phenotype of the organism bears some relationship to the proteins present. The prediction of the composition of proteins will depend on the phenomenon of degeneracy, among other things, and also must take account of certain cases of cytoplasmic directed processes which have an effect on the phenotype. These cytoplasmic phenomena, often grouped as cases of cytoplasmic inheritance, may not involve nucleic acid sequences (Sonneborn, 1963). Comparison of the genetic material of organisms which cannot interbreed can be made using the technique of nucleic acid hybridization. The method has been used to detect nucleic acid homologies in viruses, bacteria, protozoans and vertebrates (Lacy and Green, 1965; McCarthy and Bolton, 1963; Gibson, 1966; Hoyer et al., 1964). It can be used to test similarities in DNA and RNA nucleotide sequences in different tissues of the same organism or of different organisms (Whiteley et al., 1966; McCarthy and Hoyer, 1964). We have used it here to examine similarities between DNA and RNA molecules at different stages of development of some invertebrates and vertebrates.

Information is the currency of life, but the origin of prebiotic information remains a mystery. We propose transitional pathways from the cosmic building blocks of life to the complex prebiotic organic chemistry that led to the origin of information systems. The prebiotic information system, specifically the genetic code, is segregated, linear, and digital, and it appeared before the emergence of DNA. In the peptide/RNA world, lipid membranes randomly encapsulated amino acids, RNA, and peptide molecules, which are drawn from the prebiotic soup, to initiate a molecular symbiosis inside the protocells. This endosymbiosis led to the hierarchical emergence of several requisite components of the translation machine: transfer RNAs (tRNAs), aminoacyl-tRNA synthetase (aaRS), messenger RNAs (mRNAs), ribosomes, and various enzymes. When assembled in the right order, the translation machine created proteins, a process that transferred information from mRNAs to assemble amino acids into polypeptide chains. This was the beginning of the prebiotic information age. The origin of the genetic code is enigmatic; herein, we propose an evolutionary explanation: the demand for a wide range of protein enzymes over peptides in the prebiotic reactions was the main selective pressure for the origin of information-directed protein synthesis. The molecular basis of the genetic code manifests itself in the interaction of aaRS and their cognate tRNAs. In the beginning, aminoacylated ribozymes used amino acids as a cofactor with the help of bridge peptides as a process for selection between amino acids and their cognate codons/anticodons. This process selects amino acids and RNA species for the next steps. The ribozymes would give rise to pre-tRNA and the bridge peptides to pre-aaRS. Later, variants would appear and evolution would produce different but specific aaRS-tRNA-amino acid combinations. Pre-tRNA designed and built pre-mRNA for the storage of information regarding its cognate amino acid. Each pre-mRNA strand became the storage device for the genetic information that encoded the amino acid sequences in triplet nucleotides. As information appeared in the digital languages of the codon within pre-mRNA and mRNA, and the genetic code for protein synthesis evolved, the prebiotic chemistry then became more organized and directional with the emergence of the translation and genetic code. The genetic code developed in three stages that are coincident with the refinement of the translation machines: the GNC code that was developed by the pre-tRNA/pre-aaRS /pre-mRNA machine, SNS code by the tRNA/aaRS/mRNA machine, and finally the universal genetic code by the tRNA/aaRS/mRNA/ribosome machine. We suggest the coevolution of translation machines and the genetic code. The emergence of the translation machines was the beginning of the Darwinian evolution, an interplay between information and its supporting structure. Our hypothesis provides the logical and incremental steps for the origin of the programmed protein synthesis. In order to better understand the prebiotic information system, we converted letter codons into numerical codons in the Universal Genetic Code Table. We have developed a software, called CATI (Codon-Amino Acid-Translator-Imitator), to translate randomly chosen numerical codons into corresponding amino acids and vice versa. This conversion has granted us insight into how the genetic code might have evolved in the peptide/RNA world. There is great potential in the application of numerical codons to bioinformatics, such as barcoding, DNA mining, or DNA fingerprinting. We constructed the likely biochemical pathways for the origin of translation and the genetic code using the Model-View-Controller (MVC) software framework, and the translation machinery step-by-step. While using AnyLogic software, we were able to simulate and visualize the entire evolution of the translation machines, amino acids, and the genetic code.

The standard genetic code defines the rules of translation for nearly every life form on Earth. It also determines the amino acid changes accessible via single-nucleotide mutations, thus influencing protein evolvability-the ability of mutation to bring forth adaptive variation in protein function. One of the most striking features of the standard genetic code is its robustness to mutation, yet it remains an open question whether such robustness facilitates or frustrates protein evolvability. To answer this question, we use data from massively parallel sequence-to-function assays to construct and analyze 6 empirical adaptive landscapes under hundreds of thousands of rewired genetic codes, including those of codon compression schemes relevant to protein engineering and synthetic biology. We find that robust genetic codes tend to enhance protein evolvability by rendering smooth adaptive landscapes with few peaks, which are readily accessible from throughout sequence space. However, the standard genetic code is rarely exceptional in this regard, because many alternative codes render smoother landscapes than the standard code. By constructing low-dimensional visualizations of these landscapes, which each comprise more than 16 million mRNA sequences, we show that such alternative codes radically alter the topological features of the network of high-fitness genotypes. Whereas the genetic codes that optimize evolvability depend to some extent on the detailed relationship between amino acid sequence and protein function, we also uncover general design principles for engineering nonstandard genetic codes for enhanced and diminished evolvability, which may facilitate directed protein evolution experiments and the bio-containment of synthetic organisms, respectively.

Natural and artificial variations of the standard genetic code.

The genetic code establishes the relationship between all 64 possible arrangements of triplets (codons) of the four nucleotide bases contained in either DNA (A, T, G and C) or RNA (A, U, G and C) and the 20 amino acids that are used to construct proteins via ‘translation’ system as well as signals of translation initiation and termination. The historical events from 1950s to 1960s that contributed to the deciphering of the genetic code led to the development of the field of molecular biology. In 1960s, the genetic code was established to be ‘universal’ for all living organisms. However, from late 1970s, variations of genetic code have been found in various genetic systems. Variations of genetic code promote studies on the origin and evolution of the genetic code. Key Concepts: Genetic code is the correlation between nucleotide triplet and the corresponding amino acid. Genetic code consists of 64 triplet codons and sometimes ‘degenerate’. Central dogma states that genetic information flows unidirectionally from DNA to protein via RNA as an intermediary. A cell‐free protein system contains ribosome, S100 fraction, tRNA, amino acids, ATP, an energy recycling system and a template. Termination codon consists of UAG (amber codon), UAA (ochre codon) and UGA (opal codon), which code for no amino acid but instead cause protein synthesis to terminate. Initiation codon is AUG, which initiates protein synthesis with formyl‐methionine in bacteria and phage. Universal genetic code shows the way of assignment of 64 triplet codons to each of 20 amino acids and 3 termination codons, which is common to almost all extant organisms – bacteria, yeasts, viruses, plants and animals.

Evolution of the first genetic cells and the universal genetic code: A hypothesis based on macromolecular coevolution of RNA and proteins

The coevolution theory suggests that origin and evolution of the genetic code proceed along with development of synthetic pathway of amino acids. The coevolution theory is undoubtedly a correct idea, because the genetic code could not evolve, if synthetic pathways of new amino acids were not invented and the new amino acids did not accumulate at a large amount in the cells. On the other hand, studies on metabolic pathways have progressed and information about metabolic pathways obtained thus far has been stored in KEGG PATHWAY Database. Then, amino acid metabolic pathways were analyzed in detail in order to answer to the following questions. (1) The genetic code originated from what type of genetic code? (2) The genetic code has reached to the universal genetic code, passing through what type of intermediate genetic code, SNS code or RNY code? From the results, it could be reconfirmed that the genetic code originated from the GNC primeval genetic code and evolved to the universal genetic code passing through SNS genetic code. Lastly, limits and future prospects of the coevolution theory are also discussed.

Codon reassignment and the evolving genetic code: problems and pitfalls in post-genome analysis

The standard genetic code (SGC) is organized in such a way that similar codons encode similar amino acids. One of the earliest explanations for this was that the SGC is the result of natural selection to reduce the fitness cost, or “load,” from mutations in and mistranslation of protein-coding genes. However, it was later argued on both empirical and conceptual grounds that the SGC could not have evolved to reduce load. We claim that the empirical evidence has been misinterpreted and review how the pattern of amino acid similarities in the SGC are consistent with the “load minimization hypothesis” or “LM hypothesis.” We then present a model which addresses a second classical objection to the load minimization hypothesis: that selection for load minimization must be indirect or weak because it acts across generations. In this model, individual fitness is determined by a protein distribution resulting from the translation of its genetic message using a genetic code. Amino acids contribute independently and multiplicatively to the fitness of the protein distribution, which is defined relative to a fixed target protein. We show that in mutation-selection balance a fitness can be associated with a population of individuals with the same genetic code, and illustrate that structure-preserving codes that assign similar codons to similar amino acids confer higher fitness. We also show that in mutation-selection balance the total message of any individual behaves like a population of sites. That is, the usage of codons in a message in almost any individual reflects the codon frequencies across the population for a site of a given type, and consequently the fitness of almost all individuals is equal to the population fitness associated with their genetic code. We thereby establish that selection for load minimization in genetic codes acts at the level of an individual in a single generation. Comparing the fitness of two genetic codes, one more structure-preserving than the other, we find that the more structure-preserving code is associated with lower load and consequently higher fitness, despite the fact that the equilibrium fraction of mutant codons in its mutation-selection balance is larger; these results are explained and conjectured to hold in general. We conclude with comments on the origin of the genetic code from the perspective of a model of this kind, including its shortcomings and advantages over other hypotheses as a comprehensive explanation for the origin of the SGC.

A deviation from the universal genetic code was first discovered in mammalian mitochondria in 1979. In the 1980s, several unusual genetic codes were also reported in animal organella. However, the genetic code in nuclear systems is less changeable than in organella.