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At least 19 recordsLinked to original sources
PubMed2001

Evolutionary self-organization of cell-free genetic coding.

Genetic encoding provides a generic construction scheme for biomolecular functions. This paper addresses the key problem of coevolution and exploitation of the multiple components necessary to implement a replicable genetic encoding scheme. Extending earlier results on multicomponent replication, the necessity of spatial structure for the evolutionary stabilization of the genetic coding system is established. An individual-based stochastic model of interacting molecules in three-dimensional space is presented that allows the evolution of genetic coding to be analyzed explicitly. A massively parallel configurable computer (NGEN) is used to implement the model, on the time scale of millions of generations, directly in electronic hardware. The spatial correlations between components of the genetic coding system are analyzed and found to be essential for evolutionary stability.

Animals↗
PubMed2002

Coding rules for amino acids in the genetic code: the genetic code is a minimal code of mutational deterioration.

Coding rules for amino acids in the genetic code are discussed from the point that the genetic code is a minimal code of mutational deterioration. The global mutational deterioration (GMD) function is defined through several parameters describing single base mutations and amino acid distances. The problem of searching for the global minimum of the GMD function is discussed in some detail. From GMD minimization under initial constraints we have succeeded in deducing the standard genetic code.

Amino Acids↗
PubMed1997

The non-standard genetic code of Candida spp.: an evolving genetic code or a novel mechanism for adaptation?

A number of yeasts of the genus Candida translate the standard leucine-CUG codon as serine. This unique genetic code change is the only known alteration to the universal genetic code in cytoplasmic mRNAs, of either eukaryotes or prokaryotes, which involves reassignment of a sense codon. Translation of CUG as serine in these species is mediated by a novel serine-tRNA (ser-tRNACAG), which uniquely has a guanosine at position 33, 5' to the anticodon, a position that is almost invariably occupied by a pyrimidine (uridine in general) in all other tRNAs. We propose that G-33 has two important functions: lowering the decoding efficiency of the ser-tRNACAG and preventing binding of the leucyl-tRNA synthetase. This implicates this nucleotide as a key player in the evolutionary reassignment of the CUG codon. In addition, the novel ser-tRNACAG has 1-methylguanosine (m1G-37) at position 37, 3' to the anticodon, which is characteristic of leucine, but not serine tRNAs. Remarkably, m1G-37 causes leucylation of the ser-tRNACAG both in vitro and in vivo, making the CUG codon an ambiguous codon: the polysemous codon. This indicates that some Candida species tolerate ambiguous decoding and suggests either that (i) the genetic code change has not yet been fully established and is evolving at different rates in different Candida species; or (ii) CUG ambiguity is advantageous and represents the final stage of the reassignment. We propose that such dual specificity indicates that reassignment of the CUG codon evolved through a mechanism that required codon ambiguity and that ambiguous decoding evolved to generate genetic diversity and allow for rapid adaptation to environmental challenges.

Adaptation, Physiological↗
PubMed2002

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.

Animals↗
PubMed2003

Codon usage decreases the error minimization within the genetic code.

The genetic code is not random but instead is organized in such a way that single nucleotide substitutions are more likely to result in changes between similar amino acids. This fidelity, or error minimization, has been proposed to be an adaptation within the genetic code. Many models have been proposed to measure this adaptation within the genetic code. However, we find that none of these consider codon usage differences between species. Furthermore, use of different indices of amino acid physicochemical characteristics leads to different estimations of this adaptation within the code. In this study, we try to establish a more accurate model to address this problem. In our model, a weighting scheme is established for mistranslation biases of the three different codon positions, transition/transversion biases, and codon usage. Different indices of amino acids' physicochemical characteristics are also considered. In contrast to pervious work, our results show that the natural genetic code is not fully optimized for error minimization. The genetic code, therefore, is not the most optimized one for error minimization, but one that balances between flexibility and fidelity for different species.

Amino Acid Substitution↗
PubMed1997

Improving the efficiency of the genetic code by varying the codon length--the perfect genetic code.

The function of DNA is to specify protein sequences. The four-base "alphabet" used in nucleic acids is translated to the 20 base alphabet of proteins (plus a stop signal) via the genetic code. The code is neither overlapping nor punctuated, but has mRNA sequences read in successive triplet codons until reaching a stop codon. The true genetic code uses three bases for every amino acid. The efficiency of the genetic code can be significantly increased if the requirement for a fixed codon length is dropped so that the more common amino acids have shorter codon lengths and rare amino acids have longer codon lengths. More efficient codes can be derived using the Shannon-Fano and Huffman coding algorithms. The compression achieved using a Huffman code cannot be improved upon. I have used these algorithms to derive efficient codes for representing protein sequences using both two and four bases. The length of DNA required to specify the complete set of protein sequences could be significantly shorter if transcription used a variable codon length. The restriction to a fixed codon length of three bases means that it takes 42% more DNA than the minimum necessary, and the genetic code is 70% efficient. One can think of many reasons why this maximally efficient code has not evolved: there is very little redundancy so almost any mutation causes an amino acid change. Many mutations will be potentially lethal frame-shift mutations, if the mutation leads to a change in codon length. It would be more difficult for the machinery of transcription to cope with a variable codon length. Nevertheless, in the strict and narrow sense of coding for protein sequences using the minimum length of DNA possible, the Huffman code derived here is perfect.

Algorithms↗
PubMed2004

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.

Codon↗
PubMed1985

A group theory analysis of the ambiguities in the genetic code: on the existence of a generalized genetic code.

It is known that in the transcription of genetic information there are ambiguities, i.e. the fact that a triplet codes for several aminoacids. This has generally been taken as due to errors in the transcription mechanisms. However, it has been postulated that instead of accidental miscoding, ambiguities are part of the expression of a generalized genetic code which depends on biological context. Group theory has been used to find the generalized genetic code. Here we present a new group theory approach which we think removes some weaknesses of previous works. The generalized genetic code presented here is different from that previously reported. We compare our results with experimental evidence and discuss the predictions presented.

Amino Acids↗
PubMedDate not supplied

Group graph of the genetic code.

The genetic code doublets can be divided into two octets of completely degenerate and ambiguous coding dinucleotides. These two octets have the algebraic property of lying on continuously connected planes on the group graph (a tesseract) of the Cartesian product of two Klein 4-groups of nucleotide exchange operators. The K X K group can also be broken into four cosets, one of which has completely degenerate coding elements, and another that has completely ambiguous coding elements. The two octets of coding doublets have the further algebraic property that the product of their internal exchange operators naturally divide into two exactly equivalent sets. These properties of the genetic code are relevant to unraveling error-detecting and error-correcting (proof-reading) aspects of the genetic code and may be helpful in understanding the context-sensitive grammar of genetic language.

Genetic Code↗
PubMed1990

Evolutionary changes in the genetic code.

The genetic code has been influenced by directional mutation pressure affecting the base composition of DNA, sometimes in the direction of increased GC content and at other times, in the direction of AT. Such pressure led to changes in species-specific usages of codons and tRNA anticodons, and also in amino acid assignments of codons in mitochondria and in several intact organisms. These code changes are probably recent evolutionary events. The genetic code is not 'frozen', but instead it is still evolving.

Base Sequence↗
PubMedDate not supplied

Self-description and the origin of the genetic code.

The genetic code presents an important conceptual challenge within the broader context of the origin of life. Translation of genetic information captures a fundamental property of living systems, i.e. the ability of decoding proteins (e.g. aminoacyl-tRNA synthetases) to reproduce themselves from self-contained RNA/DNA descriptors. Silvano Colombano and I, as graduate students with Howard Pattee in the 1970s, focused on achieving this closure of self-description and self-reproduction in the genetic code. Simulation and analysis of competitive models that allowed alternate code assignments, exploring initial conditions, arbitrary descriptor-catalyst relationships, and degree of non-linearity, indicated that these dynamical systems undergo bifurcations, transforming initial ambiguous stable states to unstable states. New, stable, steady states, progressively closer to a code, became available as the descriptor parameters were varied. The efficiency of utilization of raw materials for the production of a coding family of catalysts is proposed as a selection criterion that drives such systems towards a coded state.

Amino Acyl-tRNA Synthetases↗
PubMed2001

Rewiring the keyboard: evolvability of the genetic code.

The genetic code evolved in two distinct phases. First, the 'canonical' code emerged before the last universal ancestor; subsequently, this code diverged in numerous nuclear and organelle lineages. Here, we examine the distribution and causes of these secondary deviations from the canonical genetic code. The majority of non-standard codes arise from alterations in the tRNA, with most occurring by post-transcriptional modifications, such as base modification or RNA editing, rather than by substitutions within tRNA anticodons.

Animals↗
PubMed1983

[Baudot's code, weft of the genetic code].

Enumerating Bn numbers using only Bn figures is possible thanks to an overlapping reading of a cyclic sequence built according to Baudot's code. This code allows the genetic code to be screened to show the distribution of the synonyms of the aminoacids. The assignments of the genetic code obey strict laws of optimisation of resistance against the effects of mutations.

Amino Acid Sequence↗
PubMed1999

Selection, history and chemistry: the three faces of the genetic code.

The genetic code might be a historical accident that was fixed in the last common ancestor of modern organisms. 'Adaptive', 'historical' and 'chemical' arguments, however, challenge such a 'frozen accident' model. These arguments propose that the current code is somehow optimal, reflects the expansion of a more primitive code to include more amino acids, or is a consequence of direct chemical interactions between RNA and amino acids, respectively. Such models are not mutually exclusive, however. They can be reconciled by an evolutionary model whereby stereochemical interactions shaped the initial code, which subsequently expanded through biosynthetic modification of encoded amino acids and, finally, was optimized through codon reassignment. Alternatively, all three forces might have acted in concert to assign the 20 'natural' amino acids to their present positions in the genetic code.

Biological Evolution↗
PubMed1999

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.

Algorithms↗
PubMed2002

Origins of gene, genetic code, protein and life: comprehensive view of life systems from a GNC-SNS primitive genetic code hypothesis.

We have investigated the origin of genes, the genetic code, proteins and life using six indices (hydropathy, alpha-helix, beta-sheet and beta-turn formabilities, acidic amino acid content and basic amino acid content) necessary for appropriate three-dimensional structure formation of globular proteins. From the analysis of microbial genes, we have concluded that newly-born genes are products of nonstop frames (NSF) on antisense strands of microbial GC-rich genes [GC-NSF(a)] and from SNS repeating sequences [(SNS)n] similar to the GC-NSF(a) (S and N mean G or C and either of four bases, respectively). We have also proposed that the universal genetic code used by most organisms on the earth presently could be derived from a GNC-SNS primitive genetic code. We have further presented the [GADV]-protein world hypothesis of the origin of life as well as a hypothesis of protein production, suggesting that proteins were originally produced by random peptide formation of amino acids restricted in specific amino acid compositions termed as GNC-, SNS- and GC-NSF(a)-0th order structures of proteins. The [GADV]-protein world hypothesis is primarily derived from the GNC-primitive genetic code hypothesis. It is also expected that basic properties of extant genes and proteins could be revealed by considerations based on the scenario with four stages.

Amino Acids↗
PubMed1987

Information theory and the genetic code.

The genetic code, which directs the protein biosynthesis, is an information system. Although all its details are not known at present, its essential characteristics are elucidated, as well for the replication or transcription as for the translation of the genetic message. A coherent picture now appears, which reveals the existence of an universal structure, the most fundamental features of which seem to obey some logic. A systematic approach has been devised, which aims to their integration in a theorectical scheme: many features of the code table can thus be interpreted as resulting from a unique principle of best resistance against the effects of mutations. Any group of triplets or amino-acids can be considered along this line. It is more difficult however, to analyse the coexistence of two (or more) different groups. In this work, we propose to extend our optimization principle into a more general one, which includes the notion of information as defined by Shannon. We explore some consequences of this new principle in the most simple models that one can build for the origin and evolution of the genetic code.

Genetic Code↗