The genetic code is nearly universal, and the arrangement of the codons in the standard codon table is highly non-random. The three main concepts on the origin and evolution of the code are the stereochemical theory, according to which codon assignments are dictated by physico-chemical affinity between amino acids and the cognate codons (anticodons); the coevolution theory, which posits that the code structure coevolved with amino acid biosynthesis pathways; and the error minimization theory under which selection to minimize the adverse effect of point mutations and translation errors was the principal factor of the code’s evolution. These theories are not mutually exclusive and are also compatible with the frozen accident hypothesis, i.e., the notion that the standard code might have no special properties but was fixed simply because all extant life forms share a common ancestor, with subsequent changes to the code, mostly, precluded by the deleterious effect of codon reassignment. Mathematical analysis of the structure and possible evolutionary trajectories of the code shows that it is highly robust to translational misreading but there are numerous more robust codes, so the standard code potentially could evolve from a random code via a short sequence of codon series reassignments. Thus, much of the evolution that led to the standard code could be a combination of frozen accident with selection for error minimization although contributions from coevolution of the code with metabolic pathways and weak affinities between amino acids and nucleotide triplets cannot be ruled out. However, such scenarios for the code evolution are based on formal schemes whose relevance to the actual primordial evolution is uncertain. A real understanding of the code origin and evolution is likely to be attainable only in conjunction with a credible scenario for the evolution of the coding principle itself and the translation system.
The standard genetic code (SGC) is virtually universal among extant life forms. Although many deviations from the universal code exist, particularly in organelles and prokaryotes with small genomes, they are limited in scope and obviously secondary. The universality of the code likely results from the combination of a frozen accident, i.e., the deleterious effect of codon reassignment in the SGC, and the inhibitory effect of changes in the code on horizontal gene transfer. The structure of the SGC is nonrandom and ensures high robustness of the code to mutational and translational errors. However, this error minimization is most likely a by-product of the primordial code expansion driven by the diversification of the repertoire of protein amino acids, rather than a direct result of selection. Phylogenetic analysis of translation system components, in particular aminoacyl-tRNA synthetases, shows that, at a stage of evolution when the translation system had already attained high fidelity, the correspondence between amino acids and cognate codons was determined by recognition of amino acids by RNA molecules, i.e., proto-tRNAs. We propose an experimentally testable scenario for the evolution of the code that combines recognition of amino acids by unique sites on proto-tRNAs (distinct from the anticodons), expansion of the code via proto-tRNA duplication, and frozen accident.
In this review, we discuss applications of the theory of birth-and-death processes to problems in biology, primarily, those of evolutionary genomics. The mathematical principles of the theory of these processes are briefly described. Birth-and-death processes, with some straightforward additions such as innovation, are a simple, natural and formal framework for modeling a vast variety of biological processes such as population dynamics, speciation, genome evolution, including growth of paralogous gene families and horizontal gene transfer and somatic evolution of cancers. We further describe how empirical data, e.g. distributions of paralogous gene family size, can be used to choose the model that best reflects the actual course of evolution among different versions of birth-death-and-innovation models. We conclude that birth-and-death processes, thanks to their mathematical transparency, flexibility and relevance to fundamental biological processes, are going to be an indispensable mathematical tool for the burgeoning field of systems biology.
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