Genetic code evolution reveals the neutral emergence of mutational robustness, and information as an evolutionary constraint

Self-similarity and the maximum entropy principle in the genetic code

This paper addresses the relationship between information and structure of the genetic code. The code has two puzzling anomalies: First, when viewed as 64 sub-cubes of a [Formula: see text] cube, the codons for serine (S) are not contiguous, and there are amino acid codons with zero redundancy, which goes counter to the objective of error correction. To make sense of this, the paper shows that the genetic code must be viewed not only on stereochemical, co-evolution, and error-correction considerations, but also on two additional factors of significance to natural systems, that of an information-theoretic dimensionality of the code data, and the principle of maximum entropy. One implication of non-integer dimensionality associated with data dimensions is self-similarity to different scales, and it is shown that the genetic code does satisfy this property, and it is further shown that the maximum entropy principle operates through the scrambling of the elements in the sense of maximum algorithmic information complexity, generated by an appropriate exponentiation mapping. It is shown that the new considerations and the use of maximum entropy transformation create new constraints that are likely the reasons for the non-uniform codon groups and codons with no redundancy.

Model of Genetic Code Structure Evolution under Various Types of Codon Reading

The standard genetic code (SGC) is a set of rules according to which 64 codons are assigned to 20 canonical amino acids and stop coding signal. As a consequence, the SGC is redundant because there is a greater number of codons than the number of encoded labels. This redundancy implies the existence of codons that encode the same genetic information. The size and organization of such synonymous codon blocks are important characteristics of the SGC structure whose evolution is still unclear. Therefore, we studied possible evolutionary mechanisms of the codon block structure. We conducted computer simulations assuming that coding systems at early stages of the SGC evolution were sets of ambiguous codon assignments with high entropy. We included three types of reading systems characterized by different inaccuracy and pattern of codon recognition. In contrast to the previous study, we allowed for evolution of the reading systems and their competition. The simulations performed under minimization of translational errors and reduction of coding ambiguity produced the coding system resistant to these errors. The reading system similar to that present in the SGC dominated the others very quickly. The survived system was also characterized by low entropy and possessed properties similar to that in the SGC. Our simulation show that the unambiguous SGC could emerged from a code with a lower level of ambiguity and the number of tRNAs increased during the evolution.

Somatic Mutation Profiles Revealed by Next Generation Sequencing (NGS) in 39 Chinese Hepatocellular Carcinoma Patients

The features and significance of somatic mutation profiles in hepatocellular carcinoma (HCC) have not been completely elucidated to date. In this study, 39 tumor specimens from HCC patients were collected for gene variation analysis by next-generation sequencing (NGS), and a correlation analysis between mutated genes and clinical characteristics was also conducted. The results were compared with genome data from cBioPortal database. Our study found that T > G/A > C transversions (Tv) and C > T/G > A transitions (Ti) were dominant. The sequence variations of TP53, MUC16, MUC12, MUC4 and others, and the copy number variations (CNVs) of FGF3, TERT, and SOX2 were found to be more frequent in our cohort than in cBioPortal datasets, and they were highly enriched in pathways in cancer and participated in complex biological regulatory processes. The TP53 mutation was the key mutation (76.9%, 30/39), and the most common amino acid alteration and mutation types were p.R249S (23.5%) and missense mutation (82.3%) in the TP53 variation. Furthermore, TP53 had more co-mutations with MUC17, NBPF10, and AHNAK2. However, there were no significant differences in clinical characteristics between HCC patients with mutant TP53 and wild-type TP53, and the overall survival rate between treatment via precision medication guided by NGS and that via empirical medication (logrank p = 0.181). Therefore, the role of NGS in the guidance of personalized targeted therapy, solely based on NGS, may be limited. Multi-center, large sample, prospective studies are needed to further verify these results.

Proteome size reduction in Apicomplexans is linked with loss of DNA repair and host redundant pathways

Apicomplexans are alveolate parasites which include Plasmodium falciparum, the main cause of malaria, one of the world's biggest killers from infectious disease. Apicomplexans are characterized by a reduction in proteome size, which appears to result from metabolic and functional simplification, commensurate with their parasitic lifestyle. However, other factors may also help to explain gene loss such as population bottlenecks experienced during transmission, and the effect of reducing the overall genomic information content. The latter constitutes an 'informational constraint', which is proposed to exert a selective pressure to evolve and maintain genes involved in informational fidelity and error correction, proportional to the quantity of information in the genome (which approximates to proteome size). The dynamics of gene loss was examined in 41 Apicomplexan genomes using orthogroup analysis. We show that loss of genes involved in amino acid metabolism and steroid biosynthesis can be explained by metabolic redundancy with the host. We also show that there is a marked tendency to lose DNA repair genes as proteome size is reduced. This may be explained by a reduction in size of the informational constraint and can help to explain elevated mutation rates in pathogens with reduced genome size. Multiple Sequentially Markovian Coalescent (MSMC) analysis indicates a recent bottleneck, consistent with predictions generated using allele-based population genetics approaches, implying that relaxed selection pressure due to reduced population size might have contributed to gene loss. However, the non-randomness of pathways that are lost challenges this scenario. Lastly, we identify unique orthogroups in malaria-causing Plasmodium species that infect humans, with a high proportion of membrane associated proteins. Thus, orthogroup analysis appears useful for identifying novel candidate pathogenic factors in parasites, when there is a wide sample of genomes available.

On the Origin of Biomolecular Networks

Biomolecular networks have already found great utility in characterizing complex biological systems arising from pairwise interactions amongst biomolecules. Here, we explore the important and hitherto neglected role of information asymmetry in the genesis and evolution of such pairwise biomolecular interactions. Information asymmetry between sender and receiver genes is identified as a key feature distinguishing early biochemical reactions from abiotic chemistry, and a driver of network topology as biomolecular systems become more complex. In this context, we review how graph theoretical approaches can be applied not only for a better understanding of various proximate (mechanistic) relations, but also, ultimate (evolutionary) structures encoded in such networks from among all types of variations they induce. Among many possible variations, we emphasize particularly the essential role of gene duplication in terms of signaling game theory, whereby sender and receiver gene players accrue benefit from gene duplication, leading to a preferential attachment mode of network growth. The study of the resulting dynamics suggests many mathematical/computational problems, the majority of which are intractable yet yield to efficient approximation algorithms, when studied through an algebraic graph theoretic lens. We relegate for future work the role of other possible generalizations, additionally involving horizontal gene transfer, sexual recombination, endo-symbiosis, etc., which enrich the underlying graph theory even further.

The influence of different types of translational inaccuracies on the genetic code structure

BACKGROUND

The standard genetic code is a recipe for assigning unambiguously 21 labels, i.e. amino acids and stop translation signal, to 64 codons. However, at early stages of the translational machinery development, the codons did not have to be read unambiguously and the early genetic codes could have contained some ambiguous assignments of codons to amino acids. Therefore, the goal of this work was to obtain the genetic code structures which could have evolved assuming different types of inaccuracy of the translational machinery starting from unambiguous assignments of codons to amino acids.

RESULTS

We developed a theoretical model assuming that the level of uncertainty of codon assignments can gradually decrease during the simulations. Since it is postulated that the standard code has evolved to be robust against point mutations and mistranslations, we developed three simulation scenarios assuming that such errors can influence one, two or three codon positions. The simulated codes were selected using the evolutionary algorithm methodology to decrease coding ambiguity and increase their robustness against mistranslation.

CONCLUSIONS

The results indicate that the typical codon block structure of the genetic code could have evolved to decrease the ambiguity of amino acid to codon assignments and to increase the fidelity of reading the genetic information. However, the robustness to errors was not the decisive factor that influenced the genetic code evolution because it is possible to find theoretical codes that minimize the reading errors better than the standard genetic code.

Evolution of the genetic code based on conservative changes of codons, amino acids, and aminoacyl tRNA synthetases

The genetic code, as arranged in the standard tabular form, displays a non-random structure relating to the characteristics of the amino acids. An alternative arrangement can be made by organizing the code according to aminoacyl-tRNA synthetases (aaRSs), codons, and reverse complement codons, which illuminates a coevolutionary process that led to the contemporary genetic code. As amino acids were added to the genetic code, they were recognized by aaRSs that interact with stereochemically similar amino acids. Single nucleotide changes in the codons and anticodons were favored over more extensive changes, such that there was a logical stepwise progression in the evolution of the genetic code. The model presented traces the evolution of the genetic code accounting for these steps. Amino acid frequencies in ancient proteins and the preponderance of GNN codons in mRNAs for ancient proteins indicate that the genetic code began with alanine, aspartate, glutamate, glycine, and valine, with alanine being in the highest proportions. In addition to being consistent in terms of conservative changes in codon nucleotides, the model also is consistent with respect to aaRS classes, aaRS attachment to the tRNA, amino acid stereochemistry, and to a large extent with amino acid physicochemistry, and biochemical pathways.

Genetic Code Error Minimization as a Non-Adaptive But Beneficial Trait

In a recent Letter, Di Giulio questions the use of the term 'neutral' when describing the process by which error minimization may have arisen as a side-product of genetic code expansion, resulting from the addition of similar amino acids to similar codons (Di Giulio, in J Mol Evol 86(9):593-597, 2018). However, I point out that in this scenario error minimization is non-adaptive, and so 'neutral' is an appropriate term to describe its imperviousness to direct selection. Error minimization is a form of mutational robustness, and so commonly viewed as beneficial. This in turn implies that not all beneficial traits may be adaptations generated by direct selection for that trait.

The optimality of the standard genetic code assessed by an eight-objective evolutionary algorithm

BACKGROUND

The standard genetic code (SGC) is a unique set of rules which assign amino acids to codons. Similar amino acids tend to have similar codons indicating that the code evolved to minimize the costs of amino acid replacements in proteins, caused by mutations or translational errors. However, if such optimization in fact occurred, many different properties of amino acids must have been taken into account during the code evolution. Therefore, this problem can be reformulated as a multi-objective optimization task, in which the selection constraints are represented by measures based on various amino acid properties.

RESULTS

To study the optimality of the SGC we applied a multi-objective evolutionary algorithm and we used the representatives of eight clusters, which grouped over 500 indices describing various physicochemical properties of amino acids. Thanks to that we avoided an arbitrary choice of amino acid features as optimization criteria. As a consequence, we were able to conduct a more general study on the properties of the SGC than the ones presented so far in other papers on this topic. We considered two models of the genetic code, one preserving the characteristic codon blocks structure of the SGC and the other without this restriction. The results revealed that the SGC could be significantly improved in terms of error minimization, hereby it is not fully optimized. Its structure differs significantly from the structure of the codes optimized to minimize the costs of amino acid replacements. On the other hand, using newly defined quality measures that placed the SGC in the global space of theoretical genetic codes, we showed that the SGC is definitely closer to the codes that minimize the costs of amino acids replacements than those maximizing them.

CONCLUSIONS

The standard genetic code represents most likely only partially optimized systems, which emerged under the influence of many different factors. Our findings can be useful to researchers involved in modifying the genetic code of the living organisms and designing artificial ones.

Optimization of the standard genetic code according to three codon positions using an evolutionary algorithm

Many biological systems are typically examined from the point of view of adaptation to certain conditions or requirements. One such system is the standard genetic code (SGC), which generally minimizes the cost of amino acid replacements resulting from mutations or mistranslations. However, no full consensus has been reached on the factors that caused the evolution of this feature. One of the hypotheses suggests that code optimality was directly selected as an advantage to preserve information about encoded proteins. An important feature that should be considered when studying the SGC is the different roles of the three codon positions. Therefore, we investigated the robustness of this code regarding the cost of amino acid replacements resulting from substitutions in these positions separately and the sum of these costs. We applied a modified evolutionary algorithm and included four models of the genetic code assuming various restrictions on its structure. The SGC was compared both with the codes that minimize the objective function and those that maximize it. This approach allowed us to place the SGC in the global space of possible codes, which is a more appropriate and unbiased comparison than that with randomly generated codes because they are characterized by relatively uniform amino acid assignments to codons. The SGC appeared to be well optimized at the global scale, but its individual positions were not fully optimized because there were codes that were optimized for only one codon position and simultaneously outperformed the SGC at the other positions. We also found that different code structures may lead to the same optimality and that random codes can show a tendency to minimize costs under some of the genetic code models. Our results suggest that the optimality of SGC could be a by-product of other processes.

The Standard Genetic Code Facilitates Exploration of the Space of Functional Nucleotide Sequences

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 universal standard 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.

Frozen Accident Pushing 50: Stereochemistry, Expansion, and Chance in the Evolution of the Genetic Code

Nearly 50 years ago, Francis Crick propounded the frozen accident scenario for the evolution of the genetic code along with the hypothesis that the early translation system consisted primarily of RNA. Under the frozen accident perspective, the code is universal among modern life forms because any change in codon assignment would be highly deleterious. The frozen accident can be considered the default theory of code evolution because it does not imply any specific interactions between amino acids and the cognate codons or anticodons, or any particular properties of the code. The subsequent 49 years of code studies have elucidated notable features of the standard code, such as high robustness to errors, but failed to develop a compelling explanation for codon assignments. In particular, stereochemical affinity between amino acids and the cognate codons or anticodons does not seem to account for the origin and evolution of the code. Here, I expand Crick’s hypothesis on RNA-only translation system by presenting evidence that this early translation already attained high fidelity that allowed protein evolution. I outline an experimentally testable scenario for the evolution of the code that combines a distinct version of the stereochemical hypothesis, in which amino acids are recognized via unique sites in the tertiary structure of proto-tRNAs, rather than by anticodons, expansion of the code via proto-tRNA duplication, and the frozen accident.

The information capacity of the genetic code: Is the natural code optimal?

We envision the molecular evolution process as an information transfer process and provide a quantitative measure for information preservation in terms of the channel capacity according to the channel coding theorem of Shannon. We calculate Information capacities of DNA on the nucleotide (for non-coding DNA) and the amino acid (for coding DNA) level using various substitution models. We extend our results on coding DNA to a discussion about the optimality of the natural codon-amino acid code. We provide the results of an adaptive search algorithm in the code domain and demonstrate the existence of a large number of genetic codes with higher information capacity. Our results support the hypothesis of an ancient extension from a 2-nucleotide codon to the current 3-nucleotide codon code to encode the various amino acids.

Optimization of amino acid replacement costs by mutational pressure in bacterial genomes

Mutations are considered a spontaneous and random process, which is important component of evolution because it generates genetic variation. On the other hand, mutations are deleterious leading to non-functional genes and energetically costly repairs. Therefore, one can expect that the mutational pressure is optimized to simultaneously generate genetic diversity and preserve genetic information. To check if empirical mutational pressures are optimized in these ways, we compared matrices of nucleotide mutation rates derived from bacterial genomes with their best possible alternatives that minimized or maximized costs of amino acid replacements associated with differences in their physicochemical properties (e.g. hydropathy and polarity). It should be noted that the studied empirical nucleotide substitution matrices and the costs of amino acid replacements are independent because these matrices were derived from sites free of selection on amino acid properties and the amino acid costs assumed only amino acid physicochemical properties without any information about mutation at the nucleotide level. Obtained results indicate that the empirical mutational matrices show a tendency to minimize costs of amino acid replacements. It implies that bacterial mutational pressures can evolve to decrease consequences of amino acid substitutions. However, the optimization is not full, which enables generation of some genetic variability.

Representations of Search Spaces in the Problem of Mutational Pressure Optimization According to Protein-Coding Sequences

The proper representation of the search space is the fundamental step in every optimization task, because it has a decisive impact on the quality of potential solutions. In particular, this problem appears when the search spaces are nonstandard and complex, with the large number of candidate solutions that differ from classical forms usually investigated. One of such spaces is the set of continuous-time, homogenous, and stationary Markov processes. They are commonly used to describe biological phenomena, for example, mutations in DNA sequences and their evolution. Because of the complexity of these processes, the representation of their search space is not an easy task but it is important for effective solving of the biological problems. One of them is optimality of mutational pressure acting on protein-coding sequences. Therefore, we described three representations of the search spaces and proposed several specific evolutionary operators that are used in evolutionary-based optimization algorithms to solve the biological problem of mutational pressure optimality. In addition, we gave a general formula for the fitness function, which can be used to measure the quality of potential solutions. The structures of these solutions are based on two models of DNA evolution described by substitution-rate matrices, which are commonly used in phylogenetic analyzes. The proposed representations have been successfully utilized in various issues, and the obtained results are very interesting from a biological point of view. For example, they show that mutational pressures are, to some extent, optimized to minimize cost of amino acid substitutions in proteins.

Social network analysis of the biblical Moses

Here, social network analysis approaches are used to characterize the figure of the biblical Moses, and his relationship with characters from the books of the Pentateuch; Genesis, Exodus, Leviticus, Numbers and Deuteronomy. The potential value of using such quantitative approaches is explored in relation to other forms of textual exegesis. Using a maximum likelihood approach, the degree distributions of the social networks are shown to approximate to a power law with exponential cutoff. The node representing Moses is very highly connected and falls outside the best fit line, as does the node representing Yahweh, which may indicate authorial emphasis. Only the social network from Genesis is assortative, a property typical of many real world social networks. A substantial proportion of disassortativity in the social network based around Moses disappears when the node is removed, potentially indicating some artificiality in its orientation within the network. The approximation of the degree distributions to a power law with exponential cutoff represents an emergent property resulting from the combinatorial and collaborative manner of composition, and indicates a bounding constraint on more highly connected nodes. Unusually highly connected nodes representing the deity and prophet may be characteristic of social networks derived from religious texts.

The neutral emergence of error minimized genetic codes superior to the standard genetic code

The standard genetic code (SGC) assigns amino acids to codons in such a way that the impact of point mutations is reduced, this is termed 'error minimization' (EM). The occurrence of EM has been attributed to the direct action of selection, however it is difficult to explain how the searching of alternative codes for an error minimized code can occur via codon reassignments, given that these are likely to be disruptive to the proteome. An alternative scenario is that EM has arisen via the process of genetic code expansion, facilitated by the duplication of genes encoding charging enzymes and adaptor molecules. This is likely to have led to similar amino acids being assigned to similar codons. Strikingly, we show that if during code expansion the most similar amino acid to the parent amino acid, out of the set of unassigned amino acids, is assigned to codons related to those of the parent amino acid, then genetic codes with EM superior to the SGC easily arise. This scheme mimics code expansion via the gene duplication of charging enzymes and adaptors. The result is obtained for a variety of different schemes of genetic code expansion and provides a mechanistically realistic manner in which EM has arisen in the SGC. These observations might be taken as evidence for self-organization in the earliest stages of life.

Anticodon Modifications in the tRNA Set of LUCA and the Fundamental Regularity in the Standard Genetic Code

Based on (i) an analysis of the regularities in the standard genetic code and (ii) comparative genomics of the anticodon modification machinery in the three branches of life, we derive the tRNA set and its anticodon modifications as it was present in LUCA. Previously we proposed that an early ancestor of LUCA contained a set of 23 tRNAs with unmodified anticodons that was capable of translating all 20 amino acids while reading 55 of the 61 sense codons of the standard genetic code (SGC). Here we use biochemical and genomic evidence to derive that LUCA contained a set of 44 or 45 tRNAs containing 2 or 3 modifications while reading 59 or 60 of the 61 sense codons. Subsequent tRNA modifications occurred independently in the Bacteria and Eucarya, while the Archaea have remained quite close to the tRNA set as it was present in LUCA.

The lack of foundation in the mechanism on which are based the physico-chemical theories for the origin of the genetic code is counterposed to the credible and natural mechanism suggested by the coevolution theory

I analyze the mechanism on which are based the majority of theories that put to the center of the origin of the genetic code the physico-chemical properties of amino acids. As this mechanism is based on excessive mutational steps, I conclude that it could not have been operative or if operative it would not have allowed a full realization of predictions of these theories, because this mechanism contained, evidently, a high indeterminacy. I make that disapproving the four-column theory of the origin of the genetic code (Higgs, 2009) and reply to the criticism that was directed towards the coevolution theory of the origin of the genetic code. In this context, I suggest a new hypothesis that clarifies the mechanism by which the domains of codons of the precursor amino acids would have evolved, as predicted by the coevolution theory. This mechanism would have used particular elongation factors that would have constrained the evolution of all amino acids belonging to a given biosynthetic family to the progenitor pre-tRNA, that for first recognized, the first codons that evolved in a certain codon domain of a determined precursor amino acid. This happened because the elongation factors recognized two characteristics of the progenitor pre-tRNAs of precursor amino acids, which prevented the elongation factors from recognizing the pre-tRNAs belonging to biosynthetic families of different precursor amino acids. Finally, I analyze by means of Fisher's exact test, the distribution, within the genetic code, of the biosynthetic classes of amino acids and the ones of polarity values of amino acids. This analysis would seem to support the biosynthetic classes of amino acids over the ones of polarity values, as the main factor that led to the structuring of the genetic code, with the physico-chemical properties of amino acids playing only a subsidiary role in this evolution. As a whole, the full analysis brings to the conclusion that the coevolution theory of the origin of the genetic code would be a theory highly corroborated.

DNA Repair Is Associated with Information Content in Bacteria, Archaea, and DNA Viruses

The concept of a "proteomic constraint" proposes that DNA repair capacity is positively correlated with the information content of a genome, which can be approximated to the size of the proteome (P). This in turn implies that DNA repair genes are more likely to be present in genomes with larger values of P. This stands in contrast to the common assumption that informational genes have a core function and so are evenly distributed across organisms. We examined the presence/absence of 18 DNA repair genes in bacterial genomes. A positive relationship between gene presence and P was observed for 17 genes in the total dataset, and 16 genes when only nonintracellular bacteria were examined. A marked reduction of DNA repair genes was observed in intracellular bacteria, consistent with their reduced value of P. We also examined archaeal and DNA virus genomes, and show that the presence of DNA repair genes is likewise related to a larger value of P. In addition, the products of the bacterial genes mutY, vsr, and ndk, involved in the correction of GC/AT mutations, are strongly associated with reduced genome GC content. We therefore propose that a reduction in information content leads to a loss of DNA repair genes and indirectly to a reduction in genome GC content in bacteria by exposure to the underlying AT mutation bias. The reduction in P may also indirectly lead to the increase in substitution rates observed in intracellular bacteria via loss of DNA repair genes.