scholarly journals Dihedral Group in The Ancient Genetic

2020 ◽  
Vol 16 (1) ◽  
pp. 13
Author(s):  
Isah Aisah ◽  
Eddy Djauhari ◽  
Asep Singgih
Keyword(s):  
Genetic Code ◽  
Dihedral Group ◽  
Symmetry Groups ◽  
Permutation Symmetry ◽  
Standard Genetic Code ◽  
Dihedral Groups ◽  
Genetic Codes ◽  
Living Things ◽  
Code Group ◽  
Nucleotide Bases

The standard genetic code consist of four nucleotide bases which encode genes to produce amino acids needed by living things. The addition of new base  (Dummy) causes a sequence of bases to become five nucleotide bases called ancient genetic codes. The five base set is denoted by , where B forms group through matching , , , , and   from set . Ancient genetic codes can be reviewed as algebraic structures as a vector spaces and other structures as symmetry groups. In this article, discussed the properties of symmetry groups from ancient genetic codes that will produce dihedral groups. The study began by constructing an expanded nucleotide base isomorphism with . The presence of base  causes  to have a cardinality of 24, denoted as  with .  isomorphic with  which is denoted by . Group  had three clasess of partitions based on strong-weak, purin-pyrimidin types, and amino-keto nucleotide groups which are denoted as , , and . All three classes are subgroups of . By using the rules of rotation and reflection in the four-side plane, it was found that only one group fulfilled the rule was named the dihedral group. Keywords: ancient genetic code, group, subgroup, permutation, symmetry group , dihedral group.

scholarly journals Dihedral Group in The Ancient Genetic

2020 ◽  
Vol 16 (1) ◽  
pp. 13
Author(s):  
Isah Aisah ◽  
Eddy Djauhari ◽  
Asep Singgih
Keyword(s):  
Amino Acids ◽  
Genetic Code ◽  
Dihedral Group ◽  
Vector Spaces ◽  
Symmetry Groups ◽  
Standard Genetic Code ◽  
Dihedral Groups ◽  
Genetic Codes ◽  
Living Things ◽  
Nucleotide Bases

The standard genetic code consist of four nucleotide bases which encode genes to produce amino acids needed by living things. The addition of new base  (Dummy) causes a sequence of bases to become five nucleotide bases called ancient genetic codes. The five base set is denoted by , where B forms group through matching , , , , and   from set . Ancient genetic codes can be reviewed as algebraic structures as a vector spaces and other structures as symmetry groups. In this article, discussed the properties of symmetry groups from ancient genetic codes that will produce dihedral groups. The study began by constructing an expanded nucleotide base isomorphism with . The presence of base  causes  to have a cardinality of 24, denoted as  with .  isomorphic with  which is denoted by . Group  had three clasess of partitions based on strong-weak, purin-pyrimidin types, and amino-keto nucleotide groups which are denoted as , , and . All three classes are subgroups of . By using the rules of rotation and reflection in the four-side plane, it was found that only one group fulfilled the rule was named the dihedral group.

scholarly journals Symmetrical Properties of Graph Representations of Genetic Codes: From Genotype to Phenotype

Symmetry ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 388 ◽  
Author(s):  
Marco José ◽  
Gabriel Zamudio
Keyword(s):  
Amino Acids ◽  
Genetic Code ◽  
Graph Representation ◽  
Symmetry Groups ◽  
Standard Genetic Code ◽  
Graph Representations ◽  
Symmetrical Structure ◽  
Genetic Codes ◽  
Mitochondrial Genetic Code

It has long been claimed that the mitochondrial genetic code possesses more symmetries than the Standard Genetic Code (SGC). To test this claim, the symmetrical structure of the SGC is compared with noncanonical genetic codes. We analyzed the symmetries of the graphs of codons and their respective phenotypic graph representation spanned by the RNY (R purines, Y pyrimidines, and N any of them) code, two RNA Extended codes, the SGC, as well as three different mitochondrial genetic codes from yeast, invertebrates, and vertebrates. The symmetry groups of the SGC and their corresponding phenotypic graphs of amino acids expose the evolvability of the SGC. Indeed, the analyzed mitochondrial genetic codes are more symmetrical than the SGC.

Many alternative and theoretical genetic codes are more robust to amino acid replacements than the standard genetic code

2019 ◽  
Vol 464 ◽  
pp. 21-32 ◽  
Author(s):  
Paweł Błażej ◽  
Małgorzata Wnętrzak ◽  
Dorota Mackiewicz ◽  
Przemysław Gagat ◽  
Paweł Mackiewicz
Keyword(s):  
Amino Acid ◽  
Genetic Code ◽  
Standard Genetic Code ◽  
Genetic Codes

scholarly journals No accident: genetic codes freeze in error–correcting patterns of the standard genetic code

2002 ◽  
Vol 357 (1427) ◽  
pp. 1625-1642 ◽  
Author(s):  
David H. Ardell ◽  
Guy Sella
Keyword(s):  
Information Processing ◽  
Genetic Code ◽  
Genetic Model ◽  
Random Pattern ◽  
Biological Organization ◽  
Standard Genetic Code ◽  
Protein Coding ◽  
Evolutionary Forces ◽  
Protein Coding Genes ◽  
Genetic Codes

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.

scholarly journals Packing the Standard Genetic Code in its box: 3-dimensional late Crick wobble

2021 ◽  
Author(s):  
Michael Yarus
Keyword(s):  
Amino Acid ◽  
Genetic Code ◽  
Dimensional Space ◽  
Parallel Evolution ◽  
Three Dimensional ◽  
Standard Genetic Code ◽  
3 Dimensional ◽  
Combinatorial Properties ◽  
Genetic Codes ◽  
Level Order

AbstractMinimally-evolved codes are constructed with randomly chosen Standard Genetic Code (SGC) triplets, and completed with completely random triplet assignments. Such “genetic codes” have not evolved, but retain SGC qualities. Retained qualities are inescapable, part of the logic of code evolution. For example, sensitivity of coding to arbitrary assignments, which must be <≈ 10%, is intrinsic. Such sensitivity comes from elementary combinatorial properties of coding, and constrains any SGC evolution hypothesis. Similarly, evolution of last-evolved functions is difficult, due to late kinetic phenomena, likely common across codes. Census of minimally-evolved code assignments shows that shape and size of wobble domains controls packing into a coding table, shifting the accuracy of codon assignments. Access to the SGC therefore requires a plausible pathway to limited randomness, avoiding difficult completion while packing a highly ordered, degenerate code into a fixed three-dimensional space. Late Crick wobble in a 3-dimensional genetic code previously assembled by lateral transfer satisfies these varied, simultaneous requirements. By allowing parallel evolution of SGC domains, it can yield shortened evolution to SGC-level order, and allow the code to arise in smaller populations. It effectively yields full codes. Less obviously, it unifies well-studied sources for order in amino acid coding, including a minority of stereochemical triplet-amino acid associations. Finally, fusion of its intermediates into the definitive SGC is credible, mirroring broadly-accepted later events in cellular evolution.

scholarly journals Fitting the standard genetic code into its triplet table

2021 ◽  
Vol 118 (36) ◽  
pp. e2021103118
Author(s):  
Michael Yarus
Keyword(s):  
Amino Acid ◽  
Genetic Code ◽  
Dimensional Space ◽  
Parallel Evolution ◽  
Three Dimensional ◽  
Standard Genetic Code ◽  
Basic Part ◽  
Combinatorial Properties ◽  
Genetic Codes ◽  
Level Order

Minimally evolved codes are constructed here; these have randomly chosen standard genetic code (SGC) triplets, completed with completely random triplet assignments. Such “genetic codes” have not evolved, but retain SGC qualities. Retained qualities are basic, part of the underpinning of coding. For example, the sensitivity of coding to arbitrary assignments, which must be < ∼10%, is intrinsic. Such sensitivity comes from the elementary combinatorial properties of coding and constrains any SGC evolution hypothesis. Similarly, assignment of last-evolved functions is difficult because of late kinetic phenomena, likely common across codes. Census of minimally evolved code assignments shows that shape and size of wobble domains controls the code’s fit into a coding table, strongly shifting accuracy of codon assignments. Access to the SGC therefore requires a plausible pathway to limited randomness, avoiding difficult completion while fitting a highly ordered, degenerate code into a preset three-dimensional space. Three-dimensional late Crick wobble in a genetic code assembled by lateral transfer between early partial codes satisfies these varied, simultaneous requirements. By allowing parallel evolution of SGC domains, this origin can yield shortened evolution to SGC-level order and allow the code to arise in smaller populations. It effectively yields full codes. Less obviously, it unifies previously studied chemical, biochemical, and wobble order in amino acid assignment, including a stereochemical minority of triplet–amino acid associations. Finally, fusion of intermediates into the final SGC is credible, mirroring broadly accepted later cellular evolution.

scholarly journals On the Importance of Asymmetry in the Phenotypic Expression of the Genetic Code upon the Molecular Evolution of Proteins

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 997
Author(s):  
Marco V. José ◽  
Gabriel S. Zamudio
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Genetic Code ◽  
Phenotypic Expression ◽  
Standard Genetic Code ◽  
Specific Amino Acid ◽  
Trna Synthetases ◽  
Probability Of Occurrence ◽  
Genetic Codes ◽  
Evolution Of Proteins

The standard genetic code (SGC) is a mapping between the 64 possible arrangements of the four RNA nucleotides (C, A, U, G) into triplets or codons, where 61 codons are assigned to a specific amino acid and the other three are stop codons for terminating protein synthesis. Aminoacyl-tRNA synthetases (aaRSs) are responsible for implementing the SGC by specifically amino-acylating only its cognate transfer RNA (tRNA), thereby linking an amino acid with its corresponding anticodon triplets. tRNAs molecules bind each codon with its anticodon. To understand the meaning of symmetrical/asymmetrical properties of the SGC, we designed synthetic genetic codes with known symmetries and with the same degeneracy of the SGC. We determined their impact on the substitution rates for each amino acid under a neutral model of protein evolution. We prove that the phenotypic graphs of the SGC for codons and anticodons for all the possible arrangements of nucleotides are asymmetric and the amino acids do not form orbits. In the symmetrical synthetic codes, the amino acids are grouped according to their codonicity, this is the number of triplets encoding a given amino acid. Both the SGC and symmetrical synthetic codes exhibit a probability of occurrence of the amino acids proportional to their degeneracy. Unlike the SGC, the synthetic codes display a constant probability of occurrence of the amino acid according to their codonicity. The asymmetry of the phenotypic graphs of codons and anticodons of the SGC, has important implications on the evolutionary processes of proteins.

scholarly journals Analysis of the optimality of the standard genetic code

2016 ◽  
Vol 12 (8) ◽  
pp. 2642-2651 ◽  
Author(s):  
Balaji Kumar ◽  
Supreet Saini
Keyword(s):  
Genetic Code ◽  
Standard Genetic Code ◽  
Frameshift Mutations ◽  
Additional Information ◽  
Genetic Codes

Many theories have been proposed attempting to explain the origin of the genetic code. In this work, we compare performance of the standard genetic code against millions of randomly generated codes. On left, ability of genetic codes to encode additional information and their robustness to frameshift mutations.

scholarly journals Analysis of the optimality of the Standard Genetic Code.

2015 ◽  
Author(s):  
Balaji Kumar ◽  
Supreet Saini
Keyword(s):  
Genetic Algorithm ◽  
Genetic Code ◽  
Point Mutation ◽  
Frameshift Mutation ◽  
Performance Indicator ◽  
Coding Region ◽  
Standard Genetic Code ◽  
Additional Information ◽  
Genetic Codes ◽  
Different Parts

Many theories have been proposed attempting to explain the origin of the genetic code. While strong reasons remain to believe that the genetic code evolved as a frozen accident, at least for the first few amino acids, other theories remain viable. In this work, we test the optimality of the standard genetic code against approximately 17 million genetic codes, and locate 18 which outperform the standard genetic code at the following three criteria: (a) robustness to point mutation; (b) robustness to frameshift mutation; and (c) ability to encode additional information in the coding region. We use a genetic algorithm to generate and score codes from different parts of the associated landscape, and are, as a result presumably more representative of the entire landscape. Our results show that while the genetic code is sub-optimal for robustness to frameshift mutation and the ability to encode additional information in the coding region, it is very strongly selected for robustness to point mutation. This coupled with the observation that the different performance indicator scores for a particular genetic code are seemingly negatively correlated, make the standard genetic code nearly optimal for the three criteria tested in this work.

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