### Abstract

The standard genetic code (SGC) is a system of rules ascribing 20 amino acids and stop translation signal to 64 codons, i.e triplets of nucleotides. It was proposed that the structure of the SGC evolved to minimize harmful consequences of mutations and translational errors. To study this problem, we described the SGC structure by a graph, in which codons are vertices and edges correspond to single nucleotide mutations occurring between the codons. We also introduced weights (W) for mutation types to distinguish transversions from transitions. Using this representation, the SGC is a partition of the set of vertices into 21 disjoint subsets. In this case, the question about the potential robustness of the genetic code to the mutations can be reformulated into the optimal graph clustering task. To investigate this problem, we applied an appropriate clustering algorithm, which searched for the codes characterized by the minimum average calculated from the set W-conductance of codon groups. Our algorithm found three best codes for various ranges of the applied weights. The average W-conductance of the SGC was the most similar to that of the best codes in the range of weights corresponding to the observed transversion/transition ratio in natural mutational pressures. However, it should be noted that the optimization of the SGC was not as perfect as the best codes. It implies that the evolution of the SGC was driven not only by the selection for the robustness against mutations or mistranslations but also other factors, e.g. subsequent addition of amino acids to the code according to the expansion of amino acid metabolic pathways.

Original language | English (US) |
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Title of host publication | BIOINFORMATICS 2019 - 10th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019 |

Editors | Elisabetta De Maria, Hugo Gamboa, Ana Fred |

Publisher | SciTePress |

Pages | 55-65 |

Number of pages | 11 |

ISBN (Electronic) | 9789897583537 |

State | Published - Jan 1 2019 |

Externally published | Yes |

Event | 10th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2019 - Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019 - Prague, Czech Republic Duration: Feb 22 2019 → Feb 24 2019 |

### Publication series

Name | BIOINFORMATICS 2019 - 10th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019 |
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### Conference

Conference | 10th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2019 - Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019 |
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Country | Czech Republic |

City | Prague |

Period | 2/22/19 → 2/24/19 |

### Fingerprint

### Keywords

- Code Degeneracy
- Graph Theory
- Mutation
- Set Conductance
- Standard Genetic Code
- Transition
- Transversion

### ASJC Scopus subject areas

- Biomedical Engineering
- Electrical and Electronic Engineering

### Cite this

*BIOINFORMATICS 2019 - 10th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019*(pp. 55-65). (BIOINFORMATICS 2019 - 10th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019). SciTePress.

**The impact of the transversion/transition ratio on the optimal genetic code graph partition.** / Aloqalaa, Daniyah A.; Kowalski, Dariusz R.; Błazej, Paweł; Wnetrzak, Małgorzata; Mackiewicz, Dorota; Mackiewicz, Paweł.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*BIOINFORMATICS 2019 - 10th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019.*BIOINFORMATICS 2019 - 10th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019, SciTePress, pp. 55-65, 10th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2019 - Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019, Prague, Czech Republic, 2/22/19.

}

TY - GEN

T1 - The impact of the transversion/transition ratio on the optimal genetic code graph partition

AU - Aloqalaa, Daniyah A.

AU - Kowalski, Dariusz R.

AU - Błazej, Paweł

AU - Wnetrzak, Małgorzata

AU - Mackiewicz, Dorota

AU - Mackiewicz, Paweł

PY - 2019/1/1

Y1 - 2019/1/1

N2 - The standard genetic code (SGC) is a system of rules ascribing 20 amino acids and stop translation signal to 64 codons, i.e triplets of nucleotides. It was proposed that the structure of the SGC evolved to minimize harmful consequences of mutations and translational errors. To study this problem, we described the SGC structure by a graph, in which codons are vertices and edges correspond to single nucleotide mutations occurring between the codons. We also introduced weights (W) for mutation types to distinguish transversions from transitions. Using this representation, the SGC is a partition of the set of vertices into 21 disjoint subsets. In this case, the question about the potential robustness of the genetic code to the mutations can be reformulated into the optimal graph clustering task. To investigate this problem, we applied an appropriate clustering algorithm, which searched for the codes characterized by the minimum average calculated from the set W-conductance of codon groups. Our algorithm found three best codes for various ranges of the applied weights. The average W-conductance of the SGC was the most similar to that of the best codes in the range of weights corresponding to the observed transversion/transition ratio in natural mutational pressures. However, it should be noted that the optimization of the SGC was not as perfect as the best codes. It implies that the evolution of the SGC was driven not only by the selection for the robustness against mutations or mistranslations but also other factors, e.g. subsequent addition of amino acids to the code according to the expansion of amino acid metabolic pathways.

AB - The standard genetic code (SGC) is a system of rules ascribing 20 amino acids and stop translation signal to 64 codons, i.e triplets of nucleotides. It was proposed that the structure of the SGC evolved to minimize harmful consequences of mutations and translational errors. To study this problem, we described the SGC structure by a graph, in which codons are vertices and edges correspond to single nucleotide mutations occurring between the codons. We also introduced weights (W) for mutation types to distinguish transversions from transitions. Using this representation, the SGC is a partition of the set of vertices into 21 disjoint subsets. In this case, the question about the potential robustness of the genetic code to the mutations can be reformulated into the optimal graph clustering task. To investigate this problem, we applied an appropriate clustering algorithm, which searched for the codes characterized by the minimum average calculated from the set W-conductance of codon groups. Our algorithm found three best codes for various ranges of the applied weights. The average W-conductance of the SGC was the most similar to that of the best codes in the range of weights corresponding to the observed transversion/transition ratio in natural mutational pressures. However, it should be noted that the optimization of the SGC was not as perfect as the best codes. It implies that the evolution of the SGC was driven not only by the selection for the robustness against mutations or mistranslations but also other factors, e.g. subsequent addition of amino acids to the code according to the expansion of amino acid metabolic pathways.

KW - Code Degeneracy

KW - Graph Theory

KW - Mutation

KW - Set Conductance

KW - Standard Genetic Code

KW - Transition

KW - Transversion

UR - http://www.scopus.com/inward/record.url?scp=85064714130&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85064714130&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85064714130

T3 - BIOINFORMATICS 2019 - 10th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019

SP - 55

EP - 65

BT - BIOINFORMATICS 2019 - 10th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019

A2 - De Maria, Elisabetta

A2 - Gamboa, Hugo

A2 - Fred, Ana

PB - SciTePress

ER -