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The Properties of the Standard Genetic Code and Its Selected Alternatives in Terms of the Optimal Graph Partition

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Book cover Biomedical Engineering Systems and Technologies (BIOSTEC 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1211))

Abstract

The standard genetic code (SGC) is a system of rules, which assigns 20 amino acids and stop translation signal to 64 codons, i.e triplets of nucleotides. The structure of the SGC shows some properties suggesting that this code evolved to minimize deleterious effects of mutations and translational errors. To analyse this issue, we presented the structure of the SGC and its natural alternative versions as a graph, in which vertices corresponded to codons and edges to point mutations between these codons. The mutations were weighted according to the mutation type, i.e. transitions and transversions. Under this representation, each genetic code is a partition of the set of vertices into 21 disjoint subsets, while its resistance to the mutation consequences can be reformulated into the optimal graph clustering task. In order to investigate this problem, we developed an appropriate clustering algorithm, which searched for the codes showing the minimum average calculated for the set conductance of codon groups. The algorithm found three best codes for various ranges of the weights for the mutations. The average weighted-conductance of the studied genetic codes 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 codes was not as perfect as the best codes and many alternative genetic codes performed better than the SGC. These results may suggest that the evolution of the SGC was driven not only by the selection for the robustness to mutations or mistranslations.

Supported by the National Science Centre, Poland (Narodowe Centrum Nauki, Polska) under Grants number UMO-2017/27/N/NZ2/00403 and UMO-2017/25/B/ST6/02553.

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Authors and Affiliations

  1. Department of Computer Science, University of Liverpool, Liverpool, UK

    Daniyah A. Aloqalaa

  2. SWPS University of Social Sciences and Humanities, Warsaw, Poland

    Dariusz R. Kowalski

  3. Faculty of Biotechnology, University of Wrocław, Wrocław, Poland

    Paweł Błażej, Małgorzata Wnȩtrzak, Dorota Mackiewicz & Paweł Mackiewicz

  4. School of Computer and Cyber Sciences, Augusta University, Augusta, USA

    Dariusz R. Kowalski

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  1. Daniyah A. Aloqalaa
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  3. Paweł Błażej
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  4. Małgorzata Wnȩtrzak
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Correspondence to Paweł Mackiewicz .

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Editors and Affiliations

  1. Universidade Nova de Lisboa, Caparica, Portugal

    Ana Roque

  2. Lodz University of Technology, Łódź, Poland

    Arkadiusz Tomczyk

  3. Nice Sophia Antipolis University, Nice Cedex 2, France

    Elisabetta De Maria

  4. University of Bremen, Bremen, Germany

    Felix Putze

  5. University of West Bohemia, Pilsen, Czech Republic

    Roman Moucek

  6. Instituto de Telecomunicações, University of Lisbon, Lisbon, Portugal

    Ana Fred

  7. Universidade Nova de Lisboa, Caparica, Portugal

    Hugo Gamboa

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Aloqalaa, D.A., Kowalski, D.R., Błażej, P., Wnȩtrzak, M., Mackiewicz, D., Mackiewicz, P. (2020). The Properties of the Standard Genetic Code and Its Selected Alternatives in Terms of the Optimal Graph Partition. In: Roque, A., et al. Biomedical Engineering Systems and Technologies. BIOSTEC 2019. Communications in Computer and Information Science, vol 1211. Springer, Cham. https://doi.org/10.1007/978-3-030-46970-2_9

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