Abstract
In this paper, we investigate the quality of selected models of theoretical genetic codes in terms of their robustness against point mutations. To deal with this problem, we used a graph representation including all possible single nucleotide point mutations occurring in codons, which are building blocks of every protein-coding sequence. Following graph theory, the quality of a given code model is measured using the set conductance property which has a useful biological interpretation. Taking this approach, we found the most robust genetic code structures for a given number of coding blocks. In addition, we tested several properties of genetic code models generated by the binary dichotomic algorithms (BDA) and compared them with randomly generated genetic code models. The results indicate that BDA-generated models possess better properties in terms of the conductance measure than the majority of randomly generated genetic code models and, even more, that BDA-models can achieve the best possible conductance values. Therefore, BDA-generated models are very robust towards changes in encoded information generated by single nucleotide substitutions.
Similar content being viewed by others
Notes
In the formula, we need for calculations always the ‘previous’ k. For instance, for calculation of \(E(S_{64}, {\bar{S}}_{64})\) we need \(k=63\). This is why we can always represent k as a three-digit number to base 4.
References
Blazej P, Wnetrzak M, Mackiewicz P (2016) The role of crossover operator in evolutionary-based approach to the problem of genetic code optimization. Biosystems 150:61–72
Blazej P, Wnetrzak M, Mackiewicz D, Mackiewicz P (2018a) Optimization of the standard genetic code according to three codon positions using an evolutionary algorithm. PLoS ONE. https://doi.org/10.1371/journal.pone.0201715
Blazej P, Kowalski D, Mackiewicz D, Wnetrzak M, Aloqalaa D, Mackiewicz P (2018b) The structure of the genetic code as an optimal graph clustering problem. https://doi.org/10.1101/332478
Bollobàs B (1998) Modern graph theory. Springer, New York
Di Giulio M (1989) The extension reached by the minimization of the polarity distances during the evolution of the genetic code. J Mol Evol 29(4):288–293
Di Giulio M (2005) The origin of the genetic code: theories and their relationships, a review. Biosystems 80(2):175–184
Di Giulio M (2017) Some pungent arguments against the physico-chemical theories of the origin of the genetic code and corroborating the coevolution theory. J Theor Biol 414:1–4
Dunnill P (1966) Triplet nucleotide-amino-acid pairing—a stereochemical basis for division between protein and non-protein amino-acids. Nature 210(5042):1267–1268
Epstein CJ (1966) Role of the amino-acid “code” and of selection for conformation in the evolution of proteins. Nature 210(5031):25–28
Fimmel E, Strüngmann L (2016) Yury Borisovich Rumer and his biological papers on the genetic code. Philos Trans R Soc A374:20150228
Fimmel E, Danielli A, Strüngmann L (2013) dichotomic classes and bijections of the genetic code. J Theor Biol 336:221–230
Fimmel E, Giannerini S, Gonzalez D, Strüngmann L (2014) Circular codes, symmetries and transformations. J Math Biol 70(7):1623–1644
Fimmel E, Michel CJ, Strüngmann L (2016) \(n\)-nucleotide circular codes in graph theory. Philos Trans A 374:20150058
Fimmel E, Michel CJ, Strüngmann L (2017) Strong comma-free codes in genetic information. Bull Math Biol 79(8):1796–1819. https://doi.org/10.1007/s11538-017-0307-0
Fimmel E, Michel CJ, Starman M, Strüngmann L (2018) Self-complementary circular codes in coding theory. Theory Biosci 137(1):51–65. https://doi.org/10.1007/s12064-018-0259-4
Freeland SJ, Hurst LD (1998a) The genetic code is one in a million. J Mol Evol 47(3):238–248
Freeland SJ, Hurst LD (1998b) Load minimization of the genetic code: history does not explain the pattern. Proc R Soc B Biol Sci 265(1410):2111–2119
Giannerini S, Gonzalez DL, Rosa R (2012) DNA, dichotomic classes and frame synchronization: a quasi-crystal framework. Philos Trans R Soc 370:2987–3006
Gumbel M, Fimmel E, Danielli A, Strüngmann L (2015) On models of the genetic code generated by binary dichotomic algorithms. BioSystems 128:9–18
José M, Zamudio GS, Morgado ER (2017) A unified model of the standard genetic code. R Soc Open Access. https://doi.org/10.1098/rsos.160908
Khorana HG, Buchi H, Ghosh H, Gupta N, Jacob TM, Kossel H, Morgan R, Narang SA, Ohtsuka E, Wells RD (1966) Polynucleotide synthesis and the genetic code. Cold Spring Harb Symp Quant Biol 31:39–49
Lee JR, Gharan SO, Trevisan L (2014) Multiway spectral partitioning and higher-order cheeger inequalities. J ACM 61(6):37. https://doi.org/10.1145/2665063
Levin DA, Peres Y, Wilmer EL (2009) Markov chains and mixing times. American Mathematical Society, Providence
Nirenberg M, Caskey T, Marshall R, Brimacombe R, Kellogg D, Doctor B, Hatfield D, Levin J, Rottman F, Pestka S, Wilcox M, Anderson F (1966) The rna code and protein synthesis. Cold Spring Harb Symp Quant Biol 31:11–24
Pelc SR, Welton MGE (1966) Stereochemical relationship between coding triplets and amino-acids. Nature 209(5026):868–870
Rumer YB (2016a) Translation of systematization of codons in the genetic code [I] by Yu. B. Rumer (1966). Philos Trans R Soc A374:20150446
Rumer YB (2016b) Translation of systematization of codons in the genetic code [II] by Yu. B. Rumer (1968). Philos Trans R Soc A374:20150447
Rumer YB (2016c) Translation of systematization of codons in the genetic code [III] by Yu. B. Rumer (1969). Philos Trans R Soc A374:20150448
Santos J, Monteagudo A (2010) Study of the genetic code adaptability by means of a genetic algorithm. J Theor Biol 264(3):854–865
Schönauer S, Clote P (1997) How optimal is the genetic code? In: Frishman D, Mewes HW (eds) Computer science and biology proceedings of the german conference on bioinformatics (GCB’97), pp 65–67
Tlusty T (2010) A colorful origin for the genetic code: information theory, statistical mechanics and the emergence of molecular codes. Phys Life Rev 7(3):362–376. https://doi.org/10.1016/j.plrev.2010.06.002
Wong JT (1975) A co-evolution theory of the genetic code. Proc Natl Acad Sci USA 72(5):1909–1912
Yarus M, Caporaso JG, Knight R (2005) Origins of the genetic code: the escaped triplet theory. Annu Rev Biochem 74:179–198
Acknowledgements
We would like to thank Lutz Strüngmann for stimulating discussions.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Błażej, P., Fimmel, E. & Gumbel, M. The Quality of Genetic Code Models in Terms of Their Robustness Against Point Mutations. Bull Math Biol 81, 2239–2257 (2019). https://doi.org/10.1007/s11538-019-00603-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11538-019-00603-2