Highly Similar Average Collateral Effect of Synonymous Mutations Across Alternative Reading Frames: A Potential Role In Evolvability

Stefan Wichmann; Zachary Ardern

doi:10.2478/biocosmos-2023-0001

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Highly Similar Average Collateral Effect of Synonymous Mutations Across Alternative Reading Frames: A Potential Role In Evolvability

BioCosmos

Volume 3 (2023): Issue 1 (January 2023)

By: Stefan Wichmann and Zachary Ardern

Open Access

|Mar 2023

Abstract

Synonymous mutations in a protein coding gene lead to a remarkably similar average “collateral” mutation effect size across alternative reading frames (1). Here we quantify the rarity of this feature among possible block structure codes as 0.77%. Then we develop a simple model of evolutionary search with two types of mutation. Across different mutation step sizes and ratios of the two types, the fitness-maximizing region corresponds to using a single average mutation value. The analogous constant average collateral mutation effect observed for the standard genetic code may likewise facilitate evolutionary search in alternative frame sequences.

References

1. Wichmann S, Ardern Z. Optimality in the standard genetic code is robust with respect to comparison code sets. Bio Systems. 2019 November;2019;185:104023. doi:10.10.1016/j.biosystems.2019.104023
Open DOI Search in Google Scholar Back to article
2. Barrell BG, Air GM, Hutchison CA 3rd. Overlapping genes in bacteriophage phiX174. Nature. 1976;264(5581):34-41. doi:10.1038/264034a0
Open DOI Search in Google Scholar Back to article
3. Firth AE, Brierley I. Non-canonical translation in RNA viruses. J Gen Virol. 2012;93(Pt 7):1385-1409. doi:10.1099/vir.0.042499-0
Open DOI Search in Google Scholar Back to article
4. Cassan E, Arigon-Chifolleau AM, Mesnard JM, Gross A, Gascuel O. Concomitant emergence of the antisense protein gene of HIV-1 and of the pandemic. Proc Natl Acad Sci USA. 2016;113(41):11537-11542. doi:10.1073/pnas.1605739113
Open DOI Search in Google Scholar Back to article
5. Affram Y, Zapata JC, Gholizadeh Z, Tolbert WD, Zhou W, Iglesias-Ussel MD, Pazgier M, Ray K, Latinovic OS, Romerio F. The HIV-1 antisense protein ASP is a transmembrane protein of the cell surface and an integral protein of the viral envelope. J Virol. 2019;93(21):e00574-19. doi:10.1128/JVI.00574-19
Open DOI Search in Google Scholar Back to article
6. Nelson CW, Ardern Z, Goldberg TL, Meng C, Kuo CH, Ludwig C, Kolokotronis SO, Wei X. Dynamically evolving novel overlapping gene as a factor in the SARS-CoV-2 pandemic. Elife. 2020;9:e59633. doi:10.7554/eLife.59633
Open DOI Search in Google Scholar Back to article
7. Firth AE. A putative new SARS-CoV protein, 3c, encoded in an ORF overlapping ORF3a. J Gen Virol. 2020;101(10):1085-1089. doi:10.1099/jgv.0.001469
Open DOI Search in Google Scholar Back to article
8. Kreitmeier M, Ardern Z, Abele M, Ludwig C, Scherer S, Neuhaus K. Spotlight on alternative frame coding: Two long overlapping genes in Pseudomonas aeruginosa are translated and under purifying selection. iScience. 2022;25(2):103844. doi:10.1016/j.isci.2022.103844
Open DOI Search in Google Scholar Back to article
9. Zehentner B, Ardern Z, Kreitmeier M, Scherer S, Neuhaus K. Evidence for numerous embedded antisense overlapping genes in diverse E. coli strains. bioRxiv. 2020. Available from: https://doi.org/10.1101/2020.11.18.388249
Open DOI Search in Google Scholar Back to article
10. Ardern Z, Neuhaus K, Scherer S. Are Antisense Proteins in Prokaryotes Functional?. Front Mol Biosci. 2020;7:187. doi:10.3389/fmolb.2020.00187
Open DOI Search in Google Scholar Back to article
11. Meydan S, Vázquez-Laslop N, Mankin Alexander S. Genes within genes in bacterial genomes. Microbiology Spectrum. 2018;6(4). Available from: https://doi.org/10.1128/microbiolspec.RWR-0020-2018
Open DOI Search in Google Scholar Back to article
12. Hücker SM, Vanderhaeghen S, Abellan-Schneyder I, Scherer S, Neuhaus K. The novel anaerobiosis-responsive overlapping gene ano is overlapping antisense to the annotated gene ECs2385 of Escherichia coli O157:H7 Sakai. Front Microbiol. 2018;9:931. doi:10.3389/fmicb.2018.00931
Open DOI Search in Google Scholar Back to article
13. Vanderhaeghen S, Zehentner B, Scherer S, Neuhaus K, Ardern Z. The novel EHEC gene asa overlaps the TEGT transporter gene in antisense and is regulated by NaCl and growth phase. Sci Rep. 2018;8(1):17875. doi:10.1038/s41598-018-35756-y
Open DOI Search in Google Scholar Back to article
14. Gelsinger DR, Dallon E, Reddy R, Mohammad F, Buskirk AR, DiRuggiero J. Ribosome profiling in archaea reveals leaderless translation, novel translational initiation sites, and ribosome pausing at single codon resolution. Nucleic Acids Res. 2020;48(10):5201-5216. doi:10.1093/nar/gkaa304
Open DOI Search in Google Scholar Back to article
15. Loughran G, Zhdanov AV, Mikhaylova MS, Andreev DE. Unusually efficient CUG initiation of an overlapping reading frame in POLG mRNA yields novel protein POLGARF. 2020;117(40):24936-24946. Available from: https://doi.org/10.1073/pnas.2001433117
Open DOI Search in Google Scholar Back to article
16. Khan YA, Jungreis I, Wright JC, Mudge JM, Choudhary JS, Firth AE, Kellis M. Evidence for a novel overlapping coding sequence in POLG initiated at a CUG start codon. BMC Genet. 2020;21(1):25. doi:10.1186/s12863-020-0828-7
Open DOI Search in Google Scholar Back to article
17. Mudge JM, Ruiz-Orera J, Prensner JR, Brunet MA, Gonzalez JM, Magrane M, Martinez T, Schulz JF, Yang YT, Alba MM, et al. A community-driven roadmap to advance research on translated open reading frames detected by Ribo-Seq. bioRxiv. 2021. Available from: https://doi.org/10.1101/2021.06.10.447896
Open DOI Search in Google Scholar Back to article
18. Cao X, Khitun A, Luo Y, Na Z, Phoodokmai T, Sappakhaw K, Olatunji E, Uttamapinant C, Slavoff SA. Alt-RPL36 downregulates the PI3K-AKT-mTOR signaling pathway by interacting with TMEM24. Nat Commun. 2021;12(1):508. doi:10.1038/s41467-020-20841-6
Open DOI Search in Google Scholar Back to article
19. Wright BW, Yi Z, Weissman JS, Chen J. The dark proteome: translation from noncanonical open reading frames. Trends Cell Biol. 2022;32(3):243-258. doi:10.1016/j.tcb.2021.10.010
Open DOI Search in Google Scholar Back to article
20. Szekely M. Triple overlapping genes. Nature. 1978;272(5653): 492.
Search in Google Scholar Back to article
21. Siegel AF, Fitch WM. Degeneracy when DNA codes for overlapping genes. Mathematical Biosciences. 1980;49(1):1-16. Available from: https://doi.org/10.1016/0025-5564(80)90107-8
Open DOI Search in Google Scholar Back to article
22. Smith TF, Waterman MS. Overlapping genes and information theory. J Theoret Biol. 1981;91(2):379-380.
Search in Google Scholar Back to article
23. Yockey HP. Rebuttal of ‘overlapping genes and information theory.’ J Theoret Biol. 1981;91(2):381-382.
Search in Google Scholar Back to article
24. Miyata T, Yasunaga T. Evolution of overlapping genes. Nature. 1978;272(5653):532-535.
Search in Google Scholar Back to article
25. Yockey HP. Do overlapping genes violate molecular biology and the theory of evolution? J Theoret Biol. 1979;80(1):21-26.
Search in Google Scholar Back to article
26. Kolata GB. Overlapping genes: more than anomalies? Science. 1977;196(4295):1187-1188.
Search in Google Scholar Back to article
27. Wright BW, Molloy MP, Jaschke PR. Overlapping genes in natural and engineered genomes. Nat Rev Genet. 2022;23(3): 154-168. doi:10.1038/s41576-021-00417-w
Open DOI Search in Google Scholar Back to article
28. Brandes N, Linial M. Gene overlapping and size constraints in the viral world. Biol Direct. 2016 May;11:26.
Search in Google Scholar Back to article
29. Vakirlis N, Carvunis AR, McLysaght A. Synteny-based analyses indicate that sequence divergence is not the main source of orphan genes. Elife. 2020;9:e53500. doi:10.7554/eLife.53500
Open DOI Search in Google Scholar Back to article
30. Keese PK, Gibbs A. Origins of genes: “big bang” or continuous creation?. Proc Natl Acad Sci USA. 1992;89(20):9489-9493. doi:10.1073/pnas.89.20.9489
Open DOI Search in Google Scholar Back to article
31. Ohno S. Evolution by gene duplication. Berlin: Springer; 1970.
Search in Google Scholar Back to article
32. Carter CW. Simultaneous codon usage, the origin of the proteome, and the emergence of de-novo proteins. Cur Opin Struct Biol. 2021;68:142-148.
Search in Google Scholar Back to article
33. Watson AK, Lopez P, Bapteste E. Hundreds of out-of-frame remodeled gene families in the escherichia coli pangenome. Mol Biol Evol. 2022;39(1):msab329. Available from: https://doi.org/10.1093/molbev/msab329
Open DOI Search in Google Scholar Back to article
34. Biba D, Klink G, Bazykin GA. Pairs of mutually compensatory frameshifting mutations contribute to protein evolution. Mol Biol Evol. 2022;39(3):msac031. Available from: https://doi.org/10.1093/molbev/msac031
Open DOI Search in Google Scholar Back to article
35. Bartonek L, Braun D, Zagrovic B. Frameshifting preserves key physicochemical properties of proteins. Proc Natl Acad Sci USA. 2020;117(11):5907-5912.
Search in Google Scholar Back to article
36. Xu H, Zhang J. On the origin of frameshift-robustness of the standard genetic code. Mol Biol Evol. 2021a;38(10):4301-4309. doi:10.1093/molbev/msab1642021a
Open DOI Search in Google Scholar Back to article
37. Blalock JE, Smith EM. Hydropathic anti-complementarity of amino acids based on the genetic code. Biochem Biophys Res Comm. 1984;121(1):203-207.
Search in Google Scholar Back to article
38. Zull JE, Smith SK. Is genetic code redundancy related to retention of structural information in both DNA strands? Trends Biochem Sci. 1990;15(7):257-261.
Search in Google Scholar Back to article
39. Konecny J, Eckert M, Schöniger M, Hofacker GL. Neutral adaptation of the genetic code to double-strand coding. J Mol Evol. 1993;36(5):407-416.
Search in Google Scholar Back to article
40. Blalock JE. Complementarity of peptides specified by ‘sense’ and ‘antisense’ strands of DNA. Trends Biotechnol. 1990;8(6): 140-144.
Search in Google Scholar Back to article
41. Willis S, Masel J. Gene birth contributes to structural disorder encoded by overlapping genes. genetics. 2018;210(1):303-313. doi:10.1534/genetics.118.301249
Open DOI Search in Google Scholar Back to article
42. Wei X, Zhang J. A simple method for estimating the strength of natural selection on overlapping genes. Genome Biol Evol. 2015;7(10): 381-390. Available from: https://doi.org/10.1093/gbe/evu294
Open DOI Search in Google Scholar Back to article
43. Osawa S. Evolution of the genetic code. Oxford: Oxford University Press; 1995.
Search in Google Scholar Back to article
44. Freeland SJ, Knight RD, Landweber LF, Hurst LD. Early fixation of an optimal genetic code. Mol Biol Evol. 2000;17(4):511-518. doi:10.1093/oxfordjournals.molbev.a026331
Open DOI Search in Google Scholar Back to article
45. Freeland SJ, Hurst LD. The genetic code is one in a million. J Mol Evol. 1998;47(3):238-248.
Search in Google Scholar Back to article
46. Itzkovitz S, Alon U. The genetic code is nearly optimal for allowing additional information within protein-coding sequences. Genome Res. 2007;17(4):405-412.
Search in Google Scholar Back to article
47. Ilardo M, Meringer M, Freeland S, Rasulev B, Cleaves HJ 2nd. Extraordinarily adaptive properties of the genetically encoded amino acids. Sci Rep. 2015;5:9414. doi:10.1038/srep09414
Open DOI Search in Google Scholar Back to article
48. Ilardo M, Bose R, Meringer M, Rasulev B, Grefenstette N, Stephenson J, Freeland S, Gillams RJ, Butch CJ, Cleaves HJ 3rd. Adaptive properties of the genetically encoded amino acid alphabet are inherited from its subsets. Sci Reports. 2019;9(12468). Available from: https://doi.org/10.1038/s41598-019-47574-x
Open DOI Search in Google Scholar Back to article
49. Mayer-Bacon C, Freeland SJ. A broader context for understanding amino acid alphabet optimality. J Theo Biol. 2021 July;520:110661.
Search in Google Scholar Back to article
50. Freeland SJ. The Darwinian genetic code: An adaptation for adapting? Genet Program Evolvable Mach. 2002;3(2):113-127. Available from: https://doi.org/10.1023/A:1015527808424
Open DOI Search in Google Scholar Back to article
51. Zhu W, Freeland SJ. The standard genetic code enhances adaptive evolution of proteins. J Theoret Biol. 2006;239(1):63-70.
Search in Google Scholar Back to article
52. Firnberg E, Ostermeier M. The genetic code constrains yet facilitates Darwinian evolution. Nucleic Acids Res. 2013;41(15): 7420-7428.
Search in Google Scholar Back to article
53. Tripathi S, Deem MW. The standard genetic code facilitates exploration of the space of functional nucleotide sequences. J Mol Evol. 2018;86(6):325-339.
Search in Google Scholar Back to article
54. Richter H, Engelbrecht A, editors. Recent advances in the theory and application of fitness landscapes. Berlin: Springer; 2014.
Search in Google Scholar Back to article
55. de Visser JA, Krug J. Empirical fitness landscapes and the predictability of evolution. Nat Rev Genet. 2014;15(7):480-490. doi:10.1038/nrg3744
Open DOI Search in Google Scholar Back to article
56. Payne JL, Wagner A. The causes of evolvability and their evolution. Nat Rev Genet. 2019;20(1):24-38.
Search in Google Scholar Back to article
57. Chen JZ, Fowler DM, Tokuriki N. Environmental selection and epistasis in an empirical phenotype-environment-fitness landscape. Nat Ecol Evol. 2022;6(4):427-438. doi:10.1038/s41559-022-01675-5
Open DOI Search in Google Scholar Back to article
58. Tenaillon O. The utility of Fisher’s geometric model in evolutionary genetics. Annu Rev Ecol Evol Syst. 2014;45:179-201. doi:10.1146/annurev-ecolsys-120213-091846
Open DOI Search in Google Scholar Back to article
59. Fisher RA. The genetical theory of natural selection. Oxford: Clarendon Press; 1930. Available from: https://doi.org/10.5962/bhl.title.27468
Open DOI Search in Google Scholar Back to article
60. Woese CR, Dugre DH, Dugre SA, Kondo M, Saxinger WC. On the fundamental nature and evolution of the genetic code. Cold Spring Harb Symp Quant Biol. 1966;31:723-736. doi:10.1101/sqb.1966.031.01.093
Open DOI Search in Google Scholar Back to article
61. Buhrman H, van der Gulik PT, Kelk SM, Koolen WM, Stougie L. Some mathematical refinements concerning error minimization in the genetic code. IEEE/ACM Trans Comput Biol Bioinform. 2011;8(5):1358-1372. doi:10.1109/TCBB.2011.40
Open DOI Search in Google Scholar Back to article
62. Lèbre S, Gascuel O. The combinatorics of overlapping genes. J Theoret Biol. 2017 February;415:90-101.
Search in Google Scholar Back to article
63. Shenhav L, Zeevi D. Resource conservation manifests in the genetic code. Science. 2020;370(6517): 683–687.
Search in Google Scholar Back to article
64. Rozhoňová H, Payne JL. Little evidence the standard genetic code is optimized for resource conservation. Mol Biol Evol. 2021;38(11):5127-5133.
Search in Google Scholar Back to article
65. Xu H, Zhang J. Is the genetic code optimized for resource conservation? Mol Biol Evol. 2021b;38(11):5122-5126.
Search in Google Scholar Back to article
66. Massey SE. A neutral origin for error minimization in the genetic code. J Mol Evol. 2008;67(5):510-516.
Search in Google Scholar Back to article
67. Massey SE. The neutral emergence of error minimized genetic codes superior to the standard genetic code. J Theoret Biol. 2016 November;408:237-242.
Search in Google Scholar Back to article
68. Di Giulio M. A non-neutral origin for error minimization in the origin of the genetic code. J Mol Evol. 2018;86(9):593-597.
Search in Google Scholar Back to article
69. Ingolia NT, Ghaemmaghami S, Newman JR, Weissman JS. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science. 2009;324(5924):218-223. doi:10.1126/science.1168978
Open DOI Search in Google Scholar Back to article
70. Finkel Y, Mizrahi O, Nachshon A, Weingarten-Gabbay S, Morgenstern D, Yahalom-Ronen Y, Tamir H, Achdout H, Stein D, Israeli O, et al. The coding capacity of SARS-CoV-2. Nature. 2021;589(7840):125-130. doi:10.1038/s41586-020-2739-1
Open DOI Search in Google Scholar Back to article
71. Firth AE. Mapping overlapping functional elements embedded within the protein-coding regions of RNA viruses. Nucleic Acids Res. 2014;42(20):12425-12439.
Search in Google Scholar Back to article
72. Sealfon RS, Lin MF, Jungreis I, Wolf MY, Kellis M, Sabeti PC. FRESCo: finding regions of excess synonymous constraint in diverse viruses. Genome Biol. 2015;16(1):38. doi:10.1186/s13059-015-0603-7
Open DOI Search in Google Scholar Back to article
73. Schlub TE, Buchmann JP, Holmes EC. A simple method to detect candidate overlapping genes in viruses using single genome sequences. Mol Biol Evol. 2018;35(10):2572-2581.
Search in Google Scholar Back to article
74. Nelson CW, Ardern Z, Wei X. OLGenie: Estimating natural selection to predict functional overlapping genes. Mol Biol Evol. 2020;37(8):2440-2449. doi:10.1093/molbev/msaa087
Open DOI Search in Google Scholar Back to article
75. Louis AA. Contingency, convergence and hyper-astronomical numbers in biological evolution. Stud Hist Philos Biol Biomed Sci. 2016;58:107-116. doi:10.1016/j.shpsc.2015.12.014
Open DOI Search in Google Scholar Back to article
76. Keefe AD, Szostak JW. Functional proteins from a random-sequence library. Nature. 2001;410(6829):715-718.
Search in Google Scholar Back to article
77. Çakir U, Gabed N, Brunet M, Roucou X, Kryvoruchko I. Mosaic translation hypothesis: Chimeric polypeptides produced via multiple ribosomal frameshifting as a basis for adaptability [published online ahead of print, 2021 Nov 7]. FEBS J. 2021;10.1111/febs.16269. doi:10.1111/febs.16269
Open DOI Search in Google Scholar Back to article
78. Kosinski LJ, Masel J. Readthrough errors purge deleterious cryptic sequences, facilitating the birth of coding sequences. Mol Biol Evol. 2020;37(6):1761-1774.
Search in Google Scholar Back to article
79. Fernandes JD, Faust TB, Strauli NB, Smith C, Crosby DC, Nakamura RL, Hernandez RD, Frankel AD. Functional segregation of overlapping genes in HIV. Cell. 2016;167(7):1762-1773. e12. doi:10.1016/j.cell.2016.11.031
Open DOI Search in Google Scholar Back to article
80. Safari M, Jayaraman B, Yang S, Smith C, Fernandes JD, Frankel AD. Functional and structural segregation of overlapping helices in HIV-1. Elife. 2022;11:e72482. doi:10.7554/eLife.72482
Open DOI Search in Google Scholar Back to article
81. Dingle K, Ghaddar F, Šulc P, Louis AA. Phenotype bias determines how natural RNA structures occupy the morphospace of all possible shapes. Mol Biol Evol. 2022;39(1):msab280. Available from: https://doi.org/10.1093/molbev/msab280.
Open DOI Search in Google Scholar Back to article
82. Schulz L, Sendker FL, Hochberg GKA. Non-adaptive complexity and biochemical function. Curr Opin Structur Biol. 2022 April;73:102339.
Search in Google Scholar Back to article
83. Gould SJ, Lewontin RC. The spandrels of San Marco and the Panglossian paradigm: A critique of the adaptationist programme. Concept Iss Evol Biol. 1979;205:79.
Search in Google Scholar Back to article
84. Morris SC. Life’s solution: Inevitable humans in a lonely universe. Cambridge: Cambridge University Press; 2003. Available from: https://doi.org/10.1017/CBO9780511535499
Open DOI Search in Google Scholar Back to article

Articles in this issue

DOI: https://doi.org/10.2478/biocosmos-2023-0001 | Journal eISSN: 2719-8634

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Language: English

Page range: 1 - 11

Published on: Mar 17, 2023

Published by: The Israel Biocomplexity Center

In partnership with: Paradigm Publishing Services

Keywords:

genetic code optimality,

evolvability,

gene origins

Related subjects:

Life sciences,

Evolutionary biology,

Chemistry,

Biochemistry,

Physics,

Astronomy and astrophysics,

Philosophy,

History of philosophy,

History of philosophy, other

© 2023 Stefan Wichmann, Zachary Ardern, published by The Israel Biocomplexity Center
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 3 (2023): Issue 1 (January 2023)