SIMULATION OF BACTERIAL GENOME EVOLUTION UNDER REPLICATIONAL MUTATIONAL PRESSURES

Paweł Błażej, Paweł Mackiewicz, Stanisław Cebrat

2012

Abstract

Directional mutational pressure associated with DNA replication is one of the most significant forces shaping nucleotide composition and structure of bacterial chromosomes as well as influencing the evolution of their genes. Here we introduced the model of bacterial genome evolution including two mutational pressures acting in differently replicated DNA strands (called leading and lagging). The simulations were performed on the population of protein coding genes from the Borrelia burgdorferi genome which shows a very strong compositional bias between the DNA strands. The simulated genomes were eliminated by selection because of: (i) stop translation codon occurrence in their gene sequences and (ii) the loss of their coding signal which was calculated according to the algorithm for recognition of protein coding sequences. This algorithm considers three independent homogeneous Markov chains to describe transition between nucleotides separately for each of three codon positions in a given DNA sequence. The negative selection for stop codons appeared much stronger than the one based on the coding signal and led to elimination of more genomes from the population. The genes were subjected both to the direct mutational pressure, characteristic of the strand on which they are located and to the reverse pressure, characteristic of the opposite strand. Generally, the elimination of genomes because of stop codons occurrence was the most frequent for the reverse pressure whereas the coding signal selection eliminated the genome most often for the direct pressure. The leading strand mutational pressure was more destructive for coding signal whereas the the lagging strand pressure generated more stop codons in the gene sequences.

References

  1. Blaz?ej, P., Mackiewicz, P., and Cebrat, S. (2010). Using the genetic code wisdom for recognizing protein coding sequences. In Proceedings of the 2010 International Conference on Bioinformatics & Computational Biology (BIOCOMP 2010), pages 302-305.
  2. Blaz?ej, P., Mackiewicz, P., and Cebrat, S. (2011). Algorithm for finding coding signal using homogeneous markov chains independently for three codon positions. In Proceedings of the 2011 International Conference on Bioinformatics and Computational Biology (ICBCB 2011), pages 20-24.
  3. Cebrat, S., Dudek, M., and Mackiewicz, P. (1998). Sequence asymmetry as a parameter indicating coding sequence in saccharomyces cerevisiae genome. Theory in Biosciences, 117:78-89.
  4. Cebrat, S., Dudek, M., Mackiewicz, P., Kowalczuk, M., and Fita, M. (1997). Asymmetry of coding versus non-coding strand in coding sequences of different genomes. Microbial and Comparative Genomics, 2:259-268.
  5. Dudkiewicz, M., Mackiewicz, P., Kowalczuk, M., Mackiewicz, D., Nowicka, A., Polak, N., Smolarczyk, K., Kriaga, J., Dudek, M., and Cebrat, S. (2004). Simulation of gene evolution under directional mutational pressure. Physica A, (336):63-73.
  6. Dudkiewicz, M., Mackiewicz, P., Mackiewicz, D., Kowalczuk, M., Nowicka, A., Polak, N., Smolarczyk, K., Kiraga, J., Dudek, M., and Cebrat, S. (2005). Higher mutation rate helps to rescue genes from the elimination by selection. Biosystems, 80:192-199.
  7. Frank, A. and Lobry, J. (1999). Asymmetric substitution patterns: a review of possible underlying mutational or selective mechanisms. Gene, 238:65-77.
  8. Freeman, J., Plasterer, T., Smith, T., and Mohr, S. (1998). Patterns of genome organization in bacteria. Science, 279:1827.
  9. Grigoriev, A. (1998). Analysing genomes with cumulative skew diagrams. Nucleic Acids Res., 26:2286-2290.
  10. Khrustalev, V. and Barkovsky, E. (2010). The probability of nonsense mutation caused by replication-associated mutational pressure is much higher for bacterial genes from lagging than from leading strands. Genomics, 96:173-180.
  11. Kowalczuk, M., Mackiewicz, P., Mackiewicz, D., Nowicka, A., Dudkiewicz, M., Dudek, M., and Cebrat, S. (2001a). DNA asymmetry and the replicational mutational pressure. J. Appl. Genet., 42:553-577.
  12. Lean, M., Devine, K., Sharp, P., and Wolfe, K. (1999). Proteome composition and codon usage in spirochaetes: species-specific and DNA strand-specific mutational biases. Acids Res., 27:1642-1649.
  13. Lobry, J. (1996). Asymmetric substitution patterns in the two DNA strands of bacteria. Mol. Biol. Evol., 13:, 660-665.
  14. Lobry, J. and Sueoka, N. (2002). Asymmetric directional mutation pressures in bacteria. Genome Biol., 3:58.
  15. Mackiewicz, D. and Cebrat, S. (2009). To understand nature - computer modelling between genetics and evolution. In J. Miekisz and M. Lachowicz (eds), From Genetics to Mathematics (Series on Advances in Mathematics for Applied Sciences) Vol. 79, pages 1-33. World Scientific.
  16. Mackiewicz, D., Mackiewicz, P., Kowalczuk, M., Dudkiewicz, M., Dudek, M., and Cebrat, S. (2003a). Rearrangements between differently replicating dna strands in asymmetric bacterial genomes. Acta Microbiologica Polonica, 52:245-261.
  17. Mackiewicz, P., Dudkiewicz, M., Kowalczuk, M., Mackiewicz, D., Kiraga, J., Polak, N., Smolarczyk, K., Nowicka, A., Dudek, M., and Cebrat, S. (2004). Differential gene survival under asymmetric directional mutational pressure. Lecture Notes in Computer Science, 3039:687-693.
  18. Mackiewicz, P., Gierlik, A., Kowalczuk, M., Dudek, M., and Cebrat, S. (1999a). Asymmetry of nucleotide composition of prokaryotic chromosomes. J. Appl. Genet., 40:1-14.
  19. Mackiewicz, P., Gierlik, A., Kowalczuk, M., Dudek, M., and Cebrat, S. (1999b). How does replicationassociated mutational pressure influence amino acid composition of proteins? Genome Res., 9:409-416.
  20. Mackiewicz, P., Gierlik, A., Kowalczuk, M., Szczepanik, D., Dudek, M., and Cebrat, S. (1999c). Mechanisms generating long-range correlation in nucleotide composition of the borrelia burgdorferi genome. Physica A, 273:103-115.
  21. Mackiewicz, P., Mackiewicz, D., Kowalczuk, M., Dudkiewicz, M., Dudek, M., and Cebrat, S. (2003b). High divergence rate of sequences located on different DNA strands in closely related bacterial genomes. J. Appl. Genet., 44:561-584.
  22. Mackiewicz, P., Szczepanik, D., Gierlik, A., Kowalczuk, M., Nowicka, A., Dudkiewicz, M., Dudek, M., and Cebrat, S. (2001). The differential killing of genes by inversions in prokaryotic genomes. J. Mol. Evol., 53:615-621.
  23. McInerney, J. (1998). Replicational and transcriptional selection on codon usage in borrelia burgdorferi. Proc. Natl. Acad. Sci. U.S.A., 95:10698-10703.
  24. McLean, M., Wolfe, K., and Devine, K. (1998). Base composition skews, replication orientation, and gene orientation in 12 prokaryote genomes. J. Mol. Evol., 47:691-696.
  25. Rocha, E. and Danchin, A. (2001). Ongoing evolution of strand composition in bacterial genomes. Mol. Biol. Evol., 18:1789-1799.
  26. Rocha, E. and Danchin, A. (2003a). Gene essentiality determines chromosome organisation in bacteria. Nucleic Acids Res., 31:5202-5211.
  27. Rocha, E. and Danchin, A. (2003b). Essentiality, not expressiveness, drives gene strand bias in bacteria. Nature Genetics, 34:377-378.
  28. Rocha, E., Danchin, A., and Viari, A. (1999). Universal replication biases in bacteria. Mol. Microbiol., 32:11- 16.
  29. Rocha, E., Touchon, M., and Feil, E. (2006). Similar compositional biases are caused by very different mutational effects. Genome Res., 16:1537-1547.
  30. Szczepanik, D., Mackiewicz, P., Kowalczuk, M., Gierlik, A., Nowicka, A., Dudek, M., and Cebrat, S. (2001). Evolution rates of genes on leading and lagging DNA strands. J. Mol. Evol., 52:426-433.
  31. Tillier, E. and Collins, R. (2000a). The contributions of replication orientation, gene direction, and signal sequences to base composition asymmetries in bacterial genomes. J. Mol. Evol., 50:249-257.
  32. Tillier, E. and Collins, R. (2000b). Replication orientation affects the rate and direction of bacterial gene evolution. J. Mol. Evol., 51:459-463.
  33. WaÁczyk, M., Blaz?ej, P., and Mackiewicz, P. (2011). Comparison of two algorithms based on markov chains applied in recognition of protein coding sequences in prokaryotes. In Proceedings of the Seventeeth National Conference on Applications of Mathematics in Biology and Medicine, pages 118-123.
Download


Paper Citation


in Harvard Style

Błażej P., Mackiewicz P. and Cebrat S. (2012). SIMULATION OF BACTERIAL GENOME EVOLUTION UNDER REPLICATIONAL MUTATIONAL PRESSURES . In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2012) ISBN 978-989-8425-90-4, pages 51-57. DOI: 10.5220/0003755900510057


in Bibtex Style

@conference{bioinformatics12,
author={Paweł Błażej and Paweł Mackiewicz and Stanisław Cebrat},
title={SIMULATION OF BACTERIAL GENOME EVOLUTION UNDER REPLICATIONAL MUTATIONAL PRESSURES},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2012)},
year={2012},
pages={51-57},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003755900510057},
isbn={978-989-8425-90-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2012)
TI - SIMULATION OF BACTERIAL GENOME EVOLUTION UNDER REPLICATIONAL MUTATIONAL PRESSURES
SN - 978-989-8425-90-4
AU - Błażej P.
AU - Mackiewicz P.
AU - Cebrat S.
PY - 2012
SP - 51
EP - 57
DO - 10.5220/0003755900510057