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Issue No.02 - March/April (2011 vol.8)
pp: 342-352
Douglas W. Raiford , Southern Methodist University, Dallas
Dan E. Krane , Wright State University, Dayton
Travis E.W. Doom , Wright State University, Dayton
Michael L. Raymer , Wright State University, Dayton
The study of codon usage bias is an important research area that contributes to our understanding of molecular evolution, phylogenetic relationships, respiratory lifestyle, and other characteristics. Translational efficiency bias is perhaps the most well-studied codon usage bias, as it is frequently utilized to predict relative protein expression levels. We present a novel approach to isolating translational efficiency bias in microbial genomes. There are several existent methods for isolating translational efficiency bias. Previous approaches are susceptible to the confounding influences of other potentially dominant biases. Additionally, existing approaches to identifying translational efficiency bias generally require both genomic sequence information and prior knowledge of a set of highly expressed genes. This novel approach provides more accurate results from sequence information alone by resisting the confounding effects of other biases. We validate this increase in accuracy in isolating translational efficiency bias on 10 microbial genomes, five of which have proven particularly difficult for existing approaches due to the presence of strong confounding biases.
Codon usage bias, evolutionary computing and genetic algorithms, miscellaneous, artificial intelligence, computing methodologies, GC-content, strand bias, translational efficiency.
Douglas W. Raiford, Dan E. Krane, Travis E.W. Doom, Michael L. Raymer, "A Genetic Optimization Approach for Isolating Translational Efficiency Bias", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.8, no. 2, pp. 342-352, March/April 2011, doi:10.1109/TCBB.2009.24
[1] M. Nei, "Molecular Population Genetics and Evolution," Frontiers of Biology, vol. 40, pp. 26-28, 1975.
[2] R. Grantham, C. Gautier, M. Gouy, R. Mercier, and A. Pavé, "Codon Catalog Usage and the Genome Hypothesis," Nucleic Acids Research, vol. 8, no. 1, pp. r49-r62, http://nar.oupjournals. org/cgi/content/ abstract/9/1r43, 1981.
[3] T. Ikemura, "Correlation between the Abundance of Escherichia Coli Transfer rnas and the Occurrence of the Respective Codons in Its Protein Genes," J. Molecular Biology, vol. 146, pp. 1-21, 1981.
[4] M. Gouy and C. Gautier, "Codon Usage in Bacteria: Correlation with Gene Expressivity," Nucleic Acids Research, vol. 10, no. 22, pp. 7055-7074, http://www.pubmedcentral.nih.govarticlerender.fcgi?tool=pubmed\&pubme%did=6760125 , 1982.
[5] T. Ikemura, "Correlation between the Abundance of Escherichia Coli Transfer rnas and the Occurrence of the Respective Codons in Its Protein Genes: A Proposal for a Synonymous Codon Choice that Is Optimal for the E. Coli Translational System," J. Molecular Biology, vol. 151, pp. 389-409, 1981.
[6] P.M. Sharp and W.H. Li, "An Evolutionary Perspective on Synonymous Codon Usage in Unicellular Organisms," J. Molecular Evolution, vol. 24, nos. 1/2, pp. 28-38, 1986.
[7] P.M. Sharp, E. Cowe, D.G. Higgins, D.C. Shields, K.H. Wolfe, and F. Wright, "Codon Usage Patterns in Escherichia Coli, Bacillus Subtilis, Saccharomyces Cerevisiae, Schizosaccharomyces Pombe, Drosophila Melanogaster and Homo Sapiens; a Review of the Considerable Within-Species Diversity," Nucleic Acids Research, vol. 16, no. 17, pp. 8207-8211, Sept. 1988.
[8] A. Carbone, A. Zinovyev, and F. Kepes, "Codon Adaptation Index as a Measure of Dominating Codon Bias," Bioinformatics, vol. 19, no. 16, pp. 2005-2015, 2003.
[9] H. Akashi and T. Gojobori, "Metabolic Efficiency and Amino Acid Composition in the Proteomes of Escherichia Coli and Bacillus Subtilis," Proc. Nat'l Academy of Sciences USA, vol. 99, no. 6, pp. 3695-3700, Mar. 2002.
[10] J. Heizer, M. Esley, I. Raiford, W. Douglas, M.L. Raymer, T.E. Doom, R.V. Miller, and D.E. Krane, "Amino Acid Cost and Codon-Usage Biases in 6 Prokaryotic Genomes: A Whole-Genome Analysis," Molecular Biology and Evolution, vol. 23, no. 9, pp. 1670-1680, abstract/23/91670, 2006.
[11] H. Seligmann, "Cost-Minimization of Amino Acid Usage," J. Molecular Evolution, vol. 56, no. 2, pp. 151-161, 2003.
[12] J.R. Lobry and C. Gautier, "Hydrophobicity, Expressivity and Aromaticity Are the Major Trends of No-Acid Usage in 999 Escherichia Coli Chromosome-Encoded Genes," Nucleic Acids Research, vol. 22, pp. 3174-3180, 1994.
[13] A. Grote, K. Hiller, M. Scheer, R. Münch, B. Nörtemann, D.C. Hempel, and D. Jahn, "JCat: A Novel Tool to Adapt Codon Usage of a Target Gene to Its Potential Expression Host," Nucleic Acids Research, vol. 33, pp. W526-W531,, July 2005.
[14] G. Hannig and S.C. Makrides, "Strategies for Optimizing Heterologous Protein Expression in Escherichia Coli," Trends in Biotechnology, vol. 16, no. 2, pp. 54-60, Feb. 1998.
[15] M. Carrondo and M. Fussenegger, "Advances in Heterologous Protein Production," J. Biotechnology, vol. 120, no. 1, p. 55-64, , Oct. 2005.
[16] P.M. Sharp and W.H. Li, "The Codon Adaptation Index—A Measure of Directional Synonymous Codon Usage Bias, and Its Potential Applications," Nucleic Acids Research, vol. 15, pp. 1281-1295, 1987.
[17] A. Carbone, F. Képès, and A. Zinovyev, "Codon Bias Signatures, Organization of Microorganisms in Codon Space, and Lifestyle," Molecular Biology and Evolution, vol. 22, no. 3, pp. 547-561,, Mar. 2005.
[18] D.C. Shields and P.M. Sharp, "Synonymous Codon Usage in Bacillus Subtilis Reflects both Translational Selection and Mutational Biases," Nuclear Acids Research, vol. 15, no. 19, pp. 8023-8040, 15/198023, 1987.
[19] M. Stenico, A.T. Lloyd, and P.M. Sharp, "Codon Usage in Caenorhabditis Elegans: Delineation of Translational Selection and Mutational Biases," Nucleic Acids Research, vol. 22, no. 13, pp. 2437-2446, July 1994.
[20] G.E. Andersson and P.M. Sharp, "Codon Usage in the Mycobacterium Tuberculosis Complex," Microbiology, vol. 142, pp. 915-925, Apr. 1996.
[21] P. Sharp, T. Tuohy, and K. Mosurski, "Codon Usage in Yeast: Cluster Analysis Clearly Differentiates Highly and Lowly Expressed Genes," Nuclear Acids Research, vol. 14, no. 13, pp. 5125-5143, 14/135125, 1986.
[22] D.W. Raiford, D.E. Krane, T.E. Doom, and M.L. Raymer, "Automated Isolation of Translational Efficiency Bias that Resists the Confounding Effect of GC(AT)-Content," IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 7, no. 2, Apr.-June 2010, TCBB.2008.65.
[23] S. Altschul, W. Gish, W. Miller, E. Myers, and D. Lipman, "Basic Local Alignment Search Tool," J. Molecular Biology, vol. 215, pp. 403-410, 1990.
[24] J.H. Holland, Adaptation in Natural and Artificial Systems. Univ. of Michigan Press, 1975.
[25] D. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, 1989.
[26] D.E. Goldberg and K. Deb, "A Comparative Analysis of Selection Schemes Used in Genetic Algorithms," Foundations of Genetic Algorithms (FOGA 1), G.J. Rawlins, ed., pp. 69-93, Morgan Kaufmann, 1991.
[27] Z. Michalewicz, Genetic Algorithms $+$ Data Structures $=$ Evolution Programs. Springer, Nov. 1998.
[28] Z. Michalewicz, G. Nazhiyath, and M. Michalewicz, "A Note on Usefulness of Geometrical Crossover for Numerical Optimization Problems," Evolutionary Programming, vol. 5, no. 1, pp. 305-312, 1996.
[29] S. Kirkpatrick, C.D. Gelatt, and M.P. Vecchi, "Optimization by Simulated Annealing," Science, vol. 220, pp. 671-680, psu.edukirkpatrick83optimization.html , May 1983.
[30] V. Cerny, "A Thermodynamical Approach to the Travelling Salesman Problem: An Efficient Simulation Algorithm," J. Optimization Theory and Applications, vol. 45, pp. 41-51, 1985.
[31] T. Bäck, F. Hoffmeister, and H.-P. Schwefel, "A Survey of Evolution Strategies," Proc. Fourth Int'l Conf. Genetic Algortihms (ICGA), R.K. Belew and L.B. Booker, eds., pp. 2-9, 1991.
[32] K.A. De Jong, "An Analysis of the Behavior of a Class of Genetic Adaptive Systems," PhD dissertation, Univ. of Michigan, 1975.
[33] J.E. Baker, "Reducing Bias and Inefficiency in the Selection Algorithm," Proc. Second Int'l Conf. Genetic Algorithms and Their Application (ICGA2), pp. 14-21, 1987.
[34] T. Barrett, D.B. Troup, S.E. Wilhite, P. Ledoux, D. Rudnev, C. Evangelista, I.F. Kim, A. Soboleva, M. Tomashevsky, and R. Edgar, "NCBI GEO: Mining Tens of Millions of Expression Profiles—Database and Tools Update," Nucleic Acids Research, vol. 35, pp. D760-D765,, Jan. 2007.
[35] R. Wünschiers and H. Eckes, "HyDaBa Hydrogen Database: Nostoc," http://www.hydaba.uni-koeln.deindex.php, Apr. 2005.
[36] E. Cantú-Paz and D. Goldberg, "Efficient Parallel Genetic Algorithms: Theory and Practice," Computer Methods in Applied Mechanics and Eng., vol. 186, nos. 2-4, pp. 221-238, 2000.
[37] R.A. Fisher, "Frequency Distribution of the Values of the Correlation Coefficient in Samples from an Indefinitely Large Population," Biometrika, vol. 10, no. 4, pp. 507-521, May 1915.
[38] E.C. Fieller, H.O. Hartley, and E.S. Pearson, "Tests for Rank Correlation Coefficients. i," Biometrika, vol. 3, no. 4, pp. 470-481, Dec. 1957.
[39] H. Hotelling, "Analysis of a Complex of Statistical Variables into Principal Components," J. Educational Psychology, vol. 24, pp. 417-441, 1933.
[40] I.T. Jolliffe, Principal Component Analysis. Springer-Verlag, 1986.
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