Molecular Biotechnology

, Volume 49, Issue 2, pp 116–128 | Cite as

Synonymous Codon Usage, GC3, and Evolutionary Patterns Across Plastomes of Three Pooid Model Species: Emerging Grass Genome Models for Monocots

  • Gaurav Sablok
  • Kinshuk Chandra Nayak
  • Franck Vazquez
  • Tatiana V. Tatarinova


We have analyzed factors affecting the codon usage pattern of the chloroplasts genomes of representative species of pooid grass family. Correspondence analysis of relative synonymous codon usages (RSCU) showed that genes on secondary axis were correlated with their GC3S values (all r > 0.3, p < 0.05), indicating mutational bias as an important selective force that shaped the variation in the codon usage among chloroplast genes. The Nc-plot showed that although a majority of the points with low-Nc values were lying below the expected curve, a few genes lied on the expected curve. Nc plot clearly showed that mutational bias plays a major role in codon biology across the monocot plastomes. The hydrophobicity and aromaticity of encoded proteins of each species were found to be other factors of codon usage variation. In the view of above light, besides natural selection, several other factors also likely to be involved in determining the selective constraints on codon bias in plastomes of pooid grass genomes. In addition, five codons (B. distachyon), seven codons (H. vulgare), and four codons (T. aestivum) were identified as optimal codons of the three grass chloroplasts. To identify genes evolving under positive selection, rates of nonsynonymous substitutions (Ka) and synonymous substitutions (Ks) were computed for all groups of orthologous gene pairs.


Brachypodium distachyon Triticum aestivum Hordeum vulgare subsp. vulgare Correspondence analysis GC3 biology Mutational bias 



Gaurav Sablok thanks Key Lab of Horticultural Plant Biology (MOE), Huazhong Agricultural University. Tsuyoshi Hachiya and Yasubumi Sakakibara of Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Japan are gratefully acknowledged for chrom-link visualization of the genomes. We gratefully acknowledge Professor Hans K. Stenoien, Systematics & Evolution Group, Norwegian University of Science and Technology, Norway for providing the peer review eye during the manuscript preparation. This work was supported by the Department of Biotechnology, Ministry of Science and Technology, Government of India. Research work of F. Vazquez is supported by an Ambizione Grant (PZ00P3_126329/1 to F.V.) of the Swiss National Science Foundation. Tatiana Tatarinova would like to thank the University of Glamorgan’s Research Investment Scheme for supporting this project.

Supplementary material

12033_2011_9383_MOESM1_ESM.ppt (815 kb)
Supplementary material 1 (PPT 815 kb)


  1. 1.
    Sau, K., & Deb, A. (2008). Temperature influences synonymous codon and amino acid usage biases in the phages infecting extremely thermophilic prokaryotes. In Silico Biology, 9, 0001.Google Scholar
  2. 2.
    Guo, F., & Yuan, J. (2009). Codon usages of genes on chromosome, and surprisingly, genes in plasmid are primarily affected by strand-specific mutational biases in Lawsonia intracellularis. DNA Research, 16, 91–104.CrossRefGoogle Scholar
  3. 3.
    Liu, Q. P., & Xue, Q. Z. (2005). Comparative studies on codon usage pattern of chloroplasts and their host nuclear genes in four plant species. Journal of Genetics, 84, 55–62.CrossRefGoogle Scholar
  4. 4.
    Stenico, M., Lloyd, A. T., & Sharp, P. M. (1994). Codon usage in Caenorhabditis elegans: delineation of translational selection and mutational biases. Nucleic Acids Research, 22, 2437–2446.CrossRefGoogle Scholar
  5. 5.
    Karlin, S., & Mrazek, J. (1996). What drives codon choices in human genes? Journal of Molecular Biology, 262, 459–472.CrossRefGoogle Scholar
  6. 6.
    Chiapello, H., Lisacek, F., Caboche, M., & Henaut, A. (1998). Codon usage and gene function are related in sequences of Arabidopsis thaliana. Gene, 209, GC1–GC38.CrossRefGoogle Scholar
  7. 7.
    Morton, B. R., & Wright, S. I. (2007). Selective constraints on codon usage of nuclear genes from Arabidopsis thaliana. Molecular Biology and Evolution, 24, 122–129.CrossRefGoogle Scholar
  8. 8.
    Wang, H. C., & Hickey, D. A. (2007). Rapid divergence of codon usage patterns within the rice genome. BMC Evolutionary Biology, 7(Suppl 1), S6.CrossRefGoogle Scholar
  9. 9.
    Tatarinova, T., Alexandrov, N., Bouck, J., & Feldman, K. (2010). GC3 biology in corn, rice, sorghum and other grasses. BMC Genomics, 11, 308.CrossRefGoogle Scholar
  10. 10.
    Douzery, E. J. P., Snell, E. A., Bapteste, E., Delsuc, F., & Philippe, H. (2004). The timing of eukaryotic evolution: does a relaxed molecular clock reconcile proteins and fossils? Proceedings of the National Academy of Sciences USA, 101, 15386–15391.CrossRefGoogle Scholar
  11. 11.
    Yoon, H. S., Hackett, J. D., Ciniglia, C., Pinto, G., & Bhattacharya, D. (2004). A molecular timeline for the origin of photosynthetic eukaryotes. Molecular Biology and Evolution, 21, 809–818.CrossRefGoogle Scholar
  12. 12.
    Waters, M. T., & Langdale, J. A. (2009). The making of a chloroplast. The EMBO Journal, 28, 2861–2873.CrossRefGoogle Scholar
  13. 13.
    Bendich, A. J. (2004). Circular chloroplast chromosomes: the grand illusion. The Plant Cell, 16, 1661–1666.CrossRefGoogle Scholar
  14. 14.
    Sugiura, M. (1992). The chloroplast genome. Plant Molecular Biology, 19, 149–168.CrossRefGoogle Scholar
  15. 15.
    Morton, B. R. (2003). The role of context-dependent mutations in generating compositional and codon usage bias in grass chloroplast DNA. Journal of Molecular Evolution, 56, 616–629.CrossRefGoogle Scholar
  16. 16.
    Morton, B. R. (1998). Selection on the codon bias of chloroplast and cyanelle genes in different plant and algal lineages. Journal of Molecular Evolution, 46, 449–459.CrossRefGoogle Scholar
  17. 17.
    Draper, J., Mur, L. A. J., Jenkins, G., Ghosh-Biswas, G. C., Bablak, P., Hasterok, R., et al. (2001). Brachypodium distachyon. A new model system for functional genomics in grasses. Plant Physiology, 127, 155–1539.CrossRefGoogle Scholar
  18. 18.
    Bortiri, E., Coleman-Derr, D., Lazo, G. R., Anderson, O. D., & Gu, Y. Q. (2008). The complete chloroplast genome sequence of Brachypodium distachyon: sequence comparison and phylogenetic analysis of eight grass plastomes. BMC Research Notes, 1, 61.CrossRefGoogle Scholar
  19. 19.
    The International Brachypodium Initiative. (2010). Genome sequencing and analysis of the model grass Brachypodium distachyon. Nature, 463, 763–768.CrossRefGoogle Scholar
  20. 20.
    Zhang, W. J., Zhou, J., Li, Z. F., Wang, L., Gu, X., & Zhong, Y. (2007). Comparative analysis of codon usage patterns among mitochondrion, chloroplast and nuclear genes in Triticum aestivum L. Journal of Integrative Plant Biology, 149, 37–44.Google Scholar
  21. 21.
    Rosenberg, M. S., Subramanian, S., & Kumar, S. (2003). Patterns of transitional mutation biases within and among mammalian genomes. Molecular Biology and Evolution, 20, 988–993.CrossRefGoogle Scholar
  22. 22.
    Wright, F. (1990). The ‘effective number of codons’ used in a gene. Gene, 87, 23–29.CrossRefGoogle Scholar
  23. 23.
    Greenacre, M. J. (1984). Theory and application of correspondence analysis (p. 223). London: Academic Press.Google Scholar
  24. 24.
    Sharp, P. M., & Li, W. H. (1987). The codon adaptation index—a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Research, 15, 1281–1295.CrossRefGoogle Scholar
  25. 25.
    Morton, B. R., & Levin, J. A. (1997). The atypical codon usage of the psbA gene may be the remnant of an ancestral bias. Proceedings of the National Academy of Sciences USA, 94, 11434–11438.CrossRefGoogle Scholar
  26. 26.
    Kyte, J., & Doolittle, R. (1982). A simple method for displaying the hydropathic character of a protein. Journal of Molecular Evolution, 157, 105–132.Google Scholar
  27. 27.
    McInerney, J. O. (1998). Replicational and transcriptional selection on codon usage in Borrelia burgdorferi. Proceedings of the National Academy of Sciences USA, 95, 10698–10703.CrossRefGoogle Scholar
  28. 28.
    Ikemura, T. (1985). Codon usage and tRNA content in unicellular and multicellular organisms. Molecular Biology and Evolution, 2, 13–34.Google Scholar
  29. 29.
    Polzin, K. M., Calvo, E. S., & Olsona, T. S. (1998). Identification of homoeologous regions in complex genomes using lambda genomic clones. Plant Science, 131, 161–171.CrossRefGoogle Scholar
  30. 30.
    Lyons, E., Pedersen, B., Kane, J., Alam, M., Ming, R., Tang, H., et al. (2008). Finding and comparing syntenic regions among arabidopsis and the outgroups papaya, poplar, and grape: CoGe with Rosids. Plant Physiology, 148(4), 1772–1781.CrossRefGoogle Scholar
  31. 31.
    Popendorf, K., Hachiya, T., Osana, Y., & Sakakibara, Y. (2010). Murasaki: a fast, parallelizable algorithm to find anchors from multiple genomes. PLoS ONE, 5(9), e12651.CrossRefGoogle Scholar
  32. 32.
    Pevzner, P. A., & Tesler, G. (2003). Genome rearrangements in mammalian evolution: lessons from human and mouse genomes. Genome Research, 13, 37–45.CrossRefGoogle Scholar
  33. 33.
    Bourque, G., Pevzner, P. A., & Tesler, G. (2004). Reconstructing the genomic architecture of ancestral mammals: lessons from human, mouse, and rat genomes. Genome Research, 14, 507–516.CrossRefGoogle Scholar
  34. 34.
    Sakakibara, Y., Osana, Y., & Popendorf, K. (2007). Development of a large-scale comparative genome system and its application to the analysis of mycobacteria genomes. Nihon Hansenbyo Gakkai Zasshi, 76, 251–256.Google Scholar
  35. 35.
    Hachiya, T., Osana, Y., Popendorf, K., & Sakakibara, Y. (2009). Accurate identification of orthologous segments among multiple genomes. Bioinformatics, 25, 853–860.CrossRefGoogle Scholar
  36. 36.
    Grigoriev, A. (1998). Analyzing genomes with cumulative skew diagrams. Nucleic Acids Research, 26, 2286–2290.CrossRefGoogle Scholar
  37. 37.
    Tatarinova, T., Brover, V., Troukhan, M., & Alexandrov, N. (2003). Skew in GC content near the transcription start site in Arabidopsis thaliana. Bioinformatics, 19(Suppl 1), i313–i314.CrossRefGoogle Scholar
  38. 38.
    Wan, X. F., Xu, D., Kleinhofs, A., & Zhou, J. (2004). Quantitative relationship between synonymous bias and GC composition across unicellular genomes. BMC Evolutionary Biology, 4, 19.CrossRefGoogle Scholar
  39. 39.
    Larkin, M. A., Blackshields, G., Brown, N. P., Chenna, R., McGettigan, P. A., McWilliam, H., et al. (2007). Clustal W and clustal X version 2.0. Bioinformatics, 23, 2947–2948.CrossRefGoogle Scholar
  40. 40.
    Sueoka, N. (1999). Translation-coupled violation of parity rule 2 in human genes is not the case of heterogeneity of the DNA G+C content of third codon position. Gene, 238, 53–58.CrossRefGoogle Scholar
  41. 41.
    Sharp, P. M., Cowe, E., Higgins, D. G., Shields, D. C., Wolfe, K. H., & Wright, F. (1988). Codon usage 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, 16, 8207–8711.CrossRefGoogle Scholar
  42. 42.
    Knight, R. D., Freeland, S. J., & Landweber, L. F. (2001). A simple model based on mutation and selection explains trends in codon and amino-acid usage and GC composition within and across genomes. Genome Biology, 2, 0010.1–0010.13.Google Scholar
  43. 43.
    Coulondre, C., Miller, J. H., Farabaugh, P. J., & Gilbert, W. (1978). Molecular basis of base substitution hotspots in Escherichia coli. Nature, 274, 775–780.CrossRefGoogle Scholar
  44. 44.
    Hasegawa, M., Cao, Y., & Yang, Z. (1998). Preponderance of slightly deleterious polymorphism in mitochondrial DNA: nonsynonymous/synonymous rate ratio is much higher within species than between species. Molecular Biology and Evolution, 15, 1499–1505.Google Scholar
  45. 45.
    Sueoka, N. (1962). On the genetic basis of variation and heterogeneity of DNA base composition. Proceedings of the National Academy of Sciences USA, 48, 582–592.CrossRefGoogle Scholar
  46. 46.
    Morton, B. R. (1999). Strand asymmetry and codon usage bias in the chloroplast genome of Euglena gracilis. Proceedings of the National Academy of Sciences USA, 96, 5123–5128.CrossRefGoogle Scholar
  47. 47.
    Meng, Z., Wei, L., & Xia, L. (2008). Analysis of synonymous codon usage in chloroplast genome of Populus alba. Journal of Forestry Research, 19, 293–297.CrossRefGoogle Scholar
  48. 48.
    Pfitzinger, H., Guillemaut, P., Weil, J. H., & Pillay, D. T. N. (1987). Adjustment of the tRNA population to the codon usage of chloroplasts. Nucleic Acids Research, 15, 137.CrossRefGoogle Scholar
  49. 49.
    Shi, X. F., Huang, J. F., Liang, C. R., Liu, S. Q., Xie, J., & Liu, C. Q. (2001). Is there a close relationship between synonymous codon bias and codon-anticodon binding strength in human genes? Chinese Science Bulletin, 12, 1015–1019.CrossRefGoogle Scholar
  50. 50.
    Xia, X. (1998). How optimized is the translational machinery in Escherichia coli, Salmonella typhimurium and Saccharomyces cerevisiae? Genetics, 149, 37–44.Google Scholar
  51. 51.
    Lynn, D. J., Singer, G. A., & Hickey, D. A. (2002). Synonymous codon usage is subject to selection in thermophilic bacteria. Nucleic Acids Research, 30, 4272–4277.CrossRefGoogle Scholar
  52. 52.
    Wolfe, K. H., & Sharp, P. M. (1988). Identification of functional open reading frames in chloroplast genomes. Gene, 66, 215–222.CrossRefGoogle Scholar
  53. 53.
    Morton, B. R. (1993). Chloroplast DNA codon use: evidence for selection at the psbA locus based on tRNA availability. Journal of Molecular Evolution, 37, 273–280.CrossRefGoogle Scholar
  54. 54.
    Zhao, S., Zhang, Q., Chen, Z., et al. (2007). The factors shaping synonymous codon usage in the genome of Burkholderia mallei. Journal of Genetics and Genomics, 34, 362–372.CrossRefGoogle Scholar
  55. 55.
    Hausner, G., Olson, R., Simon, D., Johnson, I., Sanders, E. R., Karol, K. G., et al. (2006). Origin and evolution of the chloroplast trnK (matK) intron: a model for evolution of group II intron RNA structures. Molecular Biology and Evolution, 23, 380–391.CrossRefGoogle Scholar
  56. 56.
    Selvaraj, D., Sarma, R. K., & Sathishkumar, R. (2008). Phylogenetic analysis of chloroplast matK gene from Zingiberaceae for plant DNA barcoding. Bioinformation, 3, 24–27.Google Scholar
  57. 57.
    Wolfe, K. H., Morden, C. W., Ems, S. C., & Palmer, J. D. (1992). Rapid evolution of the plastid translational apparatus in a non-photosynthetic plant: loss of accelerated sequence evolution of tRNA and ribosomal protein genes. Journal of Molecular Evolution, 35, 304–317.CrossRefGoogle Scholar
  58. 58.
    Boudreau, E., Takahashi, Y., Lemieux, C., Turmel, M., & Rochaix, J. D. (1997). The chloroplast ycf3 and ycf4 open reading frames of Chlamydomonas reinhardtii are required for the accumulation of the photosystem I complex. The EMBO Journal, 16, 6095–6104.CrossRefGoogle Scholar
  59. 59.
    Magee, A. M., Aspinall, S., Rice, D. W., Cusack, B. P., Sémon, M., Perry, A. S., et al. (2010). Localized hypermutation and associated gene losses in legume chloroplast genomes. Genome Research, 20, 1700–1710.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Key Lab of Horticultural Plant Biology (MOE)Huazhong Agricultural UniversityWuhanChina
  2. 2.Department of BiotechnologyBioinformatics Centre, Institute of Life SciencesBhubaneswarIndia
  3. 3.Zurich-Basel Plant Science CenterBotanical Institute, University of BaselBaselSwitzerland
  4. 4.Division of Mathematics and StatisticsUniversity of GlamorganPontypriddUK

Personalised recommendations