Identification of the optimal codons for acetolactate synthase from weeds: an in-silico study

https://doi.org/10.17221/562/2020-PSECitation:

Sen M.K., Hamouzová K., Mondal S.K., Soukup J. (2021): Identification of the optimal codons for acetolactate synthase from weeds: an in-silico study. Plant Soil Environ., 67: 331–336.

 

download PDF

Although various studies of codon usage bias have been reported in a broad spectrum of organisms, no studies to date have examined codon usage bias for herbicide target genes. In this study, we analysed codon usage patterns for the acetolactate synthase (ALS) gene in eight monocot weeds and one model monocot. The base composition at the third codon position follows C3 > G3 > T3 > A3. The values of the effective number of codons (ENC or Nc) indicate low bias, and ENC or Nc vs. GC3 plot suggests that this low bias is due to mutational pressure. Low codon adaptation index and codon bias index values further supported the phenomenon of low bias. Additionally, the optimal codons, along with over- and under-represented codons, were identified. Gene design using optimal codons rather than overall abundant codons produce improved protein expression results. Our results can be used for further studies, including eliciting the mechanisms of herbicide resistance (occurring due to elevation of gene expression levels) and the development of new compounds, their efficiency and risk assessment for herbicide resistance evolution.

 

References:
Bennetzen J.L., Hall B.D. (1982): Codon selection in yeast. Journal of Biological Chemistry, 257: 3026–3031. https://doi.org/10.1016/S0021-9258(19)81068-2
 
Duggleby R.G., McCourt J.A., Guddat L.W. (2008): Structure and mechanism of inhibition of plant acetohydroxyacid synthase. Plant Physiology and Biochemistry, 46: 309–324. https://doi.org/10.1016/j.plaphy.2007.12.004
 
Elhaik E., Pellegrini M., Tatarinova T.V. (2014): Gene expression and nucleotide composition are associated with genic methylation level in Oryza sativa. BMC Bioinformatics, 15: 23. https://doi.org/10.1186/1471-2105-15-23
 
Elhaik E., Tatarinova T. (2012): GC3 biology in eukaryotes and prokaryotes. In: Tatarinova T. (ed.): DNA Methylation — From Genomics To Technology. London, IntechOpen. ISBN 978-953-51-0320-2.
 
Hamouzová K., Košnarová P., Salava J., Soukup J., Hamouz P. (2014): Mechanisms of resistance to acetolactate synthase-inhibiting herbicides in populations of Apera spica-venti from the Czech Republic. Pest Management Science, 70: 541–548. https://doi.org/10.1002/ps.3563
 
Je M.Y., Kim H.Y., Son H.S. (2019): Analysis of the codon usage pattern of the RdRP gene of mycovirus infecting Aspergillus spp. Virology Journal, 16: 10. https://doi.org/10.1186/s12985-019-1115-y
 
Jugulam M., Shyam C. (2019): Non-target-site resistance to herbicides: recent developments. Plants, 8: 417. https://doi.org/10.3390/plants8100417
 
Kumar S., Stecher G., Li M., Knyaz C., Tamura K. (2018): MEGA X: molecular evolutionary genetics analysis across computing platforms. Molecular Biology and Evolution, 35: 1547–1549. https://doi.org/10.1093/molbev/msy096
 
Mazumdar P., Othman R.Y.B., Mebus K., Ramakrishnan N., Harikrishna J.A. (2017): Codon usage and codon pair patterns in non-grass monocot genomes. Annals of Botany, 120: 893–909. https://doi.org/10.1093/aob/mcx112
 
Mondal S.K., Kundu S., Das R., Roy S. (2016): Analysis of phylogeny and codon usage bias and relationship of GC content, amino acid composition with expression of the structural nif genes. Journal of Biomolecular Structure and Dynamics, 34: 1649–1666. https://doi.org/10.1080/07391102.2015.1087334
 
Murphy B.P., Tranel P.J. (2019): Target-site mutations conferring herbicide resistance. Plants (Basel), 8: 382. https://doi.org/10.3390/plants8100382
 
Powles S.B., Yu Q. (2010): Evolution in action: plants resistant to herbicides. Annual Review of Plant Biology, 61: 317–347. https://doi.org/10.1146/annurev-arplant-042809-112119
 
Quax T.E.F., Claassens N.J., Söll D., van der Oost J. (2015): Codon bias as a means to fine-tune gene expression. Molecular Cell, 59: 149–161. https://doi.org/10.1016/j.molcel.2015.05.035
 
Sharp P.M., Stenico M., Peden J.F., Lloyd A.T. (1993): Codon usage: mutational bias, translational selection, or both? Biochemistry Society Transaktions, 21: 835–841. https://doi.org/10.1042/bst0210835
 
Stoletzki N., Eyre-Walker A. (2007): Synonymous codon usage in Escherichia coli: selection for translational accuracy. Molecular Biology and Evolution, 24: 374–381. https://doi.org/10.1093/molbev/msl166
 
Wright F. (1990): The "effective number of codons" used in a gene. Gene, 87: 23–29. https://doi.org/10.1016/0378-1119(90)90491-9
 
Zhou Z., Dang Y., Zhou M., Li L., Yu C.H., Fu J., Chen S., Liu Y. (2016): Codon usage is an important determinant of gene expression levels largely through its effects on transcription. Proceedings of the National Academy of Sciences, 113: E6117–25. https://doi.org/10.1073/pnas.1606724113
 
download PDF

© 2021 Czech Academy of Agricultural Sciences | Prohlášení o přístupnosti