Author
Listed:
- Madhab Kumar Sen
(Department of Agroecology and Crop Production, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic)
- Kateřina Hamouzová
(Department of Agroecology and Crop Production, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic)
- Sunil Kanti Mondal
(Department of Biotechnology, The University of Burdwan, Burdwan, West Bengal, India)
- Josef Soukup
(Department of Agroecology and Crop Production, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic)
Abstract
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.
Suggested Citation
Madhab Kumar Sen & Kateřina Hamouzová & Sunil Kanti Mondal & Josef Soukup, 2021.
"Identification of the optimal codons for acetolactate synthase from weeds: an in-silico study,"
Plant, Soil and Environment, Czech Academy of Agricultural Sciences, vol. 67(6), pages 331-336.
Handle:
RePEc:caa:jnlpse:v:67:y:2021:i:6:id:562-2020-pse
DOI: 10.17221/562/2020-PSE
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