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Updated: Mar 30, 2026

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mRNA Interactome Capture from Plant Protoplasts
Published on: July 28, 2017
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New insights into the interplay between codon bias determinants in plants
S Camiolo1, S Melito1, A Porceddu2
1Dipartimento di Agraria, SACEG, Università degli Studi di Sassari, Sassari, Italy.
Summary
Codon bias in plants is primarily driven by neutral forces like mutation and gene conversion, with some selection for translational efficiency. Monocots show lower background bias but higher overall codon bias compared to dicots.
Area of Science:
- Genomics
- Molecular Biology
- Evolutionary Biology
Background:
- Codon bias, the non-random usage of synonymous codons, is observed across diverse species.
- Potential drivers include neutral mechanisms (mutation, gene conversion, drift) and selection (mRNA stability, translation efficiency, accuracy).
- The relative contributions of these factors to codon bias remain unclear.
Purpose of the Study:
- To dissect the contributions of mutational bias and selection to codon bias in plant genes.
- To analyze genomic composition and its influence on codon usage profiles.
- To compare codon bias patterns between monocots, dicots, and mosses.
Main Methods:
- Analysis of mononucleotide, dinucleotide, and trinucleotide frequencies in plant genes.
- Investigation of genomic compositional background.
- Comparative analysis across 15 eudicots, 4 monocots, and 2 mosses.
Main Results:
- Neutral forces, particularly mutational pressure and G|C-biased gene conversion, explain most observed codon bias.
- Evidence suggests selection for translational efficiency and mRNA folding also plays a role.
- Monocots exhibit lower background compositional bias but higher overall codon bias than dicots.
Conclusions:
- Neutral evolutionary forces are the predominant drivers of codon bias in the studied plant species.
- Selection contributes to codon usage optimization, influencing translational efficiency and mRNA structure.
- Significant compositional differences exist between monocots and dicots, impacting their codon bias patterns.
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