Comparative analysis of codon usage bias in chloroplast genomes of ten medicinal species of Rutaceae

Author:

Shen Lianwen,Chen Shengqun,Liang Mei,Qu Shang,Feng Shijing,Wang Dawei,Wang Gang

Abstract

AbstractRutaceae family comprises economically important plants due to their extensive applications in spices, food, oil, medicine, etc. The Rutaceae plants is able to better utilization through biotechnology. Modern biotechnological approaches primarily rely on the heterologous expression of functional proteins in different vectors. However, several proteins are difficult to express outside their native environment. The expression potential of functional genes in heterologous systems can be maximized by replacing the rare synonymous codons in the vector with preferred optimal codons of functional genes. Codon usage bias plays a critical role in biogenetic engineering-based research and development. In the current study, 727 coding sequences (CDSs) obtained from the chloroplast genomes of ten Rutaceae plant family members were analyzed for codon usage bias. The nucleotide composition analysis of codons showed that these codons were rich in A/T(U) bases and preferred A/T(U) endings. Analyses of neutrality plots, effective number of codons (ENC) plots, and correlations between ENC and codon adaptation index (CAI) were conducted, which revealed that natural selection is a major driving force for the Rutaceae plant family’s codon usage bias, followed by base mutation. In the ENC vs. CAI plot, codon usage bias in the Rutaceae family had a negligible relationship with gene expression level. For each sample, we screened 12 codons as preferred and high-frequency codons simultaneously, of which GCU encoding Ala, UUA encoding Leu, and AGA encoding Arg were the most preferred codons. Taken together, our study unraveled the synonymous codon usage pattern in the Rutaceae family, providing valuable information for the genetic engineering of Rutaceae plant species in the future.

Funder

the Local Walnut R&D Groups in Guizhou Province

the National Natural Science Foundation of China

Guizhou science and Technology plan Support Project

QianKehe Fundation

Guizhou Province Forestry Characteristic Forestry Industry Project

Publisher

Springer Science and Business Media LLC

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