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Codon usage bias and evolution analysis in the mitochondrial genome of Mesona chinensis Benth

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Abstract

Mesona chinensis Benth (MCB) is an edible and medicinal plant in southern China and Southeast Asian countries. Mitochondria, semi-autonomous organelles in eukaryotic cells, contain their own genome (mitogenome) and are involved in various cellular processes. Codons are the core elements of protein translation in gene-coding regions. It is of great significance to analyze the characteristics of codon usage in gene-coding regions for gene function and phylogenetic studies. Here, the codon usage pattern and the factors affecting codon usage bias (CUB), and the cluster and phylogenetic analysis based on mitogenomes were determined. Results of nucleotide composition analysis showed an unequal distribution of T, G, A, and C nucleotides and AT bias in MCB mitogenome. The GC, GC1, GC2, GC3 content, codon adaption index (CAI), and effective number codon (ENC) of MCB mitogenome were 43.09%, 48.37%, 42.67%, 38.22%, 0.632, and 55.539, respectively, while those of each gene ranged from 35.61% to 51.85%, 36.25% to 56.69%, 33.46% to 47.76%, 23.08% to 58.15%, 37.81 to 60.02, and 0.564 to 0.680, respectively. 18 out of 28 genes showed the highest GC1 content and the lowest GC3 content, and the general order of GC content in different codon positions was GC1 > GC2 > GC3. Further analysis of the neutrality plot, ENC-plot, and PR2-bias plot revealed that the CUB of MCB mitogenome was affected by natural selection and mutation. Seven optimal codons, TTG, GAC, TCA, AGA, ACC, GGG, and ATA were determined in MCB mitogenome. The phylogenetic tree based on mitogenome sequences and the cluster analysis based on relative synonymous codon usage (RSCU) values indicated that the CUB of mitogenome might have to do with the genetic relationship among species. Overall, the current study positively contributed to the molecular mechanism of biological adaptation and the evolutionary relationship of MCB.

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Acknowledgements

This study was supported by the National Key R&D Program of China (2019YFC1711000; 2019YFC1711008), National Natural Science Foundation of China (82260749; 82260750), Scientific Research Funding Project of Guangxi Botanical Garden of Medicinal Plants (GuiYaoJi202011), Guangxi Innovation-Driven Development Project (GuiKe AA18242040), Natural Science Foundation of Guangxi (2020JJA140312), Research and Promotion of China-ASEAN Medicinal Plants Conservation (KY201904001), “Guangxi Bagui Scholars” and Research Innovation Team Project (GuiYaoChuang2019005), and Fund Projects of the Central Government in Guidance of Local Science and Technology Development (2022ZYZX1100).

Funding

National Key R&D Program of China, 2019YFC1711000, Jianhua Miao, 2019YFC1711008, Jianhua Miao, National Natural Science Foundation of China, 82260749, Fan Wei, 82260750, Danfeng Tang, Scientific Research Funding Project of Guangxi Botanical Garden of Medicinal Plants, GuiYaoJi202011, Danfeng Tang, Guangxi Innovation-Driven Development Project, GuiKe AA18242040, Jianhua Miao, Natural Science Foundation of Guangxi, 2020JJA140312, Fan Wei, Research and Promotion of China-ASEAN Medicinal Plants Conservation, KY201904001, Jianhua Miao, “Guangxi Bagui Scholars” and Research Innovation Team Project, GuiYaoChuang2019005, Kunhua Wei, Fund Projects of the Central Government in Guidance of Local Science and Technology Development, 2022ZYZX1100, Danfeng Tang.

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Author notes

  1. Danfeng Tang and Fan Wei contributed equally to this study.

Authors and Affiliations

  1. Guangxi Key Laboratory of Medicinal Resources Protection and Genetic Improvement, Guangxi Botanical Garden of Medicinal Plants, Nanning, China

    Danfeng Tang, Fan Wei, Changqian Quan, Yuan Huang, Kunhua Wei & Jianhua Miao

  2. Guangxi Engineering Research Center of TCM Resource Intelligent Creation, Guangxi Botanical Garden of Medicinal Plants, Nanning, China

    Danfeng Tang, Fan Wei, Changqian Quan, Yuan Huang, Kunhua Wei & Jianhua Miao

  3. Guangxi Medical University, Nanning, China

    Suhua Huang

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  1. Danfeng Tang
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Correspondence to Danfeng Tang or Jianhua Miao.

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11738_2022_3453_MOESM1_ESM.xlsx

Table S1 Gene information used in this study. Table S2 Species information used in this study. Table S3 Statistics of nucleotide composition of all the 28 mitochondrial genes studied (XLSX 23 KB)

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Tang, D., Wei, F., Quan, C. et al. Codon usage bias and evolution analysis in the mitochondrial genome of Mesona chinensis Benth. Acta Physiol Plant 44, 118 (2022). https://doi.org/10.1007/s11738-022-03453-z

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