A detailed analysis of synonymous codon usage in human bocavirus

被引:6
|
作者
Hussain, Snawar [1 ]
Rasool, Sahibzada Tasleem [1 ]
Asif, Afzal Haq [1 ]
机构
[1] King Faisal Univ, Coll Clin Pharm, Dept Biomed Sci, POB 400, Al Hasa 31982, Saudi Arabia
关键词
NUCLEOTIDE COMPOSITION; PROTEIN EXPRESSION; MUTATION PRESSURE; GENE LENGTH; BIAS; SELECTION; GENOME; EVOLUTION; VIRUS; CPG;
D O I
10.1007/s00705-018-4063-8
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Human bocavirus (HBoV) is a recently discovered parvovirus associated with respiratory and gastroenteric infections in children. To date, four distinct subtypes have been identified worldwide. HBoV1 is the most frequently detected bocavirus in clinical samples derived from the respiratory tract. HBoV has a single-stranded DNA genome, which encodes two nonstructural proteins, NS1 and NP1, and two structural proteins, VP1 and VP2. Despite a large number of available HBoV sequences, the molecular evolution of this virus remains enigmatic. Here, we applied bioinformatic methods to measure the codon usage bias in 156 HBoV genomes and analyzed the factors responsible for preferential use of various synonymous codons. The effective number of codons (ENC) indicates a highly conserved, gene-specific codon usage bias in the HBoV genome. The structural genes exhibit a higher degree of codon usage bias than the non-structural genes. Natural selection emerged as dominant factor influencing the codon usage bias in the HBoV genome. Other factors that influence the codon usage include mutational pressure, gene length, protein properties, and the relative abundance of dinucleotides. The results presented in this study provide important insight into the molecular evolution of HBoV and may serve as a primer for HBoV gene expression studies and development of safe and effective vaccines to prevent infection.
引用
收藏
页码:335 / 347
页数:13
相关论文
共 50 条
  • [31] CHARMING: Harmonizing synonymous codon usage to replicate a desired codon usage pattern
    Wright, Gabriel
    Rodriguez, Anabel
    Li, Jun
    Milenkovic, Tijana
    Emrich, Scott J.
    Clark, Patricia L.
    PROTEIN SCIENCE, 2022, 31 (01) : 221 - 231
  • [32] A detailed analysis of codon usage patterns and influencing factors in Zika virus
    Singh, Niraj K.
    Tyagi, Anuj
    ARCHIVES OF VIROLOGY, 2017, 162 (07) : 1963 - 1973
  • [33] Analysis of Synonymous Codon Usage in the UL26.5 Gene of Duck Enteritis Virus
    Zhang, Yao
    Cheng, Anchun
    Wang, Mingshu
    Zhu, Dekang
    Jia, Renyong
    Liu, Fei
    Chen, Xiaoyue
    PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS, VOLS 1-4, 2009, : 1829 - +
  • [34] Analysis of synonymous codon usage patterns in sixty-four different bivalve species
    Gerdol, Marco
    De Moro, Gianluca
    Venier, Paola
    Pallavicini, Alberto
    PEERJ, 2015, 3
  • [35] Synonymous codon usage pattern in glycoprotein gene of rabies virus
    Morla, Sudhir
    Makhija, Aditi
    Kumar, Sachin
    GENE, 2016, 584 (01) : 1 - 6
  • [36] Genome-wide analysis of the synonymous codon usage patterns in apple
    Li Ning
    Sun Mei-hong
    Jiang Ze-sheng
    Shu Huai-rui
    Zhang Shi-zhong
    JOURNAL OF INTEGRATIVE AGRICULTURE, 2016, 15 (05) : 983 - 991
  • [37] System analysis of synonymous codon usage biases in archaeal virus genomes
    Li, Sen
    Yang, Jie
    JOURNAL OF THEORETICAL BIOLOGY, 2014, 355 : 128 - 139
  • [38] Synonymous codon usage and context analysis of genes associated with pancreatic cancer
    Chakraborty, Supriyo
    Paul, Sunanda
    Nath, Durbba
    Choudhury, Yashmin
    Ahn, Yeongseon
    Cho, Yoon Shin
    Uddin, Arif
    MUTATION RESEARCH-FUNDAMENTAL AND MOLECULAR MECHANISMS OF MUTAGENESIS, 2020, 821
  • [39] Analysis of synonymous codon usage patterns in the edible fungus Volvariella volvacea
    Jiang, Wei
    Lv, Beibei
    Wu, Xiao
    Wang, Jinbin
    Wu, Guogan
    Shi, Chunhui
    Tang, Xueming
    BIOTECHNOLOGY AND APPLIED BIOCHEMISTRY, 2017, 64 (02) : 218 - 224
  • [40] Analysis of synonymous codon usage bias in human monocytes, B, and T lymphocytes based on transcriptome data
    Ruzman, Muhammad Adib
    Ripen, Adiratna Mat
    Mirsafian, Hoda
    Ridzwan, Nor Farrah Wahidah
    Merican, Amir Feisal
    Mohamad, Saharuddin Bin
    GENE REPORTS, 2021, 23