轮状病毒蛋白编码基因共进化分析：一种生物信息学和统计学方法。
Coding-Gene Coevolution Analysis of Rotavirus Proteins: A Bioinformatics and Statistical Approach.
机构信息
Laboratory of Transmissible Diseases and Biological Active Substances LR99ES27, Faculty of Pharmacy, University of Monastir, Rue Ibn Sina, Monastir 5000, Tunisia.
High Institute of Biotechnology of Sidi Thabet, Department of Biotechnology, University Manouba, BP-66, Ariana-Tunis 2020, Tunisia.
出版信息
Genes (Basel). 2019 Dec 24;11(1):28. doi: 10.3390/genes11010028.
Rotavirus remains a major cause of diarrhea in infants and young children worldwide. The permanent emergence of new genotypes puts the potential effectiveness of vaccines under serious question. The distribution of unusual genotypes subject to viral fitness is influenced by interactions among viral proteins. The present work aimed at analyzing the genetic constellation and the coevolution of rotavirus coding genes for the available rotavirus genotypes. Seventy-two full genome sequences of different genetic constellations were analyzed using a genetic algorithm. The results revealed an extensive genome-wide covariance network among the 12 viral proteins. Altogether, the emergence of new genotypes represents a challenge to the outcome and success of vaccination and the coevolutionary analysis of rotavirus proteins may boost efforts to better understand the interaction networks of proteins during viral replication/transcription.
轮状病毒仍然是全球婴幼儿腹泻的主要原因。新基因型的不断出现使疫苗的潜在有效性受到严重质疑。病毒蛋白之间的相互作用影响了不同基因型的罕见基因型的分布。本研究旨在分析现有轮状病毒基因型的轮状病毒编码基因的遗传组合和协同进化。使用遗传算法对 72 种不同遗传组合的全基因组序列进行了分析。结果显示，12 种病毒蛋白之间存在广泛的全基因组协方差网络。总的来说，新基因型的出现对疫苗的效果和成功构成了挑战，而轮状病毒蛋白的协同进化分析可能有助于更好地理解病毒复制/转录过程中蛋白质相互作用网络。
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