人、禽、猪甲型流感病毒血凝素蛋白的基因组特征和关联分类

F. F. Sherif, Mahmoud El Hefnawi, Y. Kadah
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引用次数: 6

摘要

人类流感的全球暴发是由于甲型流感病毒具有人类没有免疫力的新型血凝素(HA)分子。因此,了解血凝素基因的起源和进化就显得尤为重要。本研究鉴定了HA蛋白在不同宿主中的基因组特征,并对宿主分型进行了关联分类。因此,我们进行了多序列比对,并使用VESPA检测了人类、鸟类和猪群序列之间最具统计学意义的差异,然后应用类关联规则挖掘来识别宿主物种特有的氨基酸保守位置,称为特征。我们采用严格的阈值,只选择在每个流感病毒宿主分离株中随时间高度保存的标记。此外,两个样本序列标识服务器被用来识别和确认主机之间的显著差异。通过扫描来自人类、猪和禽流感A型病毒的1500个HA序列,已经创建了宿主特异性签名。560个氨基酸残基的9、31、11、6、22和31个最具信息量的位置分别在禽与人、人与禽、人与猪、猪与人、禽与猪和猪与禽之间产生显著差异。438K、458N和286V位点分别与禽、人、猪相关,支持度和置信度分别为90.7%和79.5%,82.8%和92.9%,51.4%和98%。宿主特异性类关联规则有助于预测预后生物标志物,提高预后的准确性。
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Genomic signatures and associative classification of the Hemagglutinin protein for Human versus Avian versus Swine influenza A viruses
Global outbreaks of human influenza arise from influenza A viruses with novel Hemagglutinin (HA) molecules to which humans have no immunity. So understanding of the origin and evolution of HA genes is of particular importance. Here, genomic signatures of the HA protein in different hosts was identified and associative classification for host-typing was conducted. We therefore conducted multiple-sequence alignment and detecting the most statistically significant differences between human, avian and swine group of sequences using VESPA, then applying class associative rule mining to identify amino acid'conserving positions that are specific to host species, called signatures. We applied strict thresholds to select only markers which are highly preserved in each influenza virus host isolates over time. Also, the two Sample sequence logo server was used to identify and confirm significant variations between the hosts. Host-specific signatures have created from scanning 1500 sequences of HA from human, swine and avian influenza A viruses. A total of 9, 31, 11, 6, 22, and 31 most informative positions of 560 amino acid residues yielded significant differences between Avian vs. Human, Human vs. Avian, Human vs. Swine, Swine vs. Human, Avian vs. Swine, and Swine vs. Avian respectively. Positions 438K, 458N and 286V were associated with avian, human and swine respectively, with support and confidence of (90.7% and 79.5%), (82.8% and 92.9%) and (51.4% and 98%) respectively. Host-specific class association rules aid in the prediction of prognostic biomarkers and improve the accuracy of prognosis.
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