Department of Genetics and Animal Breeding, Faculty of Agriculture, Shahrekord University, Shahrekord 88186-34141, Iran.
Agricultural Biotechnology Research Institute of Iran (ABRII), Center of Iran, Isfahan 14968-13151, Iran.
Genes (Basel). 2022 Feb 26;13(3):435. doi: 10.3390/genes13030435.
The current bioinformatics study was undertaken to analyze the transcriptome of chicken () after influenza A virus challenge. A meta-analysis was carried out to explore the host expression response after challenge with lowly pathogenic avian influenza (LPAI) (H1N1, H2N3, H5N2, H5N3 and H9N2) and with highly pathogenic avian influenza (HPAI) H5N1 strains. To do so, ten microarray datasets obtained from the Gene Expression Omnibus (GEO) database were normalized and meta-analyzed for the LPAI and HPAI host response individually. Different undirected networks were constructed and their metrics determined e.g., degree centrality, closeness centrality, harmonic centrality, subgraph centrality and eigenvector centrality. The results showed that, based on criteria of centrality, the , , , , and genes were the most significant during HPAI challenge, with , , , and having the lowest values. However, for LPAI challenge, , , , , , and genes had the largest values for aforementioned criteria, with , , , , and genes having the lowest values. The results of this study can be used as a basis for future development of treatments/preventions of the effects of avian influenza in chicken.
本生物信息学研究旨在分析禽流感病毒(AIV)感染后鸡的转录组。通过元分析,探讨了低致病性禽流感(LPAI)(H1N1、H2N3、H5N2、H5N3 和 H9N2)和高致病性禽流感(HPAI)H5N1 株感染后宿主的表达反应。为此,从基因表达综合数据库(GEO)中获取了十个微阵列数据集,分别对 LPAI 和 HPAI 宿主反应进行了归一化和元分析。构建了不同的无向网络,并确定了它们的度量标准,例如度中心性、接近中心性、调和中心性、子图中心性和特征向量中心性。结果表明,根据中心性标准,在 HPAI 挑战中, 、 、 、 、 和 基因是最显著的,而 、 、 、 基因具有最低的值。然而,对于 LPAI 挑战, 、 、 、 、 、 和 基因在上述标准中具有最大的值,而 、 、 、 、 基因具有最低的值。本研究的结果可作为未来防治禽流感对鸡影响的治疗方法/预防措施的基础。