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Genes (Basel) . Network Meta-Analysis of Chicken Microarray Data following Avian Influenza Challenge-A Comparison of Highly and Lowly Pathogenic Str

tetano

Editor, Senior Moderator
Genes (Basel)


. 2022 Feb 26;13(3):435.
doi: 10.3390/genes13030435.
Network Meta-Analysis of Chicken Microarray Data following Avian Influenza Challenge-A Comparison of Highly and Lowly Pathogenic Strains


Azadeh Moradi Pirbaluty[SUP] 1 [/SUP], Hossein Mehrban[SUP] 1 [/SUP], Saeid Kadkhodaei[SUP] 2 [/SUP], Rudabeh Ravash[SUP] 3 [/SUP], Ahmad Oryan[SUP] 4 [/SUP], Mostafa Ghaderi-Zefrehei[SUP] 5 [/SUP], Jacqueline Smith[SUP] 6 [/SUP]



Affiliations

Abstract

The current bioinformatics study was undertaken to analyze the transcriptome of chicken (Gallus gallus) 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 CMTR1, EPSTI1, RNF213, HERC4L, IFIT5 and LY96 genes were the most significant during HPAI challenge, with PARD6G, HMG20A, PEX14, RNF151 and TLK1L having the lowest values. However, for LPAI challenge, ZDHHC9, IMMP2L, COX7C, RBM18, DCTN3, and NDUFB1 genes had the largest values for aforementioned criteria, with GTF3C5, DROSHA, ATRX, RFWD2, MED23 and SEC23B 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.

Keywords: HPAI; LPAI; Python; chicken; influenza; meta-analysis; microarray; network; transcriptome.
 
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