Network Meta-Analysis of Chicken Microarray Data following Avian Influenza Challenge-A Comparison of Highly and Lowly Pathogenic Strains.

Azadeh Moradi Pirbaluty,Saeid Kadkhodaei,Jacqueline Smith,Mostafa Ghaderi-Zefrehei,Hossein Mehrban,Ahmad Oryan,Rudabeh Ravash

doi:10.3390/genes13030435

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.

Highlights

The purpose of this study was to identify the most important genes involved in the Theresponse, purpose based of thison study was to identify most genes Meta-analysis involved in the avian flu the location of thesethe genes in important a gene network
When we look at the up-regulated highly pathogenic avian influenza (HPAI) differentially expressed genes (DEGs) on the other hand, we see that several are involved in the innate immune response, with
We have used network analysis methods to predict hub gene associations from a collection of microarray datasets known to be related to the avian response to influenza infection, and created gene-interaction networks by correlation amongst differentially regulated genes

Summary

Introduction

Global monitoring of influenza is crucial for improvements in disease management, rapid intervention and decreasing the potential impact of an influenza pandemic. Influenza (AI) is caused by three types of viruses: types A, B and C. Influenza A viruses (IAVs) are potentially zoonotic viruses that can cause infection in birds and a small number of mammals [1]. Influenza A virus is the only species of the alpha influenza virus genus in the Orthomyxoviridae family. Most human influenza pandemics of the 20th century were caused by IAVs that originated, either wholly or in part, from avian influenza A viruses [2]. The virus can be transmitted from wild birds to native poultry, which provides

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