Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Pirbaluty, Azadeh Moradi, Mehrban, Hossein, Kadkhodaei, Saeid, Ravash, Rudabeh, Oryan, Ahmad, Ghaderi-Zefrehei, Mostafa, Smith, Jacqueline
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8953847/
https://www.ncbi.nlm.nih.gov/pubmed/35327988
http://dx.doi.org/10.3390/genes13030435
_version_ 1784675949920387072
author Pirbaluty, Azadeh Moradi
Mehrban, Hossein
Kadkhodaei, Saeid
Ravash, Rudabeh
Oryan, Ahmad
Ghaderi-Zefrehei, Mostafa
Smith, Jacqueline
author_facet Pirbaluty, Azadeh Moradi
Mehrban, Hossein
Kadkhodaei, Saeid
Ravash, Rudabeh
Oryan, Ahmad
Ghaderi-Zefrehei, Mostafa
Smith, Jacqueline
author_sort Pirbaluty, Azadeh Moradi
collection PubMed
description 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.
format Online
Article
Text
id pubmed-8953847
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-89538472022-03-26 Network Meta-Analysis of Chicken Microarray Data following Avian Influenza Challenge—A Comparison of Highly and Lowly Pathogenic Strains Pirbaluty, Azadeh Moradi Mehrban, Hossein Kadkhodaei, Saeid Ravash, Rudabeh Oryan, Ahmad Ghaderi-Zefrehei, Mostafa Smith, Jacqueline Genes (Basel) Article 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. MDPI 2022-02-26 /pmc/articles/PMC8953847/ /pubmed/35327988 http://dx.doi.org/10.3390/genes13030435 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pirbaluty, Azadeh Moradi
Mehrban, Hossein
Kadkhodaei, Saeid
Ravash, Rudabeh
Oryan, Ahmad
Ghaderi-Zefrehei, Mostafa
Smith, Jacqueline
Network Meta-Analysis of Chicken Microarray Data following Avian Influenza Challenge—A Comparison of Highly and Lowly Pathogenic Strains
title Network Meta-Analysis of Chicken Microarray Data following Avian Influenza Challenge—A Comparison of Highly and Lowly Pathogenic Strains
title_full Network Meta-Analysis of Chicken Microarray Data following Avian Influenza Challenge—A Comparison of Highly and Lowly Pathogenic Strains
title_fullStr Network Meta-Analysis of Chicken Microarray Data following Avian Influenza Challenge—A Comparison of Highly and Lowly Pathogenic Strains
title_full_unstemmed Network Meta-Analysis of Chicken Microarray Data following Avian Influenza Challenge—A Comparison of Highly and Lowly Pathogenic Strains
title_short Network Meta-Analysis of Chicken Microarray Data following Avian Influenza Challenge—A Comparison of Highly and Lowly Pathogenic Strains
title_sort network meta-analysis of chicken microarray data following avian influenza challenge—a comparison of highly and lowly pathogenic strains
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8953847/
https://www.ncbi.nlm.nih.gov/pubmed/35327988
http://dx.doi.org/10.3390/genes13030435
work_keys_str_mv AT pirbalutyazadehmoradi networkmetaanalysisofchickenmicroarraydatafollowingavianinfluenzachallengeacomparisonofhighlyandlowlypathogenicstrains
AT mehrbanhossein networkmetaanalysisofchickenmicroarraydatafollowingavianinfluenzachallengeacomparisonofhighlyandlowlypathogenicstrains
AT kadkhodaeisaeid networkmetaanalysisofchickenmicroarraydatafollowingavianinfluenzachallengeacomparisonofhighlyandlowlypathogenicstrains
AT ravashrudabeh networkmetaanalysisofchickenmicroarraydatafollowingavianinfluenzachallengeacomparisonofhighlyandlowlypathogenicstrains
AT oryanahmad networkmetaanalysisofchickenmicroarraydatafollowingavianinfluenzachallengeacomparisonofhighlyandlowlypathogenicstrains
AT ghaderizefreheimostafa networkmetaanalysisofchickenmicroarraydatafollowingavianinfluenzachallengeacomparisonofhighlyandlowlypathogenicstrains
AT smithjacqueline networkmetaanalysisofchickenmicroarraydatafollowingavianinfluenzachallengeacomparisonofhighlyandlowlypathogenicstrains