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...
Autores principales: | , , , , , , |
---|---|
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 |