Evaluation of the host transcriptional response to human cytomegalovirus infection.

Détails

ID Serval
serval:BIB_F5CDE9E0004F
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Evaluation of the host transcriptional response to human cytomegalovirus infection.
Périodique
Physiological genomics
Auteur⸱e⸱s
Challacombe J.F., Rechtsteiner A., Gottardo R., Rocha L.M., Browne E.P., Shenk T., Altherr M.R., Brettin T.S.
ISSN
1531-2267 (Electronic)
ISSN-L
1094-8341
Statut éditorial
Publié
Date de publication
17/06/2004
Peer-reviewed
Oui
Volume
18
Numéro
1
Pages
51-62
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, U.S. Gov't, P.H.S.
Publication Status: ppublish
Résumé
Gene expression data from human cytomegalovirus (HCMV)-infected cells were analyzed using DNA-Chip Analyzer (dChip) followed by singular value decomposition (SVD) and compared with a previous analysis of the same data that employed GeneChip software and a fold change filtering approach. dChip and SVD analysis revealed two clusters of coexpressed human genes responding differently to HCMV infection: one containing some genes identified previously, and another that was largely unique to this analysis. Annotating these genes, we identified several functional categories important to host cell responses to HCMV infection. These categories included genes involved in transcriptional regulation, oncogenesis, and cell cycle regulation, which were more prevalent in cluster 1, and genes involved in immune system regulation, signal transduction, and cell adhesion, which were more prevalent in cluster 2. Within these categories, we found genes involved in the host response to HCMV infection (mainly in cluster 1), as well as genes targeted by HCMV's immune evasion strategies (mainly in cluster 2). As the second group of genes identified by the dChip and SVD approach was statistically and biologically significant, our results point out the advantages of using different methods to analyze gene expression data.
Mots-clé
Cytomegalovirus Infections/genetics, Data Interpretation, Statistical, Gene Expression Profiling/methods, Gene Expression Regulation, Viral, Humans, Multigene Family, Oligonucleotide Array Sequence Analysis, Transcription, Genetic
Pubmed
Web of science
Création de la notice
28/02/2022 11:45
Dernière modification de la notice
23/03/2024 7:24
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