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Article

A Meta-Analysis of Multiple Whole Blood Gene Expression Data Unveils a Diagnostic Host-Response Transcript Signature for Respiratory Syncytial Virus

1
Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigaciones Sanitarias (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), 15706 Galicia, Spain
2
Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, 15706 Galicia, Spain
3
Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, 15706 Santiago de Compostela, Spain
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2020, 21(5), 1831; https://doi.org/10.3390/ijms21051831
Received: 10 February 2020 / Revised: 26 February 2020 / Accepted: 3 March 2020 / Published: 6 March 2020
(This article belongs to the Special Issue Host Infectomics in the Childhood)
Respiratory syncytial virus (RSV) is one of the major causes of acute lower respiratory tract infection worldwide. The absence of a commercial vaccine and the limited success of current therapeutic strategies against RSV make further research necessary. We used a multi-cohort analysis approach to investigate host transcriptomic biomarkers and shed further light on the molecular mechanism underlying RSV-host interactions. We meta-analyzed seven transcriptome microarray studies from the public Gene Expression Omnibus (GEO) repository containing a total of 922 samples, including RSV, healthy controls, coronaviruses, enteroviruses, influenzas, rhinoviruses, and coinfections, from both adult and pediatric patients. We identified > 1500 genes differentially expressed when comparing the transcriptomes of RSV-infected patients against healthy controls. Functional enrichment analysis showed several pathways significantly altered, including immunologic response mediated by RSV infection, pattern recognition receptors, cell cycle, and olfactory signaling. In addition, we identified a minimal 17-transcript host signature specific for RSV infection by comparing transcriptomic profiles against other respiratory viruses. These multi-genic signatures might help to investigate future drug targets against RSV infection. View Full-Text
Keywords: meta-analysis; RNA; transcriptomic; RSV; respiratory syncytial virus; array meta-analysis; RNA; transcriptomic; RSV; respiratory syncytial virus; array
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MDPI and ACS Style

Barral-Arca, R.; Gómez-Carballa, A.; Cebey-López, M.; Bello, X.; Martinón-Torres, F.; Salas, A. A Meta-Analysis of Multiple Whole Blood Gene Expression Data Unveils a Diagnostic Host-Response Transcript Signature for Respiratory Syncytial Virus. Int. J. Mol. Sci. 2020, 21, 1831. https://doi.org/10.3390/ijms21051831

AMA Style

Barral-Arca R, Gómez-Carballa A, Cebey-López M, Bello X, Martinón-Torres F, Salas A. A Meta-Analysis of Multiple Whole Blood Gene Expression Data Unveils a Diagnostic Host-Response Transcript Signature for Respiratory Syncytial Virus. International Journal of Molecular Sciences. 2020; 21(5):1831. https://doi.org/10.3390/ijms21051831

Chicago/Turabian Style

Barral-Arca, Ruth; Gómez-Carballa, Alberto; Cebey-López, Miriam; Bello, Xabier; Martinón-Torres, Federico; Salas, Antonio. 2020. "A Meta-Analysis of Multiple Whole Blood Gene Expression Data Unveils a Diagnostic Host-Response Transcript Signature for Respiratory Syncytial Virus" Int. J. Mol. Sci. 21, no. 5: 1831. https://doi.org/10.3390/ijms21051831

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