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RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans

There is a growing interest in unraveling gene expression mechanisms leading to viral host invasion and infection progression. Current findings reveal that long non-coding RNAs (lncRNAs) are implicated in the regulation of the immune system by influencing gene expression through a wide range of mech...

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Autores principales: Barral-Arca, Ruth, Gómez-Carballa, Alberto, Cebey-López, Miriam, Currás-Tuala, María José, Pischedda, Sara, Viz-Lasheras, Sandra, Bello, Xabier, Martinón-Torres, Federico, Salas, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215422/
https://www.ncbi.nlm.nih.gov/pubmed/32326627
http://dx.doi.org/10.3390/ijms21082748
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author Barral-Arca, Ruth
Gómez-Carballa, Alberto
Cebey-López, Miriam
Currás-Tuala, María José
Pischedda, Sara
Viz-Lasheras, Sandra
Bello, Xabier
Martinón-Torres, Federico
Salas, Antonio
author_facet Barral-Arca, Ruth
Gómez-Carballa, Alberto
Cebey-López, Miriam
Currás-Tuala, María José
Pischedda, Sara
Viz-Lasheras, Sandra
Bello, Xabier
Martinón-Torres, Federico
Salas, Antonio
author_sort Barral-Arca, Ruth
collection PubMed
description There is a growing interest in unraveling gene expression mechanisms leading to viral host invasion and infection progression. Current findings reveal that long non-coding RNAs (lncRNAs) are implicated in the regulation of the immune system by influencing gene expression through a wide range of mechanisms. By mining whole-transcriptome shotgun sequencing (RNA-seq) data using machine learning approaches, we detected two lncRNAs (ENSG00000254680 and ENSG00000273149) that are downregulated in a wide range of viral infections and different cell types, including blood monocluclear cells, umbilical vein endothelial cells, and dermal fibroblasts. The efficiency of these two lncRNAs was positively validated in different viral phenotypic scenarios. These two lncRNAs showed a strong downregulation in virus-infected patients when compared to healthy control transcriptomes, indicating that these biomarkers are promising targets for infection diagnosis. To the best of our knowledge, this is the very first study using host lncRNAs biomarkers for the diagnosis of human viral infections.
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spelling pubmed-72154222020-05-18 RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans Barral-Arca, Ruth Gómez-Carballa, Alberto Cebey-López, Miriam Currás-Tuala, María José Pischedda, Sara Viz-Lasheras, Sandra Bello, Xabier Martinón-Torres, Federico Salas, Antonio Int J Mol Sci Article There is a growing interest in unraveling gene expression mechanisms leading to viral host invasion and infection progression. Current findings reveal that long non-coding RNAs (lncRNAs) are implicated in the regulation of the immune system by influencing gene expression through a wide range of mechanisms. By mining whole-transcriptome shotgun sequencing (RNA-seq) data using machine learning approaches, we detected two lncRNAs (ENSG00000254680 and ENSG00000273149) that are downregulated in a wide range of viral infections and different cell types, including blood monocluclear cells, umbilical vein endothelial cells, and dermal fibroblasts. The efficiency of these two lncRNAs was positively validated in different viral phenotypic scenarios. These two lncRNAs showed a strong downregulation in virus-infected patients when compared to healthy control transcriptomes, indicating that these biomarkers are promising targets for infection diagnosis. To the best of our knowledge, this is the very first study using host lncRNAs biomarkers for the diagnosis of human viral infections. MDPI 2020-04-15 /pmc/articles/PMC7215422/ /pubmed/32326627 http://dx.doi.org/10.3390/ijms21082748 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Barral-Arca, Ruth
Gómez-Carballa, Alberto
Cebey-López, Miriam
Currás-Tuala, María José
Pischedda, Sara
Viz-Lasheras, Sandra
Bello, Xabier
Martinón-Torres, Federico
Salas, Antonio
RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans
title RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans
title_full RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans
title_fullStr RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans
title_full_unstemmed RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans
title_short RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans
title_sort rna-seq data-mining allows the discovery of two long non-coding rna biomarkers of viral infection in humans
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215422/
https://www.ncbi.nlm.nih.gov/pubmed/32326627
http://dx.doi.org/10.3390/ijms21082748
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