RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans.
Ruth Barral-ArcaAlberto Gómez-CarballaMiriam Cebey-LópezMaría José Currás-TualaSara PischeddaSandra Viz-LasherasXabier BelloFederico M TorresAntonio SalasPublished in: International journal of molecular sciences (2020)
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.
Keyphrases
- single cell
- rna seq
- long non coding rna
- gene expression
- endothelial cells
- poor prognosis
- high throughput
- sars cov
- network analysis
- genome wide identification
- genome wide analysis
- dna methylation
- electronic health record
- climate change
- healthcare
- induced apoptosis
- stem cells
- cell proliferation
- small molecule
- oxidative stress
- transcription factor
- high glucose
- extracellular matrix
- cell therapy
- induced pluripotent stem cells