RT Journal Article
T1 Serial co-expression analysis of host factors from SARS-CoV viruses highly converges with former high-throughput screenings and proposes key regulators
A1 Pérez-Pulido, Antonio J.
A1 Asensio-Cortés, G
A1 Brokate-LLanos, Ana Mª
A1 Brea-Calvo, Gloria
A1 Rodríguez-Griñolo, Rosario
A1 Garzón, Andrés
A1 Muñoz, M J
K1 SARS-CoV-2
K1 SARS-CoV
K1 coronavirus
K1 reverse engineering
K1 co-expressed genes
K1 co-regulated genes
AB The current genomics era is bringing an unprecedented growth in the amount of gene expression data, only comparable to the exponential growth of sequences in databases during the last decades. This data allow the design of secondary analyses that take advantage of this information to create new knowledge. One of these feasible analyses is the evaluation of the expression level for a gene through a series of different conditions or cell types. Based on this idea, we have developed Automatic and Serial Analysis of CO-expression, which performs expression profiles for a given gene along hundreds of heterogeneous and normalized transcriptomics experiments and discover other genes that show either a similar or an inverse behavior. It might help to discover co-regulated genes, and common transcriptional regulators in any biological model. The present severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is an opportunity to test this novel approach due to the wealth of data that are being generated, which could be used for validating results. Thus, we have identified 35 host factors in the literature putatively involved in the infectious cycle of SARS-CoV viruses and searched for genes tightly co-expressed with them. We have found 1899 co-expressed genes whose assigned functions are strongly related to viral cycles. Moreover, this set of genes heavily overlaps with those identified by former laboratory high-throughput screenings (with P-value near 0). Our results reveal a series of common regulators, involved in immune and inflammatory responses that might be key virus targets to induce the coordinated expression of SARS-CoV-2 host factors.
PB Oxford University Press
YR 2021
FD 2021-01-18
LK https://hdl.handle.net/10433/19478
UL https://hdl.handle.net/10433/19478
LA en
NO Briefings in Bioinformatics, Volume 22, Issue 2, March 2021, Pages 1038–1052, https://doi.org/10.1093/bib/bbaa419
NO Departamento de Economñia, Métodos Cuantitativos e Hª Económica, Universidad Pablo de Olavide
NO Centro Andaluz de Biología del Desarrollo (CABD)
DS RIO
RD Apr 23, 2026