@article {762, title = {Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival.}, journal = {Viruses}, volume = {14}, year = {2022}, month = {2022 Aug 27}, abstract = {

OBJECTIVES: More than two years into the COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations for which the impact on COVID-19 severity and patient survival is uncertain.

METHODS: A total of 764 SARS-CoV-2 genomes, sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30 April 2021, along with their clinical data, were used for survival analysis.

RESULTS: A significant association of B.1.1.7, the alpha lineage, with patient mortality (log hazard ratio (LHR) = 0.51, C.I. = [0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome revealed 27 of them were significantly associated with higher mortality of patients. Most of these mutations were located in the genes coding for the S, ORF8, and N proteins.

CONCLUSIONS: This study illustrates how a combination of genomic and clinical data can provide solid evidence for the impact of viral lineage on patient survival.

}, keywords = {COVID-19, Genome, Viral, Humans, mutation, Pandemics, Phylogeny, SARS-CoV-2}, issn = {1999-4915}, doi = {10.3390/v14091893}, author = {Loucera, Carlos and Perez-Florido, Javier and Casimiro-Soriguer, Carlos S and Ortuno, Francisco M and Carmona, Rosario and Bostelmann, Gerrit and Mart{\'\i}nez-Gonz{\'a}lez, L Javier and Mu{\~n}oyerro-Mu{\~n}iz, Dolores and Villegas, Rom{\'a}n and Rodr{\'\i}guez-Ba{\~n}o, Jes{\'u}s and Romero-G{\'o}mez, Manuel and Lorusso, Nicola and Garcia-Le{\'o}n, Javier and Navarro-Mar{\'\i}, Jose M and Camacho-Martinez, Pedro and Merino-Diaz, Laura and Salazar, Adolfo de and Vi{\~n}uela, Laura and Lepe, Jose A and Garc{\'\i}a, Federico and Dopazo, Joaquin} } @article {712, title = {A versatile workflow to integrate RNA-seq genomic and transcriptomic data into mechanistic models of signaling pathways.}, journal = {PLoS Comput Biol}, volume = {17}, year = {2021}, month = {2021 02}, pages = {e1008748}, abstract = {

MIGNON is a workflow for the analysis of RNA-Seq experiments, which not only efficiently manages the estimation of gene expression levels from raw sequencing reads, but also calls genomic variants present in the transcripts analyzed. Moreover, this is the first workflow that provides a framework for the integration of transcriptomic and genomic data based on a mechanistic model of signaling pathway activities that allows a detailed biological interpretation of the results, including a comprehensive functional profiling of cell activity. MIGNON covers the whole process, from reads to signaling circuit activity estimations, using state-of-the-art tools, it is easy to use and it is deployable in different computational environments, allowing an optimized use of the resources available.

}, keywords = {Algorithms, Cell Line, Tumor, Computational Biology, Databases, Factual, Gene Expression Profiling, Genomics, High-Throughput Nucleotide Sequencing, Humans, Models, Theoretical, mutation, RNA-seq, Signal Transduction, Software, Transcriptome, whole exome sequencing, Workflow}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1008748}, author = {Garrido-Rodriguez, Mart{\'\i}n and L{\'o}pez-L{\'o}pez, Daniel and Ortuno, Francisco M and Pe{\~n}a-Chilet, Maria and Mu{\~n}oz, Eduardo and Calzado, Marco A and Dopazo, Joaquin} }