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10.1038/s42003-021-02095-0 http://scihub22266oqcxt.onion/10.1038/s42003-021-02095-0 34002013!8128904!34002013     free     free     free Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Commun+Biol 2021 ; 4 (1): 590 Nephropedia Template TP {{tp|p=34002013|t=2021. Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis |pdf=|usr=}}{{34002013}} gab.com Text Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis JO: Commun Biol http://www.kidney.de/pget.php?&tw=1&pmid=34002013 #FOAvip The novel betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a worldwide pandemic (COVID-19) after emerging in Wuhan, China. Here we analyzed public host and viral RNA sequencing data to better understand how SARS-CoV-2 interacts with human respiratory cells. We identified genes, isoforms and transposable element families that are specifically altered in SARS-CoV-2-infected respiratory cells. Well-known immunoregulatory genes including CSF2, IL32, IL-6 and SERPINA3 were differentially expressed, while immunoregulatory transposable element families were upregulated. We predicted conserved interactions between the SARS-CoV-2 genome and human RNA-binding proteins such as the heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) and eukaryotic initiation factor 4 (eIF4b). We also identified a viral sequence variant with a statistically significant skew associated with age of infection, that may contribute to intracellular host-pathogen interactions. These findings can help identify host mechanisms that can be targeted by prophylactics and/or therapeutics to reduce the severity of COVID-19. Twit Text FOAVip Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis ????Commun Biol http://www.kidney.de/pget.php?&tw=1&pmid=34002013 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34002013 #FOAvip English Wikipedia <ref>{{Cite pmid|34002013}}</ref> Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis #MMPMID34002013 Ferrarini MG; Lal A; Rebollo R; Gruber AJ; Guarracino A; Gonzalez IM; Floyd T; de Oliveira DS; Shanklin J; Beausoleil E; Pusa T; Pickett BE; Aguiar-Pulido V Commun Biol 2021[May]; 4 (1): 590 PMID34002013show ga The novel betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a worldwide pandemic (COVID-19) after emerging in Wuhan, China. Here we analyzed public host and viral RNA sequencing data to better understand how SARS-CoV-2 interacts with human respiratory cells. We identified genes, isoforms and transposable element families that are specifically altered in SARS-CoV-2-infected respiratory cells. Well-known immunoregulatory genes including CSF2, IL32, IL-6 and SERPINA3 were differentially expressed, while immunoregulatory transposable element families were upregulated. We predicted conserved interactions between the SARS-CoV-2 genome and human RNA-binding proteins such as the heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) and eukaryotic initiation factor 4 (eIF4b). We also identified a viral sequence variant with a statistically significant skew associated with age of infection, that may contribute to intracellular host-pathogen interactions. These findings can help identify host mechanisms that can be targeted by prophylactics and/or therapeutics to reduce the severity of COVID-19. |*Pandemics[MESH] |Binding Sites[MESH] |COVID-19/*genetics/virology[MESH] |Computational Biology/*methods[MESH] |Cytokines/genetics[MESH] |Databases, Genetic[MESH] |Gene Expression Regulation[MESH] |Genome, Viral[MESH] |Host-Pathogen Interactions/*genetics[MESH] |Humans[MESH] |RNA, Viral/genetics/metabolism[MESH] |RNA-Binding Proteins/genetics/metabolism[MESH] |RNA-Seq[MESH] |SARS-CoV-2/*genetics[MESH] |Serpins/genetics[MESH] |Signal Transduction/genetics[MESH] |Transcriptome[MESH]Genome-wide bioinformatic analyses predict key host and viral factors (epmc).pdf DeepDyve Pubget Overpricing