Minority Gene Expression Profiling: Probing the Genetic Signatures of Pathogenesis Using Ribosome Profiling

UDC.coleccionInvestigaciónes_ES
UDC.departamentoBioloxíaes_ES
UDC.endPageS357es_ES
UDC.grupoInvGrupo de Investigación en Bioloxía Evolutiva (GIBE)es_ES
UDC.institutoCentroCICA - Centro Interdisciplinar de Química e Bioloxíaes_ES
UDC.issueSupplement_3 (15 April)es_ES
UDC.journalTitleThe Journal of Infectious Diseaseses_ES
UDC.startPageS341es_ES
UDC.volume221 (2020)es_ES
dc.contributor.authorVila-Sanjurjo, Antón
dc.contributor.authorJuárez, Diana
dc.contributor.authorLoyola, Steev
dc.contributor.authorTorres, Michael
dc.contributor.authorLeguia, Mariana
dc.date.accessioned2025-01-09T21:09:50Z
dc.date.available2025-01-09T21:09:50Z
dc.date.issued2020-03-27
dc.descriptionThis is a pre-copyedited, author-produced version of an article accepted for publication in The Journal of Infectious Diseases following peer review. The version of record is available online at https://doi.org/10.1093/infdis/jiz565es_ES
dc.description.abstract[Abstract] Minority Gene Expression Profiling (MGEP) refers to a scenario where the expression profiles of specific genes of interest are concentrated in a small cellular pool that is embedded within a larger, non-expressive pool. An example of this is the analysis of disease-related genes within sub-populations of blood or biopsied tissues. These systems are characterized by low signal-to-noise ratios that make it difficult, if not impossible, to uncover the desired signatures of pathogenesis in the absence of lengthy, and often problematic, technical manipulations. We have adapted ribosome profiling (RP) workflows from the Illumina to the Ion Proton platform and used them to analyze signatures of pathogenesis in an MGEP model system consisting of human cells eliciting <3% productive dengue infection. We find that RP is powerful enough to identify relevant responses of differentially expressed genes, even in the presence of significant noise. We discuss how to deal with sources of unwanted variation, and propose ways to further improve this powerful approach to the study of pathogenic signatures within MGEP systems.es_ES
dc.description.sponsorshipThe work was supported by an award to ML from the In-House Laboratory Independent Research Program of the Naval Medical Research Center (Project ID: ILIR-4514). This supplement is sponsored by WRAIR, LANL, USAMRIID, PUCP (Pontificia Universidad Catolica del Peru), USAFSAM, NIH.es_ES
dc.description.sponsorshipEstados Unidos. Naval Medical Research Center; ILIR-4514es_ES
dc.identifier.citationVila-Sanjurjo A, Juarez D, Loyola S et al. Minority Gene Expression Profiling: Probing the Genetic Signatures of Pathogenesis Using Ribosome Profiling. The Journal of Infectious Diseases 2020;221:S341–57. https://doi.org/10.1093/infdis/jiz565es_ES
dc.identifier.doi10.1093/infdis/jiz565
dc.identifier.issn1537-6613
dc.identifier.urihttp://hdl.handle.net/2183/40648
dc.language.isoenges_ES
dc.publisherOxford Academices_ES
dc.relation.urihttps://doi.org/10.1093/infdis/jiz565es_ES
dc.rights.accessRightsopen accesses_ES
dc.subjectMinority gene expression profilinges_ES
dc.subjectRibosome profilinges_ES
dc.subjectNext generation sequencinges_ES
dc.subjectSignatures of pathogenesises_ES
dc.subjectDenguees_ES
dc.titleMinority Gene Expression Profiling: Probing the Genetic Signatures of Pathogenesis Using Ribosome Profilinges_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublicationbb5d2665-4134-4f5c-9b10-95440bfe6f86
relation.isAuthorOfPublication.latestForDiscoverybb5d2665-4134-4f5c-9b10-95440bfe6f86

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