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Fusion of genomic, proteomic and phenotypic data: the case of potyviruses

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Fusion of genomic, proteomic and phenotypic data: the case of potyviruses

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dc.contributor.author Folch-Fortuny, A. es_ES
dc.contributor.author BOSQUE-CHACON, GABRIEL es_ES
dc.contributor.author Picó, Jesús es_ES
dc.contributor.author Ferrer, A. es_ES
dc.contributor.author Elena, S.F. es_ES
dc.date.accessioned 2017-01-04T10:42:52Z
dc.date.available 2017-01-04T10:42:52Z
dc.date.issued 2016
dc.identifier.issn 1742-206X
dc.identifier.uri http://hdl.handle.net/10251/76327
dc.description.abstract Data fusion has been widely applied to analyse different sources of information, combining all of them in a single multivariate model. This methodology is mandatory when different omic data sets must be integrated to fully understand an organism using a systems biology approach. Here, a data fusion procedure is presented to combine genomic, proteomic and phenotypic data sets gathered for Tobacco etch virus (TEV). The genomic data correspond to random mutations inserted in most viral genes. The proteomic data represent both the effect of these mutations on the encoded proteins and the perturbation induced by the mutated proteins to their neighbours in the protein protein interaction net- work (PPIN). Finally, the phenotypic trait evaluated for each mutant virus is replicative fitness. To analyse these three sources of information a Partial Least Squares (PLS) regression model is fitted in order to extract the latent variables from data that explain (and relate) the significant variables to the fitness of TEV. The final output of this methodology is a set of functional modules of the PPIN relating topology and mutations with fitness. Throughout the re-analysis of these diverse TEV data, we generated valuable information on the mechanism of action of certain mutations and how they translate into organismal fitness. Results show that the effect of some mutations goes beyond the protein they directly affect and spreads on the PPIN to neighbour proteins, thus defining functional modules. es_ES
dc.description.sponsorship This work was supported by the Spanish Ministerio de Economia y Competitividad grants BFU2012-30805 (to SFE), and DPI2011-28112-C04-02, DPI2011-28112-C04-01, DPI2014-55276-C5-1-R (to AF and JP) and by Generalitat Valenciana grant PROMETEOII/2014/021 (to SFE). The first two authors are recipients of fellowships from the Spanish Ministerio de Economia y Competitividad: BES-2012-053772 (to GB) and BES-2012-057812 (to AF-F). en_EN
dc.language Inglés es_ES
dc.publisher Royal Society of Chemistry es_ES
dc.relation Spanish Ministerio de Economia y Competitividad BFU2012-30805 DPI2011-28112-C04-02 DPI2011-28112-C04-01 DPI2014-55276-C5-1-R BES-2012-053772 BES-2012-057812 es_ES
dc.relation Generalitat Valenciana grant PROMETEOII/2014/021 es_ES
dc.relation.ispartof Molecular BioSystems es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject YEAST 2-HYBRID SYSTEM es_ES
dc.subject COMPLEX NETWORKS es_ES
dc.subject VIRUS es_ES
dc.subject CHEMOMETRICS es_ES
dc.subject REGRESSION es_ES
dc.subject TUTORIAL es_ES
dc.subject CULTURE es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.title Fusion of genomic, proteomic and phenotypic data: the case of potyviruses es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1039/c5mb00507h
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario Mixto de Biología Molecular y Celular de Plantas - Institut Universitari Mixt de Biologia Molecular i Cel·lular de Plantes es_ES
dc.description.bibliographicCitation Folch-Fortuny, A.; Bosque-Chacon, G.; Picó, J.; Ferrer, A.; Elena, S. (2016). Fusion of genomic, proteomic and phenotypic data: the case of potyviruses. Molecular BioSystems. 12(1):253-261. doi:10.1039/c5mb00507h es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi. org/10.1039/c5mb00507h es_ES
dc.description.upvformatpinicio 253 es_ES
dc.description.upvformatpfin 261 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 1 es_ES
dc.relation.senia 298769 es_ES
dc.identifier.eissn 1742-2051


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