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Framework for the Integration of Genomics, Epigenomics and Transcriptomics in Complex Diseases

dc.contributor.authorPineda Sanjuan, Silvia
dc.contributor.authorGómez Rubio, Paulina
dc.contributor.authorPicornell, Antonio
dc.contributor.authorBessonov, Kyrylo
dc.contributor.authorMárquez, Mirari
dc.contributor.authorKogevinas, Manolis
dc.contributor.authorReal, Francisco Xavier
dc.contributor.authorVan Steen, Kristel
dc.contributor.authorMalats, Nuria
dc.date.accessioned2024-01-09T09:37:26Z
dc.date.available2024-01-09T09:37:26Z
dc.date.issued2015
dc.description.abstractObjectives: Different types of ‘-omics' data are becoming available in the post-genome era; still a single -omics assessment provides limited insights to understand the biological mechanism of complex diseases. Genomics, epigenomics and transcriptomics data provide insight into the molecular dysregulation of neoplastic diseases, among them urothelial bladder cancer (UBC). Here, we propose a detailed analytical framework necessary to achieve an adequate integration of the three sets of -omics data to ultimately identify previously hidden genetic mechanisms in UBC. Methods: We built a multi-staged framework to study possible pair-wise combinations and integrated the data in three-way relationships. SNP genotypes, CpG methylation levels and gene expression levels were determined for a total of 70 individuals with UBC and with fresh tumour tissue available. Results: We suggest two main hypothesis-based scenarios for gene regulation based on the -omics integration analysis, where DNA methylation affects gene expression and genetic variants co-regulate gene expression and DNA methylation. We identified several three-way trans-association ‘hotspots' that are found at the molecular level and that deserve further studies. Conclusions: The proposed integrative framework allowed us to identify relationships at the whole-genome level providing some new biological insights and highlighting the importance of integrating -omics data.
dc.description.departmentDepto. de Estadística y Ciencia de los Datos
dc.description.facultyFac. de Estudios Estadísticos
dc.description.refereedTRUE
dc.description.statuspub
dc.identifier.citationPineda, Silvia, et al. «Framework for the Integration of Genomics, Epigenomics and Transcriptomics in Complex Diseases». Human Heredity, vol. 79, n.o 3-4, 2015, pp. 124-36. https://doi.org/10.1159/000381184.
dc.identifier.doi10.1159/000381184
dc.identifier.essn1423-0062
dc.identifier.issn0001-5652
dc.identifier.officialurlhttps://doi.org/10.1159/000381184
dc.identifier.urihttps://hdl.handle.net/20.500.14352/91946
dc.journal.titleHuman Heredity
dc.language.isoeng
dc.rights.accessRightsrestricted access
dc.subject.ucmGenética
dc.subject.ucmOncología
dc.subject.unesco2409 Genética
dc.subject.unesco3201.01 Oncología
dc.titleFramework for the Integration of Genomics, Epigenomics and Transcriptomics in Complex Diseasesen
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isAuthorOfPublication9ff02bb9-3623-452e-ad72-8bb19687ec4e
relation.isAuthorOfPublication.latestForDiscovery9ff02bb9-3623-452e-ad72-8bb19687ec4e

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