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dc.contributor.authorHadwen, Jeremiah
dc.contributor.authorSchock, Sarah
dc.contributor.authorFarooq, Faraz
dc.contributor.authorMacKenzie, Alex
dc.contributor.authorPlaza Díaz, Julio 
dc.date.accessioned2021-07-01T10:01:09Z
dc.date.available2021-07-01T10:01:09Z
dc.date.issued2021
dc.identifier.citationHadwen, J.; Schock, S.; Farooq, F.; MacKenzie, A.; Plaza-Diaz, J. Separating the Wheat from the Chaff: The Use of Upstream Regulator Analysis to Identify True Differential Expression of Single Genes within Transcriptomic Datasets. Int. J. Mol. Sci. 2021, 22, 6295. https://doi.org/10.3390/ ijms22126295es_ES
dc.identifier.urihttp://hdl.handle.net/10481/69452
dc.description.abstractThe development of DNA microarray and RNA-sequencing technology has led to an explosion in the generation of transcriptomic differential expression data under a wide range of biologic systems including those recapitulating the monogenic muscular dystrophies. Data generation has increased exponentially due in large part to new platforms, improved cost-effectiveness, and processing speed. However, reproducibility and thus reliability of data remain a central issue, particularly when resource constraints limit experiments to single replicates. This was observed firsthand in a recent rare disease drug repurposing project involving RNA-seq-based transcriptomic profiling of primary cerebrocortical cultures incubated with clinic-ready blood–brain penetrant drugs. Given the low validation rates obtained for single differential expression genes, alternative approaches to identify with greater confidence genes that were truly differentially expressed in our dataset were explored. Here we outline a method for differential expression data analysis in the context of drug repurposing for rare diseases that incorporates the statistical rigour of the multigene analysis to bring greater predictive power in assessing individual gene modulation. Ingenuity Pathway Analysis upstream regulator analysis was applied to the differentially expressed genes from the Care4Rare Neuron Drug Screen transcriptomic database to identify three distinct signaling networks each perturbed by a different drug and involving a central upstream modulating protein: levothyroxine (DIO3), hydroxyurea (FOXM1), dexamethasone (PPARD). Differential expression of upstream regulator network related genes was next assessed in in vitro and in vivo systems by qPCR, revealing 5× and 10× increases in validation rates, respectively, when compared with our previous experience with individual genes in the dataset not associated with a network. The Ingenuity Pathway Analysis based gene prioritization may increase the predictive value of drug–gene interactions, especially in the context of assessing single-gene modulation in single-replicate experiments.es_ES
dc.description.sponsorshipCare4Rare Canada Consortium funded by Genome Canadaes_ES
dc.description.sponsorshipCanadian Institutes of Health Researches_ES
dc.description.sponsorshipOntario Genomics Institute (OGI-049)es_ES
dc.description.sponsorshipOntario Research Fundes_ES
dc.description.sponsorshipGenome Quebeces_ES
dc.description.sponsorshipGenome British Columbiaes_ES
dc.description.sponsorshipCHEO Foundation (3 July 2014)es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectTranscriptomicses_ES
dc.subjectDifferential expression analysises_ES
dc.subjectRare diseasees_ES
dc.subjectDrug repurposinges_ES
dc.titleSeparating the Wheat from the Chaff: The Use of Upstream Regulator Analysis to Identify True Differential Expression of Single Genes within Transcriptomic Datasetses_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.3390/ijms22126295


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Atribución 3.0 España
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