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Article

Separating the Wheat from the Chaff: The Use of Upstream Regulator Analysis to Identify True Differential Expression of Single Genes within Transcriptomic Datasets

1
Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON K1H8M5, Canada
2
Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H8L1, Canada
3
Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada, 18071 Granada, Spain
4
Instituto de Investigación Biosanitaria IBS.GRANADA, Complejo Hospitalario Universitario de Granada, 18014 Granada, Spain
*
Authors to whom correspondence should be addressed.
Academic Editor: Catherine Coirault
Int. J. Mol. Sci. 2021, 22(12), 6295; https://doi.org/10.3390/ijms22126295
Received: 3 May 2021 / Revised: 4 June 2021 / Accepted: 7 June 2021 / Published: 11 June 2021
(This article belongs to the Special Issue Cell Signaling and Omics in Muscular Dystrophies)
The 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. View Full-Text
Keywords: transcriptomics; differential expression analysis; rare disease; drug repurposing transcriptomics; differential expression analysis; rare disease; drug repurposing
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MDPI and ACS Style

Hadwen, 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/ijms22126295

AMA Style

Hadwen 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. International Journal of Molecular Sciences. 2021; 22(12):6295. https://doi.org/10.3390/ijms22126295

Chicago/Turabian Style

Hadwen, Jeremiah, Sarah Schock, Faraz Farooq, Alex MacKenzie, and Julio Plaza-Diaz. 2021. "Separating the Wheat from the Chaff: The Use of Upstream Regulator Analysis to Identify True Differential Expression of Single Genes within Transcriptomic Datasets" International Journal of Molecular Sciences 22, no. 12: 6295. https://doi.org/10.3390/ijms22126295

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