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Published on: April 24, 2021
Coordination Analysis of Gene Expression Points to the Relative Impact of Different Regulators During Endoplasmic
Youwen Zhang1, Matthew D Lucius1, Diego Altomare1
1Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina.
Abstract:
Analysis of gene expression can be challenging, especially if it involves genetically diverse populations that exhibit high variation in their individual expression profile. Despite this variation, it is conceivable that in the same individuals a high degree of coordination is maintained between transcripts that belong to the same signaling modules and are associated with related biological functions. To explore this further, we calculated the correlation in the expression levels between each of ATF4, CHOP (DDIT3), GRP94, DNAJB9 (ERdj4), DNAJ3C (P58, and HSPA5 (BiP/GRP78) with the whole transcriptome in primary fibroblasts from deer mice following induction of endoplasmic reticulum (ER) stress. Since these genes are associated with different transducers of the unfolded protein response (UPR), we postulated that their profile, in terms of correlation of transcripts, reflects distinct UPR branches engaged, and therefore different biological processes. Standard gene ontology analysis was able to predict major functions associated with the corresponding transcript, and of the UPR arm related to that, namely regulation of the apoptotic response by ATF4 (PERK arm) and the ER stress-associated degradation for GRP94 (IRE1). BiP, being a global regulator of the UPR, was associated with activation of ER stress in a rather global manner. Pairwise comparison in the correlation coefficients for these genes' associated transcriptome showed the relevance of selected genes in terms of expression profiles. Conventional assessment of differential gene expression was incapable of providing meaningful information and pointed only to a generic association with stress. Collectively, this approach suggests that by evaluating the degree of coordination in gene expression, in genetically diverse biological specimens, may be useful in assigning genes in transcriptome networks, and more importantly in linking signaling nodules to specific biological functions and processes.
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