Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina.
Department of Pathology, Microbiology and Immunology, School of Medicine, University of South Carolina, Columbia, South Carolina.
DNA Cell Biol. 2019 Sep;38(9):969-981. doi: 10.1089/dna.2019.4910. Epub 2019 Aug 6.
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 , , , , , and 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.
基因表达分析具有一定挑战性，尤其是在涉及具有高度个体表达谱变异的遗传多样化群体时。尽管存在这种变异，但可以想象，在相同个体中，属于同一信号模块的转录本之间保持着高度的协调，并且与相关的生物学功能相关。为了进一步探讨这一点，我们计算了鹿鼠原代成纤维细胞内质网（ER）应激诱导后，每个基因与整个转录组之间的表达水平相关性。由于这些基因与未折叠蛋白反应（UPR）的不同传感器相关，我们假设它们的转录本的相关性谱反映了不同的 UPR 分支的参与，因此也反映了不同的生物学过程。标准基因本体分析能够预测与相应转录本相关的主要功能，以及与其相关的 UPR 分支，即 ATF4（PERK 分支）调节凋亡反应和 GRP94（IRE1）的 ER 应激相关降解。BiP 作为 UPR 的全局调节剂，以相当全局的方式与 ER 应激的激活相关。这些基因相关转录组的相关性系数的成对比较表明了所选基因在表达谱方面的相关性。传统的差异基因表达评估无法提供有意义的信息，仅指出与应激的一般关联。总的来说，这种方法表明，通过评估遗传多样化生物样本中基因表达的协调程度，可以有助于在转录组网络中分配基因，更重要的是，将信号结节与特定的生物学功能和过程联系起来。
