Analysis of time-course microarray data: Comparison of common tools

Olfactory receptors contribute to progression of kidney fibrosis

Olfactory receptors (ORs) which are mainly known as odor-sensors in the olfactory epithelium are shown to be expressed in several non-sensory tissues. Despite the specified role of some of these receptors in normal physiology of the kidney, little is known about their potential effect in renal disorders. In this study, using the holistic view of systems biology, it was determined that ORs are significantly changed during the progression of kidney fibrosis. For further validation, common differentially expressed ORs resulted from reanalysis of two time-course microarray datasets were selected for experimental evaluation in a validated murine model of unilateral ureteral obstruction (UUO). Transcriptional analysis by real-time quantitative polymerase chain reaction demonstrated considerable changes in the expression pattern of Olfr433, Olfr129, Olfr1393, Olfr161, and Olfr622 during the progression of kidney fibrosis. For localization of these ORs, single-cell RNA-sequencing datasets of normal and UUO mice were reanalyzed. Results showed that Olfr433 is highly expressed in macrophages in day-2 and 7 post-injury in UUO mice and not in normal subgroups. Besides, like previous findings, Olfr1393 was shown to be expressed prominently in the proximal tubular cells of the kidney. In conclusion, our combinatorial temporal approach to the underlying mechanisms of chronic kidney disease highlighted the potential role of ORs in progression of fibrosis. The expression of Olfr433 in the macrophages provides some clue about its relation to molecular mechanisms promoted in the fibrotic kidney. The proposed ORs in this study could be the subject of further functional assessments in the future.

Big data to knowledge: common pitfalls in transcriptomics data analysis and representation

The omics technologies provide an invaluable opportunity to employ a global view towards human diseases. However, the appropriate translation of big data to knowledge remains a major challenge. In this study, we have performed quality control assessments for 91 transcriptomics datasets deposited in gene expression omnibus database and also have evaluated the publications derived from these datasets. This survey shows that drawbacks in the analyses and reports of transcriptomics studies are more common than one may assume. This report is concluded with some suggestions for researchers and reviewers to enhance the minimal requirements for gene expression data generation, analysis and report.

The analysis of a time-course transcriptome profile by systems biology approaches reveals key molecular processes in acute kidney injury

Background:

Acute kidney injury is a common debilitating disease with no curative treatment. The recent development of big biological data is expected to expand our understanding of the disorder if appropriately analyzed to generate translational knowledge. We have here re-analyzed a time-course microarray data on mRNA expression of rat kidneys exposed to ischemia-reperfusion to identify key underlying biological processes.

Materials and Methods:

The dataset was quality controlled by principal component analysis and hierarchical clustering. Using limma R package, differentially expressed (DE) genes were detected which were then clustered according to their expression trajectories. The biological processes related to each cluster were harvested using gene ontology enrichment analysis. In addition, the interaction map of proteins encoded by the DE genes was constructed, and the functions related to network central genes were determined. Furthermore, signaling pathways related to the DE genes were harvested using pathway enrichment analysis.

Results:

We found 8139 DE genes that drive critical processes such as the control of blood circulation, reactive species metabolism, mitochondrial respiration, apoptosis, cell proliferation, as well as inflammatory and immunological reactions. The role of less recognized pathways such as olfactory signaling in acute kidney injury is also proposed that remains to be investigated in future studies.

Conclusion:

Using systems biology top-down approach, we have suggested novel potential genes and pathways to be intervened toward kidney regeneration.