I am working with a differentiating primary cell culture undergoing chondrogenic differentiation. Following next-gen sequencing, we have a dataset containing expression levels and their changes for all genes in a time-dependent manner. Naturally, a lot of these genes undergo downregulation, or upregulation according to their function in chondrogenesis during the examined time-course. Where this gets highly interesting to me is that I have tried silencing a certain gene at an early time point. This gene - according to the already available dataset - gets downregulated without any external stimulus as chondrogenic differentiation proceeds. However, I got some very confusing results at 72 hours (when siRNA silencing is supposed to reach its peak level) showing that the actual expression of the gene displayed a higher level compared to the non-targeting control group. After stating all of this, I would very much appreciate any kind of relevant insight or suggestion as to how this is possible and what kind of approach needs to be taken to clear this apparent mess up? Thank you all in advance!
This question may have multiple possible explanations. Here are some factors that may influence gene expression levels following siRNA transfection in a differentiating model:
- Off-target effects: siRNA can sometimes affect the expression of non-target genes that have partial or complete sequence homology with the target gene. This can result in mRNA degradation, translation inhibition, or interferon response. Off-target effects can be minimized by using low siRNA concentrations, designing specific siRNAs, and validating siRNA specificity.
- Feedback regulation: Some genes may be regulated by feedback loops that sense changes in their expression levels and adjust accordingly. For example, if a gene is normally downregulated during differentiation, silencing it may trigger a compensatory mechanism that upregulates its expression or the expression of other related genes. Feedback regulation can be detected by measuring the expression of upstream or downstream genes in the same pathway.
- Transfection efficiency: The efficiency of siRNA delivery can vary depending on the cell type, transfection reagent, siRNA concentration, cell density, and exposure time. If the transfection efficiency is low or variable, it may result in incomplete or inconsistent gene silencing. Transfection efficiency can be optimized by testing different parameters and using a positive control siRNA.
- Experimental variability: There may be some sources of variability or error in the experimental design or execution that can affect the gene expression measurements. For example, differences in cell culture conditions, RNA extraction methods, sequencing protocols, or data analysis tools can introduce noise or bias in the results. Experimental variability can be reduced by using standardized protocols, replicates, controls, and statistical methods.
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