1st Hypothesis

Difference between Transfection Days

B3 vs B9 → transfection Day 4 higher Cq
B4 vs B10 → transfection Day 4 higher Cq
B5 vs B11 → transfection Day 4 higher Cq
B6 vs B12 → transfection Day 4 higher Cq
C1 vs C7 → transfection Day 3 higher Cq
C2 vs C8 → transfection Day 4 higher Cq
C3 vs C9 → transfection Day 4 higher Cq
D1 vs D7 → transfection Day 3 higher Cq
D3 vs D9 → transfection Day 3 higher Cq
D4 vs D10 → transfection Day 3 higher Cq
D5 vs D11 → transfection Day 3 higher Cq
D6 vs D12 → transfection Day 3 higher Cq
E4 vs E10 → transfection Day 4 higher Cq
E5 vs E11 → transfection Day 4 higher Cq

Interpretation: In general, for row B, wells with the same concentration exhibit consistently higher Cq values on Day 4 compared to Day 3. This initially suggests that extending the siRNA transfection duration by one more day might lead to a substantial decrease in the target gene (EHMT2) expression, reflecting a more significant reduction in concentration of the target mRNA.

However, a deeper examination of the data from row D challenges this hypothesis. For these wells, the Day 3 Cq values are consistently higher than those of Day 4, contradicting the previous assumption. This inconsistency in Cq trends between the two rows raises questions about whether transfection time alone directly correlates with gene silencing efficiency, as would be expected in typical siRNA knockdown experiments.

Potential Sources of Error: The observed discrepancies between Cq values across different rows may stem from technical inconsistencies rather than biological factors. Since the lipofectamine reagent was pipetted into all wells within a row simultaneously using a multi-channel pipette, systematic errors during the pipetting process could have occurred. For instance, variations in concentration due to uneven pipetting or the introduction of air bubbles could explain why an entire row consistently produced higher Cq values. These technical variations may have masked the true effect of transfection duration on gene silencing efficiency.

Conclusion: Due to the conflicting Cq value trends between different rows, it is challenging to draw definitive conclusions regarding the optimal transfection duration based on this dataset alone. While Day 4 transfection appears to yield higher Cq values in some cases, such as row B, this observation is contradicted by the lower Cq values seen on Day 4 in row D. Consequently, further experiments with improved pipetting accuracy and more replicates will be necessary to conclusively determine the impact of transfection duration on siRNA-mediated gene silencing.

2nd Hypothesis

Cells concentration

Interpretation: When analyzing the Cq values across varying cell concentrations with a constant siRNA concentration, an expected decrease in Cq values between 0.5 × 10^5 and 1.0 × 10^5 cells is observed. This is consistent with the notion that higher cell numbers should require more siRNA to achieve gene silencing. However, this inverse relationship does not hold between the 1.0 × 10^5 and 2.0 × 10^5 cell concentrations. The Cq values remain inconsistent, contradicting the hypothesis that increased cell concentrations would correlate with higher siRNA demand and thus lower Cq values.

Potential Sources of Error: The observed discrepancies may result from technical errors during the experimental setup, rather than biological phenomena. Specifically, the preparation of stock solution for different cell concentrations could have been inaccurately prepared, leading to misrepresented cell numbers in each well. Additionally, the use of a multi-channel pipette for distributing cells might have introduced systematic errors, such as unequal pipetting or air bubbles, which could have led to inaccurate cell concentrations across wells. These technical issues may have obscured the true relationship between cell concentration and Cq values, preventing accurate conclusions regarding the effects of cell numbers on gene silencing.

Conclusion: The inconsistency in Cq values across different cell concentrations suggests that technical errors in the preparation of cell stocks or pipetting may have skewed the data. While the initial hypothesis predicted an inverse relationship between cell concentration and Cq values, the results indicate otherwise. This highlights the importance of rigorous quality control in experimental setup and the need for further experiments to clarify the true impact of cell concentration on siRNA-mediated gene silencing.

3rd Hypothesis

Concentration of siRNA

Interpretation: When analyzing the impact of varying siRNA concentrations (2.5 nmol, 5 nmol, 10 nmol) across constant cell concentrations, no significant effect was observed in the Cq values. For instance, at 0.5 × 10^5 cells, wells transfected with 2.5 nmol siRNA (B7: 25.63, C7: 20.97) displayed values similar to those transfected with 5 nmol (B8: 25.17, C8: 25.17) and 10 nmol siRNA (B9: 26.20, C9: 23.16). This lack of variation suggests that increasing siRNA concentrations did not improve gene silencing efficiency as hypothesized.

Potential Sources of Error: Several technical issues may have contributed to the lack of observable differences in Cq values across varying siRNA concentrations. Foremost, inconsistent transfection efficiency across wells may have masked any potential effects of increased siRNA concentration. Variability in siRNA delivery, possibly due to uneven mixing or pipetting inconsistencies, may have reduced the effectiveness of siRNA uptake across wells. Additionally, siRNA degradation could have occurred prior to transfection, limiting its effectiveness regardless of concentration.

Conclusion: The data suggests that increasing siRNA concentrations did not correlate with a more pronounced reduction in Cq values, indicating no significant enhancement of gene silencing. The consistency of Cq values across siRNA concentrations implies that technical issues such as pipetting errors, siRNA degradation, or transfection inefficiencies may have masked the expected effects. Future experiments should focus on improving transfection consistency, optimizing siRNA stability, and ensuring proper siRNA-to-target gene ratios to more effectively assess the relationship between siRNA dosage and gene silencing.

4th Hypothesis

siRNA vs silencer

Interpretation: If siRNA is consistently showing fewer cycles (lower Cq values), it suggests that there may be higher G9a expression in the siRNA-treated cells. This is contrary to the expected outcome since siRNA should reduce G9a expression, leading to higher Cq values (more cycles).

Potential Sources of Error: One potential source of error in your experiment could be the ineffective siRNA knockdown. If the siRNA is not properly designed or degraded before it reaches the target gene, it might not efficiently silence G9a expression, leading to inaccurate qPCR results. Additionally, qPCR technical issues such as poorly designed primers, inconsistent amplification efficiency, or degradation of reagents like RNA, cDNA, or the qPCR mix can also affect the accuracy of the Cq values. Another potential issue is pipetting errors, where even small variations in handling can introduce significant discrepancies in qPCR cycle numbers. Furthermore, the control group, which uses a silencer expected to have no effect on G9a expression, may not be functioning properly, possibly due to contamination or unexpected impacts on gene expression. Transfection efficiency could also vary between samples, leading to inconsistent siRNA uptake and reduced gene silencing effectiveness. Lastly, off-target effects of the siRNA might cause unintended consequences on other genes or pathways, indirectly influencing G9a expression and resulting in misleading data.

Conclusion: In conclusion, the unexpected observation of fewer qPCR cycles (lower Cq values) in the siRNA-treated samples, which suggests higher G9a expression, indicates that something may be wrong with the experimental setup. The siRNA, designed to silence G9a, should have resulted in reduced gene expression and higher Cq values, but this was not the case. This discrepancy could be due to technical issues such as ineffective siRNA knockdown, problems with qPCR reagents or primer specificity, or errors in transfection efficiency. To resolve these issues, further optimization and verification of the siRNA's knockdown efficiency, careful review of the qPCR conditions, and validation of the control group's neutrality are necessary.

5th Hypothesis

siRNA vs blank

Interpretation When comparing the effects of 5 nmol siRNA treatment to blank wells across varying cell concentrations, we hypothesize that Cq values in siRNA-treated wells should **increase** compared to the blank. This is because effective gene silencing would reduce the amount of target mRNA, requiring more cycles for qPCR detection. The Cq values are expected to increase proportionally to the siRNA-induced reduction of mRNA.When analyzing the results across different cell concentrations (0.5, 1.0, and 2.0 × 10^5), inconsistencies arise. For instance, comparing BC2 (5 nmol siRNA) and E4 (blank) with 0.5 × 10^5 cells, we observe no significant difference in Cq values (21.30 vs. 21.41, respectively). Similarly, BC5 vs. E5 (1.0 × 10^5 cells) shows a lower Cq value for siRNA (19.35) than the blank (24.08), which is contradictory to expectations. In theory, siRNA-treated wells should exhibit higher Cq value due to reduced mRNA levels caused by gene silencing. This trend is also seen in other examples such as BC11 (22.22) vs. E11 (24.65), and BC8 (25.17) vs. E10 (25.33), where little to no increase in Cq values is observed.

Potential Sources of Error: Inconsistent pipetting may have led to varying siRNA concentrations across wells, causing discrepancies in the silencing effect and the resulting qPCR amplification cycles. Moreover, uneven distribution of cells during plating could have contributed to fluctuating gene expression levels, making it challenging to compare Cq values across different cell concentrations. Suboptimal transfection conditions, such as incorrect incubation times or temperature variations, could have also impaired siRNA uptake into the cells, reducing the overall silencing efficiency. Additionally, contamination between wells or during the qPCR process could have introduced noise into the results, masking the true effects of siRNA treatment and leading to unexpected deviations in Cq values.

Conclusion: The data suggest that the application of 5 nmol siRNA across varying cell concentrations does not consistently result in the expected increase in Cq values compared to blank wells. This indicates potential inefficiencies in the siRNA transfection process or technical errors during the experiment. To confirm these findings, further optimizations in transfection efficiency and qPCR procedures should be undertaken. Additionally, repeating the experiment with controls for technical variables may provide more conclusive results regarding the impact of siRNA on gene silencing.