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Revision as of 03:29, 16 October 2018
Abstract
Our model is formalized by the Linear Equation: (Linear Regression)
The Linear Regression has wide applications throughout the world of statistics. In this case, we chose this model to figure out the relationship between GC content and RNAi efficiency. By doing so we develop a better understanding of this critical parameter which isn't backed by scientific theories.
Assumptions
The model works under the below assumptions:
1. Births and natural deaths are neglected
2. The beetles cannot recover either by itself or with the help of the leaves
3. Other factors do not change throughout the experiment
Parameters
| Parameters | Meaning |
| δ | Deviation of GC content, calculated by the difference between the actual GC content and 50% |
| η | RNAi efficiency |
| w | Correlation, we are expecting a negative value |
| e | Error |
Experiments (See more)
Table 1 shRNAs corresponding to the above siRNAs
Day 1 (8 of August, 2018)
This is our first bug killing experiment, we prepared our equipment. We put farmed Phyllotreta striolata Fabricius in bottles and make sure each bottle contains 20-25 Phyllotreta striolata Fabricius. We used gauze to cover the top of bottles(gauze can allow bugs to breath but they can’t escape). Then made spray with shRNA (1µL/mL), spray it on the leaves and put the leaves inside the bottles.
Summary:
1. Put Phyllotreta striolata Fabricius in bottles (20/bottle)
2. Made spray and spray it on the leaves
3. Put leaves into the bottel
Day 2 (10 of August, 2018)
Summary:
1. Clean out the leaves from the day before
2. Configure new shRNA spray(1µL/mL)
3. Replace each bottle with 2 leaves soaked in the corresponding reagent
4. Clean out the test bench.
Day 3 (13 of August, 2018)
This is our third bug killing experiment. We configurated new shRNA spray(1µL/mL). Then spray the spray on the new leaves, take out the old leaves and replace them with new leaves. At the same time, we pick out the dead Phyllotreta striolata Fabricius and put them in tubes for RT-PCR testing.
Summary:
1. Make new spray(1µL/mL). Spray the spray on new leaves
2. Take out the old leaves and replace them with new leaves
3. Pick out the dead Phyllotreta striolata Fabricius and put them in tubes
Results from day 3
Day 4 (15 of August, 2018)
This is our forth experiment. Like the last experiment, we made new spray and replace the old leaves with new leaves which are sprayed. And then pick out dead Phyllotreta striolata Fabricius and put them in tubes.
Summary:
1. Make new spray(1µL/mL) and spray it on new leaves
2. Take out the old leaves and replace them with new leaves
3. Pick out the dead Phyllotreta striolata Fabricius and put them in tubes
Results from day 4
Day 5 (17 of August, 2018)
This is our fifth bug killing experiment, and also is our last bug killing experiment.
Summary:
1. Take out the dead bugs in the bottle, and take out the leaves in each bottle without putting new leaves
2. Record the number of deaths per bottle of bugs
3. The living bugs stay in the bottle and let them starve to death
Results from day 5
Results
Table 2 RNAi efficiencies of siRNA/shRNA
Fig. 1 The survival rate of Phyllotreta striolata at different days after siRNA/ shRNA treatment.
Fig. 2 Comparison of RNAi efficiencies between siRNA and shRNA
By looking at the statistics generally, we found that our ARK and GLS siRNAs, which has lower deviation has significantly lower survival rates than our ALR siRNAs, which has higher deviation. This matches our expectations.
Fig. 3 Sorting out the data for modelling
Fig. 4 Survival rates of different samples with variations in time
In Fig. 4, we can see the same trend in the figures before. The deviations of different siRNAs are arranged in increasing order from the left to the right. As time progresses, the difference between our ARK, GLS siRNAs and our ALR siRNAs, becomes more evident.
Fig. 5 Plotting our trend lines
In Fig. 5, we plot trendlines to visualize the growing difference. The slopes of our trendlines equal to w, being negative, are increasing in absolute value. Therefore, we know that with a low deviation of our GC content, we get better RNAi efficiency, which is represented by low survival rates.