Ran a “quick and dirty” qPCR analysis for the qPCR’s I’d previously run:

All analyses are documented in the following R Project:

20230822-cgig-polyIC-qPCR (GitHub)

Here’s a brief overview of what was done:

Select only diploid samples (currently, only have control/injected groups for diploids - not triploids)
Normalize to actin by calculating delta Cq.

This was done for the sake of time. Actin and GAPDH (the other normalizing gene run) shows evidence of a treatment effect. Actin was selected over GAPDH due to smaller range between mean Cqs of Control/Injected.

Run t-test to determine p-values between control/injected withing each actin-normalized gene.
Box plot all delta Cq values.
Calculate 2^^{(-delta delta Cq)} (subtract Control delta Cq from Injected delta Cq) to determine fold change in expression for each gene.
Plot fold change in expression as bar plots. Values >1 indicate increase in relative expression. Values <1 indicate decrease in relative expression.

RESULTS

Box Plots (delta Cq)

Box plots of delta Cq (i.e. normalize to Actin). T-test identified only a single gene (marked with orange asterisk) as significantly different between Control/Injected: DICER

boxplots comparing 6 different genes - orange asterisk above Cg_DICER indicates statistically different between Control and Injected

Fold Change (2^-(ddCq))

Fold change in gene expression of Injected individuals, relative to control samples.

RESULTS

Box Plots (delta Cq)

Fold Change (2-(ddCq))

Fold Change (2^-(ddCq))