How to perform Bonferroni test for multiple comparison after Two-way Anova?

Question

I'm performing statistical analyses on gene expression data. My samples have two different conditions. The conditions are about the genotype and health of the plants. I have 4 different situations: Genotype1-Healthy, Genotype2-Healthy, Genotype1-infected, Genotype2-infected.

I would like to evaluate the statistical differences of the expression values ​​of all combinations of the groups. They will be six melds total.

I've already done the two-way anova:

Myanova<-aov(Value~Condition1*Condition2,data=GENE).

This is for example the output for the values ​​of an analysed gene.

                      Df  Sum Sq Mean Sq F value   Pr(>F)   
Condition1             1 0.76131 0.76131  5.7649 0.035169 * 
Condition2             1 2.53138 2.53138 19.1684 0.001102 **
Condition1:Condition2  1 0.01125 0.01125  0.0852 0.775811   
Residuals             11 1.45267 0.13206 

I would like to continue with the post-hoc bonferroni test.

I searched on the net but I couldn't find the right function that gives me the values ​​for the six different combinations.

I tried the parwisettest but that's not what I'm looking for:

pairwise.t.test(Gene$Value,Gene$Condition2, p.adj="bonferroni")
pairwise.t.test(Gene$Value,Gene$Condition1, p.adj="bonferroni")

Could you tell me how to easily perform the dunn-bonferroni post-hoc test for the multiple comparison of my samples?