In two-way ANOVA, is it common for an interaction effect to be significant but for neither of the main effects to be significant? I am analysing some data using a two-way ANOVA followed by Sidak's multiple comparisons post hoc tests. I am looking at the effect of age and genotype (the independent variables) on the levels of a certain protein (the dependent variable) expressed in the brain of mice.
After performing the two-way ANOVA, the interaction effect is statistically significant (p-value = 0.0254), but neither of the main effects are statistically significant (p-value > 0.05).
I am new to two-way ANOVA analysis and I have learnt about it from online tutorials. In the examples on the tutorials, I have seen cases where the interaction effect is statistically significant, along with one main effect.
I am wondering if it is common for result of two-way ANOVA to have only the interaction effect be statistically significant? Further, would the correct interpretation of my results be that neither age or genotype alone has a significant impact on the levels of the protein; however the age and genotype in combination does have a significant impact on the levels of the protein?
Any insights are appreciated.

Yes it is very common. A significant interaction term indicates that protein levels do not differ consistently according to either age or genotype but that differences are dependent on what age group and genotype you look at. So for example, protein differs significantly for juveniles of genotype A, but does not differ for juveniles of genotype B..or protein content may differ for adults of genotype A but not for juveniles of genotype A. So in the case of a significant interaction term you would not do post hoc tests on the single upper level factors regardless of whether they are significant or not, but only do post how tests on the interactions term investigating in which levels of the interaction term there are differences.
