Do I need to use Bonferroni correction in commutation study?

Question

I have a table like this:

                Mutation_2_Present   Mutation_2_Absent
Mutation_1_Present     982                  740181
Mutation_1_Absent      111555               89355602

And I apply the Fisher test etc. The thing is that mutation 1 and 2 are not from gene A vs gene B.

They just corresponds to category1 gene and category2 gene. So for example.

cat1 cat2
A B
A C
A D
G C
Z X

So I grouped all genes into either cat1 or cat2. And then I counted the times they appeared in a population.

                Mutation_in_cat2_Present   Mutation_in_cat2_Absent
Mutation_in_cat1_Present     982                  740181
Mutation_in_cat1_Absent      111555               89355602

My question is, do I have to apply Bonferroni correction here, or is my hypothesis a single one? To see if mutations in cat1 and cat2 genes appear more often than expected together.

Note: I wrote it in this Math Stack because I think this is more of a Math/Stats question than Biology one.