Recall the classic Chapman-Kolmogorov equation for a Markov process $(X_t)_t$: if $p(s,x;t,I)=\mathbb{P}(X_t \in I | X_s = x)$ is the transition probability (where $I$ is a Borel set), then $$ p(s,x;t,I)=\int_{\mathbb{R}} p(s,x;r,dz)p(r,z;t,I) \qquad (*) $$
I am asked to rewrite the equation $(*)$ in the case that the probability measure $I \rightarrow \mathbb{P}(X_t \in I | X_s=x)$ admits density, that is $\mathbb{P}(X_t \in I | X_s=x) = \int_{I} p(s,x;t,y) \, dy$. I already know that the result should be: $$ p(s,x;t,y)=\int_{\mathbb{R}} p(s,x;z,u)p(z,u;t,y) \, du \qquad (**) $$
Back to the proof, in these hypothesis, the LHS of $(*)$ is just $\int_{I} p(s,x;t,y) \, dy$, while the RHS is:
$$ \int_{\mathbb{R}} p(s,x;r,dz)p(r,z;t,I)=\int_{\mathbb{R}} p(s,x;r,dz) \int_{I} p(r,z;t,y) \, dy $$
I'm pretty sure that the conclusion relies on the fact that we should have two integrals that are equal for every Borel set $I$, hence the argument maps coincide. By the way, I cannot see the right way to "get rid" of that $dz$ as an argument of $p$ (the notation of a transition probability with a differential variable is already unclear to me) and/or switch integration order (probably Fubini will suffice for that). Thanks in advance.