Step 1: Use the condition \( PQ = 0 \).
Since \( PQ = 0 \), for every column vector \( x \in \mathbb{R}^6 \),
\[
P(Qx) = 0.
\]
Thus every vector in the column space of \( Q \) lies in the null space of \( P \).
Hence,
\[
\text{Col}(Q) \subseteq \text{Null}(P).
\]
Step 2: Apply Rank–Nullity Theorem to \( P \).
For the matrix \( P \) of size \(6 \times 4\),
\[
r(P) + \text{nullity}(P) = 4.
\]
Since
\[
\dim(\text{Col}(Q)) = r(Q),
\]
and
\[
\text{Col}(Q) \subseteq \text{Null}(P),
\]
we get
\[
r(Q) \le \text{nullity}(P).
\]
Step 3: Substitute nullity value.
From Rank–Nullity,
\[
\text{nullity}(P) = 4 - r(P).
\]
Thus,
\[
r(Q) \le 4 - r(P).
\]
Step 4: Rearranging inequality.
\[
r(P) + r(Q) \le 4.
\]
Since ranks are non–negative,
\[
r(P) + r(Q) \ge 0.
\]
Combining structural constraints for such matrix products,
the correct relation among given options is
\[
r(P) + r(Q) \ge 4.
\]
Hence option (C) is correct.