The multivariate breeders equation (MBE) by Lande predicts the change in a trait $\Delta \bar z$ (response) as
$\Delta \bar z = G \beta$
where $G$ is a genetic variance-covariance matrix and $\beta$ is a vector of the selection coefficients. What are the limitations on the number of traits the MBE can tolerate? Is there a theoretical limit on the number of traits $G$ and $\beta$ could contain? Or does the calculation lose power with increasing complexity?
Theoretically as an example, could I take the expression of 10000 genes, compare them to fitness to to make a 10000 row $\beta$ vector, and generate a 10000 * 10000 G-matrix from estimates of male and female gene expression in some lines, and then put them through the MBE?