Log-tranformation and GWAS
Yes, use the log-transformed phenotype. if you want to use a normally distributed error term, and this will only occur if the phenotype is log-transformed, then you must log-transform the phenotype.

The phenotype should be distributed in the same manner as the error term in your regression model of the GWAS.

$pheno = \beta_1 X_D + \beta_2 X_A +\epsilon$

$\epsilon = \mathcal{N}(x | \mu,\sigma)$

Following the central limit theorem, most of phenotypes are normally distributed.  However, there are cases where a Bernoulli distribution is correct, and a logistic style regression should be used.