Podocytes are an essential component of the renal glomerular filtration barrier, their injury playing an early and important role in progressive renal dysfunction. This makes quantification of podocyte marker immunoreactivity important for early detection of glomerular histopathological changes. Here we have specifically applied a state-of-the-art automated computational method of glomerulus recognition, which we have recently developed, to study quantitatively podocyte markers in a model with selective podocyte injury, namely the rat puromycin aminonucleoside (PAN) nephropathy model. We also retrospectively investigated mRNA expression levels of these markers in glomeruli which were isolated from the same formalin-fixed, paraffin-embedded kidney samples by laser microdissection. Among the examined podocyte markers, the immunopositive area and mRNA expression level of both podoplanin and synaptopodin were decreased in PAN glomeruli. The immunopositive area of podocin showed a slight decrease in PAN glomeruli, while its mRNA level showed no change. We have also identified a novel podocyte injury marker β-enolase, which was increased exclusively by podocytes in PAN glomeruli, similarly to another widely used marker, desmin. Thus, we have shown the specific application of a state-of-the-art computational method and retrospective mRNA expression analysis to quantitatively study the changes of various podocyte markers. The proposed methods will open new avenues for quantitative elucidation of renal glomerular histopathology.