Precise measurement of gene expression changes in mouse brain areas denervated by injury

Abstract

Abstract Quantitative PCR (qPCR) is a widely used method to study gene expression changes following brain injury. The accuracy of this method depends on the tissue harvested, the time course analyzed and, in particular on the choice of appropriate internal controls, i.e., reference genes (RGs). In the present study we have developed and validated an algorithm for the accurate normalization of qPCR data using laser microdissected tissue from the mouse dentate gyrus after entorhinal denervation at 0, 1, 3, 7, 14 and 28 days postlesion. The expression stabilities of ten candidate RGs were evaluated in the denervated granule cell layer (gcl) and outer molecular layer (oml) of the dentate gyrus. Advanced software algorithms demonstrated differences in stability for single RGs in the two layers at several time points postlesion. In comparison, a normalization index of several stable RGs covered the entire post-lesional time course and showed high stability. Using these RGs, we validated our findings and quantified glial fibrillary acidic protein (Gfap) mRNA and allograft inflammatory factor 1 (Aif1/Iba1) mRNA in the denervated oml. We compared the use of single RGs for normalization with the normalization index and found that single RGs yield variable results. In contrast, the normalization index gave stable results. In sum, our study shows that qPCR can yield precise, reliable, and reproducible datasets even under such complex conditions as brain injury or denervation, provided appropriate RGs for the model are used. The algorithm reported here can easily be adapted and transferred to any other brain injury model.