Validation of reference genes for quantitative gene expression analysis in experimental epilepsy

Time- and Region-Specific Selection of Reference Genes in the Rat Brain in the Lithium-Pilocarpine Model of Acquired Temporal Lobe Epilepsy

Reverse transcription followed by quantitative polymerase chain reaction (RT-qPCR) is a commonly used tool for gene expression analysis. The selection of stably expressed reference genes is required for accurate normalization. The aim of this study was to identify the optimal reference genes for RT-qPCR normalization in various brain regions of rats at different stages of the lithium-pilocarpine model of acquired epilepsy. We tested the expression stability of nine housekeeping genes commonly used as reference genes in brain research: Actb, Gapdh, B2m, Rpl13a, Sdha, Ppia, Hprt1, Pgk1, and Ywhaz. Based on four standard algorithms (geNorm, NormFinder, BestKeeper, and comparative delta-Ct), we found that after pilocarpine-induced status epilepticus, the stability of the tested reference genes varied significantly between brain regions and depended on time after epileptogenesis induction (3 and 7 days in the latent phase, and 2 months in the chronic phase of the model). Pgk1 and Ywhaz were the most stable, while Actb, Sdha, and B2m demonstrated the lowest stability in the analyzed brain areas. We revealed time- and region-specific changes in the mRNA expression of the housekeeping genes B2m, Actb, Sdha, Rpl13a, Gapdh, Hprt1, and Sdha. These changes were more pronounced in the hippocampal region during the latent phase of the model and are thought to be related to epileptogenesis. Thus, RT-qPCR analysis of mRNA expression in acquired epilepsy models requires careful selection of reference genes depending on the brain region and time of analysis. For the time course study of epileptogenesis in the rat lithium-pilocarpine model, we recommend the use of the Pgk1 and Ywhaz genes.

Optimal Reference Genes for RT-qPCR Experiments in Hippocampus and Cortex of Rats Chronically Exposed to Excessive Fluoride

Normalization of the quantitative real-time PCR (RT-qPCR) data to the stably expressed reference genes is critically important for obtaining reliable results. However, all previous studies focused on F- toxicity for brain tissues used a single, non-validated reference gene, what might be a cause of contradictory or false results. The present study was designed to analyze the expression of a series of reference genes to select optimal ones for RT-qPCR analysis in cortex and hippocampus of rats chronically exposed to excessive fluoride (F-) amounts. Six-week-old male Wistar rats randomly assigned to four groups consumed regular tap water with 0.4 (control), 5, 20, and 50 ppm F- (NaF) for 12 months. The expression of six genes (Gapdh, Pgk1, Eef1a1, Ppia, Tbp, Helz) was compared by RT-qPCR in brain tissues from control and F--exposed animals. The stability of candidate reference genes was evaluated by coefficient of variation (CV) analysis and RefFinder online program summarizing the results of four well-acknowledged statistical methods (Delta-Ct, BestKeeper, NormFinder, and GeNorm). In spite of some discrepancies in gene ranking between these algorisms, Pgk1, Eef1a1, and Ppia were found to be most valid in cortex, while Ppia, Eef1a1, and Helz showed the greatest expression stability in hippocampus. Tbp and Helz were identified as the least stable genes in cortex, whereas Gapdh and Tbp are unsuitable for hippocampus. These data indicate that reliable mRNA quantification in the cortex and hippocampus of F--poisoned rats is possible using normalization to geometric mean of Pgk1+Eef1a1 or Ppia+Eef1a1 expression, respectively.

Mechanism of Robo1 in the pentylenetetrazol-kindled epilepsy mouse model

The neural network hypothesis is one of the important pathogenesis of drug-resistant epilepsy. Axons guide molecules through synaptic remodeling and brain tissue remodeling, which may result in the formation of abnormal neural networks. Therefore, axon guidance plays a crucial role in disease progression. However, although Robo1 is one of the important components of axon guidance, the role of Robo1 in epilepsy remains unclear. In this study, we aimed to explore the mechanism of Robo1 in epilepsy. Male adult C57BL/6 mice were intraperitoneally injected with pentylenetetrazol to establish an epilepsy model. Lentivirus (LV) was given via intracranial injection 2 weeks before pentylenetetrazol injection. Different expressions of Robo1 between the control group, LV-mediated Robo1 short hairpin RNA group, empty vector control LV group, and normal saline group were analyzed using Western blot, immunofluorescence staining, Golgi staining, and video monitoring. Robo1 was increased in the hippocampus in the pentylenetetrazol-induced epilepsy mouse model; lentiviral Robo1 knockdown prolonged the latency of seizure and reduced the seizure grade in mice and resulted in a decrease in dendritic spine density, while the number of mature dendritic spines was maintained. We speculate that Robo1 has been implicated in the development and progression of epilepsy through its effects on dendritic spine morphology and density. Epileptic mice with Robo1 knockdown virus intervention had lower seizure grade and longer latency. Follow-up findings suggest that Robo1 may modulate seizures by affecting dendritic spine density and morphology. Downregulation of Robo1 may negatively regulate epileptogenesis by decreasing the density of dendritic spines and maintaining a greater number of mature dendritic spines.

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

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.

Spatiotemporal Correlation of Epileptiform Activity and Gene Expression in vitro

Epileptiform activity alters gene expression in the central nervous system, a phenomenon that has been studied extensively in animal models. Here, we asked whether also in vitro models of seizures are in principle suitable to investigate changes in gene expression due to epileptiform activity and tested this hypothesis mainly in rodent and additionally in some human brain slices. We focused on three genes relevant for seizures and epilepsy: FOS proto-oncogene (c-Fos), inducible cAMP early repressor (Icer) and mammalian target of rapamycin (mTor). Seizure-like events (SLEs) were induced by 4-aminopyridine (4-AP) in rat entorhinal-hippocampal slices and by 4-AP/8 mM potassium in human temporal lobe slices obtained from surgical treatment of epilepsy. SLEs were monitored simultaneously by extracellular field potentials and intrinsic optical signals (IOS) for 1–4 h, mRNA expression was quantified by real time PCR. In rat slices, both duration of SLE exposure and SLE onset region were associated with increased expression of c-Fos and Icer while no such association was shown for mTor expression. Similar to rat slices, c-FOS induction in human tissue was increased in slices with epileptiform activity. Our results indicate that irrespective of limitations imposed by ex vivo conditions, in vitro models represent a suitable tool to investigate gene expression. Our finding is of relevance for the investigation of human tissue that can only be performed ex vivo. Specifically, it presents an important prerequisite for future studies on transcriptome-wide and cell-specific changes in human tissue with the goal to reveal novel candidates involved in the pathophysiology of epilepsy and possibly other CNS pathologies.

Selection and Validation of the Optimal Panel of Reference Genes for RT-qPCR Analysis in the Developing Rat Cartilage

Real-time fluorescence quantitative PCR (RT-qPCR) is widely used to detect gene expression levels, and selection of reference genes is crucial to the accuracy of RT-qPCR results. Minimum Information for Publication of RT-qPCR Experiments (MIQE) proposes that using the panel of reference genes for RT-qPCR is conducive to obtaining accurate experimental results. However, the selection of the panel of reference genes for RT-qPCR in rat developing cartilage has not been well documented. In this study, we selected eight reference genes commonly used in rat cartilage from literature (GAPDH, ACTB, 18S, GUSB, HPRT1, RPL4, RPL5, and SDHA) as candidates. Then, we screened out the optimal panel of reference genes in female and male rat cartilage of fetus (GD20), juvenile (PW6), and puberty (PW12) in physiology with stability analysis software of genes expression. Finally, we verified the reliability of the selected panel of reference genes with the rat model of intrauterine growth retardation (IUGR) induced by prenatal dexamethasone exposure (PDE). The results showed that the optimal panel of reference genes in cartilage at GD20, PW6, and PW12 in physiology was RPL4 + RPL5, which was consistent with the IUGR model, and there was no significant gender difference. Further, the results of standardizing the target genes showed that RPL4 + RPL5 performed smaller intragroup differences than other panels of reference genes or single reference genes. In conclusion, we found that the optimal panel of reference genes in female and male rat developing cartilage was RPL4 + RPL5, and there was no noticeable difference before and after birth.

Reference Gene Validation in the Brain Regions of Young Rats after Pentylenetetrazole-Induced Seizures

Reverse transcription followed by quantitative polymerase chain reaction (qRT-PCR) is a powerful and commonly used tool for gene expression analysis. It requires the right choice of stably expressed reference genes for accurate normalization. In this work, we aimed to select the optimal reference genes for qRT-PCR normalization within different brain areas during the first week following pentylenetetrazole-induced seizures in immature (P20–22) Wistar rats. We have tested the expression stability of a panel of nine housekeeping genes: Actb, Gapdh, B2m, Rpl13a, Sdha, Ppia, Hprt1, Pgk1, and Ywhaz. Based on geometric averaging of ranks obtained by four common algorithms (geNorm, NormFinder, BestKeeper, Comparative Delta-Ct), we found that the stability of tested reference genes varied significantly between different brain regions. The expression of the tested panel of genes was very stable within the medial prefrontal and temporal cortex, and the dorsal hippocampus. However, within the ventral hippocampus, the entorhinal cortex and amygdala expression levels of most of the tested genes were not steady. The data revealed that in the pentylenetetrazole-induced seizure model in juvenile rats, Pgk1, Ppia, and B2m expression are the most stable within the medial prefrontal cortex; Ppia, Rpl13a, and Sdha within the temporal cortex; Pgk1, Ppia, and Rpl13a within the entorhinal cortex; Gapdh, Ppia, and Pgk1 within the dorsal hippocampus; Rpl13a, Sdha, and Ppia within the ventral hippocampus; and Sdha, Pgk1, and Ppia within the amygdala. Our data indicate the need for a differential selection of reference genes across brain regions, including the dorsal and ventral hippocampus.

Selection of Reliable Reference Genes for RT-qPCR Analysis of Bursaphelenchus mucronatus Gene Expression From Different Habitats and Developmental Stages

Quantitative reverse transcription polymerase chain reaction (RT-qPCR), a sensitive technique for gene expression analysis, depends on the stability of the reference genes used for data normalization under different experimental conditions. Bursaphelenchus mucronatus, a pine-parasitic nematode varying in virulence, is widely distributed in natural pine forests throughout the northern hemisphere, but has not been investigated with respect to the identification of reference genes suitable for the normalization of RT-qPCR data. In the present study, eight candidate reference genes were analyzed in B. mucronatus under different habitat conditions and at different developmental stages. The expression stability of these genes was assessed by geNorm, NormFinder, BestKeeper, delta Cq, and RefFinder algorithms. In general, our results identified encoding beta-tubulin as the most stable gene. Moreover, pairwise analysis showed that three reference genes were sufficient to normalize the gene expression data under each set of conditions, with genes encoding beta-tubulin, 18S ribosomal RNA and ubiquitin-conjugating enzyme being the most suitable reference genes for different habitat conditions, whereas genes encoding beta-tubulin, histone, and 18S ribosomal RNA exhibited the most stable expression at different developmental stages. Validation of the selected reference genes was performed by profiling the expression of the fatty acid- and retinol-binding protein gene in different habitats, and by profiling the expression of the arginine kinase gene at different developmental stages. This first systematic analysis for the selection of suitable reference genes for RT-qPCR in B. mucronatus will facilitate future functional analyses and deep mining of genetic resources in this nematode.