Transcriptome of the Wistar audiogenic rat (WAR) strain following audiogenic seizures

Transcriptome of the Wistar audiogenic rat (WAR) strain following audiogenic seizures

Epilepsy Research 147 (2018) 22–31 Contents lists available at ScienceDirect Epilepsy Research journal homepage: www.elsevier.com/locate/epilepsyres...

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Epilepsy Research 147 (2018) 22–31

Contents lists available at ScienceDirect

Epilepsy Research journal homepage: www.elsevier.com/locate/epilepsyres

Transcriptome of the Wistar audiogenic rat (WAR) strain following audiogenic seizures

T

Samara Damascenoa, Nathália Bustamante de Menezesa, Cristiane de Souza Rochac, Alexandre Hilário Berenguer de Matosc, André Schwambach Vieirac, Márcio Flávio Dutra Moraesb, Almir Souza Martinsb, Iscia Lopes-Cendesc, ⁎ Ana Lúcia Brunialti Godarda, a b c

Departamento de Biologia Geral, Universidade Federal de Minas Gerais, Pampulha, CEP 31270-901, Belo Horizonte, MG, Brazil Departamento de Fisiologia e Biofísica, Universidade Federal de Minas Gerais, Pampulha, CEP 31270-901, Belo Horizonte, MG, Brazil Departamento de Genética Médica, Faculdade de Ciências Medicas, Universidade de Campinas, Cidade Universitária Zeferino Vaz, CEP 13083-887, Campinas, SP, Brazil

A R T I C LE I N FO

A B S T R A C T

Keywords: Audiogenic epilepsy RNA-Seq Seizure Transcriptome WAR

The Wistar Audiogenic Rat (WAR) is a model whose rats are predisposed to develop seizures following acoustic stimulation. We aimed to establish the transcriptional profile of the WAR model, searching for genes that help in understanding the molecular mechanisms involved in the predisposition and seizures expression of this strain. RNA-Seq of the corpora quadrigemina of WAR and Wistar rats subjected to acoustic stimulation revealed 64 genes differentially regulated in WAR. We validated twelve of these genes by qPCR in stimulated and naive (nonstimulated) WAR and Wistar rats. Among these, Acsm3 was upregulated in WAR in comparison with both control groups. In contrast, Gpr126 and Rtel1 were downregulated in naive and stimulated WAR rats in comparison with the Wistar controls. Qdpr was upregulated only in stimulated WAR rats that exhibited audiogenic seizures. Our data show that there are genes with differential intrinsic regulation in the WAR model and that seizures can alter

Abbreviations: 5-HT, Serotonin; Acsm3, Acyl-CoA synthetase medium-chain family member 3; Acsm5, Acyl-CoA synthetase medium-chain family member 5; aGPCR, G protein-coupled adhesion receptors; ANOVA, analysis of variance; AS, audiogenic seizure; BH4, tetrahidropteridina; C1ql2, complement C1q like 2 ; Calcr, calcitonin receptor; Camk2g, calcium/calmodulin-dependent protein kinase II gamma ; Chrna4, cholinergic receptor, nicotinic, alpha 4; Ctxn3, cortexin 3; DA, dopamine; DBA/2, dilute brown non-agouti 2; Ddi2, DNA damage inducible 1 homolog 2; DESeq, R package to analyses count data from high-throughput sequencing assays; DHPR, dihydropteridine reductase; Dlk1, delta like non-canonical notch ligand 1; Dstnl1, destrin-like 1; EdgeR, package for the differential expression analysis of digital gene expression data; Egr1, early growth response 1; Egr2, early growth response 2; Egr3, early growth response 3; Eqtn, equatorin; FastQC, quality control tool for high-throughput sequence data; FDR, false discovery rate; featureCounts, R function designed for summarizing sequencing reads to genomic features; Fhad1, Forkhead associated phosphopeptide binding domain 1; Fut9, fucosyl transferase 9; GAERS, genetic absence epilepsy rat from Strasbourg; GASH-Sal, genetic audiogenic seizure hamster from Salamanca; Gda, guanine deaminase; Gdi2, GDP dissociation inhibitor 2; GEP, Genetically epilepsy-prone; GEPR, Genetic epilepsy prone rats; Ghdc, GH3 domain containing; GLUR2, glutamate receptor, ionotropic, AMPA 2; GO, gene ontology; Gpr126, adhesion G protein-coupled receptor G6; Gria2, glutamate ionotropic receptor AMPA type subunit 2; Grifin, galectin-related inter-fiber protein; Hlcs, holocarboxylase synthetase; HTSeq, python package to work with high-throughput sequencing; IC, Inferior colliculus; Kcnip3, potassium voltage-gated channel interacting protein 3; Kcnq2, potassium voltage-gated channel subfamily Q member 2; Lrp4, LDL receptor related protein 4; Mfrp, membrane frizzled-related protein; Mylk, myosin light chain kinase; NCBI, National Center for Biotechnology Information; Ndc1, NDC1 transmembrane nucleoporin; Ndufa10, NADH dehydrogenase (ubiquinone) 1 alpha subcomplex 10; Nek3, NIMArelated kinase 3; NO, nitric oxide; Nr2f2, nuclear receptor subfamily 2, group F, member 2; Nudt12, nudix hydrolase 12; Opalin, oligodendrocytic myelin paranodal and inner loop protein; PCA, principal component analysis; Pcdha7, protocadherin alpha 7; Pex11a, peroxisomal biogenesis factor 11 alpha; PND, postnatal day; Polr3k, RNA polymerase III subunit K; Psmg3, proteasome assembly chaperone 3; Pyroxd2, pyridine nucleotide-disulphide oxidoreductase domain 2; Qdpr, quinoid dihydropteridine reductase; Ralgapa2, Ral GTPase activating protein catalytic alpha subunit 2; RNA-Seq, RNA sequencing; Rpl30, ribosomal protein L30; Rps26, ribossomal protein S26; Rtel1, regulator of telomere elongation helicase 1; SC, superior colliculus; Scel, sciellin; SI, severity index; Slc10a4, solute carrier family 10, member 4; Slc17a8, solute carrier family 17 member 8; Slc18a2, solute carrier family 18 member A2; Slc35c2, solute carrier family 35 member C2; Slc6a4, solute carrier family 6 member 4; Slc7a11, solute carrier family 7 member 11; Smoc1, SPARC related modular calcium binding 1; Spc25, SPC25, NDC80 kinetochore complex component; St5, suppression of tumorigenicity 5; St7l, suppression of tumorigenicity 7-like; Tph2, tryptophan hydroxylase 2; Trpv5, transient receptor potential cation channel, subfamily V, member 5; WAR, Wistar audiogenic rat; WAR-N, Wistar audiogenic rats naive; WAR-S, Wistar audiogenic rats stimulated; WisN, Wistar rats naive; Wis-S, Wistar rats stimulated; Ybx1-ps3, Y box protein 1 related, pseudogene 3 ⁎ Corresponding author at: Laboratório de Genética Animal e Humana, Departamento de Biologia Geral - B2-179, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais – UFMG, Avenida Antônio Carlos, 6627 - Campus Pampulha, Belo Horizonte, MG, CEP 31270-901, Brazil. E-mail address: [email protected] (A.L.B. Godard). https://doi.org/10.1016/j.eplepsyres.2018.08.010 Received 31 May 2018; Received in revised form 24 July 2018; Accepted 27 August 2018 Available online 29 August 2018 0920-1211/ © 2018 Elsevier B.V. All rights reserved.

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gene regulation. We identified new genes that might be involved in the epileptic phenotype and comorbidities of the WAR model.

1. Introduction

et al., 2010). However, molecular studies on corpus quadrigeminum are still scarce. The increase in the cytokine levels was observed in the IC and cortex of WAR that showed seizures (Bernardino et al., 2015), and recently, López-López et al. (2017) compared the WAR with another model of AS named GASH-Sal and demonstrated, through a large-scale analysis, that the transcript levels of Egr1, Egr2 and Egr3 were altered in the IC of both strains as a consequence of the seizures (López-López et al., 2017). We investigated the differences in gene regulation in the WAR strain, in an attempt to elucidate the molecular processes related to AS susceptibility and initiation. We established the transcriptional profile of the corpus quadrigeminum in WAR by RNA-Seq (RNA Sequencing) and showed that seizures can alter gene regulation in this structure. Additionally, we demonstrated the existence of genes differentially expressed in the WAR model, regardless of the occurrence of seizures.

Epilepsy is characterised by the predisposition to recurrent seizures, and affects around 50 million people in the world today (Fisher, 2015; World Health Orgazization (WHO, 2017). It may have genetic, metabolic or structural components, but for many cases, the causes are unknown (Berg and Scheffer, 2011; Shorvon, 2011). To worsen the scenario, the treatment options currently available are ineffective for approximately 30% of the patients (World Health Orgazization (WHO, 2017). In an attempt to better understand this complex neurological disorder and to develop new therapeutic strategies, research heavily depends on a myriad of animal models that target different aspects of the disease (Grone and Baraban, 2015; Kandratavicius et al., 2014; Serikawa et al., 2015). The epilepsy models established by selective reproduction are preferred for studies targeting the genetic predisposition of the animals to develop seizures, precluding the influence of the artificially induced ictogenic process (Kandratavicius et al., 2014; Serikawa et al., 2015). In this context stand out the audiogenic models, that is reflex epilepsy models whose animals are predisposed to develop seizures induced by acoustic stimulation - named Audiogenic Seizures (AS). Studies about those models go beyond reflex epilepsy, also used on temporal lobe epilepsy and epilepsy’s comorbidities investigation (Kandratavicius et al., 2014). Furthermore, genetic predisposition and characterization of alterations caused by epileptic seizures allow AS models to be used to understand ictogenic and epileptogenic processes (De Sarro et al., 2017; Kandratavicius et al., 2014). The Wistar Audiogenic Rat (WAR) is a genetic model of reflex epilepsy in which rats develop AS tonic-clonic generalized induced by high-intensity acoustic stimulation (120 dB SPL stimulus) (Doretto et al., 2003). Nevertheless, it is important to highlight that the WAR seizure susceptibility is not restricted to acoustic stimulation and presents lower thresholds to many other pro-convulsive stimuli, such as transauricular electroshock, pilocarpine and pentylenetetrazol (Magalhães et al., 2004; Scarlatelli-Lima et al., 2003). Several audiogenic models have been reported throughout literature (Muñoz et al., 2017; Poletaeva et al., 2017; Ribak, 2017), accumulating evidence suggesting that the corpus quadrigeminum, comprised of inferior and superior colliculus (IC and SC), is a critical structure for AS development (Garcia-Cairasco et al., 1993; Garcia-Cairasco, 2002). The IC is crucial in the initiation and transmission of the paroxysmal activity (Faingold, 2004; Garcia-Cairasco et al., 1993; Ross and Coleman, 2000; Rossetti et al., 2006). Furthermore, during a protocol of daily AS stimulation, the IC plays an important role in the kindling of forebrain structures into seizures - a phenomenon known as Audiogenic Kindling (Moraes et al., 2000). The SC, on the other hand, integrates sensorial and motor areas and is also involved in the propagation of abnormal activity during AS (Faingold, 2004; Garcia-Cairasco, 2002; Ross and Coleman, 2000; Rossetti et al., 2006). After more than 50 generations of inbred crosses, the WAR shows continuously increased homozygosity and gene linkage (GarciaCairasco et al., 2017) with consequent phenotypic homogeneity of the seizures (Doretto et al., 2003). However, the model still lacks studies that correlate its genetic-molecular aspects with AS susceptibility (Garcia-Cairasco et al., 2017). In order to understand the epileptogenic process of the WAR strain, studies have shown alterations in gene expression on animals that had epileptic seizures. The GluR2-flip variant of the glutamate receptor in the hippocampus of WAR after the seizures (Gitaí et al., 2010); the up-regulation of the angiotensin-converting enzyme (ACE) and of a receptor of the renin-angiotensin system in the hippocampus of WAR subjected to repetitive stimulations (Pereira

2. Material and methods 2.1. Animals and experimental design Sixteen WAR and sixteen Wistar 70 days’ old (PND-70) male rats were provided by the Animal Facility of the University Federal de Minas Gerais (ICB-UFMG). Animals were kept under a 12/12 h light-dark cycle, room temperature of 22 ± 1 °C, with food and water ad libitum. All applicable international, national, and institutional guidelines for the care and use of animals were followed and the study was approved by the Ethics Committee for Animal Use of UFMG (CEUA-UFMG), protocol number 251/2012. Rats were divided into four groups of eight animals each: Wistar naive (Wis-N), WAR naive (WAR-N), Wistar stimulated (Wis-S), and WAR stimulated (WAR-S). Animals in the naïve groups were not subjected to acoustic stimulation, whereas animals in the latter two groups were subjected to three presentations of high-intensity acoustic stimulus with interval of 48 h according protocol (Bernardino et al., 2015; Garcia-Cairasco et al., 2004; Rossetti et al., 2006, 2012). This stimulus was applied individually for 60 s each or until the beginning of the seizure. The stimulus is the sound of a ring bell recorded on an audiotape digitalized with a high pass filter (> 500 Hz) and reproduced by a computer coupled to amplifiers and tweeters in the upper side of the cage (120 dB) (Rossetti et al., 2006). During stimulation, animals were evaluated by the severity index (SI) (Doretto et al., 2003; GarciaCairasco et al., 1996) (Table S1). The Wis-S group was composed of Wistar rats that did not respond to sound and Wistar rats that responded to sound with wild running and jumping. All of the Wistar rats presented severity index less or equal 0.23 (SI ≤ 0.23). The WAR-S group was composed of WARs that presented generalized tonic-clonic seizures and clonic spasms. All of the WAR presented severity index greater or equal 0.85 (SI ≥ 0.85) in three stimulations. In order to avoid the identification of immediate expression genes, at PND-80 (96 h after the last stimulation) all the animals were euthanised and had their brains removed. The corpora quadrigemina were dissected and stored at −80 °C until ready for RNA extraction procedure (Fig. S1). 2.2. Total RNA isolation Total RNA was extracted from 32 samples using TRIzol Reagent (Invitrogen), according to manufacturer’s instructions. The pellets were each resuspended in 20 μL of Ultrapure water (Qiagen). Total RNA was quantified using DS-11 Spectrophotometer (DeNovix) and Qubit 2.0 Fluorometer (Invitrogen). All the samples presented 260/230 nm and 260/280 nm ratios ≥ 1.8. RNA integrity was verified by electrophoresis 23

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were compared using one-way ANOVA followed by Tukey’s multiple comparisons test. The relationship among the genes was evaluated by Pearson’s correlation. Analyses were performed using GraphPad Prism (version 6.05). Results were considered statistically significant at p < 0.05.

on a 1% agarose gel. 2.3. RNA-Seq and data analysis RNA samples of the corpora quadrigemina of two rats from each of the groups Wis-S and WAR-S were used for sequencing. One μg of total RNA of each sample was used to prepare the libraries according to the TruSeq RNA Sample Preparation kit v2 Guide (Illumina). Following the validation of the libraries, paired-end sequencing was performed in the Illumina Miseq platform of the Laboratório de Biotecnologia e Marcadores Moleculares (UFMG, Brazil). Raw sequence reads were assessed for sequencing quality using FastQC (version 0.11.5), which attributes values of the identification of the sequences according to the error rate using the Phred quality score (0–40). Following this initial evaluation, data were submitted for trimming by the software Cutadapt, which removes the sequences of the adapters and excludes reads with Phred values < 25. The reference genome sequence Rattus novergicus (R.nor 6.0) was obtained from the NCBI database and the filtered reads were mapped using the software Bowtie2 (version 2.2.4.0). The identification of differentially regulated genes was performed using different types of software. The genes were counted using the software HTseq and featureCounts, and the differential expression between the two groups was calculated using the software DESeq and EdgeR. Genes presenting False discovery rate (FDR) ≤ 0.05 were considered differentially expressed (Fig. 1). The principal component analysis (PCA) was performed in R and functional annotation was performed using the Gene Ontology (GO) Consortium database.

3. Results 3.1. Transcriptome analysis The transcriptional profiles were established for the animals subjected to the acoustic stimulation, WAR-S and Wis-S groups. This approach allowed us to identify genes differentially regulated in WAR that presented AS. We collected the corpora quadrigemina 96 h after the last stimulus to verify the differential regulation outside the post-ictal period in order to identify genes that are not immediate-early response. The sequencing generated high-quality data, resulting in up to 8.2 million reads per library, with an average fragment size of 151 pb. The low error rate observed reflected the trimming stage, in which over 99.8% of the reads were approved. Following filtering, each library had more than 80% of the pairs aligned to the reference genome (Table 1). The analysis using the software featureCounts and EdgeR identified 62 genes differentially expressed between WAR-S and Wis-S groups, considering an FDR ≤ 0.05, 27 up-regulated and 35 down-regulated in

2.4. Primer design Gene sequences were obtained from the Ensembl Genome Browser database and primer pairs were designed aligned in different exons, using the software Primer3 v.0.4.0 (Table S2). Quality and specificity were evaluated using the software NetPrimer and Primer-BLAST, respectively. Primers were synthesized by IDT - Integrated DNA Technologies (Síntese Biotecnologia) and tested by conventional PCR and electrophoresis on a 1% agarose gel. 2.5. Reverse transcription and quantitative PCR Reverse transcription reaction was carried out with total RNA from 32 samples from all groups using the RevertAID Reverse Transcriptase (Thermo Fisher Scientific) according to manufacturer’s instruction. Quantitative PCR (qPCR) was performed using the CFX 96 T M Real Time system (BioRad) and the protocol of the intercalating agent SYBR Fast qPCR Kit Master Mix (Kapa Biosystems). The efficiency of the primers was verified through a dilution series curve. Calculated efficiencies showed < 10% variation between the target genes and the reference genes. We quantified transcript levels of cDNA samples from all the groups (Wis-N, Wis-S, WAR-N and WAR-S). Samples were analysed in duplicates, with each reaction containing: 10 μL of SYBR Fast qPCR Master Mix; 1 μL of cDNA (10 ng); 0.4 μL of each primer (forward and reverse, 10 μM); and 8.2 μL DNAse and RNAse-free water. In all the reactions, we used a negative control without sample and the melting curves were analysed to assure the absence of spurious products. The housekeeping genes Gdi2 (GDP dissociation inhibitor 2) and Rps26 (Ribosomal protein S26) were selected as reference genes. Transcript levels were normalized using the Wis-N group as the calibrator, and data of quantification cycles (Cqs) were analysed according to Vandesompele et al., (2002).

Fig. 1. Flowchart of mRNA sequencing data analysis. mRNA samples of the corpora quadrigeminas of two rats from of the groups Wis-S and WAR-S were sequenced. The raw data were evaluated by the FastQC quality control tool and submitted to trimming by the software Cutadapt, excluding reads with Phred values < 25. The filtered reads were mapped using reference genome sequence R.nor 6.0 (Rattus novergicus) and the software Bowtie2. The genes were counted using the software HTseq and featuresCounts, and the differential expression was calculated using the software DESeq and EdgeR considering FDR values ≤ 0.05. The analysis using EdgeR identified 62 genes differentially regulated and using DESeq identified 16 genes, 14 of them identified in both analyses.

2.6. Statistical analyses Relative quantification data were tested for normality using the D’Agostino-Pearson and Shapiro-Wilk tests. Relative mRNAs quantities 24

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in WAR-N and WAR-S groups in comparison with the control group Wis-N. Chrna4 (F3,28 = 16.63; p < 0.0001) was down-regulated in both WAR groups in comparison with the controls but showed upregulation in WAR that were stimulated (WAR-S) and had the AS in comparison with the naive WAR (WAR-N). The transcriptional profile of Kcnq2 was similar to that of Rtel1, with a strong positive correlation (r = 0.8428; p < 0.0001), whereas Chrna4 and Rtel1 showed a moderate correlation (r = 0.6704; p < 0.0001).

Table 1 RNA-Seq data. Number of reads in the raw data processing steps of the sequenced libraries. Library

Raw data Paired reads

Clean reads Remaining reads (%)

Mapping to Genome Paired reads aligned (%)

Wis-S 1 Wis-S 2 WAR-S 1 WAR-S 2

3926374 8299803 3489721 7669330

3921335 8289375 3485349 7657548

3195372 7088221 3054089 6529241

(99.87) (99.87) (99.87) (99.84)

(81.48) (85.50) (87.62) (85.26)

4. Discussion WAR that had seizures (Table S3). The more robust analysis using HTseq and DESeq revealed 16 genes differentially expressed (Table 2), 14 of which had been previously identified by EdgeR (Fig. 2A). PCA analysis of the transcripts resulted in the grouping of the two samples from stimulated Wistar (Wis-S1 and Wis-S2) and the two from stimulated WAR (WAR-S1 and WAR-S2); the first principal component represented 95.8% of the variance of the expression data (Fig. 2B). We performed GO functional annotation of the all genes differentially regulated (64 genes) using the database from the Gene Ontology Consortium and identified six categories of cellular components, six categories of molecular functions and nine categories of biological processes (Fig. 3). Based on the molecular functions, the category “catalytic activity” had the highest number of differentially regulated genes. Based on the biological process, the category “cellular process” was the most represented followed by the category “metabolic process”. This category included genes from different metabolic pathways: Acsm3 (Acyl-CoA synthetase medium-chain family member 3), Acsm5 (AcylCoA synthetase medium-chain family member 5), Fut9 (Fucosyl transferase 9), Gda (Guanine deaminase), Hlcs (Holocarboxylase synthetase), Ndufa10 (NADH dehydrogenase (ubiquinone) 1 alpha subcomplex 10), Nr2f2 (Nuclear receptor subfamily 2, group F, member 2), Nudt12 (Nudix hydrolase 12), Polrk3 (RNA polymerase III subunit K), Qdpr (Quinoid dihydropteridine reductase), Ralgapa2 (Ral GTPase activating protein catalytic alpha subunit 2), Rtel1 (Regulator of telomere elongation helicase 1).

Transcriptomic analysis of the corpora quadrigemina of WAR and Wistar rats after acoustic stimulation allowed us to identify a set of 62 differentially regulated genes at the epileptic model using EdgeR software and 16 genes using DESeq software. PCA of the transcripts of these genes revealed grouping of Wistar samples separated from the WAR, indicating that the variance in the data of the transcripts was explained by the phenotypic differences observed. GO enrichment analysis showed that “catalytic activity” and “metabolic processes” categories were among the most represented functional categories of the genes differentially regulated in WAR suggesting that the model presents metabolic alterations. This result is further evidence to support the hypothesis that reproductive selection of WARs for AS susceptibility resulted in changes in multiple levels of metabolic regulation as reported by Botion and Doretto, (2003). By qPCR we evaluated the amount of transcripts from ten genes identified as differentially regulated in which four transcriptional profiles stood out: Acsm3, Gpr126, Rtel and Qdpr. The Acsm3 gene was exorbitantly up-regulated in the corpus quadrigeminum of WAR in comparison with the Wistar controls. This gene belongs to the metabolic processes category and just as Acsm5, Ndufa10 and Nudt12 are specifically involved in mitochondrial metabolism. Acsm3 encodes a coenzyme (acyl-CoA synthetase) that activates medium-chain fatty acids favouring their entrance in the mitochondria, where they go through beta-oxidation with consequent generation of acetyl-CoA (Ellis et al., 2015). The up-regulation of Acsm3 gene had also been reported in a microarray analysis of IC of WAR from colony maintained at the University of São Paulo (López-López et al., 2017) and isolated for more than 20 years from the colony maintained at the Federal University of Minas Gerais (Garcia-Cairasco et al., 2017), suggesting that the observed transcriptional profile is characteristic of the WAR strain and corroborating the hypothesis that this model presents metabolic alterations. Acsm3, also known as Sah, has already had a gene locus related to arterial blood pressure control in rats (Frantz et al., 1998; Harris et al.,

3.2. Quantitative PCR We evaluated the transcript levels of the genes identified in both analyses: Acsm3, Gpr126, Rtel1, Qdpr, Slc35c2, Dstnl1, Slc18a2, Tph2, Ddi2, Fhad1, Rpl30 and Acsm5. We compared the groups of animals subjected to acoustic stimulation (Wis-S and WAR-S) with the groups of animals that were not stimulated (Wis-N and WAR-N). The inclusion of the non-stimulated (naive) groups generated a better perception of the transcriptional profile and allowed us to determine whether the differences in transcript levels were due to specificities of this strain or whether they were modulated by ictogenic process. We did not evaluate the open read frames (LOC102555474; LOC103693813) as they did not have defined products and sequences. Among the analysed genes, four stood out for their transcriptional profiles (Fig. 4A–D). One-way ANOVA followed by post hoc comparison of the groups revealed that Acsm3 (F3,27 = 176.0; p < 0.0001) was up-regulated in WAR-N and WAR-S when compared with the controls. However, when we compared the two WAR groups, the gene was down-regulated in WAR-S in comparison with WAR-N. Gpr126 (F3,28 = 41.11; p < 0.0001) and Rtel1 (F3,28 = 60.85; p < 0.0001) were down-regulated in WAR-N and WAR-S groups in comparison with the control groups (Wis-N and WisS). Qdpr (F3,27 = 11.80; p < 0.0001), on the other hand, was upregulated in WAR-S rats in comparison with the other groups (Wis-N, Wis-S and WAR-N). The qPCR results for the other genes are presented in the Supplementary Material (Fig. S2). Following the analyses of the genes identified by DESeq, we evaluated other genes that are in linkage disequilibrium with Rtel1 and that could help in understanding the epileptic phenotype: Kcnq2 and Chrna4 (Fig. 4E–F). Kcnq2 (F3,28 = 34.90; p < 0.0001) was down-regulated

Table 2 Genes identified as differentially expressed in the analysis by software DESeq, with FDR ≤ 0.05. Gene symbol

log2 fold change

p-value

FDR

Ddi2 Fhad1 LOC102555474 Slc35c2 Qdpr LOC103693813 Acsm3 Acsm5 Gria2 * Ndufa10 * Slc18a2 Rtel1 Rpl30 Gpr126 Dstnl1 Tph2

0.8802 0.8196 0.7467 0.6482 0.6016 0.5868 0.5034 0.4896 0.4252 −0.5211 −0.6762 −0.7068 −0.7453 −0.9645 −1.1976 −1.3987

5.68E-13 3.67E-09 1.63E-10 4.82E-06 1.44E-08 1.81E-07 1.56E-05 2.11E-05 4.60E-05 6.40E-07 1.72E-06 2.10E-07 2.52E-08 1.86E-12 4.50E-19 7.72E-24

2.81E-09 9.05E-06 4.83E-07 5.49E-03 3.05E-05 2.98E-04 1.65E-02 2.08E-02 4.26E-02 8.62E-04 2.12E-03 3.11E-04 4.67E-05 6.90E-09 3.33E-15 1.14E-19

* Genes not recognised as differentially expressed by the software EdgeR. 25

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In the present study, we verified that the WAR model shows downregulation of Gpr126 in the corpus quadrigeminum. It is hard to speculate about the possible alterations in the myelination of the neurons in this structure, as central nervous system myelination is performed by oligodendrocytes and the Gpr126 receptor seems to be dispensable in this process (Monk et al., 2011). Nevertheless, we believe that Gpr126 gene down-regulated, also observed in WAR from University of São Paulo’s colony, is most likely due to the selection process of the lineage and may have contributed for the development of the epileptic phenotype. The Rtel1 gene was down-regulated in WAR-N and WAR-S in comparison with the Wistar controls, regardless of the occurrence of seizures. This gene encodes a helicase that acts in the protection, stability and elongation of telomeres (Le Guen et al., 2013). Several studies have reported variants of this gene associated with cerebral tumours, conferring higher susceptibility to high-grade glioma, astrocytomas and glioblastomas (Jin et al., 2013; Vannier et al., 2014; Fahmideh et al., 2015; Ghasimi et al., 2016); and it is known that seizures are very common in patients with cerebral tumours (Kerkhof and Vecht, 2013; Koekkoek et al., 2014; Maschio, 2012). However, there are no reports of the direct association of Rtel1 with epilepsy so far. In humans, this gene is located on the short arm of chromosome 20 (20q13.33), in a chromosomic region associated with ring chromosome 20 syndromes, which is mainly characterised by refractory epilepsy and mental retardation (Conlin et al., 2011; Yip, 2015). The cause of this syndrome remains uncovered, but it may be related to the haploinsufficiency of two other genes located in the same region: Kcnq2 and Chrna4, both previously associated with epilepsy (Conlin et al., 2011; Elghezal et al., 2007). In rats, the Rtel1 gene is located on chromosome 3 (3q43) also in linkage disequilibrium with Kcnq2 and Chrna4. Therefore, we also evaluated the transcript levels of these genes in the corpus quadrigeminum to investigate their possible involvement on the WAR epileptic phenotype Kcnq2 gene presented a transcriptional profile similar to the Rtel1 gene with a strong positive correlation between them. Mutations in the Kcnq2 are associated with benign familial neonatal seizures (Singh et al., 1998; Charlier et al., 1998; Zara et al., 2013) and early onset epileptic encephalopathy (Abidi et al., 2015; Allen et al., 2014; Weckhuysen et al., 2012). This gene encodes a subunit to a voltagegated potassium channel also known as M-channel that mediates a lowthreshold neuronal current, M-current (Richard et al., 2004). M-currents regulate neuronal excitability by the firing properties of neurons and their response to synaptic input (Richard et al., 2004; Wang et al., 1998). In this way, channel activity limits the repetitive firing and tends to stabilize the membrane potential (Jin et al., 2009; Peters et al., 2005). Functional changes or reduction in the number of M channels can cause suppression of M-currents resulting in the increase of neuronal excitability (Peters et al., 2005; Robbins et al., 2013). Therefore, the down-regulated of Kcnq2 in WAR may be an indication of the scarcity of these channels on the corpus quadrigeminum and this gene may be involved in the lack of control of neuronal excitability favouring the development of seizures in WAR Chrna4 was down-regulated in WAR when compared to Wistar controls and up-regulated in WAR that presented seizures in relation to naive WAR. This gene encodes a subunit of the nicotinic acetylcholine receptor (nAChR) that is permeable to cations and leads to depolarization of the plasma membrane leading to a postsynaptic excitatory potential (Becchetti et al., 2015; Ghasemi and Hadipour-Niktarash, 2015). Mutations in Chrna4 are associated with nocturnal frontal lobe epilepsy (Hirose et al., 1999; Leniger et al., 2003; Steinlein et al., 1995, 1997) and febrile seizures (Chou et al., 2003) and were related to increasing the receptors sensitivity to acetylcholine, reduce calcium permeability and rapid desensitization of nAChR (Bertrand et al., 2002; Combi et al., 2004; Kuryatov et al., 1997; Moulard et al., 2001; Weiland et al., 1996). It is believed that the reduction of nAChR activity may disrupt the balance between neuronal excitation and inhibition (Kuryatov et al., 1997). In this context, the Chrna4 down-regulated in

Fig. 2. A: Diagram representing the number of genes identified as differentially regulated among the groups WAR-S and Wis-S, using the selection criterium of FDR ≤ 0.05 in both software: EdgeR and DESeq. B: Plot of the two principal components of variance for the transcripts of the genes identified as differentially regulated. Red: samples Wis-S 1 and Wis-S 2. Black: samples WAR-S 1 and WAR-S 2 (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).

1993; Iwai and Inagami, 1992). Fazan et al. (2011) when comparing blood pressure of males young adults (PND-70) of WAR and naive Wistar, reported mild hypertension in audiogenic animals. Therefore, this gene dysregulation seems not to be directly related to the epileptic phenotype but to hypertension, comorbidity associated with the model. The Gpr126 gene was down-regulated in WAR-N and WAR-S in comparison with Wistar rats, in agreement with the study by LópezLópez et al. (2017). The down-regulation of this gene independent of the occurrence of seizures indicates that its regulation is inherent to the WAR strain and possibly a result of selective reproduction that led to its generation. Gpr126 encodes a receptor (Gpr126) from the family of G protein-coupled adhesion receptors (aGPCR) (Patra et al., 2014). Gpr126 was characterised by Moriguchi et al. (2004) and had its biological function elucidated through studies in zebrafish, which revealed its importance for the onset of myelination in the peripheral nervous system (PNS) due to its role in the maturation of Schwann cells (Langenhan et al., 2016; Glenn and Talbot, 2013; Mogha et al., 2013; Monk et al., 2009). Gpr126 is also important for the morphogenesis of the semi-circular channel of the inner ear in zebrafish (Geng et al., 2013). Altogether, these reports suggest that the differential expression of this receptor could be associated with alterations in the acquisition or the processing of acoustic information. Although the physiological activities of Gpr126 are not yet fully understood in mammals, but its function in peripheric myelination is conserved (Monk et al., 2011; Mogha et al., 2013; Langenhan et al., 2016). In rodents, Gpr126 is required for embryonic development (Waller-Evans et al., 2010) and lossof-function mutations in Gpr126 result in embryonic lethality, mainly due to cardiovascular defects (Monk et al., 2011; Waller-Evans et al., 2010). This type of mutation also results in lack of peripheric myelination, extension of central myelination in the central-peripheral transitional zone, and abnormal organisation of perineurial fibroblasts (Monk et al., 2011). 26

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Fig. 3. Functional annotation of the genes identified as differentially regulated. X-axis: functional categories. Y-axis: number of genes up- and down-regulated in each category. Two genes and the open read frames were not annotated in the GO database.

GERPs, have been reported with deficiency of 5-HT and noradrenaline (NA) which DA is precursor (De Sarro et al., 2017). 5-HT is generally considered in the epileptic events inhibition and its depletion in the brain has been related to lower threshold to audiogenically, chemically and electrically evoked seizures (Bagdy et al., 2007; Gharedaghi et al., 2014). 5-HT is involved in the action mechanism of anticonvulsant drugs such as valproate, carbamazepine and lamotrigine (Mainardi et al., 2008; Theodore, 2003). The increase extracellular concentration such as inhibition of 5-HT reuptake are process related to its anticonvulsive effect (Bagdy et al., 2007; Mainardi et al., 2008; Theodore, 2003). In contrast, the studies of DA are controversial about its involvement in seizures. It is believed that DA acts as proconvulsant through the D1 receptors activation, whereas D2 receptors are considered in anticonvulsive effect (Bozzi and Borrelli, 2013). The NO exerts an effect or another depending on its interaction with others molecules present (Han et al., 2000; Kovács et al., 2009; Hrnčić et al., 2012). The inhibitor of NO synthesis, L-NG-nitroarginine (LNOARG) was reported to potentiate seizures induced by kainic acid (Tutka et al., 1996) and bicuculline (Wang et al., 1994). However, the L-NG-nitroarginine methyl ester (L-NAME) seems to attenuate seizures induced by focal injection of NMDA or kainic acid (De Sarro et al., 1991, 1993) while the inhibitor 7-nitroindazole is able to increase the protective activity of some conventional antiepileptics (De Sarro et al., 2000). It has been demonstrated that NO levels increase deeply during seizures in the genetic model of absence seizures (GAERS) (Bashkatova et al., 2003; Faradji et al., 2000; Zhu et al., 2016), in animal models

WAR in relation to the controls suggests a smaller number of receptors and a consequent reduction of the synaptic process exerted by them. Therefore, the Chrna4 gene may be related to the epileptic phenotype due to its involvement in the imbalance between the excitatory and inhibitory processes. In addition, this gene has been shown to be modulated by the ictal events as observed on its up-regulated on stimulated WARs when compared with the naïve. The transcriptional profile of Qdpr (up-regulated only in the WAR-S group) indicated that the regulation of this gene is a response to the ictal events. López-López et al. (2017) showed that the occurrence of a single epileptic episode can cause immediate alteration in the regulation of some genes but did not report Qdpr. We observed the up-regulation of Qdpr 96 h after the last of three episodes of seizures. This suggests that the up-regulation of Qdpr is not just an immediate response but also an adaptation of the cells to the epileptic insults in order to recover the homeostasis. This gene encodes the enzyme Dhpr (Dihidopterina redutase quinoide) that is responsible for recycling of BH4 (Tetrahidropteridina), a molecule that acts as enzyme cofactor and is involved in the synthesis of serotonin (5-HT), dopamine (DA) and nitric oxide (NO) (Werner et al., 2011). Dhpr deficiency impairs BH4 regeneration and may reduce the levels of serotonin and dopamine (Ng et al., 2014). We believe that the up-regulation of Qdpr, with the consequent up-expression of Dhpr and increase in BH4 levels, might influence synthesis of this monoamines and NO. The involvement of these three neurotransmitters in seizures have been previously described and two audiogenic models, DBA/2 and 27

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Fig. 4. Relative quantities of transcripts in the corpora quadrigemina. A: Acsm3 (F3,27 = 76.0); B: Grp126 (F3,28 = 41.11); C: Rtel1 (F3,28 = 60.85); D: Qdpr (F3,27 = 11.80); E: Kcnq2 (F3,28 = 34.90); F: Chrna4 (F3,28 = 16.63). X-axis: Relative quantities of mRNA in arbitrary units. Y-axis: Experimental groups: naïve Wistar rats (Wis-N); stimulated Wistar rats (Wis-S); naive WAR (WAR-N); and stimulated WAR (WAR-S) that presented seizures. Bars represent mean ± SEM. Statistical analyses: one-way ANOVA followed by post-hoc Tukey’s multiple comparisons test, * p < 0.05.

occurrence of seizures, seems to be a mechanism to recover cell homeostasis. Considering that this regulation interferes in synthesis of 5-HT, DA and NO is possible there is an imbalance between proconvulsive and anticonvulsive action. Furthermore, we may consider that a Qdpr up-regulation is involved in the high levels of NO during the seizures and this may contribute to occurrence of new insults and kindling audiogenic process.

with genetic predisposition to AS (DBA/2, GEP) (Bashkatova et al., 2003) and in models with seizures induced by electroshock and chemical agents (Zhu et al., 2016). The increase in NO is considered an response of the seizures and it has already been suggested that it could exert an important role in the development of kindling, since it is involved in the mechanisms of synaptic plasticity (Han et al., 2000). Given the above, the up-regulation of Qdpr as a response to the 28

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5. Conclusions

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Our data show that WAR animals have a differential transcriptome in the corpus quadrigeminum in comparison with the Wistar control rats. We observed that the seizures alter gene regulation in this structure and demonstrated that there are genes with differential expression inherent to the WAR model, regardless of the occurrence of seizures. It is possible that these genes are modulating the epileptic phenotype and, involved in the epileptogenic process in this strain. Funding This work was supported by Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) grant number EDT-193/09 and Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) 2009/53444-8. Conflict of interest None. Acknowledgements The authors thank the Programa de Pós-Graduação em Genética (ICB-UFMG) and the Laboratório de Biotecnologia e Marcadores Moleculares under the coordination of Dr Evanguedes Kalapothakis for making the sequencing possible. We thank the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for fellowship awarded to first author. Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.eplepsyres.2018.08. 010. References Abidi, A., Devaux, J.J., Molinari, F., Alcaraz, G., Michon, F.X., Sutera-Sardo, J., Becq, H., Lacoste, C., Altuzarra, C., Afenjar, A., Mignot, C., Doummar, D., Isidor, B., Guyen, S.N., Colin, E., De La Vaissière, S., Haye, D., Trauffler, A., Badens, C., Prieur, F., Lesca, G., Villard, L., Milh, M., Aniksztejn, L., 2015. A recurrent KCNQ2 pore mutation causing early onset epileptic encephalopathy has a moderate effect on M current but alters subcellular localization of Kv7 channels. Neurobiol. Dis. 80, 80–92. https://doi. org/10.1016/j.nbd.2015.04.017. Allen, N.M., Mannion, M., Conroy, J., Lynch, S.A., Shahwan, A., Lynch, B., King, M.D., 2014. The variable phenotypes of KCNQ-related epilepsy. Epilepsia 55, 99–105. https://doi.org/10.1111/epi.12715. Bagdy, G., Kecskemeti, V., Riba, P., Jakus, R., 2007. Serotonin and epilepsy. J. Neurochem. 100, 857–873. https://doi.org/10.1111/j.1471-4159.2006.04277.x. Bashkatova, V.G., Mikoyan, V.D., Malikova, L.A., Raevskii, K.S., 2003. Role of nitric oxide and lipid peroxidation in pathophysiological mechanisms of audiogenic seizures in GEP Rats and DBA/2 mice. Bull. Exp. Biol. Med. 136, 7–10 ISSN: 0007-4888/03/ 1361 07. Becchetti, A., Aracri, P., Meneghini, S., Brusco, S., Amadeo, A., 2015. The role of nicotinic acetylcholine receptors in autosomal dominant nocturnal frontal lobe epilepsy. Front. Physiol. 6, 22. https://doi.org/10.3389/fphys.2015.00022. Berg, A.T., Scheffer, I.E., 2011. New concepts in classification of the epilepsies: entering the 21st century. Epilepsia 52, 1058–1062. https://doi.org/10.1111/j.1528-1167. 2011.03101.x. Bernardino, T.C.S., Teixeira, A.L., Miranda, A.S., Guidine, P.M., Rezende, G., Doretto, M.C., Castro, G.P., Drummond, L., Moraes, M.F.D., Tito, P.A.L., Oliveira, A.C.P., Reis, H.J., 2015. Wistar audiogenic rats (WAR) exhibit altered levels of cytokines and brain-derived neurotrophic factor following audiogenic seizures. Neurosci. Lett. 597, 154–158. https://doi.org/10.1016/j.neulet.2015.04.046. Bertrand, D., Picard, F., Le Hellard, S., Weiland, S., Favre, I., Phillips, H., Bertrand, S., Berkovic, S.F., Malafosse, A., Mulley, J., 2002. How mutations in the nAChRs can cause ADNFLE epilepsy. Epilepsia 43, 112–122. https://doi.org/10.1046/j.15281157.43.s.5.16.x. Botion, L.M., Doretto, M.C., 2003. Changes in peripheral energy metabolism during audiogenic seizures in rats. Physiol. Behav. 78, 535–541. https://doi.org/10.1016/ S0031-9384(03)00061-1. Bozzi, Y., Borrelli, E., 2013. The role of dopamine signaling in epileptogenesis. Front. Cell. Neurosci. 7, 157. https://doi.org/10.3389/fncel.2013.00157.

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