© 2017. Published by The Company of Biologists Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License

(http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution and reproduction

in any medium provided that the original work is properly attributed.

Temporal analysis of hippocampal CA3 gene co-expression

networks in a rat model of febrile seizures

Hatylas Azevedo1*, Nathália Amato Khaled1, Paula Santos1, Fernanda Bernardi

Bertonha1, Carlos Alberto Moreira-Filho1*

1Department of Pediatrics, Faculdade de Medicina, University of São Paulo (FMUSP)

* Corresponding author:

Carlos Alberto Moreira-Filho

carlos.moreira@hc.fm.usp.br

Abbreviations

MTLE: Mesial temporal lobe epilepsy; HS: hyperthermic seizures; FS: Febrile seizures;

WGCNA: weighted gene co-expression network analysis.

Keywords: febrile seizures; co-expression networks; epilepsy; microarray; gene

expression profile; network analysis

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http://dmm.biologists.org/lookup/doi/10.1242/dmm.029074Access the most recent version at First posted online on 30 November 2017 as 10.1242/dmm.029074

Abstract

Complex febrile seizures during infancy constitute an important risk factor for epilepsy

development. However, little is known about the alterations induced by febrile seizures

that may turn the brain susceptible to epileptic activity. In this context, the use of animal

models of hyperthermic seizures (HS) could allow the temporal analysis of brain

molecular changes that arise after febrile seizures. Here, we investigated temporal

changes in hippocampal gene co-expression networks during the development of rats

submitted to HS. Total RNA samples were obtained from the ventral hippocampal CA3

region at four time points after HS at postnatal day 11 (P11) and later used for gene

expression profiling. Temporal endpoints were selected for investigating the acute (P12),

latent (P30 and P60) and chronic (P120) stages of the HS model. A weighted gene co-

expression network analysis was employed to characterize modules of co-expressed

genes, as these modules may contain genes with similar functions. The transcriptome

analysis pipeline consisted in building gene co-expression networks, identifying network

modules and hubs, performing gene-trait correlations and examining module connectivity

changes. Modules were functionally enriched to identify functions associated to HS. Our

data showed that HS induce changes in developmental, cell adhesion and immune

pathways, like Wnt, Hippo, Notch, JAK-STAT and MAPK. Interestingly, modules

involved in cell adhesion, neuronal differentiation and synaptic transmission were

activated as early as one day after HS. These results suggest that HS trigger transcriptional

alterations that may lead to persistent neurogenesis, tissue remodeling and inflammation

in the CA3 hippocampus, turning the brain prone to epileptic activity.

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Introduction

Mesial temporal lobe epilepsy (MTLE) is the most common cause of drug-resistant

epilepsy (Engel, 2001). Surgical treatment has proved to be successful for

pharmacoresistant MTLE, but less than 1% of the patients are referred to surgery, and

usually too late for preventing psychological disabilities (Engel, 2011). Approximately

40% of MTLE patients have a history of febrile seizures (FS) (Chungath and Shorvon,

2008). Notably, MTLE patients with a history of complex FS (MTLE-FS) exhibit higher

hippocampal granule cell loss than patients without such antecedent (Alegro et al., 2012).

These patients may also experience increased cognitive deficits, since poor memory

acquisition correlates to granule cell loss in temporal lobe epilepsy (Pauli et al., 2006).

Moreover, the analysis of hippocampal CA3 explants obtained after surgery revealed

distinct transcriptional signatures between patients with MTLE-FS and those with no

history of complex FS (Bando et al., 2013).

Complex FS are defined as those lasting longer than 15 minutes, occurring more than

once over a 24-hour period, or associated with brain infection (French, 2012). They are

particular relevant because children experiencing them exhibit acute hippocampal injury

and also have abnormalities in hippocampal development (Shinnar et al., 2012). In

addition, around 7% of the children undergoing complex FS will develop epilepsy later

in life (Vestergaard et al., 2007).

Animal models have been used for investigating the mechanisms underlying complex FS

in humans, as they allow the temporal analysis of biological processes activated after the

initial seizures. In these models, immature animals are subjected to hyperthermia episodes

that promote the hyperexcitability of the limbic system and lead to prolonged seizures.

These models were already employed to characterize long-lasting histological, behavioral

and electrophysiological changes in brain after FS (Dubé et al., 2012). They reproduce

several features of human epilepsy with a history of febrile seizures, such as age

dependence, hyperthermia, duration of seizures and lack of immediate morbidity (Bender

et al., 2004). The synaptic reorganization of dentate granule cells is also observed in both

the model and in human epilepsy - a histological feature that is correlated with enhanced

hippocampal excitability (Bender et al., 2003). However, there is still a knowledge gap

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about the persistent molecular changes in hippocampal neurons that may lead to MTLE

after complex FS (Dubé et al., 2012).

MTLE is considered to be multifactorial, with environmental factors and genetic

background contributing to the final outcome (Nakayama, 2009). Therefore, exploring

the mechanisms underlying MTLE-FS requires research not only focused on the

examination of individual genes, but also on the understanding of the interplay between

the genome and the FS insults. To this end, the use of a systems biology approach may

reveal how clusters of genes operate at a network level and contribute to the molecular

mechanisms of complex brain disorders (Gaiteri et al., 2014). More specifically, this

analysis could further clarify the molecular pathways involved in increased brain

excitability after FS.

Here, we investigated temporal alterations in hippocampal gene co-expression networks

in rats submitted to hyperthermia-induced seizures (HS). We sought to obtain further

insights into the hippocampal molecular changes elicited by HS that may contribute to

chronic epilepsy. The ventral region of rat hippocampus was selected for transcriptional

profiling because hippocampal hyperexcitability may occur preferentially in the ventral

CA3 circuitry (Wu et al., 2005). Moreover, the rat ventral hippocampus is homologous

to the human anterior hippocampus, which is the region related to histological changes in

patients with MTLE (Toyoda et al., 2013). Our rationale was to investigate transcriptional

pathways related to epileptogenesis to identify potential targets for therapeutic

interventions aimed at disrupting MTLE-FS onset or progression.

Materials and Methods

Animal model of hyperthermic seizures

The experimental model used here is similar to the original model of HS in immature rats

described by Baram (Baram et al., 1997). Briefly, Wistar rats were allowed to mate during

four consecutive days in a standard 12-hour light/ 12-hour dark cycle. The age of the pups

was determined from the day of birth (post-natal day P0). At the eleventh day of postnatal

life (P11), animals were subjected to hyperthermia (39.5 to 42.3 ° C) in a glass box with

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incandescent lamps until they reached a body temperature of 39°C for 45 minutes. The

control group consisted of animals that were placed in the glass container but were not

exposed to the heat insult. Animals that underwent a 45-minutes hyperthermia interval

were subsequently monitored under euthermic conditions for one hour. The post-

induction interval was video recorded and behavioral seizures were classified according

to the Racine scale: orofacial automatisms (stage 1); head nodding (stage 2); forelimb

clonus (stage 3); forelimb clonus with rearing (stage 4); and forelimb clonus with rearing

and fallings (stage 5). The Ethics Committee of FMUSP approved this study under the

number 460/13.

Experimental design

Rat pups in equal male: female ratio (n = 6-8 per group and time interval) were divided

into two groups: controls (CTRL) and animals that developed seizures after the

hyperthermic treatment (HS). Only those animals that exhibited seizures classified as

stage 2 or higher in the Racine scale were assigned to the HS group. The selection of the

temporal endpoints was based on previous studies (see below) showing associations

between specific time intervals and seizure susceptibility or resistance after

pharmacological seizure induction. For instance, a decrease in the incidence of seizures

generated by pentylenetetrazole was observed after 24 hours (P12), and also after 20 days

of the hyperthermia episode (Gonzalez-Ramirez et al., 2009). Conversely, animals

submitted to hyperthermic seizures at P11 are prone to develop seizures at P60 (Zhao et

al., 1985) and P90 (Dube et al., 2000) when treated with a sub-convulsive dose of kainate.

In this experimental model, the majority (90%) of the animals exhibit interictal

epileptiform discharges (Dubé et al., 2006), and spontaneous seizures occur in 45% of the

animals, starting around 3 to 4 months (P120) of age (Dubé et al., 2010).

RNA extraction from ventral CA3 hippocampus

Brain tissue samples were collected from the ventral CA3 hippocampus at one (P12), 19

(P30), 49 (P60) and 109 (P120) days after hyperthermia-induced seizures. These time

intervals were selected for evaluating the acute (P12), latent (P30 and P60) and chronic

(P120) stages of the experimental model. Brain microdissection was performed as

previously described (Gorter et al., 2006). Briefly, after decapitation, the temporal lobe

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and hippocampus were removed by incision at the ventrocaudal part underneath the rhinal

fissure, until 5 mm posterior to bregma. Then, the hippocampus was cut into smaller

pieces (200-300 uM) and the CA3 region was selected and removed in phosphate buffered

saline (PBS) at 4°C under a dissecting microscope. The CA3a and CA3b regions were

included in the analysis and the dentate gyrus was not sampled. The material obtained

from the ventral CA3 region was placed in Eppendorf tubes of 0.5 mL containing RNA

later (Qiagen) for subsequent total RNA extraction. Total RNA was extracted using

RNeasy® Mini Kit (Qiagen) and stored at -80oC until use in subsequent experiments.

RNA integrity was analyzed in all samples using Bioanalyzer 2100 (Agilent

Technologies, Santa Clara, CA, USA). The analysis performed by the Bioanalyzer

platform calculates an RNA integrity parameter (RIN), which is based on the ratio of

28S:18S bands (Schroeder et al., 2006). RIN values range from 10 (intact) to 1 (totally

degraded). We only used samples with RIN ≥ 7.

Oligonucleotide microarray data analysis

Microarray data was obtained as previously described (Correa-Costa et al., 2012). Gene

expression experiments were accomplished in the Agilent microarray platform, according

to manufacturer’s instructions. Agilent whole rat genome 4X44K v3 oligonucleotide

microarrays (G2519F-028 282) were used to examine the transcriptional profiles. The R

environment (http://www.r-project.org) was employed to analyze the data. The processed

signal (gProcessedSignal) generated by software Feature Expression (v9.5.3) was utilized

for further analyses. The mean expression value for each gene was calculated and then

the data was log2-transformed. Data was processed and normalized by quantile

normalization using the Limma package in R(Smyth, 2005). The differentially expressed

(DE) genes were identified using the significance analysis of microarrays algorithm

implemented in TMeV (Saeed et al., 2003), with a false discovery rate of 10% (Benjamini

Y, 1995). The microarray data set is available at the NCBI Gene Expression Omnibus,

through the accession number GSE84289.

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Gene co-expression network analysis

The network analysis workflow employed here is depicted in Figure S1. We performed

an unsigned weighted gene co-expression network analysis (WGCNA) to identify clusters

of co-expressed genes, since genes with correlated expression levels may be associated

to common regulatory mechanisms. The WGCNA method calculates a matrix of pairwise

correlation coefficients from the expression data and transforms it into an adjacency

matrix that contains the co-expression values raised to a soft threshold beta. The beta

value is selected for maximizing the networks’ scale-free topology. The analysis was

implemented using the WGCNA package in R, which constructs networks by means of

maximizing the scale free topology fit (Langfelder and Horvath, 2008). The soft-

threshold of 10 was chosen to maximize the scale-free topology index. The resulted R2

for this function was larger than 0.8 in all generated networks.

The algorithms were applied for finding clusters (modules) of co-expressed genes,

summarizing clusters using the module eigengene, identifying hub genes, relating specific

modules to experimental groups or to other modules, and comparing module parameters

(e.g. module membership) between networks. In the WGCNA package different colors

are arbitrarily assigned to the modules in order to distinguish them. The modules are

summarized by the parameter module eigengene (ME), which corresponds to the first

principal component of gene expression variation in each module. The biweight mid-

correlation coefficient was used to calculate the expression similarities between all gene

pairs. Only the 5000 most variable genes in each time interval were analyzed in order to

reduce background noise. The minimum module size was set to 50 genes.

Gene significance was calculated by correlating each gene expression profile with a

sample trait. Module significance was calculated using eigengene significance

(correlation between sample trait and eigengene) and its corresponding p-value for each

module. Only genes with a p-value ≤ 0.05 and modules with a p-value ≤ 0.1 were

considered significantly correlated to a sample trait. Intramodular hubs were identified as

the10 top-ranked genes based on intramodular connectivity in each module. Genes were

ranked according to their intramodular connectivity and changes in ranking positions

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were determined between networks for identifying nodes and modules associated with

gain or loss of connectivity.

Module preservation statistics (Langfelder et al., 2011) was implemented to evaluate the

degree of similarity between the same modules assigned in the networks. The permutation

Z score was used to assess module density and connectivity. Zsummary < 2 denotes no

preservation, 2 < Zsummary < 10 indicates weak to moderate evidence of preservation,

and Zsummary > 10 suggests strong module preservation (Langfelder et al., 2011). Genes

not clustered into any modules were assigned to grey modules in WGCNA package, i.e.

grey module may contain genes associated with traits that are not part of a WGCNA

module. The gold modules consisted of 1000 random genes selected for the module

preservation analyses. When the networks were constructed in separate for CTRL and HS

groups, modules were identified in the CTRL network and the correspondent genes for

each module were kept the same in the HS network in order to allow network comparison.

Gene lists enrichment analysis

The online softwares EnrichR (Chen et al., 2013) and PANTHER (Thomas et al., 2003)

were used to identify functions overrepresented by lists corresponding to DE genes or to

modules of co-expressed genes. The databases Gene Ontology, KEGG, WikiPathways,

Reactome and Biocarta were used for selecting enriched functions. Only functions

displaying a p-value ≤ 0.05 and encompassing at least three enriched genes were

considered significant. No background gene set was used for the functional enrichment

analysis. Similar functions were grouped together to facilitate the analysis of the

functional enrichment results. Pie charts were constructed to visualize enriched functions

with the highest number of genes at each time interval using META-CHART

(https://www.meta-chart.com/pie#/data).

Quantitative polymerase chain reaction (qPCR)

Validation of microarray results was performed by qPCR. This procedure was carried out

using the SuperScript® III Reverse Transcriptase (Life Technologies, USA) and

QuantiFast SYBR Green PCR (Qiagen, USA) kits. Samples were incubated at 95°C for

5 minutes and subjected to 40 cycles of 95°C for 30s and 60°C for 30s. Primers were

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designed in the Primer 3 software (http://bioinfo.ut.ee/primer3-0.4.0/). Gene expression

was quantified by the 2-ΔΔCT method. Data was normalized by the expression of the

GAPDH housekeeping gene. Statistical significance was determined by Student's t-test,

with p <0.1. The list of primer sequences is displayed in Table S1.

Results

Hyperthermic seizures induction in immature rats

The post-induction behavioral alterations were analyzed after the animals were subjected

to a hyperthermic insult. Behavioral seizures were classified according to the Racine

scale. Around 60% of the animals exhibited seizures after hyperthermia. Among these

animals, 45% showed head nodding, (stage 2), 10% exhibited forelimb clonus (stage 3);

16% displayed forelimb clonus with rearing (stage 4), and the remaining 29% showed

forelimb clonus with rearing and fallings (stage 5).

Differentially expressed genes in the CA3 hippocampus of rats that displayed HS

Differentially expressed (DE) genes between were statistically determined at four post-

HS stages to determine individual gene expression changes between HS and CTRL

groups. The main DE genes in terms of fold changes and the enriched functions for each

time interval are displayed in Tables 1 to 3. Microarray results were validated using qPCR

experiments for selected genes (Figure S2). These genes were selected based on their

differential expression at specific time intervals and relevance for epileptic processes.

P12 analysis. 89 DE genes (80 up and 9 down-regulated) were observed between the

experimental groups at P12. These genes were found to be associated with Ras pathway,

amino acid metabolism, apoptosis and ion transmembrane transport. Among these genes,

the down-regulated gene Hes6 participates in neuronal differentiation (Bae et al., 2000)

whereas the up-regulated gene Nlk codes for a kinase that contributes to cell proliferation

and differentiation during nervous system development (Ishitani and Ishitani, 2013).

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P30 analysis. The 83 DE genes (56 up and 27 down-regulated) at P30 were related to

organic anion transport, tissue morphogenesis and positive regulation of kinase activity.

Interestingly, the protein encoded by the down-regulated gene Gfra2 influences the

severity of kindling-evoked seizures in mice (Nanobashvili et al., 2003).

P60 analysis. The 263 DE genes (162 up and 101 down-regulated) at P60 were related

to Wnt, Rap1, Notch, HIF and interferon signaling pathways, platelet activation, focal

adhesion, mRNA processing, chromatin organization, regulation of cell migration and

cell differentiation. Among these genes, the up-regulated genes Sox9 (Guo et al., 2012)

and Tpt1 (Johansson and Simonsson, 2010) play a role in the self-renewal of stem cells.

P120 analysis. The 341 down-regulated genes were mostly associated with MAPK, JAK-

STAT and Wnt pathways, transport of ions and amino acids, cell morphogenesis and

neurotransmitters transport. In particular, the down-regulated genes Rhox8 (Artegiani et

al., 2015) and Mta2 (MuhChyi et al., 2013) are involved in neurogenesis.

Modules and hubs related to hyperthermic seizures at each time interval

We analyzed co-expression patterns in CA3 hippocampal transcriptome data to reveal

modules of co-expressed genes and their relationship with a seizure-related state. We

constructed two separate networks for each time interval using, respectively, the HS and

the CTRL samples. This analysis allowed the comparison of module preservation and

connectivity between CTRL and HS networks.

Nodes were rank-ordered by their intramodular connectivity and compared between the

HS and CTRL networks. This analysis allowed the evaluation of module preservation

between the networks and the identification of modules that gain connectivity in the HS

network (Figure 1). Modules that show increased connectivity are considered to be related

to gain of function in the HS group. The hubs and main functions enriched by the genes

in these modules are shown in Tables S2 to S5.

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P12 analysis. The top modules associated with gain of connectivity in the P12

comparison were blue, green, magenta and salmon, while the top modules that lost

connectivity at P12 were brown, red and turquoise (Figure 1A). Modules less preserved

between the CTRL and HS networks at P12 were darkred, royalblue, grey60 and

darkgreen. Among these modules, the blue module showed the highest number of genes

with gain of connectivity. This module exhibited enriched functions related to apoptosis,

regulation of cell adhesion and migration, cellular response to stress and axonogenesis.

The hub Bcar1 in this module codes for an adaptor protein relevant to cell migration and

axon elongation (Huang et al., 2006), while the hub Entpd2 is a gene that controls

progenitor cell proliferation in brain neurogenic niches (Gampe et al., 2015).

The turquoise module also encompassed many genes showing gain of connectivity. This

module was associated with apoptosis, tight junction, synaptic transmission, neuron

differentiation, immune-related pathways, Hippo pathway and Wnt pathway. The hubs

Rtn2 and Rtn3 in the module turquoise are part of the reticulon protein family that play a

role in neuronal sprouting. Indeed, mice overexpressing Rtn3 were described to develop

neuritic abnormalities (Hu et al., 2007).The darkred module was the less preserved

module at P12. This module was related to pathways linked to neurotrophin, FGFR, HIF-

1 and Wnt, apoptosis, activation of NMDA receptors, cell differentiation and

axonogenesis. The hub Nefl in this module is a marker of differentiated neurons, while

the hub Ssbp3 encodes a protein that induces the differentiation of embryonic stem cells

into trophoblast-like cells (Liu et al., 2016).

P30 analysis. The top modules associated with gain of connectivity at P30 were brown,

green, lightcyan, magenta and red, while modules that lost connectivity at P30 were black,

blue, greenyellow, pink, turquoise and yellow (Figure 1B). Modules less preserved

between the CTRL and HS networks at P30 were darkred, turquoise, pink, darkturquoise

and green. Among the modules in the P30 network, the brown module showed the highest

number of genes with gain of connectivity. This module showed enriched functions

related to cellular metabolism, protein degradation pathways, cell differentiation,

apoptosis and synaptic transmission. The hub Osm in this module encodes oncostatin M,

that inhibits the proliferation of neural precursor cells (Beatus et al., 2011).

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The magenta module also showed many genes with connectivity gain. These genes were

associated with phospholipase D pathway, actin cytoskeleton organization, regulation of

cell adhesion and chemotaxis, positive regulation of neurogenesis and regulation of stem

cell maintenance and differentiation. For example, the hub gene RalA (Ras-like small

GTPase) is involved in cell polarization during neuronal development (Das et al., 2014).

The darkgreen module was the less conserved in the P30 network. This module was

related to axon guidance, long-term potentiation, apoptosis, BDNF pathway, IL-1

pathway, cell adhesion, EPH-Ephrin signaling, innate immune pathways and Rho GTPase

Effectors. The hubs Pif1, Chac1 and Noxa1 in this module are associated to cell viability

and oxidative stress, while the hub Epha10 participates of the EPH-Ephrin signaling,

which is involved in axon guidance and activated in the hippocampus of pilocarpine-

treated mouse (Xia et al., 2013).

P60 analysis. The top modules associated with gain of connectivity at P60 were brown,

midnightblue, pink, red, salmon, turquoise and yellow, while the top modules that lost

connectivity at P60 were black, blue, green and magenta (Figure 1C). Modules less

preserved between the CTRL and HS networks at P60 were grey60, skyblue,

greenyellow, orange and brown. The brown and turquoise modules exhibited many genes

with gain of connectivity. The brown module was also the less preserved module in the

P60 network. Genes in the brown module were related to focal adhesion, stem cell

pluripotency, lymphocyte proliferation, cell migration and neuron projection

development. Among the hubs in this module, Actn1, Fkbp8 and Acap3 are involved in

neurite extension. In particular, hippocampal neurons have shown abolished neurite

outgrowth after Acap3 knockdown (Miura et al., 2016). Other hubs were Cacnb3, a

voltage-activated calcium channel, and the immune-related genes Cnrip and Il16.

The main enriched functions for the turquoise module were calcium and potassium

transport, axon guidance and neuron migration, developmental pathways like Wnt and

Robo, synaptic transmission and inflammatory regulation of TRP channels. Among the

hubs in the turquoise module, the hub gene Scx (scleraxis) encodes a transcription factor

that is important to fate determination of stem cells. The hub Mx1 codes for a protein

expressed in oligodendrocytes and the hub Ednra encodes an endothelin receptor that act

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as an axonal guidance cue for sympathetic neurons (Makita et al., 2008). Finally, the

greenyellow module was also little preserved at P60. This module was related to Wnt

pathway, p53 pathway, Axonal guidance, neuron cell morphogenesis, protein

ubiquitination, synaptic transmission. Among the hubs in this module, the gene Ptprt

codes for a tyrosine kinase that regulates synaptic formation and neuronal

development(Lee, 2015). Another relevant hubs were Pomgnt1, which encodes an

enzyme that performs protein glycan modification during brain development (Dwyer et

al., 2015) and Taok2, whose encoded kinase is essential for dendrite morphogenesis (de

Anda et al., 2012).

P120 analysis. The top modules associated with gain of connectivity at P120 were blue,

brown, grey60, pink, purple, royalblue and tan, while the top modules that lost

connectivity at P120 were black, green, magenta, red, turquoise and yellow (Figure 1D).

Modules less preserved between the CTRL and HS networks at P120 were green, grey60,

lightgreen, orange and skyblue. Genes in blue module were associated with MAPK

pathway, extracellular matrix organization, synaptic transmission, apoptosis, cell

differentiation, regulation of neurogenesis, neuron projection guidance and response to

oxidative stress. Among the hub genes in this module, Ndufb3 and Ndufs5 participate in

the oxidative phosphorylation process, Npdc1 is a regulator of neuronal proliferation and

differentiation, and Shank3 modulates NMDA receptor levels at axon terminals (Halbedl

et al., 2016). The brown module was related to synaptic transmission, focal adhesion,

regulation of actin cytoskeleton, axon guidance, signaling by Wnt, Signaling by Robo and

neuron differentiation. Among the hubs in this module, Gria1 codes for a glutamate

AMPA receptor and Robo2 is part of the Robo pathway that regulates axon guidance.

The grey60 and skyblue modules were the less preserved in the P120 analysis. The grey60

module was associated with immune functions like Fc gamma R-mediated phagocytosis,

lymphocyte proliferation and activation, regulation of NF-κB signaling, as well with cell

projection organization and cell morphogenesis. Among the hubs in this module, Gatad2a

is part of the chromatin-remodeling complex NuRD, which regulates dendrite pruning

and neuronal connectivity (Yamada et al., 2014). In parallel, the skyblue module was

related to TNFα-NFκB pathway, hyaluronan metabolism, Wnt pathway, neuron

differentiation and cell migration. The hub Ska3, for example, encodes a spindle

checkpoint protein that promotes neurite outgrowth (Tong et al., 2013). Moreover, Hyal2

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and Hmmr participate of hyaluronan metabolism, which is relevant for cell motility, while

Avl9 is also involved in cell migration.

Modules and genes associated to seizure susceptibility or resistance time intervals

A single co-expression network was also constructed using the gene expression data from

all samples obtained in this study. The modules obtained in this network were then

correlated to each time interval for disclosing modules linked to specific time intervals

(Figure 2). This analysis allowed the identification of modules correlated to time intervals

involved in seizure resistance (P12 and P30) and susceptibility (P60 and P120). For

example, the blue module was positively correlated to P12 and the magenta and purple

modules were positively correlated to P30. The pink, greenyellow and turquoise modules

were in turn mainly related to P60. Finally, the green module was positively correlated to

P120, and the modules brown and red were correlated to P60 and P120.

Although none of the above-mentioned modules were significantly correlated to the HS

group, specific genes in these modules were significantly associated with the HS group.

After filtering the genes with the p-value for gene significance (GS) lower than 0.1

(Figure 3A), we built scatter plots using the Kwithin and GS values for each module

(Figures 3B-3L). These plots supported the selection of some genes for further detailing

in each module.

P12 analysis. In the blue module, the genes Ptprz1, Lypla1, Mum1l1, Grm7, Atf6 and

Il1rapl1 showed relative high Kwithin and GS values. Lypla1 was the highest connected

node in this module. Lypla1 codes for a thioesterase that regulates protein palmitoylation

during dendritic spine morphogenesis (Siegel et al., 2009). In addition, the hubs Grm7

(glutamate receptor, metabotropic 7) and Il1rapl1 (Interleukin-1 receptor accessory

protein-like 1), this last regulating the formation of glutamatergic synapses(Hayashi et

al., 2013), revealed the transcriptional regulation of the glutamatergic signaling at P12.

P30 analysis. For the modules associated with P30, the nodes Smdt1, Ccdc153, Cyp4f1,

Tmem119 (module magenta) and Gmcl1 and Ddx41 (purple module) were the most

important genes related to the HS group. Tmem119 is a marker of resident microglia in

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human brain (Satoh et al., 2016), while Cyp4f1 expression is increased in hippocampal

astrocytes of rats subjected to brain injury (Wang et al., 2008).

P60 analysis. The pink, greenyellow and turquoise modules in turn were mainly related

to P60. The main hubs associated to the HS group were Cyb5d2, Ubqln1, Rc3h1

(greenyellow), Cml1, Ralbp1 and Rab2b (pink), and Tma7, Sumo2, Apln, Foxm1

(turquoise). Among these genes, Ubqln1 (Zhang et al, 2015) and Ralbp1 (Bae et al., 2013)

regulate seizure threshold via the GABAergic signaling. In parallel, Rab2b (Ayala et al.,

1990) and Foxm1 (Ueno et al., 2008) play a role for neuronal differentiation. Finally, the

genes Cyb5d2, Sumo2 (Datwyler et al., 2011) and Apln (Zhang et al., 2011) participate

in injury protection mechanisms.

P120 analysis. The brown and red modules were also correlated to the late stages of the

experimental model (P60 and P120). Several of the hubs and genes with top GS values in

the brown module are closely related with epilepsy. Stim2 encodes a calcium sensor

protein that modulates neuronal activity in a model of chronic epilepsy (Steinbeck et al.,

2011). Plk2 is a gene required for plasticity of hippocampal neurons during epileptiform

activity (Seeburg and Sheng, 2008), whereas Cacng3 encodes a calcium channel

associated to childhood absence epilepsy (Everett et al., 2007). For the red module, some

of the relevant genes in terms of Kwithin or GS were Atmin, which is protective against

oxidative stress in the aging brain (Kanu et al., 2010), and Ndel1 that regulates neuronal

migration (Sasaki et al., 2005). Finally, the green module (linked to P120) exhibited many

genes significantly correlated to the HS group. Among the hubs in this module, Slc25a9,

Ucp2, Ndufv3, Mrpl9 and Hspd1 are all located in mitochondria.

Frequent functions related to hyperthermic seizures at different time points

We also constructed pie charts to visualize the functions that exhibit the highest number

of genes in the specific modules related to hyperthermic seizures at each time interval.

The pie charts showing the number of genes in each function are depicted in Figure 4.

Figure 4A-4D exhibits the analysis performed in the modules from the networks built

using the HS and CTRL samples in separate for each time interval. This analysis showed

that modules related to hyperthermic seizures were mostly associated with developmental

processes, immune system processes and biological adhesion.

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Discussion

In this study, we investigated the molecular pathways underlying the process by which

neonatal FS could contribute to seizure recurrence at a later age, using a rat model of HS.

The temporal analysis of hippocampal gene co-expression networks enabled the

identification of co-expression modules and hub genes relevant to the acute, latent and

chronic phases of the animal mode. In general, hub genes and HS-related modules were

mostly related to functions involved in immune response, cell adhesion and neurogenesis.

Inflammatory-related functions were enriched by relevant modules during the acute and

advanced stages of the experimental model. Previous experiments have disclosed

mechanisms by which inflammation mediates epileptogenesis, leading to the

development of MTLE after complex FS (Choy et al., 2014). Moreover, inflammatory

markers are increased in hippocampus and correlate to epilepsy development in the rat

model of HS (Patterson et al., 2015).

Cell adhesion functions were also frequently observed in relevant modules from

hippocampal gene co-expression networks of rats that displayed HS. Notably, cell

adhesion molecules participate in many biological functions relevant for epilepsy

development such as inflammatory processes, synaptic plasticity, signal transduction,

neuronal sprouting and cell migration (Engel et al., 2008). In fact, experimental FS trigger

a transcriptional response that leads to tissue structural remodeling in hippocampus

during the acute and latent phases of the HS model in mice (Jongbloets et al., 2015).

Genes and modules associated with neurogenesis were regulated in all evaluated time

intervals. Neurogenesis in hippocampal dentate gyrus was previously characterized after

neonatal FS (Scott RC, 2012). These cells are generated in the subgranular zone and

migrate to the dentate granular cell layer. The ectopic granule cells send their axons and

form excitatory connections with CA3, leading to enhanced hippocampal excitability

after FS (Scott RC, 2012). Nevertheless, neurogenesis is still poorly understood in the

CA3 region. Hippocampal neurogenesis was already shown to occur in CA3 following

kainic acid administration in neonatal rats at P7. In these animals, the number of BrdU-

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positive cells increased in CA3 at P40 and P60, suggesting a late stimulation of

neurogenesis by kainic acid in neonatal rats (Dong et al., 2003). Neural stem cells from

CA3 are capable of differentiating in vitro to neurons, astrocytes, and oligodendrocytes.

Interestingly, postnatal age influences the extent to which progenitor cells give rise to

differentiated cells in CA3. It is observed that neuronal differentiation decreases whereas

oligodendrocyte differentiation increases with age (Shetty and Hattiangady, 2013).

Biological functions activated at P12 revealed the response to brain injury just after HS,

like amino acid metabolism, apoptosis, immune response, response to cellular stress and

ion transmembrane transport. Interestingly, many functions related to neuronal

differentiation, axonogenesis and regulation of cell migration were already activated one

day after the hyperthermia episode. In fact, recent data suggested that neurogenesis is

induced by acute seizures or precipitating insults, whereas the capacity of neuronal

recruitment and proliferation substantially decreases in the chronic phase of epilepsy

(Huang et al., 2015).

The regulation of several genes from the Hippo and Wnt pathways at P12 suggests that

seizure-induced injury may recapitulate pathways related to development and

homeostasis in the brain. These two pathways are interconnected and regulate one another

to promote a proper tissue response (Konsavage and Yochum, 2013). Moreover, the fact

that Wnt pathway modulates neuroimmune interactions after injury places this pathway

as an intersecting player between inflammation and neurogenesis (Marchetti and

Pluchino, 2013).

Modules involved in glycolysis and gluconeogenesis were related to the HS group at P30,

a time point linked to a seizure resistance phenotype. Previous studies have shown that

glycolysis increases during seizures, generating lactic acid and providing energy during

seizures. However, lactic acid reduces tissue pH and generates metabolic acidosis, which

ultimately terminates seizures (Yang et al., 2013). Therefore, one of the mechanisms

underlying seizure tolerance at P30 may be linked to the metabolic acidosis in the brain.

Relevant modules at P30 were also involved in neurogenesis, such as cell differentiation,

axon guidance, stem cell differentiation and regulation of cell adhesion. Indeed, genes

linked to the phospholipase D and EPH-Ephrin pathways were associated with gain of

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connectivity at P30. Phospholipase D promotes the release of tissue plasminogen

activator, initiating a proteolytic cascade of extracellular matrix components and

facilitating neurite outgrowth (Zhang et al., 2005). In parallel, EPH-Ephrin signaling is

increased in epileptic hippocampus, resulting in axonal sprouting and epileptogenesis (Xu

et al., 2003). Modules linked to innate immune pathways were also identified at P30,

together with hubs related to microglia and astrocytes markers. This observation

highlights that proconvulsant events can activate microglia and astrocytes to release

inflammatory mediators, initiating a cascade of events that may affect neuronal

excitability. The Delta-Notch pathway was also an enriched function in relevant modules

at P30. This pathway induces proliferation during neurogenesis but also promotes

neuronal excitation when activated after seizures (Sha et al., 2014).

Modules correlated to the P60 interval were involved in immune functions, chromatin

organization, synaptic development, cell migration, Wnt pathway, focal adhesion,

potassium transport, axon guidance and neuron migration. This time interval may be

particularly important to epileptogenesis, since epigenetic-related functions were

observed at P60, which may account for the long-lasting molecular alterations induced

by febrile seizures. In parallel, the expression of focal adhesion genes suggests that the

interaction between extracellular matrix and brain cells is important for the epileptogenic

process that generates the hyper-excitable tissue after initial seizures. Indeed, focal

adhesion signaling play a role in hippocampal mossy fiber sprouting in the

pentylenetetrazole kindling model (Song et al., 2015). In addition, the gene expression

regulation of potassium channels may be related to the kainate seizure susceptibility

phenotype observed at this time interval.

Finally, the modules related to the P120 interval were mostly involved in oxidative stress

response, apoptosis, cell differentiation, cell migration, immune pathways and

developmental signals like Hippo, Polycomb repressive complex 2, Robo, Wnt. The fact

that modules associated to oxidative stress and mitochondria dysfunction were strongly

related to P120 indicates that mitochondrial respiration deficits and the resultant oxidative

stress play a role in chronic epilepsy (Rowley and Patel, 2013). Interestingly, the

transcriptional regulation of genes related to the Polycomb repressive complex 2 (PRC2)

indicates that a long-term silencing of genes involved in stem cell pluripotency and

differentiation may be regulated by PRC2 at P120. This can also be correlated to the

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several down-regulated genes observed at P120 in this experimental model. Interestingly,

it was recently shown that PRC2 silences genes responsible for neurodegeneration in

mouse striatal neurons (von Schimmelmann et al., 2016).

Other interesting functions were also enriched in HS-related modules at P30, P60 and

P120. The CCK (Cholecystokinin) signaling pathway for example is inversely associated

with pharmacoresistance in epilepsy, because it controls the activity of hippocampal

inhibitory interneurons (Mirza et al., 2011). Another relevant function was the

gonadotropin releasing hormone (GnRH) pathway, that was involved in epileptogenesis

after enrichment analysis of microarray datasets (Subramanian et al., 2005).

This study has some limitations. The first one is related to the use of mixed cell

populations from hippocampal CA3 samples, which does not allow the determination of

specific cell-type roles among the identified transcriptional changes. The other limitation

comprises the inclusion of animals with distinct seizure behaviors in the same

experimental group. This approach was taken due to feasibility reasons, because

otherwise a much larger number of animals would be necessary, considering the mortality

inherent to the protocol, number of time points and phenotypic variability issues.

Conclusions

To our knowledge, this is the first study to provide a temporal network analysis of rat

CA3 hippocampal gene expression profiles after hyperthermia-induced seizures. The

analysis revealed transcriptional modules that may relate to epilepsy development after

febrile seizures, contributing to the identification of potential targets for the therapeutic

treatment of MTLE-FS. Our data suggest that drugs interfering with developmental and

immune pathways, like Wnt, Hippo, Notch, JAK-STAT and MAPK, could constitute the

basis of effective therapies for preventing MTLE onset after early-life febrile seizures.

Further studies using orthogonal methods like immunohistochemistry will help to identify

specific hippocampal cell types related to changes observed after hyperthermic seizures.

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Acknowledgements

This work was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo

(FAPESP), grant 2011/50761-2, and Conselho Nacional de Desenvolvimento Científico

e Tecnológico (CNPq), grant 307626/2014-8. This work was also supported by the NAP

e-Science USP.

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References

Alegro, M., Silva, A. V., Bando, S. Y., De Deus Lopes, R., Martins De Castro, L. H., Hungtsu,

W., Moreira-Filho, C. A. and Amaro, E. (2012). Texture analysis of high resolution MRI

allows discrimination between febrile and afebrile initial precipitating injury in mesial

temporal sclerosis. Magn. Reson. Med. 68, 1647–1653.

Artegiani, B., de Jesus Domingues, A. M., Bragado Alonso, S., Brandl, E., Massalini, S.,

Dahl, A. and Calegari, F. (2015). Tox: a multifunctional transcription factor and novel

regulator of mammalian corticogenesis. EMBO J. 34, 896–910.

Ayala, J., Touchot, N., Zahraoui, A., Tavitian, A. and Prochiantz, A. (1990). The product of

rab2, a small GTP binding protein, increases neuronal adhesion, and neurite growth in vitro.

Neuron 4, 797–805.

Bae, S., Bessho, Y., Hojo, M. and Kageyama, R. (2000). The bHLH gene Hes6, an inhibitor of

Hes1, promotes neuronal differentiation. Development 127, 2933–2943.

Bae, Y. S., Chung, W., Han, K., Park, K. Y., Kim, H., Kim, E. and Kim, M. H. (2013). Down-

regulation of RalBP1 expression reduces seizure threshold and synaptic inhibition in mice.

Biochem. Biophys. Res. Commun. 433, 175–180.

Bando, S. Y., Silva, F. N., Costa, L. D. F., Silva, A. V., Pimentel-Silva, L. R., Castro, L. H.

M., Wen, H. T., Amaro, E. and Moreira-Filho, C. A. (2013). Complex network analysis

of CA3 transcriptome reveals pathogenic and compensatory pathways in refractory temporal

lobe epilepsy. PLoS One 8,.

Baram, T. Z., Gerth, A. and Schultz, L. (1997). Febrile seizures: An appropriate-aged model

suitable for long-term studies. Dev. Brain Res. 98, 265–270.

Beatus, P., Jhaveri, D. J., Walker, T. L., Lucas, P. G., Rietze, R. L., Cooper, H. M.,

Morikawa, Y. and Bartlett, P. F. (2011). Oncostatin M regulates neural precursor activity

in the adult brain. Dev. Neurobiol. 71, 619–633.

Bender, R. A., Dubé, C., Gonzalez-Vega, R., Mina, E. W. and Baram, T. Z. (2003). Mossy

fiber plasticity and enhanced hippocampal excitability, without hippocampal cell loss or

altered neurogenesis, in an animal model of prolonged febrile seizures. Hippocampus 13,

399–412.

Bender, R. A., Dubé, C. and Baram, T. Z. (2004). Febrile seizures and mechanisms of

epileptogenesis: insights from an animal model. Adv. Exp. Med. Biol. 548, 213–25.

Benjamini Y, H. Y. (1995). Controlling the false discovery rate: a practical and powerful

approach to multiple testing. J Roy Stat. Soc Ser B 10, 130–142.

Chen, E. Y., Tan, C. M., Kou, Y., Duan, Q., Wang, Z., Meirelles, G. V., Clark, N. R. and

Ma’ayan, A. (2013). Enrichr: interactive and collaborative HTML5 gene list enrichment

analysis tool. BMC Bioinformatics 14, 128.

Choy, M., Dubé, C. M., Ehrengruber, M. and Baram, T. Z. (2014). Inflammatory processes,

febrile seizures, and subsequent epileptogenesis. Epilepsy Curr. 14, 15–22.

Chungath, M. and Shorvon, S. (2008). The mortality and morbidity of febrile seizures. Nat.

Clin. Pract. Neurol. 4, 610–21.

Correa-Costa, M., Azevedo, H., Amano, M. T., Gonçalves, G. M., Hyane, M. I., Cenedeze,

M. A., Renesto, P. G., Pacheco-Silva, A., Moreira-Filho, C. A. and Câmara, N. O. S. (2012). Transcriptome Analysis of Renal Ischemia/Reperfusion Injury and Its Modulation

by Ischemic Pre-Conditioning or Hemin Treatment. PLoS One 7,.

Das, A., Gajendra, S., Falenta, K., Oudin, M. J., Peschard, P., Feng, S., Wu, B., Marshall,

C. J., Doherty, P., Guo, W., et al. (2014). RalA promotes a direct exocyst-Par6 interaction

to regulate polarity in neuronal development. J. Cell Sci. 127, 686–99.

Datwyler, A. L., Lättig-Tünnemann, G., Yang, W., Paschen, W., Lee, S. L. L., Dirnagl, U.,

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Endres, M. and Harms, C. (2011). SUMO2/3 conjugation is an endogenous

neuroprotective mechanism. J. Cereb. Blood Flow Metab. 31, 2152–2159.

de Anda, F. C., Rosario, A. L., Durak, O., Tran, T., Gräff, J., Meletis, K., Rei, D., Soda, T.,

Madabhushi, R., Ginty, D. D., et al. (2012). Autism spectrum disorder susceptibility gene

TAOK2 affects basal dendrite formation in the neocortex. Nat. Neurosci. 15, 1022–31.

Dong, H., Csernansky, C. a, Goico, B. and Csernansky, J. G. (2003). Hippocampal

neurogenesis follows kainic acid-induced apoptosis in neonatal rats. J. Neurosci. 23, 1742–

1749.

Dube, C., Chen, K., Eghbal-Ahmadi, M., Brunson, K., Soltesz, I. and Baram, T. Z. (2000).

Prolonged febrile seizures in the immature rat model enhance hippocampal excitability long

term. Ann. Neurol. 47, 336–44.

Dubé, C., Richichi, C., Bender, R. A., Chung, G., Litt, B. and Baram, T. Z. (2006). Temporal

lobe epilepsy after experimental prolonged febrile seizures: prospective analysis. Brain 129,

911–22.

Dubé, C. M., Ravizza, T., Hamamura, M., Zha, Q., Keebaugh, A., Fok, K., Andres, A. L.,

Nalcioglu, O., Obenaus, A., Vezzani, A., et al. (2010). Epileptogenesis provoked by

prolonged experimental febrile seizures: mechanisms and biomarkers. J. Neurosci. 30,

7484–94.

Dubé, C. M., McClelland, S., Choy, M., Brewster, A. L., Noam, Y. and Baram, T. Z. (2012).

Fever, febrile seizures and epileptogenesis.

Dwyer, C. A., Katoh, T., Tiemeyer, M. and Matthews, R. T. (2015). Neurons and glia modify

receptor protein-tyrosine phosphatase ζ (RPTPζ)/phosphacan with cell-specific O-mannosyl

glycans in the developing brain. J. Biol. Chem. 290, 10256–10273.

Engel, J. (2001). Neuroscientist Mesial Temporal Lobe Epilepsy : What Have We Learned?

Neuroscientist 340–52.

Engel, J. J. (2011). Another good reason to consider surgical treatment for epilepsy more often

and sooner. Arch. Neurol. 68, 707–708.

Engel, J., Pedley, T. A. and Aicardi, J. (2008). Epilepsy : a comprehensive textbook.

Everett, K. V, Chioza, B., Aicardi, J., Aschauer, H., Brouwer, O., Callenbach, P., Covanis,

A., Dulac, O., Eeg-Olofsson, O., Feucht, M., et al. (2007). Linkage and association

analysis of CACNG3 in childhood absence epilepsy. Eur. J. Hum. Genet. 15, 463–472.

French, J. A. (2012). Febrile seizures: possible outcomes. Neurology 79, e80-2.

Gaiteri, C., Ding, Y., French, B., Tseng, G. C. and Sibille, E. (2014). Beyond modules and

hubs: The potential of gene coexpression networks for investigating molecular mechanisms

of complex brain disorders. Genes, Brain Behav. 13, 13–24.

Gampe, K., Stefani, J., Hammer, K., Brendel, P., Potzsch, A., Enikolopov, G., Enjyoji, K.,

Acker-Palmer, A., Robson, S. C. and Zimmermann, H. (2015). NTPDase2 and

purinergic signaling control progenitor cell proliferation in neurogenic niches of the adult

mouse brain. Stem Cells 33, 253–264.

Gonzalez-Ramirez, M., Salgado-Ceballos, H., Orozco-Suarez, S. A. and Rocha, L. (2009).

Hyperthermic seizures and hyperthermia in immature rats modify the subsequent

pentylenetetrazole-induced seizures. Seizure 18, 533–536.

Gorter, J. A., van Vliet, E. A., Aronica, E., Breit, T., Rauwerda, H., Lopes da Silva, F. H.

and Wadman, W. J. (2006). Potential new antiepileptogenic targets indicated by

microarray analysis in a rat model for temporal lobe epilepsy. J. Neurosci. 26, 11083–110.

Guo, W., Keckesova, Z., Donaher, J. L., Shibue, T., Tischler, V., Reinhardt, F., Itzkovitz,

S., Noske, A., Zurrer-Hardi, U., Bell, G., et al. (2012). Slug and Sox9 cooperatively

determine the mammary stem cell state. Cell 148, 1015–1028.

Halbedl, S., Schoen, M., Feiler, M. S., Boeckers, T. M. and Schmeisser, M. J. (2016). Shank3

is localized in axons and presynaptic specializations of developing hippocampal neurons

and involved in the modulation of NMDA receptor levels at axon terminals. J. Neurochem.

26–32.

Hayashi, T., Yoshida, T., Ra, M., Taguchi, R. and Mishina, M. (2013). IL1RAPL1 Associated

with Mental Retardation and Autism Regulates the Formation and Stabilization of

Glutamatergic Synapses of Cortical Neurons through RhoA Signaling Pathway. PLoS One

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

8,.

Hu, X., Shi, Q., Zhou, X., He, W., Yi, H., Yin, X., Gearing, M., Levey, A. and Yan, R. (2007).

Transgenic mice overexpressing reticulon 3 develop neuritic abnormalities. EMBO J. 26,

2755–67.

Huang, J., Sakai, R. and Furuichi, T. (2006). The docking protein Cas links tyrosine

phosphorylation signaling to elongation of cerebellar granule cell axons. Mol. Biol. Cell 17,

3187–96.

Huang, C., Fu, X.-H., Zhou, D. and Li, J.-M. (2015). The Role of Wnt/β-Catenin Signaling

Pathway in Disrupted Hippocampal Neurogenesis of Temporal Lobe Epilepsy: A Potential

Therapeutic Target? Neurochem. Res. 40, 1–14.

Ishitani, T. and Ishitani, S. (2013). Nemo-like kinase, a multifaceted cell signaling regulator.

Cell. Signal. 25, 190–197.

Johansson, H. and Simonsson, S. (2010). Core transcription factors, Oct4, Sox2 and Nanog,

individually form complexes with nucleophosmin (Npm1) to control embryonic stem (ES)

cell fate determination. Aging (Albany. NY). 2, 815–822.

Jongbloets, B. C., Van Gassen, K. L. I., Kan, A. A., Olde Engberink, A. H. O., De Wit, M.,

Wolterink-Donselaar, I. G., Groot Koerkamp, M. J. A., Van Nieuwenhuizen, O.,

Holstege, F. C. P. and De Graan, P. N. E. (2015). Expression profiling after prolonged

experimental febrile seizures in mice suggests structural remodeling in the hippocampus.

PLoS One 10,.

Kanu, N., Penicud, K., Hristova, M., Wong, B., Irvine, E., Plattner, F., Raivich, G. and

Behrens, A. (2010). The ATM cofactor ATMIN protects against oxidative stress and

accumulation of DNA damage in the aging brain. J. Biol. Chem. 285, 38534–38542.

Konsavage, W. M. and Yochum, G. S. (2013). Intersection of Hippo/YAP and Wnt/β-catenin

signaling pathways. Acta Biochim. Biophys. Sin. (Shanghai). 45, 71–79.

Langfelder, P. and Horvath, S. (2008). WGCNA: an R package for weighted correlation

network analysis. BMC Bioinformatics 9, 559.

Langfelder, P., Luo, R., Oldham, M. C. and Horvath, S. (2011). Is my network module

preserved and reproducible? PLoS Comput. Biol. 7, e1001057.

Lee, J.-R. (2015). Protein tyrosine phosphatase PTPRT as a regulator of synaptic formation and

neuronal development. BMB Rep. 48, 249–55.

Liu, J., Luo, X., Xu, Y., Gu, J., Tang, F., Jin, Y. and Li, H. (2016). Single-stranded DNA

binding protein Ssbp3 induces differentiation of mouse embryonic stem cells into

trophoblast-like cells. Stem Cell Res. Ther. 7, 79.

Makita, T., Sucov, H. M., Gariepy, C. E., Yanagisawa, M. and Ginty, D. D. (2008).

Endothelins are vascular-derived axonal guidance cues for developing sympathetic neurons.

Nature 452, 759–763.

Marchetti, B. and Pluchino, S. (2013). Wnt your brain be inflamed? Yes, it Wnt! Trends Mol.

Med. 19, 144–156.

Masuda, T., Tsuda, M., Yoshinaga, R., Tozaki-Saitoh, H., Ozato, K., Tamura, T. and Inoue,

K. (2012). IRF8 Is a Critical Transcription Factor for Transforming Microglia into a

Reactive Phenotype. Cell Rep. 1, 334–340.

Mirza, N., Vasieva, O., Marson, A. G. and Pirmohamed, M. (2011). Exploring the genomic

basis of pharmacoresistance in epilepsy: An integrative analysis of large-scale gene

expression profiling studies on brain tissue from epilepsy surgery. Hum. Mol. Genet. 20,

4381–4394.

Miura et al., Y. (2016). ACAP3 regulates neurite outgrowth through its GAP activity specific to

Arf6 in mouse hippocampal neurons. Biochem J.

Mochida, G. H., Ganesh, V. S., de Michelena, M. I., Dias, H., Atabay, K. D., Kathrein, K.

L., Huang, H.-T., Hill, R. S., Felie, J. M., Rakiec, D., et al. (2012). CHMP1A encodes an

essential regulator of BMI1-INK4A in cerebellar development. Nat. Genet. 44, 1260–4.

Moreno, N., Schmidt, C., Ahlfeld, J., Poschl, J., Dittmar, S., Pfister, S. M., Kool, M., Kerl,

K. and Schuller, U. (2014). Loss of Smarc proteins impairs cerebellar development. J

Neurosci 34, 13486–13491.

MuhChyi, C., Juliandi, B., Matsuda, T. and Nakashima, K. (2013). Epigenetic regulation of

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

neural stem cell fate during corticogenesis. Int. J. Dev. Neurosci. 31, 424–433.

Nakayama, J. (2009). Progress in searching for the febrile seizure susceptibility genes. Brain

Dev. 31, 359–65.

Nanobashvili, A., Kokaia, Z. and Lindvall, O. (2003). Generalization of rapidly recurring

seizures is suppressed in mice lacking glial cell line-derived neurotrophic factor family

receptor alpha-2. Neuroscience 118, 845–852.

Patterson, K. P., Brennan, G. P., Curran, M., Kinney-lang, E., Dubé, C., Ly, C., Obenaus,

A. and Baram, T. Z. (2015). Rapid, Coordinate Inflammatory Responses after

Experimental Febrile Status Epilepticus: Implications for Epileptogenesis. eNeuro 2, 1–12.

Pauli, E., Hildebrandt, M., Romstock, J., Stefan, H. and Blumcke, I. (2006). Deficient

memory acquisition in temporal lobe epilepsy is predicted by hippocampal granule cell loss.

Neurology 67, 1383–1389.

Perrier, A. L., Tabar, V., Barberi, T., Rubio, M. E., Bruses, J., Topf, N., Harrison, N. L. and

Studer, L. (2004). Derivation of midbrain dopamine neurons from human embryonic stem

cells. Proc. Natl. Acad. Sci. U. S. A. 101, 12543–12548.

Pettem, K., Yokomaku, D., Luo, L., Linhoff, M., Prasad, T., Connor, S., Siddiqui, T.,

Kawabe, H., Chen, F., Zhang, L., et al. (2013). The Specific α-Neurexin Interactor

Calsyntenin-3 Promotes Excitatory and Inhibitory Synapse Development. Neuron 80, 113–

128.

Rowley, S. and Patel, M. (2013). Mitochondrial involvement and oxidative stress in temporal

lobe epilepsy. Free Radic. Biol. Med. 62, 121–131.

Saeed, A. I., Sharov, V., White, J., Li, J., Liang, W., Bhagabati, N., Braisted, J., Klapa, M.,

Currier, T., Thiagarajan, M., et al. (2003). TM4: a free, open-source system for

microarray data management and analysis. Biotechniques 34, 374–8.

Sasaki, S., Mori, D., Toyo-oka, K., Chen, A., Garrett-beal, L., Muramatsu, M., Miyagawa,

S., Hiraiwa, N., Yoshiki, A., Wynshaw-boris, A., et al. (2005). Complete Loss of Ndel1

Results in Neuronal Migration Defects and Early Embryonic Lethality. Mol. Cell. Biol. 25,

7812–7827.

Satoh, J. ichi, Kino, Y., Asahina, N., Takitani, M., Miyoshi, J., Ishida, T. and Saito, Y. (2016).

TMEM119 marks a subset of microglia in the human brain. Neuropathology 36, 39–49.

Schroeder, A., Mueller, O., Stocker, S., Salowsky, R., Leiber, M., Gassmann, M., Lightfoot,

S., Menzel, W., Granzow, M. and Ragg, T. (2006). The RIN: an RNA integrity number

for assigning integrity values to RNA measurements. BMC Mol. Biol. 7, 3.

Scott RC, H. G. (2012). Febrile seizures and the wandering granule cell. Nat. Med. 18, 1180–2.

Seeburg, D. P. and Sheng, M. (2008). Activity-induced Polo-like kinase 2 is required for

homeostatic plasticity of hippocampal neurons during epileptiform activity. J. Neurosci. 28,

6583–6591.

Sha, L., Wu, X., Yao, Y., Wen, B., Feng, J., Sha, Z., Wang, X., Xing, X., Dou, W., Jin, L., et

al. (2014). Notch signaling activation promotes seizure activity in temporal lobe epilepsy.

Mol. Neurobiol. 49, 633–644.

Shetty, A. K. and Hattiangady, B. (2013). Postnatal age governs the extent of differentiation of

hippocampal CA1 and CA3 subfield neural stem/progenitor cells into neurons and

oligodendrocytes. Int. J. Dev. Neurosci. 31, 646–656.

Shi, J., Li, H., Jin, G., Zhu, P., Tian, M., Qin, J., Tan, X., Zhao, S., Wang, F., Hua, Y., et al. (2012). Lhx8 promote differentiation of hippocampal neural stem/progenitor cells into

cholinergic neurons in vitro. Vitr. Cell. Dev. Biol. - Anim. 48, 603–609.

Shinnar, S., Bello, J. A., Chan, S., Hesdorffer, D. C., Lewis, D. V, Macfall, J., Pellock, J. M.,

Nordli, D. R., Frank, L. M., Moshe, S. L., et al. (2012). MRI abnormalities following

febrile status epilepticus in children: the FEBSTAT study. Neurology 79, 871–7.

Siegel, G., Obernosterer, G., Fiore, R., Oehmen, M., Bicker, S., Christensen, M.,

Khudayberdiev, S., Leuschner, P. F., Busch, C. J. L., Kane, C., et al. (2009). A

functional screen implicates microRNA-138-dependent regulation of the depalmitoylation

enzyme APT1 in dendritic spine morphogenesis. Nat. Cell Biol. 11, 705-U36.

Smyth, G. K. (2005). limma: Linear Models for Microarray Data. In Bioinformatics and

Computational Biology Solutions Using R and Bioconductor, pp. 397–420. New York:

Dis

ease

Mo

dels

& M

echa

nism

s •

DM

M •

Acc

epte

d m

anus

crip

t

Springer-Verlag.

Song, M. Y., Tian, F. F., Wang, Y. Z., Huang, X., Guo, J. L. and Ding, D. X. (2015). Potential

roles of the RGMa-FAK-Ras pathway in hippocampal mossy fiber sprouting in the

pentylenetetrazole kindling model. Mol. Med. Rep. 11, 1738–1744.

Steinbeck, J. A., Henke, N., Opatz, J., Gruszczynska-Biegala, J., Schneider, L., Theiss, S.,

Hamacher, N., Steinfarz, B., Golz, S., Brüstle, O., et al. (2011). Store-operated calcium

entry modulates neuronal network activity in a model of chronic epilepsy. Exp. Neurol. 232,

185–194.

Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. a,

Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005). Gene set

enrichment analysis: a knowledge-based approach for interpreting genome-wide expression

profiles. Proc. Natl. Acad. Sci. U. S. A. 102, 15545–50.

Thomas, P. D., Campbell, M. J., Kejariwal, A., Mi, H., Karlak, B., Daverman, R., Diemer,

K., Muruganujan, A. and Narechania, A. (2003). PANTHER: A library of protein

families and subfamilies indexed by function. Genome Res. 13, 2129–2141.

Tong, C. W., Wang, J. L., Jiang, M. S., Hsu, C. H., Chang, W. T. and Huang, A. M. (2013).

Novel genes that mediate nuclear respiratory factor 1-regualted neurite outgrowth in

neuroblastoma IMR-32 cells. Gene 515, 62–70.

Toyoda, I., Bower, M. R., Leyva, F. and Buckmaster, P. S. (2013). Early activation of ventral

hippocampus and subiculum during spontaneous seizures in a rat model of temporal lobe

epilepsy. J. Neurosci. 33, 11100–15.

Ueno, H., Nakajo, N., Watanabe, M., Isoda, M. and Sagata, N. (2008). FoxM1-driven cell

division is required for neuronal differentiation in early Xenopus embryos. Development

135, 2023–30.

Vestergaard, M., Pedersen, C. B., Sidenius, P., Olsen, J. and Christensen, J. (2007). The long-

term risk of epilepsy after febrile seizures in susceptible subgroups. Am. J. Epidemiol. 165,

911–918.

von Schimmelmann, M., Feinberg, P. A., Sullivan, J. M., Ku, S. M., Badimon, A., Duff, M.

K., Wang, Z., Lachmann, A., Dewell, S., Ma’ayan, A., et al. (2016). Polycomb repressive

complex 2 (PRC2) silences genes responsible for neurodegeneration. Nat. Neurosci. 2, 1–

14.

Wang, Y., Zhao, J., Kalsotra, A., Turman, C. M., Grill, R. J., Dash, P. K. and Strobel, H.

W. (2008). CYP4Fs expression in rat brain correlates with changes in LTB4 levels after

traumatic brain injury. J. Neurotrauma 25, 1187–94.

Wu, C. P., Cheung, G., Rakhshani, N., Parvardeh, S., Asl, M. N., Huang, H. L. and Zhang,

L. (2005). Ca3 neuronal activities of dorsal and ventral hippocampus are differentially

altered in rats after prolonged post-ischemic survival. Neuroscience 130, 527–39.

Xia, Y., Luo, C., Dai, S. and Yao, D. (2013). Increased EphA/ephrinA expression in

hippocampus of pilocarpine treated mouse. Epilepsy Res. 105, 20–29.

Xu, B., Li, S., Brown, A., Gerlai, R., Fahnestock, M. and Racine, R. J. (2003). EphA/ephrin-

A interactions regulate epileptogenesis and activity-dependent axonal sprouting in adult rats.

Mol. Cell. Neurosci. 24, 984–999.

Yamada, T., Yang, Y., Hemberg, M., Yoshida, T., Cho, H. Y., Murphy, J. P., Fioravante,

D., Regehr, W. G., Gygi, S. P., Georgopoulos, K., et al. (2014). Promoter

decommissioning by the NuRD chromatin remodeling complex triggers synaptic

connectivity in the mammalian brain. Neuron 83, 122–134.

Yang, H., Wu, J., Guo, R., Peng, Y., Zheng, W., Liu, D. and Song, Z. (2013). Glycolysis in

energy metabolism during seizures. Neural Regen. Res. 8, 1316–1326.

Zhang, Y., Kanaho, Y., Frohman, M. A. and Tsirka, S. E. (2005). Phospholipase D1-promoted

release of tissue plasminogen activator facilitates neurite outgrowth. J. Neurosci. 25, 1797–

805.

Zhang, X., Peng, X., Fang, M., Zhou, C., Zhao, F., Zhang, Y., Xu, Y., Zhu, Q., Luo, J., Chen,

G., et al. (2011). Up-regulation of apelin in brain tissue of patients with epilepsy and an

epileptic rat model. Peptides 32, 1793–1799.

Zhang et al, Y. (2015). Plic-1, a new target in repressing epileptic seizure by regulation of

Dis

ease

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nism

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GABAAR function in patients and a rat model of epilepsy. Clin Sci 1207–23.

Zhao, D. Y., Wu, X. R., Pei, Y. Q. and Zuo, Q. H. (1985). Long-term effects of febrile

convulsion on seizure susceptibility in P77PMC rat--resistant to acoustic stimuli but

susceptible to kainate-induced seizures. Exp. Neurol. 88, 688–95.

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Figures

Figure 1. Analyses of module preservation and intramodular connectivity changes

between HS and CTRL networks. Genes were ranked according to their intramodular

connectivity and changes in ranking positions were determined between networks for

identifying nodes and modules associated with gain or loss of connectivity. The summary

statistic Zsummary is used to assess preservation of module density and connectivity

between the networks. Zsummary < 2 denotes no preservation, 2 < Zsummary < 10

indicates weak to moderate evidence of preservation, and Zsummary > 10 suggests strong

module preservation.

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Figure 2. Module-trait relationships from the WGCNA analysis in which networks

were built using all microarray samples. Module names are displayed on the left, and

the correlation coefficients to the hyperthermic seizures (HS) group are shown at the top

of each row. The corresponding p-values for each module are displayed at the bottom of

each row with a parenthesis. The rows are colored based on the correlation of the module

to the HS group: red for positive and green for negative correlation.

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Figure 3. Significant genes correlated to the HS group in each module, based on the

analysis depicted in Figure 4. Specific genes in each module were significantly

associated to the HS group. Figure 4A displays the number of genes in each module that

displayed a p-value for gene significance (GS) lower than 0.1. Figures 4B-4L show the

scatter plots constructed using the Kwithin (x-axis) and GS (y-axis) values for each gene in

their corresponding modules.

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Figure 4. Pie charts showing the percentage of genes for selected enriched biological

functions and pathways at different time points after hyperthermic seizures. Figures

6A-6D display the functions identified in the modules that gain connectivity in the HS

networks. Networks were constructed using the HS and CTRL samples in separate for

allowing the comparison between HS and CTRL networks at each time point.

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Table 1. Genes with top fold changes (FC) identified at each time point. Fold changes were determined between the expression from samples of

hyperthermic seizures and from normothermic controls.

P12 P30 P60 P120

Gene FC Gene FC Gene FC Gene FC Gene FC

March9 0.48 Olr791 0.49 Cpne4 0.62 Trip12 0.41 Mcpt1l4 0.58

Cartpt 0.55 Tmem255b 0.53 RT1-M1-2 0.65 Zfp280b 0.49 Prl7b1 0.58

Hes6 0.58 Gfra2 0.53 Adcy3 0.67 Pkib 0.51 Actc1 0.57

Srsf7 0.67 Ctrb1 0.55 Lonp2 0.67 Trpv5 0.50 Slc6a18 0.58

H2afv 0.72 Tomm20l 0.55 Cabp7 0.67 Adgrg7 0.49 Tesb 0.58

Ccdc85a 0.75 Tmprss6 0.57 Abca3 0.68 Bcl2l1 0.51 Hcn4 0.60

Galr2 0.77 Rhox2 0.58 Inpp5j 0.67 Ppp1r3a 0.50 Adgrg1 0.58

Ppp1r1a 0.77 Trim26 0.58 Ttc4 0,68 Ovol2 0.52 Fabp12 0.59

Psma7 0.78 Ston1 0.60 Cep19 0.69 Krt14 0.52 Dlx3 0.60

Dnajb6 1.52 Ptgir 0.62 Chmp1a 0.69 Bpifa1 0.55 Il20 0.61

Usp46 1.53 Uqcrc1 1.39 Habp4 0.70 Ece1 0.56 Tmc1 0.60

Nlk 1.53 Rasip1 1.43 Syt12 0.70 Mta2 0.54

Smpd3 1.56 Zkscan5 1.41 Pax5 1.58 Igf2bp2 0.51

Brap 1.66 Katnb1 1.40 Hes7 1.61 Cyp4a1 0.55

Ric8a 1.63 Cpt1c 1.43 Rpl23a 1.59 Kirrel 0.59

Polr2m 1.62 Fhl2 1.45 Tpt1 1.70 Rhox8 0.56

Cyb5r1 1.65 Atp9b 1.47 Ghdc 1.62 Gabrq 0.58

Pax3 1.81 Inpp5d 1.49 Dcun1d1 1.66 Otor 0.57

Ier5 1.53 Hif1a 1.67

Wfs1 2.05 Sox9 1.67

Olr143 1.67

Trim42 1.89

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Table 2. Selected enriched functions among the differentially expressed genes identified at P12 and P30.

ENRICHED FUNCTIONS DE GENES DATABASE P-VALUE

P12

Ras signaling Pathway Brap, Angpt2, Pld1, Bcl2l1 KEGG 0.031

Metabolism of amino acids Psat1, Ndufab1, Rpl13, Dlat, Prodh, Psma7 REACTOME 0.010

apoptotic signaling pathway Vav3, Hint1, Arhgef3, Trib3, Prodh, Bcl2l1 Gene Ontology 0.005

nitrogen compound transport Smpd3, Slc43a1, Slc1a1, Cartpt, Slc25a5, Srsf7, Slc28a1 Gene Ontology 0.007

ion transmembrane transport Knh6, Galr2, Kcna2, Scn4a, Clcn1 Gene Ontology 0.019

P30

Metabolism of vitamins Sdc3, Ctrb1, Slc19a1 REACTOME 0.031

organic anion transport Slc35b4, Slc6a12, Nfkbie, Atp9b, Slc19a1 Gene Ontology 0.009

Protein targeting in cell Sun1, Nfbie, Pkd1, Dbn1, Pex14 Gene Ontology 0.001

tissue morphogenesis Ahi1, Luzp1, Pkd1, Rasip1 Gene Ontology 0.050

positive regulation of kinase

activity Wfs1, Lmna, Adcy4, Mapk8ip3, Pkd1 Gene Ontology 0.038

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Table 3. Selected enriched functions among the differentially expressed genes identified at P60 and P120.

ENRICHED FUNCTIONS DE GENES DATABASE P-VALUE

P60

Platelet activation Col1a1, Mapk11, Adcy3, Arhgef1, Myl12a, Mapk13, Pik3r5 KEGG 0.003

Rap1 signaling pathway Pdgfrb, Mapk11, Csf1, Hgf, Flt4, Ctnnd1, Adcy3, Mapk13, Pik3r5 KEGG 0.005

HIF-1 signaling pathway Egln2, Slc2a1, Hmox1, Hif1a, Pik3r5 KEGG 0.020

Focal adhesion Col1a1, Pdgfrb, Hgf, Flt4, Zyx, Myl12a, Pik3r5 KEGG 0.033

mRNA processing Srp19, Ddx6, Sf3a1, Rnasel, Myef2, Rbm4b, Ybx1, Rpl9, Hnrnpab,

Uhmk1, Snrpd2, Auh, Pcbp2 WikiPathways 0.014

Chromatin organization Hist2h2aa3, Kat2a, Dot1l, H2afx, Elp6, Padi1, Smarca4, Hcfc1 Reactome 0.004

Hox activation Hist2h2aa3, Cnot6, H2afx, Rqcd1, Rarb Reactome 0.007

TCF/Wnt signaling pathway Hist2h2aa3, Tnks2, Ppp2r1a, H2afx, Sox9, Psmb8, Smarca4 Reactome 0.018

Interferon signaling Nup205, Rnasel, Irf7, Psmb8, Kpnb1, Ip6k2 Reactome 0.049

Wnt signaling pathway Sdhaf2, Tnks2, Ppp2r1a, Ppap2b, Sfrp5, Ctnnd1, Sox9, Zbed3h Gene Ontology 0.003

Regulation of cell migration Col1a1, Pdgfrb, Ccl24, Tgfb2, Csf1, Hgf, Flt4, Sox9, Hif1a, Elp6 Gene Ontology 0.006

Notch signaling pathway Hes7, Notch3, Ncstn, Mdk, Wdr12, Hif1a, Kat2a Gene Ontology 0.010

Stem cell differentiation Col1a1, Tgfb2, Sdhaf2, Cnot3, Sox9 Gene Ontology 0.009

P120

MAPK signaling pathway Ppp5c, Hspa1l, Flnc, Mapk14, Fgf1, Ngf, Tp53 KEGG 0.039

JAK-STAT signaling pathway Ctnfr, Il20, Stat6, Il2rg, Bcl2l1 KEGG 0.047

Transport of ions and amino acids Slc12a3, Slc12a5, Slc6a18, Slc43a2, Slc1a3, Slc6a20 Reactome 0.003

Tcf/Wnt signaling pathway Amer1, Ctbp1, Ppp2r5e, Sox13, Psmd1, Smarca4, Lrp6 Reactome 0.024

Cell morphogenesis Sema4a, Dst, Slc1a3, Mapk14, Ngf, Rtn4, Gje1, Smarca4, Lrp6, Pax8,

Peak1, Numb, Pacsin2, Vhl, Bcl2l1, Shank1 Gene Ontology 0.001

Anion transmembrane transport Clcn7, Gabrq, Slc12a3, Slc12a5, Slc6a18, Slc43a2, Slc25a42, Slc6a20 Gene Ontology 0.001

Neurotransmitter transport Gabrq, Slc6a18, Snph, Nrxn3, Slc1a3, Slc6a20, Slc6a2 Gene Ontology 0.001

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Table S1. List of primer sequences used for the quantitative real time polymerase chain reactions.

Gene Primer Code Sequence (5’ to 3’)

PTGIR PTGIR FW TGGGACGATGCTGTGTGA

PTGIR RV GAAAGCGTAGATGGAAGGCAA

SOX9 SOX9 FW AGGAAGCTGGCAGACCAGTA

SOX9 RV ACGAAGGGTCTCTTCTCGCT

TRIP12 TRIP12 FW CCAACCCAGAAATCAACCAGTC

TRIP12 RV GATTTCCAACATGGCCCGGGAG

RHOX8 RHOX8 FW TGCCTGGACCCCTACTATTG

RHOX8 RV CTGGCTGGCACATAGTCCTG

GAPDH GAPDH FW GACATGCCGCCTGGAGAAAC

GAPDH RV AGCCCAGGATGCCCTTTAGT

Disease Models & Mechanisms 10: doi:10.1242/dmm.029074: Supplementary information

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Table S2. Functional enrichment analysis in modules that gain or lose connectivity after hyperthermic seizures at P12.

MODULE

(GENES)

MODULE

TYPE HUBS MAIN ENRICHED FUNCTIONS

Blue

(367)

Gain of

connectivity

Bcar1, Slc25a5, Entpd2, Zfp148,

Gimap9, Srp72, Rarres1, Hspa9, Rassf2,

Romo1

Cell cycle, Endocytosis, Focal Adhesion, Regulation of Actin Cytoskeleton, EGFR

Pathway, Apoptosis, Cellular response to stress, Autophagy, DNA replication,

axonogenesis, neuron cell-cell adhesion

Green

(215)

Gain of

connectivity

Abcb6, Exosc5, Rbm7, C1ql1, Uri1,

Pycr2, Mpdz, Hdgfrp3, Cstf2, Nudt16l1

Endocannabinoid signaling, Proteoglycans in cancer, PI3K-Akt pathway,

GABAergic synapse, Focal Adhesion, Class I MHC mediated antigen processing,

EPH-ephrin mediated repulsion of cells, oxidative phosphorylation, cell projection

organization, positive regulation of neuron differentiation

Magenta

(160)

Gain of

connectivity

Slc4a2, Zfp407, Nes, Etv3, Cd6, Glrx2,

Phb, Clrn2, Ccnf, Kcnk2

Proteoglycans, FoxO pathway, MAPK pathway, Chromatin organization, Gastrin-

CREB signaling pathway via PKC and MAPK, Regulation of synaptic

transmission, regulation of membrane potential

Salmon

(132)

Gain of

connectivity

Cct5, Col1a2, Mien1, Mettl2b, Mxi1,

Foxe1, Cfl1, Rreb1, Hyal3, Cdhr1

Oxidative phosphorylation, TGF-β Pathway, Cell cycle, NF-κB activation, Ion

channel transport, response to IL-1, Wnt pathway, apoptosis, actin cytoskeleton

organization, stem cell maintenance

Darkred

(97)

Less

preserved

Nefl, Ssbp3, Epm2aip1, Sat1, Psmg4,

Cmas, Srgap3, Zc3h18, Ctss, Scml4

p53 pathway, HIF-1 pathway, Neurotrophin pathway, Wnt pathway,

Apoptosis, Activation of NMDA receptor, Hemostasis, Signaling by FGFR, Cell

differentiation, axonogenesis

Royalblue

(98)

Less

preserved

Tmem212, Tbkbp1, Nxph1, Adcyap1,

Fcgr1a, Tspyl4, Eif4ebp1, Aars, Mal2,

Apex1

PI3K-Akt-mTOR-signaling, EPH-Ephrin signaling, Axon guidance, SLC-mediated

transmembrane transport, Signaling by VEGF, negative regulation of neuron death, neuron projection development, neurogenesis

grey60

(106)

Less

preserved

Ddx39b, Ap2s1, Ddx24, Atg16l1,

Commd4, Acin1, Bloc1s2, Eif3e, Tpm3,

Chmp4b

Calcium Regulation, Integrin-mediated cell adhesion, Focal Adhesion, PI3K-Akt-

mTOR-signaling, Signaling by EGFR, vesicle-mediated transport, cellular response

to stress, regulation of vasculature development

Darkgreen

(97)

Less

preserved

Prpf40a, Sort1, Cd33, Uqcrc1, Smarca4,

Ubc, Rnf187, Gdi1, Cript, Otx1

Cholinergic synapse, potassium channels, Signaling by Wnt, mitotic cell cycle

phase transition, T cell activation, neuron differentiation

Disease Models & Mechanisms 10: doi:10.1242/dmm.029074: Supplementary information

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Table S3. Functional enrichment analysis in modules that gain or lose connectivity after hyperthermic seizures at P30.

MODULE

(GENES)

MODULE

TYPE HUBS MAIN ENRICHED FUNCTIONS

Blue

(345)

Gain of

connectivity

Slc30a5, Hypk, Ankrd33b, Axin1,

Arv1, Inip, Dscr3, Ptp4a3, Zfyve1,

Acy3

Protein processing in endoplasmic reticulum, Hippo pathway, Wnt pathway, apoptosis,

Chemokine receptors bind chemokines, L1CAM interactions, myeloid cell

differentiation, actin filament organization, regulation of neuron apoptotic process

Brown

(301)

Gain of

connectivity

Osm, B2m, Wbp4, Spata18, Retsat,

Pomt1, Olr546, Stra6,

Pcdhga7, Usp5

Parkinson's disease, Dopaminergic and cholinergic synapses, long term potentiation,

TCA cycle, cellular metabolism, proteasome, autophagy, negative regulation of

apoptosis, nervous system development, negative regulation of cell differentiation

Green

(282)

Gain of

connectivity

Chac2, Tmed7, Ivd, Tmx3, Smarcb1,

Gmpr, Sav1, Ndufb2, Cpt1a, Sqstm1

Glutamatergic synapse, GABAergic synapse, Ubiquitin-mediated proteolysis,

Metabolic pathways, Oncostatin M Pathway, DNA damage response, Class I MHC

mediated antigen processing, cell junction assembly, neuron projection development,

synaptic transmission

Lightcyan

(165)

Gain of

connectivity

Tmem171, R3hdml, Chd5, Pth2, Eif1,

Foxp3, Gja8, Rap2a, Polr1b, Pik3r5

Electron Transport Chain, Glutathione conjugation, DNA Repair, regulation of neuron

differentiation, neurogenesis, calcium ion homeostasis

Magenta

(202)

Gain of

connectivity

Sapcd1, RalA, Olr567, Gpr137,

Lace1, Creb3, Rabggta, Mum1,

Med25

Phospholipase D signaling pathway, Actin cytoskeleton organization, Gastrin-CREB

signaling pathway, positive regulation of cell adhesion and chemotaxis, stem cell

maintenance, positive regulation of neurogenesis, stem cell differentiation

Red

(228)

Gain of

connectivity

Tmem246, Sult4a1, Vps11, Psmd8,

Armc9, Dopey2, Prkar1b, Dctn2,

Ankrd46, Pcyox1

Synaptic vesicle, lysosome, Leukocyte transendothelial migration, glutamatergic

synapse, Regulation of Actin Cytoskeleton, Neuronal System, MHC class II antigen

presentation, signaling by VEGF, signaling by EGFR, synaptic transmission, neuron

projection development, neuron apoptosis, neuron differentiation

Darkgreen

(137)

Less

preserved

Chac1, Pif1, Hpcal4, Noxa1, Defb24,

Epha10, Atp6ap1l, Zfp516, Htr5b,

Ncf1

Axon guidance, Ras pathway, Long-term potentiation, Apoptosis, BDNF signaling

pathway, IL-1 pathway, Cell Adhesion, EPH-Ephrin signaling, Innate immune

pathway, Rho GTPase Effectors

Pink

(207)

Less

preserved

Sectm1b, Ube3d, Fam134b, Idh3g,

Anapc13, S100b, Cpne8, Pgam1,

Dpysl2, Itgb3bp

Synaptic transmission, glycolysis, oxidative phosphorylation, metabolism of amino

acids, immune system, iron ion homeostasis, neuron migration, organic acid transport

Tan

(191)

Less

preserved

Wfdc10, Gpd1l, Sfrp5, Baiap2,

Myo5b, Tmem229b, Bsdc1, Nup62,

Thop1, Cacna1e

Wnt signaling pathway, MAPK pathway, Calcium signaling, Axon guidance, Neural

Crest Differentiation, neuronal System, synaptic transmission, regulation of ion

membrane transport, actin cytoskeleton organization, axon guidance

Disease Models & Mechanisms 10: doi:10.1242/dmm.029074: Supplementary information

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Table S4. Functional enrichment analysis in modules that gain or lose connectivity after hyperthermic seizures at P60.

MODULE

(GENES) MODULE TYPE HUBS MAIN ENRICHED FUNCTIONS

Brown

(249)

Gain of connectivity

and Less preserved

Rmnd5b, Bop1, Actn1, Sec14l5,

Tmem25, Fkbp8, Acap3, Cacnb3,

Cnrip1, Il16

Focal adhesion, stem cell pluripotency, metabolism of lipids, positive

regulation of lymphocyte proliferation, negative regulation of cell migration,

neuron projection development

Midnightblue

(160) Gain of connectivity

Anxa7, Snd1, Klhdc3, C5ar1,

Gosr2, Bpifb6, Or10ad1, Rpp30,

Rps19, Atp6v0a1

Synaptic vesicle, Glutamatergic synapse, BDNF signaling pathway, Neuronal

System, Antigen processing: Ubiquitination & Proteasome degradation, Ion

channel transport, synaptic transmission, neuronal plasticity

Red

(212) Gain of connectivity

Dctn1, Dapk3, Dgat1, Mus81,

Unc45a, Rnft2, Dcaf15, Pomgnt2,

Abcb8, Ogdh

Hippo pathway, interleukin signaling, neural crest differentiation, Extracellular matrix organization, hippocampus development, innate immune

response

Turquoise

(438) Gain of connectivity

Tpd52l1, Scx, Mx1, Ednra, Ano3,

Dleu7, Slc7a3, Nr2f2, Epha5,

Gpr155

Calcium ion transport, cholinergic synapse, axon guidance, Wnt pathway,

inflammatory regulation of TRP channels, Neuronal system, gastrin-CREB

signaling pathway, Signaling by Robo, Potassium Channels, neuron

migration, synaptic transmission

Yellow

(235) Gain of connectivity

Bckdk, Rmdn1, Ninj1, Robo1, Tst,

Dchs1, Galt, Lsm3, Olr733, Gja10

Metabolic pathways, neuroactive ligand-receptor interaction, GABAergic

synapse, Extracellular matrix organization, neuron projection development,

synaptic transmission, neuron differentiation, neurogenesis

Greenyellow

(176) Less preserved

Ptprt, Armcx1, Tpcn1, Ube2m,

Acbd5, Mta2, Celf4, Taok2,

Pomgnt1, Slc16a13

Wnt pathway, p53 pathway, Axonal guidance, regulation of RNA splicing,

neuron cell morphogenesis, regulation of protein ubiquitination, synaptic

transmission

Orange

(114) Less preserved

Olr1516, March9, Ache, Abcc6,

Dusp9, Dynlt1, Sin3b, Sept2,

Rnf182, Gltp

Long-term potentiation, cholinergic synapse, axon guidance, Kit receptor

signaling pathway, signaling by EGF, cell junction assembly, cell

differentiation, positive regulation of cell migration

Skyblue

(97) Less preserved

Calr, Sobp, Acin1, Rabgap1, Nrgn,

Epn1, Sstr4, Ring1, Scaf1, Sncb

Endocytosis, Notch Pathway, Sphingolipid metabolism, ERBB signaling,

nervous system development, small GTPase mediated signal transduction

Disease Models & Mechanisms 10: doi:10.1242/dmm.029074: Supplementary information

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Table S5. Functional enrichment analysis in modules that gain or lose connectivity after hyperthermic seizures at P120.

MODULE

(GENES)

MODULE

TYPE HUBS MAIN ENRICHED FUNCTIONS

Brown

(249)

Gain of

connectivity

Dgkz, Armt1, Acp2, Robo2, Gria1,

Ppp2r5c, Pard6a, Mast3, Scd2, Pdpk1

Synaptic transmission, Long-term potentiation, Leukocyte transendothelial

migration, Focal adhesion, Regulation of actin cytoskeleton, Rap1 pathway, Axon

guidance, signaling by Wnt, Signaling by Robo, neuron projection development,

neuron differentiation

Blue

(264)

Gain of

connectivity

Pdap1, Pcbd2, Eif3f, Npdc1, Rnf34,

Ndufb3, Shank3, Ndufs5, Bmpr1b,

Map3k7

MAPK signaling pathway, Extracellular matrix organization, regulation of synaptic

transmission, apoptosis, regulation of cell morphogenesis involved in

differentiation, negative regulation of neurogenesis, neuron projection guidance,

response to oxidative stress

Pink

(208)

Gain of

connectivity

Cerk, Prpf8, Ipo13, Ncaph2, Sptan1,

Apc2, Exosc7, Arhgdia, Exoc6b, Kdm3a

Alzheimer's disease, Complement and coagulation cascades, Foxo signaling

pathway, Phospholipase D signaling pathway, Toll-like receptor signaling pathway,

regulation of actin cytoskeleton, Antigen processing, Wnt signaling pathway

Grey60

(128)

Less

preserved

Ciz1, Vps4b, Cryga, Gatad2a, Tnrc6a,

Cybrd1, Med1, Casp7, Abcd4, Sbno2

Fc gamma R-mediated phagocytosis, positive regulation of lymphocyte

proliferation, positive regulation of lymphocyte activation, regulation of I-

kappaB kinase/NF-kappaB signaling, cell projection organization, regulation of cell

morphogenesis

Skyblue

(93)

Less

preserved

Polr1c, Ska3, Hyal2, Hmmr, Ttc21b,

Avl9, Hacd2, Mecr, Vom1r81, Prrc1

TNF-alpha NF-kB Pathway, Hyaluronic metabolism, regulation of Wnt pathway,

negative regulation of neuron differentiation, actin filament organization, negative

regulation of cell migration, regulation of MAPK activity

Lightgreen

(125)

Less

preserved

Tbx3, Ciapin1, Adprm, Scly, Atf4,

Commd8, Sf3b3, Bpgm, Ccdc50, Stat1

Metabolism, Extracellular matrix organization, regulation of anion transport,

neuron projection development

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Figure S1. Schematic representation of the network analysis workflow. Microarray data was log2-transformed and normalized using

lowess normalization. This data was used for weighted correlation network analysis. The network analysis consisted in building gene

co-expression networks, identifying network modules and hubs, performing gene-trait correlations and examining module preservation

and connectivity changes. Relevant modules were also functionally enriched to identify functions associated to hyperthermic seizures.

Disease Models & Mechanisms 10: doi:10.1242/dmm.029074: Supplementary information

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Figure S2. Comparison of microarray and qPCR results for selected genes. The genes Trip12, Rhox8, Ptgir and Sox9 were selected

for validating microarray results using qPCR analysis.

Disease Models & Mechanisms 10: doi:10.1242/dmm.029074: Supplementary information

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