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. Author manuscript; available in PMC: 2018 Dec 1.
Published in final edited form as: Mol Cell Neurosci. 2017 Oct 18;85:183–189. doi: 10.1016/j.mcn.2017.10.003

Cocaine alters Homer1 natural antisense transcript in the nucleus accumbens

Gregory C Sartor 1,*, Samuel K Powell 1,*, Dmitry Velmeshev 1, David Y Lin 1, Marco Magistri 1, Hannah J Wiedner 1, Andrea M Malvezzi 1, Nadja S Andrade 1, Mohammad A Faghihi 1, Claes Wahlestedt 1
PMCID: PMC5698162  NIHMSID: NIHMS917213  PMID: 29055697

Abstract

Natural antisense transcripts (NATs) are an abundant class of long noncoding RNAs that have recently been shown to be key regulators of chromatin dynamics and gene expression in nervous system development and neurological disorders. However, it is currently unclear if NAT-based mechanisms also play a role in drug-induced neuroadaptations. Aberrant regulation of gene expression is one critical factor underlying the long-lasting behavioral abnormalities that characterize substance use disorder, and it is possible that some drug-induced transcriptional responses are mediated, in part, by perturbations in NAT activity. To test this hypothesis, we used an automated algorithm that mines the NCBI AceView transcriptomics database to identify NAT overlapping genes linked to addiction. We found that 22% of the genes examined contain NATs and that expression of Homer1 natural antisense transcript (Homer1-AS) was altered in the nucleus accumbens (NAc) of mice 2 hours and 10 days following repeated cocaine administration. In in vitro studies, depletion of Homer1-AS lead to an increase in the corresponding sense gene expression, indicating a potential regulatory mechanisms of Homer1 expression by its corresponding antisense transcript. However, future in vivo studies are needed to definitely determine a role for Homer1-AS in cocaine-induced behavioral and molecular adaptations.

Keywords: long noncoding RNA, natural antisense transcripts, cocaine, nucleus accumbens, epigenetics

Introduction

Recent high-throughput sequencing studies have uncovered tens of thousands of RNA transcripts with little or no protein-coding potential (termed noncoding RNAs) (Carninci et al., 2005; Katayama et al., 2005a; Birney et al., 2007). Initially thought of as transcriptional noise, research has now shown that noncoding RNAs have fundamental roles in multiple aspects of cellular physiology (Magistri et al., 2012; Qureshi & Mehler, 2012). Long noncoding RNAs (lncRNAs), defined as noncoding transcripts greater than 200 nucleotide bases in length, are pervasively expressed across mammalian genomes and have been implicated in several aspects of transcriptional and posttranscriptional regulation (Feng et al., 2006; Rinn et al., 2007; Nowacki et al., 2008; Huarte et al., 2010). LncRNAs are generally classified based on their anatomical properties and their gene loci. For example, natural antisense transcripts (NATs) overlap other genes on the opposite strand of the DNA while intergenic lncRNAs (lincRNAs) are located between genes. Interestingly, many of these lncRNAs show specific spatial and temporal expression patterns within tissues and cells (Clark et al., 2011). In the brain, for example, numerous lncRNAs are selectively expressed in neurons (Mercer et al., 2008; Belgard et al., 2011), indicating that some lncRNAs may be specifically involved in neuronal function (Qureshi & Mehler, 2012).

Natural Antisense Transcripts (NATs) are transcribed from the opposite DNA strand of other RNA transcripts with which they share sequence complementarities (Magistri et al., 2012). Transcriptome-wide analyses by the FANTOM and ENCODE consortia have revealed that up to 66% of protein-coding genes contain NATs (Katayama et al., 2005b; Djebali et al., 2012), indicating their vast prevalence and potential importance in biological mechanisms. Of the proposed functional mechanisms of NATs, regulation of chromatin architecture and epigenetic memory have received much attention, as some antisense transcripts may provide a scaffold by which proteins can interact with DNA and chromatin in a locus-specific manner (Saxena & Carninci, 2011; Magistri et al., 2012). Moreover, many NATs are expressed in the CNS where they have been shown to play fundamental roles in a variety of biological processes. For example, our previous work demonstrates that NAT dysregulation is associated with Alzheimer’s disease pathophysiology (Modarresi et al., 2011; Magistri et al., 2016), and in separate reports we have also revealed that NATs contribute to Parkinson’s disease, Autism, Fragile X mental retardation, seizures and metabolism (Scheele et al., 2007; Faghihi et al., 2010a; Pastori et al., 2014; Hsiao et al., 2016; Silva et al., 2016). Mechanistically, we and others have shown that NATs can mediate epigenetic modification of genes in cis, making them unexplored targets to achieve specific up-regulation of gene expression (Modarresi et al., 2012). Additionally, NATs have been found to affect disease-related gene expression by modifying mRNA stability and microRNA function (Faghihi et al., 2010b; Modarresi et al., 2011). Thus, these findings suggest that NATs are dysregulated in multiple neuropathologies and that endogenous gene expression can be specifically regulated by targeting NATs.

With such integral roles in transcriptional and posttranscriptional regulation, it is not surprising that dysregulation of NATs have been linked to multiple diseases (Scheele et al., 2007; Faghihi et al., 2008; Han et al., 2012; Yang et al., 2012), but little is known about their involvement in substance use disorder. Two recent reports, however, indicate that lncRNAs, in general, may play a role in cocaine-induced adaptations, as expression of several lncRNAs was altered in the nucleus accumbens (NAc) and midbrain of post-mortem human cocaine abusers (Michelhaugh et al., 2011; Bannon et al., 2015) and in mice following cocaine conditioned place preference (Bu et al., 2012). To better understand a role for NATs in response to repeated cocaine use, we took advantage of a recently published automated algorithm that mines the AceView transcriptomic database to identify biologically relevant sense-antisense pairs (Velmeshev et al., 2013) and revealed that numerous genes that have been previously associated with cocaine-induced neuroadaptations contain NATs. In in vivo studies, we found that expression of Homer1-AS was significantly altered in the NAc of mice following repeated cocaine administration, and that siRNA-mediated depletion of Homer1-AS in vitro altered corresponding sense gene expression. Together, these data indicate NAT-based mechanisms may contribute to cocaine-mediated molecular adaptations.

Methods and materials

Animals

Male C57BL/6 mice (8–10 weeks old, Charles River Laboratories) were housed 4 animals per cage, under a regular 12h/12h light/dark cycle with ad libitum access to food and water. Mice were housed in a humidity and temperature-controlled, AAALAC-accredited, animal facility at the University of Miami Miller School of Medicine. All experiments were approved by the Institutional Animal Care and Use Committee (IACUC) and conducted according to specifications of the NIH as outlined in the Guide for the Care and Use of Laboratory Animals.

Drug Treatments

Cocaine HCl (NIDA, Research Triangle Park, NC) was dissolved in 0.9% sterile saline. Animals received one intraperitoneal (i.p.) injection of saline or cocaine (20 mg/kg) once a day for 10 consecutive days for repeated exposure experiments and a single injection of saline or cocaine (20 mg/kg) for acute studies. Two hours or 10 days after the last injection, bilateral tissue punches of the nucleus accumbens (NAc) were collected on ice and flash frozen in liquid nitrogen and then processed for RNA analysis as described below. Doses for all drugs were based on their salt form.

Bioinformatics analysis

We utilized a previously published bioinformatics algorithm to identify Natural Antisense Transcripts (NATs) from AceView transcriptome database (Velmeshev et al., 2013). The open-access algorithm and the manual are available at https://github.com/DmitryVel/NATs. Briefly, the algorithm takes an input list of genes and first identifies all transcripts expressed from the antisense strand of the target locus or the gene promoter (1kb downstream from the transcription start site). Next, transcripts containing a significant open reading frame according to the annotation on AceView are filtered out to retain noncoding NATs. We utilized this pipeline to investigate the expression of antisense transcripts overlapping with 545 genes. This list was based on previously published genes that have been implicated in cocaine-induced neuroadaptations (Renthal et al., 2009; Maze et al., 2010; Ferguson et al., 2013; Feng et al., 2014) and from the top gene searches on Allan Brain Atlas related to neuroplasticity. The pipeline output yielded the existence of an antisense overlap, the position of the overlap, the NAT Aceview name, the NAT length and the overlap start and stop sites (Table S1). PANTHER (http://www.pantherdb.org/) was used to categorize NAT-containing genes based on protein class.

Cell culture

Neuro-2a (N2a) cell lines (ATCC) were maintained in Advanced DMEM supplemented with 10% FBS and 1% primocin. In a 6 well plate, ~400,000 cells were plated and transfected 24 h later with scrambled control (Qiagen SI03650318) or Homer1-AS siRNA (Forward: 5′ GUACAAAUGCAAUGUGUUAUU 3′, Reverse: 5′ UAACACAUUGCAUUUGUACUU 3′) in lipofectamine RNAiMax (Invitrogen) according to the manufacturer’s instructions (20 or 40 nM for 48 h). A blank group treated with transfection reagent only was also included as an additional control. After treatment, N2a cells (6 biological replicates with the same passage number and treatment time) were harvested for RNA analysis as described below.

Quantitative Real-Time PCR

Following treatment, RNA was isolated using a Trizol and column RNA extraction kit as described by the manufacturer (RNeasy kit, Qiagen). Samples were run in triplicate replicates, normalized to beta-actin and analyzed using the 2−ΔΔCT method. NAT primers (Table S1) were preferentially designed to span a spliced junction of the antisense transcript that does not overlap any spliced junction of the sense gene to avoid sense transcript amplification. In cases where no junctional primers could be designed, we designed a primer pair targeting an exon of the antisense transcript and utilized a strand-specific qRT-PCR to amplify only the antisense transcript. To perform strand-specific measurement of antisense transcript expression, we designed primers for a region of antisense transcript that overlaps with an intron or the promoter of the sense gene. Using the one-step RNA-to-Ct SYBR Green Kit (Life Technologies, 4389986), the reverse transcription (RT) step was performed in a 384-well optical plate using reverse primers to specifically reverse-transcribe antisense RNA and to exclude the possibility of measuring the expression of the sense pre-mRNA. Samples were then incubated at 95°C for 5 minutes to inactivate the reverse transcriptase enzyme. Forward primers were then added to the reaction and quantitative PCR was performed on the same plate. We included no-RT control and no-template controls for each set of primers to control for non-specific binding and melting curves were analyzed to verify PCR specificity. Homer1 and beta-actin expression were measured with Taqman assays as described by the manufacturer (ThermoFisher, Mm00516275_m1 and Mm02619580_g1). A map of the sense/antisense overlap of Homer1/Homer1-AS may be found on the Aceview mouse database (https://www.ncbi.nlm.nih.gov/ieb/research/acembly/) by searching for mahemo. Using SnapGene software, an additional map of Homer1 sense and antisense is shown in Figure 4. In Figures 2, 3 and 5, the spliced form of Homer1-AS was measured.

Figure 4. Graphical representation of Homer1 sense and antisense map.

Figure 4

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Genomic location of mouse antisense (blue) and sense (green) RNA pairs for Homer1.

Figure 2. Expression of noncoding antisense RNAs in the NAc.

Figure 2

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Following repeated cocaine or saline injections, NAc was collected for qPCR analysis. Significant change in Homer1-AS expression was revealed in cocaine-treated mice. *P < 0.0001 compared to saline via Benjamini and Hochberg false discovery rate test, n = 7–9.

Figure 3. Homer1 and Homer1-AS expression following repeated or acute cocaine injections.

Figure 3

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Repeated cocaine injections increased Homer1-AS, but not Homer1, in the NAc 2 hours (A) and 10 days (B) after the last injection. C) Increased Homer1, but not Homer1-AS, expression in the NAc 2 hours following a single injection of cocaine. *P < 0.005 and **P < 0.0005 compared to saline via Bonferroni post-hoc test, n = 6–9.

Figure 5. Sense and antisense expression following Homer1-AS knockdown.

Figure 5

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A) Reduction of Homer1-AS following siRNA treatment in N2a cells. B) Increase in Homer1 expression following Homer1-AS knockdown in N2a cells. *P < 0.05, **P < 0.01, ***P < 0.0001 compared to si-Control via Newman-Keuls post-hoc test.

Data Analysis

Graphpad Prism software was used for graph preparation and statistical analysis. Rq values were normalized to saline or vehicle-treated samples and compared between groups using one- or two-way ANOVA. Newman-Keuls, Bonferroni or Benjamini and Hochberg false discovery rate test was performed for post-hoc comparisons. Data are mean ±SEM, and the level of significance was set to ≤ 0.05.

Results

To explore a potential role for NATs in response to repeated cocaine exposure, we compiled a list of 545 genes that have been associated with neuroplasticity and/or addiction, and used our previously described algorithm to mine the AceView database to identify overlapping sense-antisense pairs (Velmeshev et al., 2013) (Table S1). Using this pipeline (Figure 1A), we found that 22% (121/545) of the genes examined contained NATs, several of which (23/121) contained two or more NATs per gene (Figure 1B). Gene ontologies were diverse, with the largest proportion of the NAT-containing genes classified under receptor and signaling molecules (Figure 1C). The vast majority of these antisense RNAs were classified as intronic overlap with respect to the sense gene, though some were found to overlap with the promoter and exonic regions (Table S1).

Figure 1. Bioinformatics pipeline and classification of noncoding antisense RNAs.

Figure 1

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(A) Schematic of bioinformatics pipeline used to identify natural antisense transcripts. (B) One hundred and twenty-one noncoding antisense (AS) RNAs were identified from 545 genes examined. (C) Gene ontology analysis of NAT-containing genes based on protein class.

To determine if the expression of these transcripts was altered in response to cocaine, we selected 25 antisense RNAs, many of which overlap with genes that have been implicated in cocaine-induced adaptations (Table 1), and quantified their expression in the nucleus accumbens (NAc) 2 hours following the last cocaine or saline injection. A two-way ANOVA showed significant interaction between antisense transcript and treatment (F(24, 394) = 3.0, P < 0.0001), a main effect for antisense transcript (F(24, 394) = 3.0, P < 0.0001, n = 7-9) but no main effect for treatment (F(1, 394) = 0.6, P > 0.05) (Figure 2). Benjamini and Hochberg post hoc test revealed that Homer1-AS was significantly altered following repeated cocaine treatment (P < 0.0005, Figure 2, Table S2). Although Homer1-AS was increased in the NAc following repeated cocaine administration, no change in Homer1 expression was observed at the same time point following repeated cocaine injections (Figure 3A). Homer1-AS remained significantly elevated 10 days following repeated cocaine injections (P < 0.005, Figure 3B). In additional experiments, an acute injection of cocaine increased Homer1, but not Homer-AS, expression in the NAc (P < 0.0005, Figure 3C). A schematic of the sense-antisense overlap between Homer1/Homer1-AS is shown in Figure 4.

Table 1.

Antisense RNAs examined in the mouse Nac

Gene name NAT name Interaction type Overlap with sense
adenylate cyclase 2 Adcy2-AS intronic 69137671-69138140
beta arrestin 1 Arrb1-AS intronic 106751848-106751978
Brain-derived neurotrophic factor Bdnf-AS promoter 109513857-109514010
Chromodomain helicase DNA binding protein 4 Chd4-AS intronic 125078861-125078948
cholinergic receptor, muscarinic 1B, CNS Chrm1-AS promoter 8737279-8737826
catechol-O-methyltransferase Comt-AS intronic 18421262-18421605
DNA (Cytosine-5-)-Methyltransferase 3 Alpha Dnmt3a-AS intronic 3884675-3884792
dopamine receptor 5 Drd5-AS intronic 38712870-38713757
GABA receptor 1 Gabbr1-AS intronic 37169668-37169798
glutamate receptor, AMPA 4, ionotropic Gria4-AS intronic 4514665-4514849
glutamate receptor, AMPA 4, ionotropic Gria3-AS intronic 39016690-39017360
glutamate kainate receptor 2 Grik2-AS intronic 48863035-48865786
Glutamate Metabotropic Receptor 7 Grm7-AS exonic 110595506-110595915
glycogen synthase kinase 3 Gsk3-AS intronic 38089077-38089347
Homer homolog 1 Homer1-AS intronic 94073408-94073537
5-HT1a receptor Htr1a-AS intronic 106236748-106238201
5-HT receptor 1B Htr1b-AS intronic 81525537-81525886
5-HT receptor 1D Htr1d-AS intronic 135990295-135990924
5-HT2b receptor Htr2b-AS promoter 88009163-88009546
potassium inwardly-rectifying channel, subfamily J, member 6 Kcnj6-AS exonic 94970290-94970498
potassium channel, subfamily K, member 1 Kcnk1-AS exonic 128553148-128553570
K large conductance Ca-activated channel, subfamily M, a1 Kcnma1-AS intronic 24824213-24825059
K large conductance Ca-activated channel, subfamily M, b4 Kcnmb4-AS exonic 115911266-115911408
potassium voltage-gated channel, subfamily Q, member 1. Kcnq1-AS intronic 150399016-150403528
sirtuin 2 Sirt2-AS intronic 29566257-29566534
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NATs typically employ cis-regulatory mechanisms to positively (concordant) or negatively (discordant) regulate the expression of their overlapping sense mRNA (Magistri et al., 2012). Though Homer1 is known to be altered in the NAc following cocaine administration (Szumlinski et al., 2008), it is unclear if Homer1-AS modulates its expression. To identify the relationship between Homer1/Homer-AS expression, we utilized siRNA-mediated knockdown to significantly deplete Homer1-AS in N2a cells (F(3, 20) = 8.1, P < 0.005, n = 6) (Figure 5A). Homer1-AS knockdown resulted in a discordant regulation of Homer1 (F(3, 20) = 60.7, P < 0.0001, n = 6) (Figure 5B), indicating a potential regulatory mechanisms between the protein-coding gene by its corresponding antisense transcript.

Discussion

Recent transcriptomic studies by FANTOM, GENCODE and ENCODE consortia have revealed that RNA plays a variety of roles in nuclear architecture, X chromosome inactivation, imprinting, DNA looping, transcription, translation and epigenetic processes (Magistri et al., 2012). While small noncoding RNAs such as microRNAs have been shown to be important in regulating addiction-relevant neuroplasticity in the brain and cocaine-seeking behaviors (Bali & Kenny, 2013), little is known about the involvement of long noncoding RNAs, particularly natural antisense transcripts (NATs), in cocaine-induced neuroadaptations and behavior. Our results show that numerous genes contain NATs and reveal that Homer1-AS was altered in the nucleus accumbens following repeated cocaine administration. Thus, these data, along with previous reports, indicate that NAT-based mechanisms may regulate transcriptional and/or post-transcriptional responses to cocaine and contribute to cocaine-induced neuroadaptations.

Although cocaine-mediated regulation of Homer1 is an important adaptation underlying drug-seeking behaviors, the effects of cocaine on Homer1 expression are quite complex and dependent upon the duration of cocaine administration, length of withdrawal, and the brain region/isoform examined (Szumlinski et al., 2008). For example, acute cocaine administration transiently increases mRNA and protein of the immediate early gene, Homer1a, and the constitutively expressed isoform, Homer1b/c, in the NAc (Brakeman et al., 1997; Fourgeaud et al., 2004; Zhang et al., 2007). Following 3 weeks of withdrawal from repeated cocaine injections, Homer1b/c protein is decreased in the NAc, which also coincides with reductions in mGluR5 protein and manifestation of cocaine-induced behavioral sensitization (Swanson et al., 2001). In functional studies, knockout or oligo-induced depletion of Homer1 in the NAc enhances locomotor responses to cocaine, whereas over-expression of the constitutive isoform prevents cocaine sensitization (Ghasemzadeh et al., 2003; Szumlinski et al., 2004). The data presented here add another layer of complexity to the regulation of Homer1 in response to cocaine. We identified a noncoding antisense RNA that overlaps with Homer1 and whose expression is increased in the NAc in response to repeated, but not acute, cocaine injections. Although we revealed that acute cocaine transiently increases Homer1 in the NAc, we did not observe a change in Homer1 mRNA expression 2 hours after repeated cocaine administration. These data are consistent with previous studies that have shown a temporary increase in Homer1 mRNA and protein following an acute cocaine injection (Brakeman et al., 1997; Fourgeaud et al., 2004; Zhang et al., 2007) and a delayed decrease in Homer1 protein following repeated cocaine injections (Swanson et al., 2001). Thus, based on the differences in temporal regulation of Homer1 and Homer1-AS, it is conceivable that Homer1-AS affects Homer1 protein expression in the NAc via post-transcriptional processes. In in vitro studies, we revealed that siRNA-mediated knockdown of Homer1-AS increased Homer1 mRNA expression, indicating a discordant regulation mechanism between Homer1 sense and antisense expression. Although we have previously shown that NAT knockdown produced a similar upregulation of sense gene expression in both in vivo and in vitro experiments (Modarresi et al., 2012), it is possible that Homer1/Homer-AS interact differently in specific cells types and under in vitro vs. in vivo conditions. Thus, future in vivo studies are needed to determine a mechanistic role for Homer1-AS. Nonetheless, given that cocaine increases Homer1-AS and that changes in Homer1 contribute to the long-lasting neurochemical and behavioral abnormalities that characterize addiction (Szumlinski et al., 2008), antisense transcripts that overlap with Homer1 may play an important role in cocaine-induced neuroadaptations.

Our earlier findings indicate that the expression of Bdnf, a gene importantly involved in the development of cocaine-induced neuroplasticity and behaviors (Li & Wolf, 2014), is regulated by a Bdnf antisense transcript (Modarresi et al., 2012). Interestingly, in our current studies, Bdnf-AS was reduced 38% following repeated cocaine exposure, though this reduction was not statistically significant when adjusted for multiple comparisons. Due to the stringency of the Benjamini and Hochberg false discovery rate test, Type II errors (false negatives) are possible and future studies are needed to address the functional role of Bdnf-AS in response to cocaine. However, given that Bdnf is known to increase in the NAc following cocaine exposure and self-administration (Graham et al., 2007), it is possible that Bdnf and Bdnf-AS also interact in a discordant manner to regulate behavioral and molecular responses to drugs of abuse. Indeed, a recent study revealed a correlation between polymorphisms in BDNF-AS and heroin abuse in the Han Chinese population (Jin et al., 2016), indicating the potential clinical importance of BDNF-AS in substance use disorders. Likewise, the antisense transcript of Kcnq1 (referred to as Kcnq1ot1), which was reduced by 35% in the NAc by cocaine, has been studied extensively and is known to silence multiple genes in the Kcnq1 domain by establishing a repressive higher order chromatin structure (Mohammad et al., 2009) and, similar to our results, is altered in the mouse NAc by methamphetamine (Zhu et al., 2015). Thus, the epigenetic mechanisms by which Kcnq1-AS and other NATs regulate transcriptional and behavioral responses to psychostimulants merit further investigation.

Utilizing microarray analysis, previous studies have also identified several long noncoding RNAs that were altered in the NAc and midbrain dopamine neurons of human cocaine and heroin abusers (Michelhaugh et al., 2011; Bannon et al., 2015) and in the NAc of mice following cocaine conditioned place preference (Bu et al., 2012). Although NATs were not the primary focus of these previous studies, several of the long noncoding RNAs that were altered by cocaine were antisense transcripts (52/603 in the mouse NAc and 16/32 in the human midbrain) (Bu et al., 2012; Bannon et al., 2015). To our knowledge, Homer1-AS and other NATs examined in the current study were not investigated in previous cocaine studies. However, our current results and previous studies are far from exhaustive. Subsequent RNA-seq studies utilizing the latest lncRNA annotations are needed in order to have comprehensive understanding of the NATs involved in substance use disorder. Another interesting observation in the current study is that few NATs were significantly altered in the NAc by repeated cocaine injections. The stringency of the Benjamini and Hochberg false discovery rate test likely accounts for why only one of the NATs examined met statistical significance. Although only a portion of lncRNAs that were significantly altered by drugs of abuse were NATs in the above studies, it is important to note that many NATs are expressed at low levels and in a cell type-specific manner (Cabili et al., 2011; Derrien et al., 2012; Li et al., 2013; Dong et al., 2015). Thus, small changes in expression that are observed in tissue homogenate may have functional importance in specific cell types. In fact, recent FANTOM5 analyses indicate the potential functionality of 69% of lncRNAs (Hon et al., 2017). Future studies examining brain region-, cell type- and temporal-specific expression profiles of noncoding antisense RNAs following cocaine use, along with functional experiments examining the behavioral consequences of NAT manipulation on drug-seeking behaviors, will lead to a better understanding of NATs in drug-induced neurobehavioral adaptations.

In summary, imbalanced expression of NATs may result in the silencing or activation of partner protein-coding genes, thus providing a potentially interesting and novel mechanism to explain the aberrant gene regulation following repeated drug use. Based on these initial findings and previously published data, we hypothesize that repeated cocaine administration leads to a dysregulation of natural antisense transcripts that may act in concert with transcriptional and post-transcriptional machinery to pathologically alter gene expression and behavior. However, additional studies are needed to better understand the anatomical and temporal dynamics of NAT expression following acute and repeated cocaine exposure and to reveal the functional importance of specific NATs during drug-seeking behaviors. Such experiments may lead to the incorporation of NATs into epigenetic models of drug-induced plasticity and open the door for critically-needed new therapeutic avenues for substance use disorder.

Supplementary Material

1
2

Highlights.

  • Many genes that have been implicated in addiction overlap with natural antisense transcripts.

  • Homer1 antisense transcript is significantly increased in the nucleus accumbens by cocaine.

  • Knockdown of Homer1 antisense transcript increases expression of Homer1 in vitro.

Acknowledgments

In remembrance of David Lin, for his skill and dedication were essential to this work. This research was supported by National Institute on Drug Abuse Grant: R21DA035592. S.K.P. was supported by Howard Hughes Medical Institute (HHMI) Undergraduate Research Program. The cocaine used in these studies was obtained from the NIDA Drug Supply Program. G.C.S., S.K.P., D.V., M.M. and C.W. designed the experiments. G.C.S., S.K.P., D.Y.L., H.J.W., A.M. and D.V. conducted the experiments. G.C.S. and D.V. wrote the paper with input from S.K.P., M.M., H.J.W., A.M., M.A.F. and C.W.

Footnotes

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Associated Data

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Supplementary Materials

1
NIHMS917213-supplement-1.xlsx (37.7KB, xlsx)
2
NIHMS917213-supplement-2.xlsx (33.4KB, xlsx)

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