Candidate Agtr2 influenced genes and pathways identified by expression profiling in the developing brain of Agtr2−/y mice

doi:10.1016/j.ygeno.2009.05.011

Genomics. Author manuscript; available in PMC 2011 August 31.

Published in final edited form as:

Genomics. 2009 September; 94(3): 188–195.

Published online 2009 June 6. doi: 10.1016/j.ygeno.2009.05.011

PMCID: PMC3164574

NIHMSID: NIHMS122557

Candidate Agtr2 influenced genes and pathways identified by expression profiling in the developing brain of Agtr2⁻^/y mice

Traci L. Pawlowski,^a^b^d Silvia Heringer-Walther,^c^e Chun-Huai Cheng,^b John G. Archie,^a^f Chin-Fu Chen,^b Thomas Walther,^c^g and Anand K. Srivastava^a^b^*

^aJ. C. Self Research Institute of Human Genetics, Greenwood Genetic Center, Greenwood, South Carolina

^bDepartment of Genetics and Biochemistry, Clemson University, Clemson, South Carolina

^cDepartment of Cardiology, Charité, Campus Benjamin Franklin, Berlin, Germany

^* Correspondence author. J.C. Self Research Institute of Human Genetics, Greenwood Genetic Center, 113 Gregor Mendel Circle, Greenwood, SC 29646, USA. Tel. 1 864 388 1806; Fax: 1 864 388 1808; E-mail: anand/at/ggc.org (A.K. Srivastava)

^dPresent address: Neurogenomics Division, TGEN, Phoenix, Arizona;

^ePresent address: Department of Obstetrics, University of Leipzig, Leipzig, Germany;

^fPresent address: Department of Biomolecular Engineering, University of California at Santa Cruz, Santa Cruz, California;

^gPresent address: Department of Biomedical Sciences, Hull York Medical School, University of Hull, UK.

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Abstract

Intellectual disability (ID) is a common developmental disability observed in one to three percent of the human population. A possible role for the Angiotensin II type 2 receptor (AGTR2) in brain function, affecting learning, memory, and behavior, has been suggested in humans and rodents. Mice lacking the Agtr2 gene (Agtr2⁻^/y) showed significant impairment in their spatial memory and exhibited abnormal dendritic spine morphology. To identify Agtr2 influenced genes and pathways, we performed whole genome microarray analysis on RNA isolated from brains of Agtr2⁻^/y and control male mice at embryonic day 15 (E15) and postnatal day one (P1). The gene expression profiles of the Agtr2⁻^/y brain samples were significantly different when compared to profiles of the age-matched control brains. We identified 62 differently expressed genes (p ≤ 0.005) at E15 and in P1 brains of the Agtr2⁻^/y mice. We verified the differential expression of several of these genes in brain samples using quantitative RT-PCR. Differentially expressed genes encode molecules involved in multiple cellular processes including microtubule functions associated with dendritic spine morphology. This study provides insight into Agtr2 influenced candidate genes and suggests that expression dysregulation of these genes may modulate Agtr2 actions in the brain that influences learning and memory.

Keywords: Learning and memory, Intellectual Disability, Dendritic spine, Expression profiling, Agtr2

Introduction

Intellectual disability (ID), also known as mental retardation, is a genetically and clinically heterogeneous condition characterized by below average intellectual functioning (IQ<70) in conjunction with significant limitations in adaptive functioning. The genetic component of ID likely includes deficiencies in the function of a large number of genes distributed throughout the human genome [1].

Angiotensin II (Ang II), a component of the renin-angiotensin system (RAS), mediates its majority of functions through two major Ang II receptor subtypes, type 1 receptor (AGTR1) and type 2 receptor (AGTR2). Studies in mice and humans indicated a possible role for AGTR2 in learning, memory, and behavior [2–6]. Neurological findings in Agtr2-deficient male mice (Agtr2⁻^/y) provided an initial hypothesis of a likely role for Agtr2 in the brain [7, 8]. Recently, a detailed examination of the Agtr2-deficient mice revealed significant impairment in their learning performance in a spatial memory task [9]. These mice exhibited abnormal dendritic spine morphology [9], a feature previously shown to be associated with several cases of ID [10–12].

AGTR2 is a 323-residue G-protein-coupled receptor transcribed from an X-linked gene. Expression of the Agtr2 gene has been shown to be transiently expressed in the mesenchyme of the rat fetus, in various brain structures through embryonic development, with its expression declining rapidly after birth and becoming restricted to a few organs including the brain [13]. At the cellular level, Agtr2 has been shown to be localized in neurons [14]. Involvement of Agtr2 in several signaling cascades influencing neurite outgrowth and elongation, neuronal differentiation, cell proliferation, growth inhibition and induction of apoptosis has emerged in recent years but none is fully defined. Several proteins, avian erythroblastosis oncogene B 3 receptor (ERBB3), zinc finger and BTB domain containing 16 (ZBTB16), solute carrier family 9 (sodium/hydrogen exchanger), member 6 (NHE6/SLC9A6), and mitochondrial tumor suppressor 1 (MTUS1), have been found to interact with regions of AGTR2 [15–18]. Interestingly, defects in the NHE6/SLC9A6 gene have recently been found to cause Christianson syndrome, an X-linked ID condition [19].

To assess the impact of Agtr2 on gene expression and to identify dysregulated genes and pathways relevant to Agtr2 function, we profiled gene expression patterns of Agtr2⁻^/y brains at developmental stage E15 and at birth and compared them to profiles of the age matched control brains. This study revealed a number of candidate genes and cellular processes that may potentially influence brain structure and function critical for learning and memory.

Results

Microarray analysis

Expression microarray analysis was performed using RNA isolated from brains of male Agtr2-deficient (Agtr2⁻^/y) and control mice of identical genetic background using Agilent whole mouse genome 44K expression arrays. Gene expression profiles of the Agtr2⁻^/y brain samples were compared to profiles of the control brains for two developmental stages, E15 and birth (P1). Multiple biological replicates (eight Agtr2⁻^/y and six control brains at E15 and four Agtr2⁻^/y and four control brains at birth) were analyzed individually using a dye swap experimental design. The raw data were analyzed as detailed in the Materials and methods. Hierarchical clustering of each developmental set demonstrated that, overall, the Agtr2⁻^/y mouse brains had significantly different expression patterns than controls (Fig. 1).

Fig. 1

Hierarchical clustering showing knockout animals have different expression profiles as represented by the dye swap color coding below the tree, with the red bar and tree branches being the control group and yellow the Agtr2⁻^/y group. Each row (more ...)

Data analysis revealed 62 differently expressed genes (52 up-regulated and 10 down-regulated, p≤0.005) (Table 1). A similar analysis in P1 brains resulted in a list of 50 up-regulated and 12 down-regulated genes (Table 2) identified with a fold change greater than or equal to 1.4 and p-value less than 0.005. Fold change was computed with Bioconductor limma software with a log2 transformation. Two genes, phosphatidylserine decarboxylase (Pisd) and RAB30, member RAS oncogene family (Rab30), were found to be upregulated at both developmental stages (Tables 1 and and22).

Table 1

Genes at developmental stage E15 showing fold change ≥ 1.3 and p < 0.005 in Agtr2^−/y brains

Table 2

Genes at P1 Showing Fold Change ≥ 1.4 and p < 0.005 in Agtr2^−/y Brains

We further validated the differential expression of a subset of genes identified by microarray analysis using an independent method. We performed quantitative real-time PCR analysis of transcripts randomly selected from the E15 list (Table 1) and P1 list (Table 2). Changes in expression of these genes in Agtr2⁻^/y brain samples relative to control brains were in agreement with the direction of the expression profile array data (Table 3). Four genes tested were significantly (p≤0.05) differentially expressed by qRT-PCR. The expression of seven other genes were comparatively not statistically significant (p≥0.07) but reflected the direction and approximate magnitude of fold-change as observed on the expression arrays. Failure to reach statistical significance in these cases may be either due to some potential false positive findings in the expression array data or due to the small sample size (four controls and four knockouts) used for the secondary verification by qRT-PCR.

Table 3

Q-RT-PCR Results of Selected Genes at E15 and Postnatal Day 1

Functional grouping

In an attempt to uncover common functions among the dysregulated genes, we classified genes into gene ontology groups. A summary of functions for dysregulated genes in the E15 knockouts are presented in Supplementary Table 1. The largest gene categories over-expressed in E15 Agtr2⁻^/y brains are transcription factors and genes with Agtr1-related functions (Supplementary Table 1). Other categories include genes involved in microtubule and actin processing, cell adhesion, protein transport and/or binding, nucleic acid binding, immunity, cell cycle arrest, and ubiquitin/proteosome function. In the E15 Agtr2⁻^/y brains, genes predominantly involved in apoptosis, polo-like kinase 1 (Plk1), prostaglandin E synthase 2 (Ptges2), growth factor erv1 (Gfer) and ubiquitin-conjugating enzyme E2M (Ube2m), were down-regulated.

Up-regulated genes in the P1 Agtr2⁻^/y brains were involved in protein binding and transport, RNA processing, DNA binding, transcription, glutamate metabolism, cell adhesion as well as cytoskeleton and microtubule expression. A complete summary of the categories is listed in Supplementary Table 2.

Examination of the P1 down-regulated results (Supplementary Table 2) show that some of the gene functions involved are histone modification (Nasp, nuclear autoantigenic sperm protein and Ppp2cb, protein phosphatase 2 (formerly 2A), catalytic subunit, beta isoform), nucleotide metabolism (Itpa, inosine triphosphatase), NADP+ activity (Idh1, isocitrate dehydrogenase 1 (NADP+) soluble), protein ubiquitination (Fbxo11, F-box protein 11 and Ndfip2, Nedd4 family interacting protein 2), rRNA processing (Frg1, FSHD region gene 1), chromatin remodeling (Chmp5, chromatin modifying protein 5), and calcium ion binding (Creld1, calcium ion binding, cysteine-rich with EGF-like domains 1).

Pathway and network analysis

Pathway Studio (Ariadne, Rockville, MD) was used to visualize common functions for dysregulated genes in the E15 Agtr2⁻^/y brains. Examining the up-regulated genes in the Agtr2⁻^/y E15 brains with 1.3 fold or greater expression revealed a complex picture. Among the up-regulated genes, microtubule-associated protein 2 (Mtap2), microtubule-associated protein 1B (Mtap1B), A kinase (PRKA) anchor protein (Akap9), formin binding protein 1-like (Fnbp1l), triple functional domain (Trio) and Src-like-adaptor 2 (Sla2) are all associated with microtubule, actin and cytoskeleton function (Fig. 2A). Agtr2 has previously been shown to down-regulate MAP1B (Mtap1b) but up-regulate MAP2 (Mtap2) in PC12W cells [20]. In this study, Mtap2 and Mtap1b are both up-regulated in the E15 Agtr2⁻^/y brains. MAP2 has previously been shown to be phosphorylated by JNK and subsequently defines dendritic shape in the brain [21]. MAP2 is found in dendrites and is crucial for microtubule stability [22]. Mtap1b is found in growth cones and is needed for neurite outgrowth [20]. These genes also regulate actin along with Fnbp1l and Sla2 genes [23] which are up-regulated in E15 Agtr2⁻^/y brain. Genes involved in regulation of microtubules, adducin 1 (alpha) (Add1), echinoderm microtubule associated protein like 5 (Eml5), Huntingtin (Htt), hook homolog 1(Hook1), NudC domain containing 3 (Nudcd3) and septin 11 (Sept11), are also well represented in the over-expressed genes of the P1 knockouts.

Fig. 2

Pathway analysis of selected up-regulated transcripts in Agtr2⁻^/y brains (A) Transcripts up-regulated in Agtr2⁻^/y embryo brains are involved in pathways affecting microtubules, actin and cytoskeleton expression as well as other cell functions (more ...)

Map kinase 8 (Mapk8) (also known as JNK1) is part of the Agtr1 signaling cascade and is one of the most significantly up-regulated genes in the P1 knockout brains. It has been shown to be a regulator of morphogenesis in early nervous system development [24]. JNK1 phosphorylates the microtubule depolymerizing factor SCG10 which determines microtubule stability and axodendritic length [24].

The up-regulation of conserved helix-loop-helix ubiquitous kinase (Chuk) (also known as IKK1) in the P1 brains is significant in that it is also influenced by angiotensin II [25], and activates the NF-kappa-B complex, which in turn causes cell proliferation and anti-apoptotic effects [26]. Notch gene homolog 2 (Notch2) and Htt are up-regulated in P1 knockouts and both have anti-apoptotic effects [27–29]. Htt up-regulates brain derived neurotrophic factor (BDNF) [30] and associates with the epidermal growth factor (EGF) pathway, potentially causing over-growth of neuronal cells. Notch2 is also negatively associated with glial differentiation [31].

Consistent with previous findings that Agtr2 induces apoptosis, three genes down-regulated in E15 Agtr2⁻^/y brains, Ptges2, histocompatibility 2, T region locus 10 (H2-T10) and Ube2m, are all involved in inducing apoptosis.

In the P1 knockouts several over-expressed genes, AMPA-selective glutamate receptor 4 (Gria4), glutaminase (Gls) and Htt, were found to be involved in glutamate metabolism. Glutamate metabolism is integral to NMDA receptors which are essential in neuronal development and synaptic plasticity.

Other important up-regulated genes in the P1 list are the cell adhesion genes (Ncam1, Gria4, nuclear receptor subfamily 1, group I, member 3 (Nr1i3) and Mapk8). Ncam1, neural cell adhesion molecule 1, has been associated with NMDA receptors [32] and the inhibition of cell death [33]. Poliovirus receptor-related 4 (Pvrl4) is also a cell to cell adhesion gene [34]. Ncam1, Gria4, Nr1i3 and Mapk8 all share several important neurological functions (Fig. 2B).

Discussion

Cognitive function and adaptive behavior are two major functions of the brain that are consistently found to be impaired at variable levels in people with intellectual disability. Several genes, when defective, have been identified that cause learning and memory impairment in humans and mice. A role for Agtr2 in brain development and function has been suggested and a likely involvement of AGTR2 in human ID has been previously shown [2–6]. A detailed examination in Agtr2-deficient mice further revealed a deficit in spatial memory that was not related to fear [7, 8]. These mice have demonstrated cellular over-growth in all examined brain regions [35]. Importantly, these mice showed abnormal dendritic spine morphology and length [9]. Both features are also found in some cases of ID. Thus, these mice provided a model system for studying genes whose function might be dependent or influenced by Agtr2 gene function.

Expression of Agtr2 has been shown to be variable and transient in various brain structures during embryogenesis with expression declining rapidly after birth [13, 22]. We confirmed expression of the Agtr2 gene at the E15 stage of mouse embryonic brain and chose to use this developmental stage to study the impact of Agtr2 gene action. We examined expression levels of 44,000 probes representing approximately 25,000 genes in Agtr2 ⁻^/y and control mouse brains at developmental stage E15 and at birth (P1). Significant differences in gene expression were demonstrated by hierarchical clustering and t-test analyses. Agtr2⁻^/y samples grouped together and were distinct from control samples.

Expression profiles of Agtr2⁻^/y brains also shed light on possible cellular mechanisms and genes that might be contributing to the cognitive impairment and defective dendritic morphology observed in these mice [9]. These mice had altered spine morphology in areas of CA1, including stubby, enlarged spine formation, aberrant protrusions, and hydropic spine degeneration [9]. Dendritic spines and their morphological plasticity play a critical role in learning and memory function of the brain. Many forms of ID have been shown to be associated with abnormalities in dendritic spine morphology and structure [10–12, 36]. The structure and dynamics of these structures have been shown to be influenced by the underlying actin-cytoskelton and microtubules. Thus the expression levels of genes regulating these structures are likely to play a critical role. Similar findings were previously reported in Fmr-1 knockout mice [12]. Interestingly, several genes up-regulated in Agtr2⁻^/y brains are involved in cytoskeleton and microtubule regulation. The over-expression of these genes may potentially lead to alterations in the actin-cytoskeleton and dendritic spine seen in Agtr2⁻^/y mouse brains.

Several genes involved in apoptosis were down regulated in E15 Agtr2⁻^/y brains which support a role for Agtr2 as a mediator of apoptosis. Consistently, genes involved in anti-apoptosis activities were upregulated in P1 Agtr2⁻^/y brains and may reflect the increase in the number of neuronal cells observed in adult Agtr2⁻^/y mice brain regions [35].

Surprisingly only two dysregulated genes, Pisd and Rab30, were found in common between the two developmental stages. Significance of this observation is not clear. However, differences in expression of Agtr2 influenced genes at two different time points of brain development may relate to the observed variation in Agtr2 gene expression during embryogenesis [13, 22].

Activation of Agtr2 has been shown to negatively regulate some of the actions of Agtr1 [37]. The absence of Agtr2 did not cause increased expression of Agtr1 in the brains of E15 or P1 Agtr2⁻^/y mice. There was also no difference in the expression of several genes in the RAS between knockouts and controls (data not shown). However, our results show that genes downstream of Agtr1 are up-regulated in the absence of Agtr2.

Previous studies have indicated involvement of Agtr2 in various signaling cascades influencing neurite outgrowth and elongation, neuronal differentiation, cell proliferation, growth inhibition and induction of apoptosis [20, 38–41]. Furthermore, Agtr2 has also been shown to directly interact with a variety of proteins, ERBB3, ZBTB16, SLC9A6/NHE6 and MTUS1 [15–18]. Thus it is not surprising that our study revealed a great variety of Agtr2 influenced genes. However, a detailed mechanism of Agtr2 actions remains to be elucidated and it is conceivable that some of the Agtr2 effects are likely direct and others may be indirect.

The data in this study provide a first glimpse of the gene expression profile of developing and newborn brains in the absence of Agtr2 expression. Although it would be premature to propose a direct link between genes dysregulated in Agtr2⁻^/y brain and observed features in Agtr2⁻^/y mice, the data provide clues to these functional correlations and can be examined further by additional experimental means. Expression profiling using specific brain regions or at additional developmental stages may reveal critical genes that may have been masked in our analyses of whole brain. Further studies may reveal that dysregulation of expression of some of the genes influenced by Agtr2 may contribute either directly or through other factors to the pathophysiology of intellectual disability.

Materials and methods

Animals

Agtr2⁻^/y mice were described previously [3, 9] and are from the 129/sv strain on a C57BL/6 × 129 mixed genetic background with a disrupted Agtr2 gene. Pre-dissected organs from Agtr2⁻^/y and control mice were isolated from the breeding stocks maintained at the Charité, Campus Benjamin Franklin, Berlin, Germany. Experiments were conducted according to the guidelines of the National Act on Use of Experimental Animals of the German Federal State [9].

Animal genotyping was performed after isolating liver DNA using the Qiagen DNA tissue kit (Qiagen Inc., Valencia, CA) according to manufacturer’s recommendation and was used for animal genotyping. PCR was performed with the following primer sets: knockout- NeoPvu-F, 5′-GGCAGCGCGGCTATCGTGG-3′ and control AT25-F, 5′-CCACCAGCAGAAACATTACC-3′ and the same reverse primer was used for both: AT23-R, 5′-GAACTACATAAGATGCTTGCCAGG-3′. The cycling conditions were: 95 ºC for 5 min followed by 30 cycles of 95 ºC for 30 sec, 60 ºC for 30 sec and 72 ºC for 45 sec, with a final extension of 7 min. Sex was determined by genotyping with an X-linked gene Jarid1 C, using the following primers: Forward, 5′-CTGAAGCTTTTGGCTTTGAG-3′ and reverse, 5′-CCACTGCCAAATTCTTTGG-3′ with the following conditions: initial denaturation at 95 °C for 5 min, followed by 20 sec at 95 °C, 30 sec at 56 °C, and 40 sec at 72 °C for 30 cycles with a final extension at 72 °C for 7 min [42]. Jarid1 C primers produced a 331 bp (chromosome X-specific fragment) and 302 bp (specific to a homologue to Jarid1 C on the Y chromosome) DNA fragments in males and a single 331 bp DNA fragment in females.

RNA extraction, cDNA synthesis and array hybridization

Total RNA was extracted from frozen whole brain samples weighing less than 30μg using the Qiagen RNeasy kit (Qiagen Inc., Valencia, CA) according to manufacturer instructions. Samples were cleaned with DNase using the Ambion Turbo DNase-free kit (Ambion Inc., Austin, TX). RNA samples were analyzed on the Agilent 2100 expert bioanalyzer (Agilent, Santa Clara, CA) for purity and concentration.

RNA from six male controls and eight male knockouts at stage E15 were amplified individually and labeled with the Agilent low RNA Input Linear Amplification Kit (Agilent, Santa Clara, CA) according to the manufacturer’s instructions. In brief, cDNA was synthesized using a T7 primer and was then labeled with Cy3- or Cy5-CTP. Samples were purified with Qiagen RNasey mini spin columns (Qiagen, Valencia, CA). Equal amounts of control sample and Agtr2⁻^/y sample were labeled with Cy3 or Cy5 respectively and were hybridized to the first set of 8 Agilent Whole Mouse Genome Oligo 44K Microarrays slides (Agilent, Santa Clara, CA) according to the manufacturer’s protocol. On the second set of microarray slides, the control samples were paired with a different knockout sample. Arrays were hybridized for 17 hours at 65ºC and then washed with 6X SSC, 0.005% Triton X-102 for one min and then with 0.1X SSC, 0.005% Triton X-102 for one min and then for 30 sec in ozone scavenging solution (Agilent #5185–5979). The microarray slides were scanned on an Agilent microarray scanner and data was normalized and extracted with Feature Extraction 8.0 software (Agilent, Santa Clara, CA). RNA from four male control and four P1 Agtr2 ⁻^/y brains was handled in the same fashion, with all controls being dye-swapped with a different knockout in each dye selection.

Microarray analysis

MIAME-compliant microarray data files are located on the GEO site at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=jnwbzucukeckkbs&acc=GSE12412 (project accession # GSE12412). Two arrays from the E15 set were not included due to poor hybridization. The data sets were first filtered for probes that had a presence in at least 50 percent of the arrays using dye swap as a parameter. This left 33,583 probes in the E15 data set and 32,974 probes in the P1 data set. Both data sets were then filtered by an absolute fold change of 2 fold (log10) or greater between knockouts and controls as determined by GeneSpring GX (Agilent, Santa Clara, CA). This filtering produced a list of 313 probes in the E15 set and 1340 probes in the P1 set. This data was then subject to a Student’s t-test with a p-value ≤ 0.005 (which compared favorably to a similar test with a Benjamini and Hochberg False-Discovery rate of ≤ 0.01). This analysis led to an E15 list of 133 probes and a P1 list of 397 probes. Fold change (log2) was then calculated using limma [43, 44]. The lists were further narrowed by using the most significant probes by fold change as determined by limma to a list of 62 transcripts for the E15 set and a similar number of transcripts for the P1 stage. Fold change (log2) threshold values of 1.3 and 1.4 as determined by limma were chosen for the E15 and P1 list respectively to generate a more focused set of genes for further analysis.

Hierarchical clustering (condition tree and gene tree) of the E15 and P1 arrays was performed by GeneSpring GX using a Pearson correlation with a clustering algorithm = average linkage, with a separation ratio of 1 and a minimum distance of 0.001 using the E15 or P1 final list.

Quantitative RT-PCR

RNA was isolated as previously described on four controls and four knockouts from each developmental stage, and from animals not used in the microarray experiment previously. Primers were designed using the Primer3 program (http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi) [45]. Biorad I-Script 1 step RT-PCR with SYBR green (Biorad, Hercules, CA) was used according to manufacturer instructions with 5 ng of RNA per sample used. Samples were run in triplicate on a Biorad i-cycler and analyzed using a standard curve method [46] and normalized to a control gene. The control gene, AK029535 (Riken cDNA493050c13) was selected from a list of genes showing the least difference in expression generated by limma using the model 1a algorithm as described earlier [47]. The list of primers used is in Supplementary Table 3. After normalization to the control gene, the mean log2 expression ratio for knockouts was divided by the same for controls, to arrive at the fold change. Two-tailed t-tests were implemented to determine significance of changes between the two groups.

Functional grouping, annotation and pathway analysis

Annotation of genes in the list was enhanced by using the DAVID Gene Id Conversion Tool with a p-value threshold of ≤ 0.05 [48]. Gene ontology for genes in the final lists was also enhanced individually investigating the gene ontology information provided by the Entrez Gene search tool of NCBI.

Pathway Studio (Ariadne Genomics, Rockville, MD) was utilized by loading each up or down-regulated list and using the shortest path function. This software builds a network from information available from curated databases. This information is used to draw functional relationships between proteins, cell objects, small molecules, diseases and cell processes.

Supplementary Material

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Acknowledgments

We thank Drs. Liangjiang Wang and Julianne Collins for helpful discussions and technical assistance. We also thank Dr Minoru Ko for assistance in experimental planning. This work was supported, in part, by a grant from the NIH (R01 HD39331) to A.K.S. and a grant from the South Carolina Department of Disabilities and Special Needs (SCDDSN).

Footnotes

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