Neurobiology of Disease 59 (2013) 257–266

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Neurobiology of Disease

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Loss of MeCP2 function is associated with distinct expression changes in the striatum

Ying-Tao Zhao 1,DarrenGoffin 1, Brian S. Johnson 1, Zhaolan Zhou ⁎

Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA article info abstract

Article history: Rett syndrome (RTT) is a neurodevelopmental disorder characterized by developmental regression beginning Received 1 May 2013 6–18 months after birth, followed by a lifetime of intellectual disability, stereotyped behaviors, and motor defi- Revised 5 July 2013 cits. RTT is caused by mutations in the gene encoding MeCP2, a methyl-CpG binding protein believed to modulate Accepted 2 August 2013 gene transcription. Gene expression studies of individual brain regions have reported that Mecp2 loss-of-function Available online 13 August 2013 leads to both activation and repression of its gene targets in mice. Conditional deletion of MeCP2 from different brain regions has revealed unique insights into the role of these structures in mediating particular RTT-like phe- Keywords: Methyl-CpG binding protein 2 notypes. However, the function of MeCP2 in the striatum, a major brain region involved in motor control and MeCP2 executive cognitive functions, has yet to be studied. Here, we characterized the gene expression changes in the Rett syndrome striatum of Mecp2 mutant mice. We found a number of differentially expressed in the striatum of both con- RTT stitutive Mecp2-null mice and mice lacking MeCP2 only from forebrain GABAergic neurons. These changes only Gene expression occurred when MeCP2 expression levels had reached mature levels and RTT-like symptoms were manifest, Striatum supporting a role for MeCP2 in maintaining proper brain function. Many of the gene expression changes identi- fied in the striatum have not previously been shown to change in the hypothalamus or cerebellum. Bioinformatic analysis of differentially expressed genes in striatum as well as hypothalamus and cerebellum revealed that loss of MeCP2 does not affect the global landscape of gene expression. Additionally, we uncovered a number of differ- entially expressed genes in the liver of Mecp2-null mice suggesting an important role for MeCP2 in non-neuronal tissues. Collectively, our data suggest that the differential expression of genes following loss of MeCP2 occurs in a tissue- or cell-type specific manner and thus MeCP2 function should be understood in a cellular context. © 2013 Elsevier Inc. All rights reserved.

Introduction Mecp2-null mice such as reduced brain and body weight, decreased locomotor activity, motor incoordination, gait and breathing abnormal- RTT is a severe X-linked neurological disorder that affects 1 in ities (Chen et al., 2001; Guy et al., 2001). These studies demonstrate that 10,000–15,000 females. Patients with RTT experience a relatively nor- RTT is primarily a neurological disorder and that MeCP2 is indispensable mal first 6–18 months of life after which they enter a period of develop- for proper brain function. Furthermore, conditional deletion of Mecp2 mental stagnation or regression. Subsequently, patients lose learned from specific brain regions or specific population of brain cells have motor and communication skills, and develop hand stereotypies and demonstrated that different symptoms of RTT may manifest through gait apraxia (Katz et al., 2012; Neul et al., 2010). Approximately 95% of loss of MeCP2 function from particular brain regions or cell types RTT cases are associated with mutations in the gene encoding methyl- (Adachi et al., 2009; Chao et al., 2010; Fyffe et al., 2008; Lioy et al., CpG binding protein 2 (MeCP2). 2011; Samaco et al., 2009; Ward et al., 2011). However, while specific Genetic studies using Mecp2 knockout mice, or mice carrying neurotransmitter systems and neuronal populations play important RTT-associated mutations, have established a causal role of MeCP2 in roles in the etiology of individual RTT-like phenotypes, the large-scale the etiology of RTT (Chen et al., 2001; Goffin et al., 2012; Guy et al., disruption of MeCP2 function is required for the appearance of pheno- 2001; M. Shahbazian et al., 2002; Pelka, 2006). Conditional deletion of types that mimic constitutive Mecp2-null mice (see GoffinandZhou, Mecp2 from the mouse brain recapitulates the phenotypes observed in 2012 for review). MeCP2 is a highly abundant nuclear protein that binds methylated CpGs (5mC) in vitro and in vivo (Skene et al., 2010). Through its interac- Abbreviations: RTT, Rett syndrome; MeCP2, methyl-CpG binding protein 2; WGCNA, tion with co-repressor complexes, such as Sin3A and histone deacetylases weighted gene co-expression network analysis. 2 (HDAC2), MeCP2 was originally postulated to repress gene transcrip- ⁎ Corresponding author. tion (Nan et al., 1997); however initial gene expression studies did E-mail address: [email protected] (Z. Zhou). Available online on ScienceDirect (www.sciencedirect.com). not find significant changes in gene expression upon loss of MeCP2 1 These authors contributed equally to this work. (Kriaucionis et al., 2006; Tudor et al., 2002). To reduce the potentially

0969-9961/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.nbd.2013.08.001 258 Y.-T. Zhao et al. / Neurobiology of Disease 59 (2013) 257–266 confounding effects of cellular heterogeneity in the brain, other studies in the pathogenesis of RTT, or a biochemical maker of striatal dysfunc- examined gene expression changes using individual brain regions; tion, however, has yet to be examined. these studies identified hundreds to thousands of genes whose expres- Given the potential role for MeCP2 in the repression and activation sion is affected by MeCP2 dysfunction in the hypothalamus and cerebel- of gene transcription, we examined whether loss of MeCP2 alters gene lum (Ben-Shachar et al., 2009; Chahrour et al., 2008). Notably, most of expression within the striatum. The striatum affords a unique advan- these differentially expressed genes were down-regulated in Mecp2- tage for gene expression studies because it is composed primarily of null mice and up-regulated in Mecp2-overexpressing mice, arguing GABAergic MSNs. This homogeneity in cell type reduces the confound- against a primary role for MeCP2 in gene repression. This additional ing effects that multiple unique cell types with highly divergent role for MeCP2 in gene activation may result from the recruitment gene transcriptional programs can have on gene expression analyses of CREB by MeCP2 (Chahrour et al., 2008) or the binding of MeCP2 (Heiman et al., 2008). Since altered neuronal activity caused by the to 5-hydroxymethylcytosine (5hmC), which is enriched over active loss of MeCP2 from afferent inputs to the striatum may indirectly affect genes (Mellén et al., 2012; Szulwach et al., 2011). Since the pattern of striatal gene expression, we conditionally deleted MeCP2 from fore- 5mC and 5hmC localization across the genome is cell-type dependent brain GABAergic neurons, including striatal MSNs, while preserving (Mellén et al., 2012), genes that have been previously identified as dif- expression in those neurons that provide inputs to the striatum. We ferentially expressed in the hypothalamus and cerebellum may reflect achieved this by breeding floxed Mecp2 mice (Mecp22lox/+)(Chen the composite changes across multiple cell types. et al., 2001) to mice expressing Cre-recombinase localized to striatal One brain region that has received little attention in the RTT field is MSNs and forebrain GABAergic interneurons (Dlx5/6-cre) (Monory the striatum. This brain region serves as the input center for the basal et al., 2006). The behavioral consequences of deletion of MeCP2 from ganglia, a subcortical region of the brain that processes and integrates forebrain GABAergic neurons using Dlx5/6-cre have previously been de- information associated with motor control and various executive cogni- termined (Chao et al., 2010). These mice do not show any of the overt tive functions. Indeed, hand stereotypies, impaired motor coordination RTT-like phenotypes – such as hypoactivity, gait, breathing difficulties and disrupted cognitive functions are common for all RTT patients. In or premature lethality – that are readily apparent in constitutive addition, RTT patients often display a volumetric decrease in the size Mecp2-null mice. However, behavioral characterization of these mice of the striatum (Reiss et al., 1993; Subramaniam et al., 1997). Deletion revealed phenotypic alterations involving social interaction preference, of MeCP2 from forebrain GABAergic neurons leads to the expression motor coordination and repetitive behaviors (Chao et al., 2010). To de- of several RTT-like phenotypes (Chao et al., 2010). However, the role termine the efficiency of cre recombinase in the striatum of these mice, the striatum plays in mediating these phenotypes is not known. Addi- we performed immunohistochemistry using an antibody directed tionally, the genes regulated by MeCP2 in the striatum have yet to be against MeCP2 in the male progeny of mice with the Mecp22lox/y; defined. Given that 97–98% of striatal neurons are GABAergic medium Dlx5/6-cre genotype (referred hereafter as cKO) and their Mecp22lox/y spiny neurons (MSNs), this cell homogeneity affords this region a (WT) littermates. Indeed, we demonstrate a significant loss of MeCP2 unique advantage for the study of MeCP2-regulated gene expression. immunoreactivity from the striatum of cKO mice but not their WT litter- In this study, we profiled gene expression changes in the striatum of mates (Fig. 1A). In addition, close examination of MeCP2 expression re- mice following the conditional deletion of MeCP2 from the striatum vealed the existence of b1% of MeCP2-positive cells in the striatum during early development and at an adult stage. We identified 21 differ- (Supplementary Fig. S1). entially expressed genes only in adult mice and not during develop- RTT-like symptoms in mice manifest in an age-dependent manner. ment, highlighting the importance of MeCP2 in maintenance of proper Mice show relatively normal behavior during the early stages of postna- brain function. We also examined gene expression changes in the stria- tal development followed by the gradual appearance and increased tum of constitutive Mecp2-null mice and found that 59 genes are signif- severity of RTT-like phenotypes. We therefore examined striatal gene icantly down-regulated and 68 genes are significantly up-regulated in expression levels at two developmental time points: the first at P7 the absence of MeCP2. We found that the majority of differentially during early postnatal development when MeCP2 protein levels are expressed genes in the striatum are distinct from those identified in still increasing and the second following development at P90 when the hypothalamus and cerebellum. Weighted gene co-expression net- MeCP2 protein levels have plateaued (Skene et al., 2010). In addition, work analysis revealed that the overall transcriptome differs largely behavioral testing has previously shown that cKO mice exhibit motor between brain regions rather than between WT and Mecp2-null geno- deficits at this time point (Chao et al., 2010). We therefore dissected types, indicating that the gene expression landscape is not globally the striatum from male cKO and WT littermates at P7 and P90 and affected by loss of MeCP2. Together, our data suggests that MeCP2 reg- obtained genome-wide whole transcript coverage expression data ulates gene expression in a region-specific manner, most likely driven using Affymetrix GeneChip Mouse Gene 1.0 ST Arrays (Gene Arrays). by cell type, and that the aggregated differences in gene expression We first examined whether striatal gene expression changed over the within individual cells and regions lead to the pathogenesis of RTT. course of development from P7 to P90. Using the criteria of a fold- Given that MeCP2 is a 5mC and 5hmC binding protein and these meth- change of ≥1.2 with FDR ≤ 0.05 we identified over 7000 genes that ylation patterns likely differ between different cell types, we propose were differentially expressed between P7 and P90 in both the WT and that the role of MeCP2 in regulating target gene expression should be cKO samples (Figs. 1B and C). These data demonstrate that there is a studied with individual cell types in consideration. large-scale reorganization of the striatal transcriptome across develop- ment and that this occurs to a similar extent in both WT mice and Results mice lacking MeCP2 from striatal neurons. We also compared gene expression changes between cKO mice and Differentially expressed genes in the striatum of Mecp2 conditional their WT littermates at P7 and P90. During early postnatal development knockout mice at P7 we did not detect any significant differential gene expression between genotypes using the aforementioned criteria (Fig. 1D). In The striatum serves as the major site of input and integration for cor- contrast, in adult mice at P90 we identified the differential expression tical, thalamic, and midbrain afferents in the basal ganglia, a brain region of 21 genes in the cKO mice relative to the WT littermates (Fig. 1E, essential for maintaining proper sensorimotor and executive cognitive Supplementary Table 1). These results demonstrate that the conditional functions. The manifestation of motor and cognitive disturbances in loss of MeCP2 from striatal neurons leads to changes in the expression RTT, together with the observed decreased striatal volume in RTT pa- of a small number of genes only following postnatal development. tients (Reiss et al., 1993; Subramaniam et al., 1997), point to a possible Therefore, MeCP2 may not be required for striatal gene regulation role for the striatum in the etiology of RTT. A causal role for the striatum during the early stages of development, but rather plays a critical role Y.-T. Zhao et al. / Neurobiology of Disease 59 (2013) 257–266 259

Fig. 1. Gene expression changes in the striatum of Mecp2 conditional knockout mice. (A) Immunohistochemistry for MeCP2 expression in Mecp22lox/y and Mecp22lox/y; Dlx5/6-cre mice at P90. The presence of Dlx5/6 leads to a substantial loss of MeCP2 from striatum. Scale bar corresponds to 500 μm. (B-C) Volcano plots depicting fold-change and FDR-correct p-values for striatal gene expression between P7 versus P90 in WT and Mecp22lox/y; Dlx5/6-cre (cKO) mice. (D-E) Volcano plots for gene expression changes between WT and cKO mice at P7 and P90. Green dots represent genes showing a fold change of ≥1.2 with FDR ≤ 0.05 that were considered differentially regulated. 260 Y.-T. Zhao et al. / Neurobiology of Disease 59 (2013) 257–266 in maintaining proper brain function. In support of this hypothesis, con- terms. As expected, most of the enriched terms involve neural morphol- ditional deletion of Mecp2 from adult mice is sufficient to recapitulate ogy or function. We found that the 59 down-regulated genes are signif- numerous RTT-like symptoms (Cheval et al., 2012; McGraw et al., icantly enriched with functions associated with ion and chemical 2011; Nguyen et al., 2012) and restoration of MeCP2 in adult mice can homeostasis (Fig. 2B), whereas the 68 genes up-regulated in Mecp2- reverse RTT-like neurological phenotypes (Guy et al., 2007). null mice are highly enriched for functions associated with transcription- al regulation, development and differentiation (Fig. 2C). Therefore, the Differentially expressed genes in the striatum of Mecp2 constitutive differentially expressed genes identified from the striatum are likely knockout mice functionally related to neuronal function.

The limited number of differentially expressed genes in the striatum Differentially expressed genes in the striatum are distinct from other of cKO mice is in contrast to previous studies examining gene expression brain regions changes in the hypothalamus or cerebellum of constitutive Mecp2-null mice where hundreds to thousands of genes are differentially expressed To determine whether gene expression changes upon loss of MeCP2 (Ben-Shachar et al., 2009; Chahrour et al., 2008). This difference may re- are consistent across the brain regions, we compared the identified 127 sult from the differences in cellular composition between brain regions, differentially expressed striatal genes with genes previously shown the identity of the mouse model used, the array platform used or the to be significantly altered by loss of MeCP2 (defined as those genes cell autonomous and non-cell autonomous effects of MeCP2. To address showing fold change of ≥1.2 with FDR ≤ 0.05) in the hypothalamus the possibility that the identity of the brain region mediates these differ- (Chahrour et al., 2008)orcerebellum(Ben-Shachar et al., 2009)be- ences, we examined gene expression changes in the striatum of the tween WT and Mecp2-null mice. Unsupervised hierarchical clustering same constitutive Mecp2-null mice using the same Affymetrix GeneChip of differentially expressed genes between Mecp2-null and WT litter- MouseExon1.0STArrays(ExonArray)usedinpreviousstudies mates in these three brain regions revealed largely distinct classes of (Ben-Shachar et al., 2009; Chahrour et al., 2008). Striata were dissected genes affected by the loss of MeCP2 (Fig. 3A). Comparison of these from symptomatic P60 Mecp2-null mice (Guy et al., 2001)andtheir differentially expressed genes revealed that only a small number of WT littermates, extracted total RNA, converted to cDNA and hybridized genes are altered in all three brain regions (Fig. 3 and Supplementary to individual exon arrays. Since exon arrays have 1.2 million probe sets Dataset S2). Indeed, only 2 genes (including Irak1) are commonly up- with approximately 40 probes per gene, the calculation of gene expres- regulated between brain regions (Fig. 3B), whereas 3 genes (including sion levels is a greater challenge than that required for gene arrays: Mecp2)arecommonlydown-regulated (Fig. 3C). In addition, comparison that is, multiple probes will be mapped to individual genes with varying between differentially expressed genes in the cerebellum of Mecp2-null intensities, leading to difficulty in calculating the level of gene expres- mice and their WT littermates identified using RNA-seq (Mellén et al., sion. Multiple distinct, but related, methods have been developed to an- 2012) revealed that only three genes were commonly down-regulated alyze exon array data with respect to the calculation of gene expression (including Mecp2) in the striatum. Furthermore, analysis of the GO levels. To analyze differentially expressed genes in a comprehensive terms for these differentially expressed genes yields a transcriptional sig- manner we applied four different methods to measure gene expression nature for the striatum that is different to that observed in the hypothal- levels: assessing expression levels using the mean values from individual amus or cerebellum (Fig. 2BandC)(Ben-Shachar et al., 2009; Chahrour probes for a given gene, the median values from individual probes for a et al., 2008). These data therefore support amodelinwhichMeCP2regu- given gene, the Affymetrix Power Tools (APT) software package and lates gene expression in a region-specificmanner. the JETTA software package (Seok et al., 2012). Using these different methods, we have compiled four lists of genes Similar gene co-expression networks in WT and Mecp2-null mice that are differentially expressed in the striatum of WT and Mecp2-null mice. These four lists of genes overlap with one another to a large degree, Given the observations that MeCP2 binds to 5mC and 5hmC across but unique genes are also identified by each method. Using criteria of the genome (Mellén et al., 2012; Skene et al., 2010), it has been sug- fold change of ≥1.2 with FDR ≤ 0.05 we identified a total of 127 genes gested that MeCP2 may affect gene functions at a global scale in addition that are differentially expressed in the striatum of Mecp2-null mice in to specific genes. To assess the global effect of MeCP2 on gene transcrip- at least one of the four approaches (68 up-regulated genes, 59 down- tion, we analyzed gene expression level data from striatum, hypothala- regulated genes) (Supplementary Dataset S1). Of these, 67 were identi- mus and cerebellum of Mecp2-null mice and their WT littermates using fied using at least two of these analytical methods (Supplementary hierarchical clustering algorithms. We found that the overall gene ex- Dataset S1) and 57% of those genes dysregulated in P90 cKO mice pression profiles are clustered based on brain regions but not genotypes were also differentially expressed in Mecp2-null mice (Supplementary (Fig. 4A). These data demonstrate that the overall biochemical signature Table 1). Importantly, we find that Mecp2 is significantly down- of an individual brain region is maintained in the absence of MeCP2. regulated, whereas interleukin-1 receptor-associated kinase 1 (Irak1)is To gain higher-order and system level insight into how loss of significantly up-regulated in Mecp2-null mice. Since the Irak1 gene is MeCP2 affects the expression of functionally related genes, we next ap- located only 3 kb distal to Mecp2, this alteration is likely due to the al- plied weighted-gene co-expression network analysis (WGCNA) to gene tered genomic environment caused by deletion of Mecp2 exons 3 and 4 expression data from the striatum, cerebellum and hypothalamus. (Urdinguio et al., 2008). WGCNA examines groups of genes whose expression profiles are highly To verify the exon array analysis, we randomly selected six genes correlated across samples and give rise to gene modules containing sub- from our list of differentially expressed genes (Exph5, Robo3, Drd3, sets of genes with similar biochemical and functional properties as well Satb1, Dsg1c,andDlk1) and analyzed their mRNA levels in WT and as anatomical localization (Johnson et al., 2009; Oldham et al., 2008; Mecp2-null striatal tissues using quantitative real-time PCR (qRT-PCR). Zhang and Horvath, 2005). This technique has recently been used to We also included Mecp2 and Irak1 as positive controls. We found that identify modules of dysregulated genes in autism patients, providing all eight of these selected genes show expression changes that are evidence for convergent molecular pathologies in ASD (Voineagu consistent with those seen in our exon array data (Fig. 2A), validating et al., 2011). We therefore constructed a co-expression network using our approach in using exon array analysis to identify differentially the entire data set, composed of both Mecp2-null mice and their WT expressed genes in the striatum of Mecp2-null mice. littermate samples from the striatum, hypothalamus and cerebellum. To characterize the major biological themes present in differentially Gene expression profiles were classified into nine modules (ME1–9) expressed striatal genes, we assigned (GO) annotations with the expression levels of each module summarized by the first to the genes and tested for significant enrichment of functionally related principle component (the module eigengene). Y.-T. Zhao et al. / Neurobiology of Disease 59 (2013) 257–266 261

Fig. 2. Gene expression changes in the striatum of Mecp2 constitutive knockout mice. (A) Validation of differentially expressed genes in the striatum of WT and constitutive knockout (Mecp2-null) mice by quantitative real-time RT-PCR. (B) Gene ontology (GO) analysis for genes down-regulated in the striatum of Mecp2-null mice compared to their WT littermates. (C) GO analysis for genes up-regulated in the striatum of Mecp2-null mice compared to their WT littermates. The enrichment p-values were calculated by hypergeometric test and adjusted by the Yekutieli method using GOEAST software. 262 Y.-T. Zhao et al. / Neurobiology of Disease 59 (2013) 257–266

Fig. 3. Differential gene expression in different brain regions of Mecp2-null mice. (A) Heat map of the differentially expressed genes in the striatum, hypothalamus and cerebellum of Mecp2-null mice. Expression values are color-coded according to the legend to the right. The dendrogram depicts unsupervised hierarchical clustering based on fold-changes. (B) Venn diagram depicting the overlap between genes up-regulated in striatum, hypo- thalamus and cerebellum. (C) Venn diagram depicting the overlap between genes down-regulated in the striatum, hypothalamus and cerebellum.

We first asked whether global differences in the organization of the brain transcriptome exist between different brain regions. Indeed, eigengene values across all modules were markedly different between the striatum, hypothalamus and cerebellum (Fig. 4B and Supplementary Fig. S2), consistent with the existence of robust modules of co-expressed genes that are related to specific cell types and reflect anatomical locali- zation and functional divergence (Oldham et al., 2008). We then sought to identify discrete groups of co-expressed genes showing transcriptional differences between Mecp2-null mice and their WT littermates. We found no significant differences in module eigengenes between WT and Mecp2-null mice across the striatum, hypothalamus or cerebellum (Fig. 4B and Supplementary Fig. S2). Therefore, the loss of MeCP2 func- tion does not alter the general organization and molecular distinctions of transcriptomes in different brain regions. Finally, we wanted to deter- mine whether those genes differentially expressed in the striatum were distributed across modules or clustered together. We found that 70% of differentially expressed genes in the striatum are clustered within three modules: 33% of genes within module 1, 25% in module 3 and 12% in module 4 (Fig. 4C). These data suggest therefore that loss of MeCP2 from the striatum leads to alterations in genes that are functionally related to one another. The overall transcriptome differs largely between brain regions rather than between WT and Mecp2-null genotypes.

Evaluation of gene expression variation in Mecp2-null mice

Fig. 4. Gene expression network analysis in different brain regions of WT and Mecp2-null MeCP2 has been suggested to organize global chromatin structure mice. (A) Unsupervised hierarchical clustering of the gene expression profiles of the stri- and tighten transcriptional regulation by dampening transcriptional atum (ST), hypothalamus (HY), and cerebellum (CE) in Mecp2-null (null) and WT mice. noise (Muotri et al., 2010; Skene et al., 2010). This raises the possibility (B, top) Heat map of the gene expression profiles in Mecp2-null and WT data sets across that loss of MeCP2 function may lead to the stochastic dysregulation three brain regions. (B, bottom) A representative module (ME6) of co-regulated genes generated based on topological overlap of gene expression data from WT and KO mice. of genes within a given brain region across individual animals: that A clear separation of eigengene values can be seen based on brain region but not genotype. fi is, altered gene expression pro les within different brain regions of (C) Localization of differentially expressed genes within modules assigned using WGCNA Mecp2-null mice may reflect an increase in inter-subject variance in in the striatum. Y.-T. Zhao et al. / Neurobiology of Disease 59 (2013) 257–266 263 gene expression. To examine this possibility we calculated the variance be indirectly associated with MeCP2 due to general alterations in me- for individual gene expression levels across animals in the striatum, tabolism not yet characterized in Mecp2-null mice. Nevertheless, these hypothalamus and cerebellum of Mecp2-null mice and their WT litter- data suggest that Mecp2-null mice may have altered liver metabolism mates. However, we found no significant differences in gene expression consistent with a recent finding that mice lacking MeCP2 show numer- variance in any of these three brain regions (Bartlett's test, Supplemen- ous alterations in liver metabolism (Pitcher et al., 2013). It is possible tary Fig. S3). To investigate whether the abundance of gene expression therefore that these altered metabolic processes may also contribute may override individual variation across the transcriptome, we further to the pathology of RTT. classified all expressed genes into three groups based on their expres- sion levels (low, medium or high), and calculated expression variance Discussion within these individual groups. Again, we found no significant differ- ences in gene expression variance between genotypes in any of these RTT is a devastating neurological disorder that leads to the manifes- groups (Supplementary Fig. S4). These data indicate that increased tation of a number of diverse symptoms including gait apraxia, loss of variance in gene expression levels is not the major contributor to the purposeful hand movements, respiratory abnormalities and loss of differential expression of genes between Mecp2-null mice and their communication. The particular symptoms observed in RTT suggest WT littermates. Therefore, loss of MeCP2 function is unlikely to modu- that striatal dysfunction may play an important role in its etiology. late gene expression levels through a stochastic disruption of gene reg- Indeed, volumetric analyses of RTT individuals have consistently identi- ulation processes; rather MeCP2 appears to modulate gene expression fied a decrease in the size of the neostriatum, even when taking into through a coordinated, cell-type specific mechanism. Consistent with account the smaller brain size of these patients (Reiss et al., 1993; this, we found that MeCP2 also affects neuronal morphology in a brain Subramaniam et al., 1997).Thestriatumservesastheinputcenterfor region- and cell type-specific manner (Wang et al., 2013). the basal ganglia, a subcortical region of the brain which processes and integrates information associated with learning and memory, Loss of MeCP2 function affects both neuronal and non-neuronal genes motor control and various executive cognitive functions. The condition- al deletion of MeCP2 from forebrain GABAergic neurons, including Distinct gene expression changes occurring in different brain regions MSNs of the striatum, leads to the development of a number of symp- would be expected if those genes were particularly enriched in a single toms in mice including impaired motor coordination, ataxia and social brain region. To investigate this possibility, we isolated liver tissue from deficits (Chao et al., 2010). The role that MeCP2 loss-of-function in the Mecp2-null mice and normalized gene expression data from the stria- striatum plays in the development of these symptoms, however, is tum, hypothalamus and cerebellum to that of liver in order to identify unclear. Similarly, the identity of genes affected by loss of MeCP2 in region-enriched genes. We next generated a classification scheme by a this region has not been investigated. direct comparison of WT gene expression profiles between our liver In order to examine changes in gene expression within the striatum dataset and the datasets from the striatum, hypothalamus, and cerebel- we utilized two mouse models: mice lacking MeCP2 only from forebrain lum (Fig. 5A). Genes exhibiting higher fold expression (fold change ≥ 2 GABAergic neurons including MSNs of the striatum, and constitutive with FDR ≤ 0.05) in the three brain regions relative to liver were Mecp2-null mice. Using the first model, we profiled gene expression considered brain-enriched genes. Among this class of genes, those that changes in the striatum across development from P7 to P90. We found only appeared in a single brain region relative to the remaining two considerable changes in the gene expression profiles of the striatum were considered specific brain region-enriched genes. Using these during these time points, with over 7000 genes being affected develop- criteria, we identified striatum- (622 genes), hypothalamus- (1109 mentally in both cKO mice and their WT littermates. In contrast, we ob- genes) and cerebellum-enriched genes (714 genes) (Fig. 5A and Supple- served only a small number of differentially expressed genes between mentary Dataset S3). To verify the fidelity of this classification scheme, cKO mice and their WT littermates. These alterations only occurred at we obtained the top 50 highly expressed genes in the striatum from P90 when MeCP2 levels are high and not during early postnatal devel- the Allen Mouse Brain Atlas and confirmed that 98% of the genes opment. These data suggest therefore that MeCP2 is not required for from the atlas are present in our list of striatum-enriched genes striatal gene regulation during early development; rather, MeCP2 (Supplementary Dataset S4). A similar analysis with hypothalamus- appears to be essential for maintaining proper brain function at later and cerebellum-enriched gene lists revealed 83% and 89% overlaps, postnatal stages. Indeed, conditional deletion of Mecp2 from adult respectively. mice is sufficient to recapitulate many RTT-like symptoms and altered We next examined whether genes differentially expressed between hypothalamic gene expression (Cheval et al., 2012; McGraw et al., WT and Mecp2-null mice were classified as brain region-enriched genes 2011; Nguyen et al., 2012). or demonstrated similar expression levels in different brain regions. We Notably, the number of differentially expressed genes in the stria- found that the majority of genes deregulated in Mecp2-null datasets tum is markedly different in the cKO striatum compared to those previ- tended to be those expressed across different brain regions or showed ously observed in the hypothalamus and cerebellum of constitutive similar expression levels in the liver. Indeed, only a small portion, 3 to Mecp2-null mice (Ben-Shachar et al., 2009; Chahrour et al., 2008). To 10%, of all differentially expressed genes, are enriched in a single brain address the possibility that these differences were the result of different region (Fig. 5A). Thus, brain region-specific differential gene expression mouse models we repeated our striatal gene expression studies using in Mecp2-null mice is unlikely to be a consequence of the enrichment of symptomatic Mecp2-null mice and exon arrays similar to previous those genes in that particular brain region. studies. Indeed, up to 127 genes were differentially expressed in symp- MeCP2 is ubiquitously expressed throughout the body although tomatic Mecp2-null mice at P60 compared to WT littermates. The great- its function in non-neuronal tissues is not well understood er number of genes identified in the striatum of Mecp2-null mice (Shahbazian et al., 2002). To examine whether loss of Mecp2 function relative to cKO mice may result from differences in cell autonomous affects gene expression in non-neuronal tissues, we profiled gene and non-cell autonomous effects of MeCP2 loss-of-function. Most of expression levels from the liver of Mecp2-null mice and their WT the genes identified in cKO mice were also identified in Mecp2-null littermates. We found that 161 genes are differentially expressed in mice suggesting that they are indeed regulated by MeCP2. the livers of Mecp2-null compared to their WT littermates (Fig. 5Band Among the small number of differentially expressed genes found in Supplementary Dataset S5). Of these genes, 73 are up-regulated and the striatum, the majority of the affected genes were not identified were enriched for lipid, fatty acid and small molecule metabolism as de- in analyses of the hypothalamus or cerebellum. These data suggest termined by GO analysis (Fig. 5C). Since MeCP2 expression is relatively that MeCP2 regulates gene expression in a region- or cell-type-specific low in the liver (Shahbazian et al., 2002), these expression changes may manner. Furthermore, the majority of these region-specificchangesin 264 Y.-T. Zhao et al. / Neurobiology of Disease 59 (2013) 257–266

Fig. 5. Distribution of differentially expressed genes (DEX) in WT and Mecp2-null mice. (A) Genes differentially expressed in WT and Mecp2-null tissues were separated into those that show enrichment within their representative brain region, those enriched in brain versus liver, and those that are not enriched. (B) The number of genes up-regulated and down-regulated in the liver of Mecp2-null mice compared with WT littermates. (C) Gene ontology (GO) analysis showing biological functions of the genes up-regulated in the liver of Mecp2-null mice compared to their WT littermates. The enrichment p-values are calculated by a hypergeometric test and adjusted by the Yekutieli method using GOEAST software. gene expression involve genes that are typically expressed in multiple related to one another. These findings suggest that MeCP2 does not brain regions and non-neuronal cell types. Distinct gene expression alter the gene expression landscape globally, but rather shows a brain profiles in different brain regions are likely governed by local alterations region-orcell-type-specific effect. Thus, while individual gene expres- to chromatin structure in addition to cell-type specific 5mC and 5hmC sion changes in individual cell types may be small, the composite effects, localization (Mellén et al., 2012; Szulwach et al., 2011). Thus region- however, lead to global disruption in brain function and the pathogene- specific alterations in gene expression may reflect differential binding sis of RTT. of MeCP2 to 5mC and 5hmC, respectively. Most of the work regarding MeCP2 has centered around its function Our analysis of the gene expression changes in the striatum revealed in the brain since brain-specificdeletionofMeCP2issufficient to reca- considerably fewer genes differentially expressed by loss of MeCP2 rela- pitulate most RTT-like symptoms observed in constitutive Mecp2-null tive to the hypothalamus and cerebellum that together exhibited N2000 mice (Chen et al., 2001; Guy et al., 2001). Although MeCP2 is ubiqui- genes differentially expressed (Ben-Shachar et al., 2009; Chahrour et al., tously expressed, its function in other tissues remains unknown. 2008). The larger number of genes altered in these two regions may re- In this study, we also examined gene expression changes in the liver flect the greater heterogeneity in cell types within these regions in com- of symptomatic Mecp2-null mice and identified 161 genes that were parison to the striatum that is primarily composed of MSNs. It would be differentially expressed, with 73 upregulated genes being enriched for interesting to determine whether individual cell types, such as granule lipid, fatty acid and small molecule metabolism. These data may indicate cells, Purkinje cells and Bergmann glia from the cerebellum, demonstrate that Mecp2-null mice may have altered liver metabolic processes. a more restricted alteration in gene transcription in Mecp2-null mice. Indeed, it has been suggested that Mecp2-null mice have a metabolic Moreover, analysis of gene expression at a systems level using WGCNA disorder (Pitcher et al., 2013). Mecp2-null mice were found to have revealed modules of genes functionally and anatomically classified marked increases in sera levels of triglycerides and cholesterol and de- based on brain region and are unaltered by loss of MeCP2. However, creased sera levels of insulin-like growth factor binding-protein 2. those genes that are differentially expressed in the striatum cluster with- These alterations were associated with an increase in fat, but not lean in discrete sets of modules arguing that these genes are functionally mass and insulin resistance. Since MeCP2 expression remains low in Y.-T. Zhao et al. / Neurobiology of Disease 59 (2013) 257–266 265 the liver (M.D. Shahbazian et al., 2002), it is not known whether these and R environment. The raw CEL files of hypothalamus (accession alterations in the expression of genes related to metabolism in the number GSE11150) and cerebellum (accession number GSE15574) liver are directly caused by loss of MeCP2 function in the liver, or are datasets were downloaded from the National Center for Biotechnology secondary to occur indirectly through altered metabolic pathways in Information Gene Expression Omnibus (GEO) database. Mecp2-null mice. Further study into the function of MeCP2 in the liver Four methods were used to process the raw exon array data and and the greater characterization of metabolic processes affected by to calculate gene-level expression values. The Affymetrix power tools loss of MeCP2 will provide greater insight into the role of metabolism (APT) command line program was used to process raw data using the in the pathogenesis of RTT. robust multichip average method and generate gene-level expression In summary, we identified a number of differentially expressed values based on the core probesets using median polish. The JETTA genes in the striatum of Mecp2-null mice. These differentially expressed bioconductor package was used to normalize raw data using the genes in the striatum were largely unique to those previously identified quantile method and to calculate gene-level expression values based in the cerebellum or hypothalamus. We have therefore uncovered a on the core probesets using a median polish. The last two methods previously under-appreciated feature of MeCP2 in regulating gene ex- utilized the affy and xmapcore (exonmap) bioconductor packages. pression in a region-specific manner within the brain. We demonstrate Raw data was processed using the robust multichip average method. that differential gene expression in different regions of the Mecp2-null Probesets that mapped uniquely to gene exons using the exmapcore brain does not occur due to region-specific expression or increased package were used for subsequent analysis. Gene-level expression gene expression variance within a particular functional biochemical values were calculated using either the median or mean value of all network. Differential gene expression is likely caused by other region- uniquely-mapped exon probsets. Differentially expressed genes were specific mechanisms such as local differences in 5mC and 5hmC identified using the limma bioconductor package. A linear model was patterns. Our findings add new possibilities to the molecular function fitted for every gene, and the p-values of differentially expressed of MeCP2 and identify genes that may be novel therapeutic targets for genes were calculated using the empirical Bayes moderated t-test. the treatment of RTT Next, multiple comparisons were processed to adjust the raw p-value of t-test using Benjamini and Hochberg's method and to generate the Materials and methods false discovery rate (FDR). The significance threshold was set at a fold change ≥ 1.2 with a FDR ≤ 0.05 for identifying differentially expressed Mouse strains, sample collection, and RNA extraction genes between Mecp2-null mice and their WT littermates. The signifi- cance threshold was set at a fold change ≥ 2withaFDR≤ 0.05 for tis- Experiments were conducted in accordance with the ethical guide- sue and region-enriched genes between the striatum, hypothalamus, lines of the National Institutes of Health and with the approval of the cerebellum, and liver datasets. Genes that were identified by at least Institutional Animal Care and Use Committee of the University of one of the four methods described were considered to be differentially Pennsylvania. Conditional deletion of Mecp2 from forebrain GABAergic expressed genes. neurons was achieved by breeding Mecp2flox/+ females (Chen et al., The GOEAST online software using default settings was used for 2001) to transgenic Dlx5/6-cre males. Constitutive Mecp2-null mice Gene Ontology (GO) enrichment analysis. Gene ID conversion was (Guy et al., 2001) were generated by breeding Mecp2−/+ females to performed using the DAVID Bioinformatics Resources. WT males. All mice were maintained on the C57BL/6 background. Striata were dissected from cKO mice at P7 and P90 and immediately Weighted gene co-expression network analysis (WGCNA) frozen in liquid nitrogen. Striatal and liver tissue were dissected from constitutive Mecp2-null mice at P60 and flash frozen in liquid nitrogen. The weighted gene co-expression network was built using the RNA was extracted using TRIzol reagent (Invitrogen Corporation, WGCNA package in the R environment. The JETTA package was used Carlsbad, CA, USA), DNase I treated, and purified using the miRNAeasy to generate the gene expression profiles of WT and constitutive mini kit according to the manufacturer's protocol (Qiagen, Valencia, Mecp2-null mice, and a network was constructed using all striatum, cer- CA, USA). ebellum, and hypothalamus datasets. Network constructions were performed using the blockwise modules method in the WGCNA pack- Microarray target preparation and hybridization age. Using the scale-free topology criterion, the power of six was chosen to construct the total network. Dynamic hybrid tree cutting was used to Microarray services were provided by the Penn Microarray Facility, cut the hierarchical clustering trees and to identify individual modules. including quality control tests of the total RNA samples by an Agilent The minimum module size was set to 30 genes and the minimum height Bioanalyzer and Nanodrop spectrophotometry. All protocols were for merging modules was set to 0.1. Default parameters were used for conducted as described in the Affymetrix GeneChip Expression Analysis other settings. Technical Manual. Briefly, 100 ng of total RNA was converted to first- strand cDNA using reverse transcriptase primed by poly(T) and random Quantitative real-time PCR oligomers that incorporated the T7 promoter sequence. Second-strand cDNA synthesis was followed by in vitro transcription with T7 RNA po- For each sample, 1 μg of total RNA was digested with DNAseI lymerase for linear amplification of each transcript, and the resulting (Invitrogen, Carlsbad, CA) and reverse-transcribed by oligodT-priming cRNA was converted to cDNA, fragmented, assessed by the Bioanalyzer, using SuperScriptIII reverse transcriptase (Invitrogen, Carlsbad, CA). and biotinylated by terminal transferase end labeling. cRNA yields and The amount of each transcript of interest present in the sample was 5 μg of labeled cDNA was added to Affymetrix hybridization cocktails, measured by quantitative real-time PCR on 1/10th of the resulting heated at 99 °C for 5 min and hybridized to Affymetrix Mouse Exon cDNA using SYBR Green detection (Applied Biosystems) on an ABI 1.0 ST GeneChips (for constitutive Mecp2-null mice and their WT litter- 7900HT instrument. Each sample was measured in triplicate using mates) or Affymetrix GeneChip Mouse Gene 1.0 ST Arrays (for cKO mice exon-spanning qRT-PCR primers. GAPDH amplification served as an in- and their WT littermates) according to the manufacturer's instructions. ternal RNA control for relative quantification. The following mouse primers were used for qRT-PCR analysis: Gapdh (F: 5′-AATGGTGAA Microarray data analysis GGTCGGTGTG-3′;R:5′-GTGGAGTCATACTGGAACATG-3′), Mecp2 (F: 5′-CATACATAGGTCCCCGGTCA-3′;R:5′-CAGGCAAAGCAGAAACATCA- The bioinformatics analysis of all the microarray datasets used 3′), Irak1 (F: 5′-GTCTTGGATAGCCTGCAACTG-3′;R:5′-TGAGGGATTTGT in this manuscript was processed in the MAC terminal window CAGAGTGAAC-3′), Drd3 (F: 5′-TTATCCACATCCCTGAAGCTG-3′;R:5′- 266 Y.-T. Zhao et al. / Neurobiology of Disease 59 (2013) 257–266

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SUPPLEMENTARY INFORMATION

Loss of MeCP2 function is associated with distinct gene expression changes in the striatum

Ying-Tao Zhao, Darren Goffin, Brian Johnson and Zhaolan Zhou

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Figure S1

Figure S1. Loss of MeCP2 from the striatum with expression of Dlx5/6-cre. Immunohistochemistry for MeCP2 expression in Mecp22lox/y and Mecp2lox/y; Dlx5/6-cre mice at P90. The presence of Dlx5/6 leads to a substantial loss of MeCP2 from striatum although small numbers of MeCP2-expressing cells remain. Scale bar corresponds to 100 µm.

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Figure S2

Figure S2. Weighted gene co-expression network analysis (WGCNA) in Mecp2-null and wild-type mice. Gene expression profiles and module eigengene of the 8 modules in the co-expression network constructed using the Mecp2-null and wild-type data sets.

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Figure S3

Figure S3. Gene expression variances between replicates in striatum, hypothalamus, and cerebellum in Mecp2-null and wild type (WT) mice. Gene level expression profiles used in this analysis were generated by the mean (A), median (B), APT (C), and JETTA (D) methods, respectively. Differentially expressed genes between Mecp2-null and WT mice in striatum are labeled in red.

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Figure S4

Figure S4. Expression variances between replicates for the highly-expressed (red), intermediately- expressed (grey), and lowly-expressed (green) genes in striatum (A), hypothalamus (B), cerebellum (C), and liver (D) in Mecp2-null and wild type (WT) mice. Gene level expression profiles used in this analysis were generated by the JETTA package.

Supplemental Table 1. Differentially expressed genes in the striatum in P90 cKO mice Gene logFC in Mecp2- Symbol logFC FDR null mice Gene Annotation Fxyd7 -0.83 9.06E-03 -0.77 FXYD domain-containing ion transport regulator 7 Hpcal4 -0.53 1.18E-02 -- hippocalcin-like 4 Crabp1 -1.04 1.37E-02 -0.89 cellular retinoic acid binding protein I Gpr26 0.64 1.87E-02 -- G protein-coupled receptor 26 Pitpnm2 0.59 2.15E-02 0.46 phosphatidylinositol transfer protein, membrane-associated 2 Spag6 -0.76 2.63E-02 -- sperm associated antigen 6 Gstm6 -0.83 3.77E-02 -0.75 S-transferase, mu 6 Dab1 0.56 4.43E-02 0.51 disabled homolog 1 Drd3 0.77 4.43E-02 1.08 dopamine receptor D3 Tbc1d4 0.58 4.43E-02 -- TBC1 domain family, member 4 Pacsin2 0.58 4.43E-02 0.68 protein kinase C and casein kinase substrate in neurons 2 Peli2 0.53 4.43E-02 -- pellino 2 Tacr1 -0.62 4.43E-02 -0.68 tachykinin receptor 1 Stc1 -0.95 4.63E-02 -1.13 stanniocalcin 1 Galnt7 0.49 4.63E-02 -- UDP-N-acetyl-alpha-D-galactosamine: polypeptide N- acetylgalactosaminyltransferase 7 Kcnh7 0.85 4.63E-02 0.88 potassium voltage-gated channel, subfamily H, member 7 Mrap2 -0.48 4.63E-02 -- melanocortin 2 receptor accessory protein 2 Arhgap6 0.49 4.63E-02 0.54 Rho GTPase activating protein 6 Lrp12 0.35 4.43E-02 -- low density lipoprotein-related protein 12 Auts2 0.37 4.43E-02 -- autism susceptibility candidate 2 Fgf11 -0.85 4.83E-02 -0.97 fibroblast growth factor 11

Supplemental Dataset S5. List of differentially expressed genes in liver between Mecp2-null and wild-type mice.

Fold Change of Mecp2-null vs wild-type (log2 scale) Gene Symbol APT JETTA Mean Median Cyp7b1 -3.491 -3.565 -3.724 -3.586 C6 -2.516 -2.574 -2.657 -2.553 Selenbp2 -2.279 -1.490 -2.574 -3.186 Susd4 -2.147 -2.302 -1.963 -2.067 Serpina12 -2.000 -2.438 -2.150 -2.267 Gstp1 -1.622 -1.460 -1.290 -1.290 Scara5 -1.575 -2.254 -1.773 -1.936 Tmeff2 -1.518 -2.272 -1.396 -1.693 Dpy19l3 -1.353 -1.401 -1.109 -1.067 Tuft1 -1.037 -1.112 -0.956 -1.017 Fgfr1 -0.900 -0.917 -0.811 -0.888 C9 -0.854 -0.874 -0.922 -0.965 Aox3 -0.829 -0.860 -0.909 -0.862 Capn8 -0.823 -1.124 -1.131 -1.361 Tiam2 -0.794 -1.031 -0.701 -0.877 C8a -0.691 -0.705 -0.702 -0.739 Cadm4 -0.625 -0.850 -0.649 -0.735 Mecp2 -0.591 -0.706 -0.988 -0.902 Fkbp11 -0.432 -0.690 -0.848 -0.730 Mup21 -3.134 0 -2.632 -3.057 Selenbp1 -0.753 -1.052 -0.782 0 Zfp445 -0.735 -0.757 -0.734 0 Tmem19 -0.632 -0.655 -0.680 0 Ppp1r9a -0.608 -0.769 -0.671 0 Aadat -0.581 -0.624 -0.605 0 Slc6a8 -0.556 -0.570 -0.398 0 Ugt2b1 -0.485 -0.502 -0.521 0 Serpina11 -0.424 -0.502 -0.398 0 Ldhd -0.374 -0.413 -0.388 0 Elovl3 0 -2.345 -2.135 -2.317 Adrb3 0 -1.165 -0.778 -0.838 Mmp15 0 -0.890 -0.776 -0.866 F11 0 -0.806 -0.824 -0.909 Ces8 -1.038 -1.146 0 0 Gvin1 -0.971 -0.951 0 0 Gstp2 -0.934 -1.398 0 0 Slc35e3 -0.848 -0.900 0 0 Rgs5 -0.795 -0.763 0 0 Ifi27l1 -0.673 -0.660 0 0 Irak1 -0.344 -0.385 0 0 Cyp4a12b 0 -1.804 -1.995 0 Nat8 0 -0.793 -0.710 0 Tspan33 0 -0.642 -0.555 0 Sntg2 0 -0.562 -0.500 0 Fmn2 0 -0.560 -0.553 0 AC079845.1 0 0 -2.117 -1.959 Cyp4a12a 0 0 -1.723 -1.962 Gm12718 0 0 -1.641 -1.955 C4a 0 0 -1.563 -1.700 Ugt2b38 0 0 -1.230 -1.630 Ces4a 0 0 -1.053 -1.075 AC163038.1 0 0 -0.886 -0.886 Lama3 0 0 -0.728 -0.809 Ces2b 0 0 -0.702 -0.696 AC160526.1 0 0 -0.572 -0.933 Bche 0.419 0.429 0.473 0.623 Pbx1 0.627 0.638 0.601 0.695 Postn 0.750 0.780 0.636 0.948 Robo1 0.799 0.846 0.738 0.806 Pparg 0.944 0.988 0.984 1.152 Atp6v0d2 1.358 1.431 1.251 1.306 Slco1a4 1.451 1.319 1.445 1.516 Gstt3 1.483 1.568 1.415 1.606 Vldlr 1.899 2.004 1.484 1.949 Cd36 2.014 1.976 1.904 2.237 Acot3 2.178 2.388 2.110 2.395 Cyp2b10 2.269 2.546 1.969 2.615 Abcd2 2.380 2.332 2.390 2.446 Fmo3 4.812 4.743 4.480 4.647 Slc16a7 0.770 0.756 0.711 0 Mgst3 0.953 1.030 0.668 0 Tox 1.250 1.280 1.034 0 Fmo4 0 0.825 0.803 0.928 Nqo1 0 0.826 0.859 0.902 Acot4 0 1.265 1.192 1.368 Mmd2 0 1.668 1.531 1.765 Cyp4a14 0 2.404 2.588 2.564 Srebf2 0.425 0 0.369 0 Pcp4l1 0.466 0.563 0 0 BC089597 0.643 0.529 0 0 Dmxl1 5.433 5.844 0 0 Abcb1a 0 1.022 0.949 0 Cyp2b19 0 1.431 0.862 0 Cyp2c39 0 1.997 2.018 0 Gm15455 0 0 1.047 1.047 Gm16734 0 0 1.289 1.289 Slc16a5 0 0 1.456 1.679 Hamp2 0 0 1.701 2.988 Cyp2c38 0 0 1.891 1.855 Gm11695 0 0 2.094 2.094 AB056442 0 0 3.974 5.240 BC014805 0 0 4.645 5.059 AC167659.1 0 0 4.786 5.998 Cyp2b9 0 0 6.646 6.874 Serpina1e -2.655 - - - Itch -0.390 - - - Spin1 -0.329 - - - Gm12836 - -1.723 - - Olfr918 - -1.453 - - LOC100048479 - -1.425 - - Hspb1 - -1.357 - - Serpine2 - -1.354 - - Esco2 - -0.876 - - Bmyc - -0.845 - - Bmp7 - -0.744 - - Wipi1 - -0.664 - - Olfr853 - -0.630 - - Tes - -0.612 - - Myh10 - -0.600 - - Snx29 - -0.583 - - Klhl2 - -0.525 - - Cd200r3 - -0.503 - - Efcab1 - -0.478 - - Zfp322a - -0.444 - - Ntf5 - -0.415 - - Gas7 - -0.379 - - Grm8 - - -0.527 - Mup-ps21 - - -0.937 - Apol9a - - -0.728 - Serpina3c - - -0.689 - Snora43 - - -0.607 - C330002G04Rik - - -0.584 - Wnk4 - - -0.471 - Kcnk10 - - -0.412 - Lcn13 - - - -2.576 Lipt2 - - - -0.975 4930507D10Rik - - - -0.690 Acad10 0.343 - - - Tceal8 0.517 - - - Mfge8 - 0.394 - - Tead1 - 0.416 - - Ogn - 0.440 - - Sparcl1 - 0.483 - - Soat2 - 0.487 - - Hexb - 0.597 - - LOC100048408 - 0.601 - - Lass6 - 0.664 - - Stambpl1 - 0.681 - - Arrdc4 - 0.747 - - Tm6sf2 - 0.797 - - Rnase10 - 0.809 - - Acss3 - 1.007 - - Lrtm1 - 1.252 - - Prlr - 1.279 - - Defb1 - 1.297 - - Hmcn1 - - 0.292 - Ces1d - - 0.388 - AC152076.1 - - 0.437 - Elovl5 - - 0.557 - Greb1l - - 0.583 - Dhrs7 - - 0.597 - Bhlhb9 - - 0.622 - Abcc4 - - 0.636 - Abhd2 - - 0.659 - Serpina6 - - 0.666 - Steap2 - - 0.682 - Gm16612 - - 0.765 - Arhgef9 - - 0.893 - Gm10567 - - 2.131 - Gm16055 - - - 0.585 Sytl5 - - - 1.334