The Pharmacogenomics Journal (2004) 4, 208–218 & 2004 Nature Publishing Group All rights reserved 1470-269X/04 $25.00 www.nature.com/tpj ORIGINAL ARTICLE

A cluster of differentially expressed signal transduction identified by microarray analysis in a rat genetic model of alcoholism

C Arlinde1 ABSTRACT 1 Analyzing expression patterns in genetic models of alcoholism may W Sommer uncover previously unknown susceptibility genes, and point to novel targets 1 K Bjo¨rk for drug development. Here, we compared expression profiles in alcohol- M Reimers2 preferring AA rats with the alcohol-avoiding counterpart ANA line, and P Hyytia¨3 unselected Wistar rats. Cingulate cortex, Nc. accumbens, amygdala and K Kiianmaa3 hippocampus of each line were analyzed using the Afymetrix RN U34 1 arrays and dChip 1.1 software. Analysis of line-specific expression revealed 48 M Heilig differentially expressed genes between AA and ANA rats. Elevated hippocam- pal neuropeptide Y (NPY) was found in ANA rats in agreement with previous 1NEUROTEC, Karolinska Institute, Sweden; 2Center for Genomics and Bioinformatics, studies. A cluster of MAP- indicating altered signal transduction was Karolinska Institute, Sweden; 3National Public upregulated within the Nc. Accumbens of the AA line, and is of particular Health Institute, Helsinki, Finland functional interest. Within the amygdala, a more loosely inter-related cluster of cytoskeleton-associated genes may point to structural abnormalities. The Correspondence: observed dysregulations may contribute to the alcohol-preferring phenotype. Dr W Sommer M 57, Huddinge University Hospital, The Pharmacogenomics Journal (2004) 4, 208–218. doi:10.1038/sj.tpj.6500243 S-14186 Stockholm, Sweden. Published online 30 March 2004 Tel: þ 46 8 5858 5728; Fax: þ 46 8 5858 5785. Keywords: profiling; Nc. accumbens; amygdala; ethanol prefer- E-mail: [email protected] ence; addiction

INTRODUCTION Alcoholism is a multifactorial disease with an overall heritability estimated to 50– 60%, the remaining variance being accounted for by nonshared environmental factors. A subgroup with particularly high heritability is composed of approxi- mately one fourth of alcohol-dependent patients, characterized by early onset of alcohol problems, deficient impulse control and pronounced positively reinfor- cing effects of alcohol. On the basis of their functional role, several candidate genes have been suggested to confer genetic susceptibility for alcoholism. Among these are monoaminergic genes involved in brain reward pathways and serotonergic genes involved in impulse control and anxiety traits (for review, see Enoch and Goldman1). More recently, on the basis of animal studies, an involvement has been suggested for neuropeptide Y (NPY),2 but human findings have been inconsistent,3,4 possibly due to the methodological difficulties involved, and due to the limited quantitative contribution of individual loci in the complex trait of alcoholism. Models in experimental animals therefore offer a useful complement to human genetic studies. No single paradigm models the complex clinical syndrome of Received: 06 January 2004 Accepted: 20 January 2004 alcohol dependence, but models of clinically relevant traits are available, and Published online 30 March 2004 have demonstrated a predictive validity.5 One of the best established among Expression profiling in AA and ANA rats C Arlinde et al 209

these models is the alcohol-preferring AA rat line,6 which by its low throughput. Recent advances in DNA-microarray has been bred for high alcohol consumption for-over 90 technology have markedly improved the feasibility of generations, and displays a stable phenotype of alcohol identifying differential gene expression patterns, and have preference. Its genetic counterpart is the ANA (alcohol non- been useful in identifying novel candidate genes in alcohol- accepting) rat line, which was bred for low alcohol con- related neuroadaptations.9,10 sumption in parallel with the AA line. Besides its genetic Here, we therefore used oligonucleotide DNA-microarrays preference for high ethanol drinking, the AA rat shows to compare profiles of gene expression in the forebrain of behavioral disinhibition.7 Together with the high ethanol AA and ANA rats. Nonselected Wistar rats were initially also consumption, this rat line thus shares intermediate pheno- included in the analysis, since they quantitatively represent typic traits with early-onset alcoholism.1 Interestingly, these a behavioral phenotype that falls between the two selected traits have cosegregated also when breeding the counterpart lines both with regard to alcohol preference and anxiety. line for low alcohol preference, such that the ANAs display Based on available knowledge of brain reward pathways higher than normal behavioral suppression, with the pheno- and key areas involved in the regulation of ethanol intake,11 typic hierarchy for ethanol preference being AA4Wistar4 we analysed cingulate cortex, amygdala, accumbens and ANA, while the opposite is true for behavioral inhibition. hippocampus. Analysis of mRNA expression profiles offers an attractive tool for studying interactions between genetic susceptibility factors and neuroadaptive processes in the development of RESULTS alcohol dependence. In a previous study of the AA and ANA After quality assessment, 32 out of 36 chips (eight per region) rats performed with differential display RT-PCR,8 we were were included into the quantitative expression analysis. able to detect and confirm differential gene expression of Chipwise expression estimates and the probability of detec- two transcripts in the parietal cortex: the ribosomal tion for each probe set are available from the author on L18A and diacylglycerol iota (DGKI). The utility of request. The initial evaluation focused on the specificity and the differential display strategy is, however, severely limited sensitivity of the microarray analysis. Figure 1 demonstrates

Figure 1 This radial dendrogram displays the differences between gene expression profiles of the samples. The centroid represents the average profile over all samples. Samples from different brain regions form separate clusters. Also, expression patterns in the cingulate cortex visualise the genetic relationship between the lines resulting from the breeding program: that is, AA and ANA coming from the same parental strain (Brown Norway), while the Wistar strain has been used at a later stage of the breeding to revitalise the AA and ANA lines. In the other brain regions, the genetic relationship between lines does not emerge as clearly. The dendrogram was obtained via the Neighbor-Joining option in the Phylip program and the radial option in the TreeView program.39 The distance data for the dendrogram were the ‘Manhattan’ distances between gene expression profiles. Only genes called ‘Present’ (see Materials and Methods) in at least half the samples were used. Sample labeling is as follows: region (Acc, Amy, CCx, Hip for amygdala, accumbens, cingulate cortex and hippocampus, respectively), strain (AA, ANA and Wistar) and an individual number of the sample.

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that the GeneChip-generated expression profiles form, as accumbens, cingulate cortex and hippocampus, respectively. expected, clusters according to brain region. The differences Notably, fold change differences are generally below two- between the lines are most clearly reflected in the dendro- fold. Only a few genes are flagged in more than one region. gram for the cingulate cortex. This visualizes that, despite To elucidate if the pressure of genetic selection has acted at their divergence of alcohol preference, AA and ANA are specific regions of the rat genome, we analysed the genomic closer to each other than to the nonselected Wistar line, distribution of loci giving rise to gene expression differences presumably reflecting that they were originally selected (Figure 3). No particular or chromosomal from a common parental strain, which was different from region appears to be predominantly affected. the Wistar line. Owing to the availability of prior data,12 and the fact that We also assessed regionally highly enriched gene expres- NPY was flagged as differentially expressed within the sion independent of line effects. A total of 688 probe sets, hippocampus, real-time RT-PCR was performed to obtain that is 52% of the probe sets present on the RN34U arrays, relative mRNA levels for NPY gene expression in this region. fulfilled the criteria for detection (‘present-call’; for criteria After normalisation to cyclophilin, a significant difference definition, see Method section) in at least one of the brain (approx. 20%) was obtained between the AA and ANA lines regions. Only 17 probe sets were found to be present in a in preproNPY mRNA levels (F(1,14) ¼ 5.49, Po0.05). single region and absent in all others. Of these, five genes Since b-arrestin 2 had consistently lower expression levels had signals clearly distinguishable from background and in three of four regions of the AA line we developed a real- their expression was classified as region specific. In addition, time RT-PCR assay and compared relative mRNA levels for nine genes showed highly enriched expression in a parti- this gene in the hippocampus. After normalization to cyclo- cular region. Expression patterns for most of these genes are philin, we confirmed significantly lower b-arrestin expres- well described in the literature and fully concordant with sion in the hippocampus (approx. 15%, F(1,14) ¼ 4.81, the present analysis (Table 1). Po0.05). There were no differences in cyclophilin A gene We statistically evaluated differences in regional gene expression between the lines (F(1,14) ¼ 0.397, P ¼ 0.54 expression only between the genetically related AA and and F(1,14) ¼ 0.211, P ¼ 0.65 for the NPY and b-arrestin ANA lines. In total, 48 genes were differentially expressed assays, respectively). Similar results for NPY and b-arrestin between the AA and ANA lines, with the number of dif- have been obtained using b- gene expression for ferentially expressed genes varying between 11 and 18 per normalization (data not shown). region. The nucleus (Nc.) Accumbens appeared to be the most divergent region. Functional clustering of differentially expressed genes DISCUSSION suggested two subgroups: those involved in signal transduc- Compared to a prior attempt by our group,8 the application tion most prominently in the accumbens, and cytoskeleton- of GeneChip technology appears to offer an advantageous associated genes in the amygdala (Figure 2). Tables 2–5 strategy for identifying genes potentially underlying phe- give the expression estimates and t-statistics for amygdala, notypic differences between the alcohol-preferring AA and

Table 1 Region-specific gene expression in the rat forebrain

Gene Acc Amy CCx Hip Mapping studies

Restricted Drd1a 1628769.6 372732.3 18477.8 207718.3 Mengod et al 40 Drd2 857742.4 338716.2 24776.9 24576.9 Mengod et al 41 Ania-1 84711.3 3970.0 3970.0 3970.0 Berke et al 42 Mtap1b 3970.0 4671.9 118711.8 4472.3 Htr2a 4271.9 4070.8 7573.6 3970.0 Pompeiano et al 43 Ntf3 6871.7 7573.2 8073.0 132717.6 Phillips et al 44 Highly enriched Pcp4 40007147.5 1658787.4 12817109.9 1688797.2 Sangamewaran et al 45 Tac1 34567147.8 9647100.7 659782.5 491736.0 Chesselet et al 46 Adora2a 1456766.8 567736.8 345710.3 406715.4 Weaver 47 Cck 14167135.3 2037778.6 43037133.7 2035792.9 Savasta et al 48 Pja1 590740.3 773745.7 1645773.8 652732.7 Kcnv1 399722.6 375727.4 811729.6 393712.5 Hugnot et al 49 Gfap 20527160.4 22787148.6 21257172.8 45797168.7 Nrp 14875.6 180716.9 202718.8 527733.1 Fgfr1 15374.5 229721.7 166719.7 517724.5 Belluardo et al 50 dChip estimates (mean7SEM) from four forebrain regions were calculated using eight chips per region, with pooled material from three subjects on each chip. Rat line effects were neglected in this analysis. Bold letters mark the region with restricted or highly enriched gene expression. For criteria of restricted and highly enriched gene expression see the Materials and method section. The present findings are in concordance with available in situ mapping studies cited.

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miscellanous 8% chaperone 4% signal transduction 33% 25% cell adhesion 18% 4% 11% 23% 27% transcription regulation 6% 13%

48 genes 15% 13% 55% 11% neurodegeneration 8% 20%

13% Hip 15% CCx cytoskeleton channel 18% Amy 17% 8% 11% Acc

Na+, K+ -ATPase subunit 8% receptor 10%

Figure 2 Functional clustering of genes differentially expressed between AA and ANA rats. In all, 13 genes involved in signal transduction form the most prominent cluster. The broken outer ring gives cluster distribution in percent of the total number of genes (n ¼ 48) identified in the microarray analysis. The numbers in the inner circles correspond to the distribution within a brain region and are given in percent of the number of genes flagged in that region (Acc: Nc. accumbens n ¼ 18; Amy: amygdala n ¼ 11; CCx cingulate cortex n ¼ 13; Hip: hippocampus n ¼ 15). For clusters containing only a single member, no percentage values are given.

the avoiding ANA lines. An initial indication of this method- independent methods provides a validation of the array ology’s ability to identify differentially expressed genes analysis, despite difficulties inherent in analyzing differen- correctly was provided by the analysis of region-specific tial gene expression in heterogeneous tissues. expression in the brain areas examined. To our knowledge, When gene expression profiles were compared between data for regional patterns of gene expression in the the lines, only modest differences in transcript levels were mammalian brain have previously only been available in detected. Since regions known to be involved in the control the mouse.13 Our analysis in the rat correctly identified a of alcohol intake were analysed, this indicates that changes limited set of genes known to be preferentially expressed of this magnitude, although perhaps involving numerous within the Nc. Accumbens, including dopamine D1 and D2 genes, are sufficient to encode phenotypic differences known receptors, substance P (tachykinin 1) and adenosin A2A to exist between the lines. This finding is in agreement receptors. A further degree of confirmation was provided by with earlier reports on brain expression profiles associated the preproNPY expression results. Here, the GeneChip data with ethanol preference and consumption in humans and on relative hippocampal expression between the lines were rodents.8–10,14,15 Interestingly, the Nc. Accumbens, a key in close agreement with results previously obtained in our component of brain reward systems, showed the highest laboratory using in situ hybridization,15 and were subse- divergence of gene expression among the regions examined. quently possible to further confirm using quantitative real- The array analysis indicated that b-arrestin is robustly time PCR. This finding per se is not likely to account for the downregulated in the Nc. Accumbens, amygdala and alcohol-preferring phenotype of the AA line, since NPY hippocampus of the AA line. This gene is a key component expression does not differ between this line and Wistars. of receptor trafficking, by forming complexes with activated However, the upregulated expression in nonpreferring G-protein-coupled receptors, leading to their uncoupling ANA rats could reflect a protective effect of potentiated and sequestration/recycling via endocytosis into clathrin- NPY signaling, in agreement with previous findings.2 coated vesicles.16 This mechanism has been demonstrated More importantly, however, the close correlation of the for the alpha1b- and beta2-adrenergic receptors, mu- GeneChip data with quantitation obtained using two other and delta-opioid receptors, the dopamine D1 receptor

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Table 2 Differential gene expression in the Nc. Accumbens of AA, ANA and Wistar rats

Gene Description FC p LCB UCB AA ANA Wistar

Signal transduction Map2k2 Mitogen-activated protein kinase kinase2 1.99 0.007 1.46 3.09 478712 240752 1867103 Map2k1 Mitogen-activated protein kinase kinase 1.51 0.045 1.17 1.96 27057271 17927210 16917850 Mapk14 p38 mitogen-activated protein kinase 1.37 0.026 1.17 1.59 548743 400720 3007151 Mapk3 Mitogen-activated protein kinase3 1.30 0.034 1.11 1.54 2177777 16807153 13677684 Camk2d Ca2+/-dependent protein kinase2 À1.24 0.010 À1.14 À1.34 8872 1097561731 Arrb2 Arrestin beta 2 À1.50 0.000 À1.37 À1.66 338719 508710 2687135

Receptor Nptxr Neuronal pentraxin receptor 1.42 0.018 1.21 1.68 527737 370727 2587149 Ednrb Nonselective-type endothelin receptor À1.37 0.044 À1.12 À1.70 161717 220714 154778

Neurodegeneration Sod2 Superoxide dismutase 2, mitochondrial 1.73 0.012 1.33 2.43 345718 199734 142772 Sod1 Superoxide dismutase 1, soluble 1.40 0.019 1.18 1.68 21817102 15627150 11047560

Chaperone St13 Suppression of tumorigenicity 13 2.33 0.025 1.58 3.35 228739 98714 71738 Hsp60 Heat-shock protein 60 1.31 0.027 1.14 1.51 1363783 1042763 8967448

Transcription regulation Rb1 Retinoblastoma 1 1.60 0.003 1.37 1.90 11574727775738

Na+,K+-ATPase subunit Atp1a1 Na+,K+-ATPase alpha-1 1.37 0.037 1.14 1.65 16857130 1227796 10127508

Cell adhesion Nt Neurotrimin À1.26 0.031 À1.11 À1.45 447732 563723 2907145

Cytoskeleton Gsk3b Glycogen synthase kinase 3 beta/ 1.45 0.004 1.30 1.61 354721 24475 160782 Tau-protein kinase Miscellaneous Maoa Monoamine oxidase A 1.59 0.040 1.19 2.28 371729 233741 92747 Il18 Interleukin18 À1.21 0.006 À1.13 À1.29 5371647232716

Data represent expression estimates (mean7SEM) from individual arrays (n ¼ 3/strain) analysed by dChip software as described in the Materials and method section. Linear fold changes (FC), P-values, and 90% lower and upper confidence bounds (LCB and UCB, respectively) refer to AA vs ANA comparison. Positive or negative FC refer to up-or downregulation in AA, respectively. p-values result from individual t-tests (AA vs. ANA) for each gene. Only genes meeting the following filtering criteria are shown: (1) Po0.05, (2) UCB471.1, and (3) reliable detection on at least half of the arrays region. Gene symbols are assigned according to annotation of the respective mouse orthologs using the Ensembl Genome Browser. Same clusters as in Figure 2 are used.

and cannabinoid CB1 receptor.17,18 Upon ligand binding b-arrestin. Mitogen-activated protein kinases (MAP kinases), b-arrestin also recruits cAMP phosphodiesterase type IV to also called extracellular signal-regulated protein kinases the recetor-adenylate cyclase complex.19 Both mechanisms (ERKs), form a three-level network of that, through lead to receptor desensitization and cAP signal termination. successive phosphorylation steps, transduces extracellular Consequently, b-arrestin downregulation may produce an signals into cytoplasmic and ultimately nuclear events.24 increased responsiveness in several neurotransmitter sys- The upregulated MAPK pathway in AA rats may thus reflect tems and thus might offer a mechanism for the reported altered signal transduction upon activation of upstream increased opiate and dopamine responsiveness in the AA receptors. Several neurotransmitter receptors, including line.20–22 An involvement of b-arrestin in morphine toler- NMDA, beta-2-adrenergic and CB1 receptors, can induce ance has been reported.23 Interestingly, an overexpression MAPK and stress-activated protein kinase (SAPK) MAPK of b-arrestin in the amygdala was found in our earlier cascades.25–28 We have previously reported that this path- microarray study of ethanol-exposed rats.9 way is activated in the cingulate cortex of another animal Further, we found several members of the MAPK pathways model characterized by persistently increased voluntary to be upregulated in the AA Nc. Accumbens. This could ethanol consumption and preference.9 One of the genes be secondary to increased receptor signaling due to low detected in that model, Mapk9, was also upregulated in the

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Table 3 Differential gene expression in the amygdala of AA, ANA and Wistar rats

Gene Description FC p LCB UCB AA ANA Wistar

Signal transduction Camk2a Calcium-calmodulin-dependent protein kinase 1.30 0.012 1.17 1.43 1007377748675 Arrb2 Arrestin beta 2 À1.52 0.007 À1.32 À1.77 418733 636726 472755

Cytoskeleton Gsk3b Glycogen synthase kinase3 beta/tau-protein kinase 1.52 0.001 1.41 1.63 22978 15174 138737 Mtap2 Microtubule-associated protein2 1.38 0.028 1.19 1.60 472734 342719 294725 Cnp1 2’, 3’-Cyclic nucleotide 3’-phosphodiesterase À1.19 0.005 À1.13 À1.25 2300753 2729758 25957356 Mapt Microtubule-associated protein tau À1.12 0.009 À1.14 À1.31 1196744 1456733 12617297 Tubb5 Class I beta- À1.43 0.044 À1.16 À1.79 513757 732750 6447103 Gfap Glial fibrillary acidic proteins alpha and delta À1.37 0.010 À1.22 À1.56 18807120 2584798 22367316

Neurodegeneration Capns1 , small subunit 1 À1.28 0.038 À1.12 À1.48 17677132 2261795 2276778

Na+,K+-ATPase subunit Atp1b2 Na+,K+-ATPase beta-2 À1.24 0.030 À1.11 À1.38 403723 498717 390757 Atp1a2 Na+,K+-ATPase alpha-2 À1.48 0.033 À1.19 À1.94 7987114 1179736 9927156

For legend see Table 2.

Table 4 Differential gene expression in the cingulate cortex of AA, ANA and Wistar rats

Gene Description FC p LCB UCB AA ANA Wistar

Signal transduction Mapk9 Stress activated protein kinase alpha II 1.78 0.030 1.29 2.86 498719 280764 30376 Camk4 Ca2+/calmodulin-dependent protein kinase 1.58 0.024 1.26 1.98 907657765372 Itpr1 Olfactory inositol 1,4,5-trisphosphate receptor 1.25 0.040 1.11 1.41 559731 446721 37879

Receptor Tacr1 Tachykinin 1 receptor 1.33 0.031 1.14 1.55 727354756172 Fgfr1 Fibroblast growth factor receptor 1 1.32 0.046 1.12 1.54 221714 168712 109717

Cytoskeleton Itgav Integrin alpha V 1.31 0.018 1.16 1.50 1097383768271 Mtap1b Microtubule-associated protein 1B 1.20 0.012 1..12 1.28 15174 126748073

Neurodegeneration Capns1 Calpain, small subunit 1 À1.16 0.005 À1.11 À1.20 2754748 3180761 23847221 Transcription regulation Nfyc Nuclear transcription factor-Y gamma 1.22 0.033 1.10 1.33 17478 14374 12775

Na+,K+-ATPase subunit Atp1b3 Na+,K+-ATPase beta-3 1.17 0.017 1.10 1.26 515716 439711 240745

Ion channel Kcnc2 voltage-gated channel, Shaw-related 1.21 0.020 1.11 1.30 18677 15474 13674

Miscellaneous Maoa Monoamine oxidase A 1.23 0.027 1.11 1.35 588727 479717 473767 Mipep Mitochondrial intermediate peptidase 1.22 0.029 1.11 1.36 827367736173

For legend see Table 2.

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Table 5 Differential gene expression in the hippocampus of AA, ANA and Wistar rats

Gene Description FC p LCB UCB AA ANA Wistar

Signal transduction Mapk14 p38 mitogen-activated protein kinase 1.81 0.036 1.34 2.49 363744 201728 313747 Pik3c3 Phosphatidyl inositol 3-kinase 1.28 0.042 1.12 1.47 204713 15979 196710 Itpka Inositol 1,4,5-triphosphate 3-kinase À1.34 0.002 À1.26 À1.43 913725 1227735 1277767 Arrb2 Arrestin beta 2 À1.61 0.017 À1.31 À2.02 408745 658746 537712

Ion channel Vgcnl1 Voltage-gated channel like 1 1.26 0.042 1.10 1.46 923725 735759 779771 Kcna4 Voltage-gated protein À1.17 0.008 À1.10 À1.23 29579 34474 33175 Cacnb3 subunit beta 3 À1.72 0.024 À1.31 À2.52 61711 10575 11174

Receptor Fgfr1 Fibroblast growth factor receptor 1 1.40 0.025 1.19 1.67 704733 504747 601771 Gpr51 GABAB receptor 2 1.32 0.031 1.15 1.54 201711 152710 130723

Neurodegeneration Sod2 Superoxide dismutase 2, mitochondrial 1.43 0.030 1.17 1.83 283711 198725 241716 Bax bcl2-associated X protein À1.14 0.002 À1.11 À1.17 2138727 2433730 23827100

Cell adhesion Bcan Chondroitin sulfate proteoglycan À1.21 0.012 À1.12 À1.30 1715772 2071737 2173729 Nt Neurotrimin À1.35 0.049 À1.12 À1.67 373742 504720 447710

Transcription regulation Madh2 Mad homolog 2 1.22 0.017 1.12 1.33 49177 404721 450765

Miscellaneous Npy Neuropeptide Y À1.36 0.005 À1.25 À1.47 843720 1145750 835723

For legend see Table 2.

cingulate cortex of AA animals in the present study. A dysregulations.10 Whether these structural dysregulations potential functional relevance of these changes is under- contribute to function remains to be established. lined by recent functional findings that ERK activity is Few genes were flagged as differentially expressed in more regulated in the rat brain by chronic ethanol exposure and than one region. This suggests that, rather than reflecting withdrawal. Chronically elevated blood alcohol levels were global changes in brain function, altered gene expression reported to reduce activity of ERK, whereas activity rose conferring phenotypic differences between the lines may be during the withdrawal state. These findings were most confined to specific neuronal circuits. We hypothesized that pronounced in the amygdala and in particular in the the observed differences in basal gene expression may be intermittent model of ethanol exposure.29 caused by several independent mutations in the respective In the amygdala, we found a cluster of downregulated genes. A physical clustering of these mutations to a genes related to cytoskeleton and tissue structure. Among particular region of the rat genome would have pointed to these, the microtubule-associated protein 2 (Mtap2) has an element of particular sensitivity to the selection pressure been shown to be strongly responsive to long-term ethanol applied during breeding for ethanol preference. Contrary to consumption, especially in the basal ganglia and the hippo- this hypothesis, the affected genes appear to be scattered campus.30 We found a decrease in mRNA levels for two across the genome, and, with the exception of NPY, none of subunits of the /potassium-specific ATPase, Atp1a2 these genes is located near known quantitative trait loci and Atp1b2, a combination predominantly found in glia.31 (QTL) for alcohol preference or consumption in rats.33,34 Together with a concomitant downregulation of glial fibril- Although, due to the relatively limited number of genes lary acidic protein (Gfap), these genes may reflect glia- analysed, this conclusion must be regarded as preliminary. A specific alterations in the amygdala. Studies of cerebellar true pathway or cluster assessment would require screens of tissue from AA rats have demonstrated downregulated at least ten times the present size, which is becoming fea- Gfap expression after long-term ethanol consumption,32 sible with the arrival of new generations of arrays for the rat while a cDNA array study of cortical tissue from . However, despite its limitation, the present study alcoholics identified cytoskeleton-related genes, in particular may be advantageous in identifying functional clusters, as myelin-associated genes and Gfap, as the most prominent seen by the findings in the Nc. Accumbens and amygdala.

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Figure 3 Chromosomal localisation of genes differentially expressed between AA and ANA rats. Mapping information was obtained from Ensembl Genome Browser. Gene symbols are taken from mouse orthologs. Only a few genes appear tfso map closely together. None of the shows an extensive accumulation out of the 48 mapped genes.

In summary, we report a number of differences in gene putative tool in the search for novel targets for pharmaco- expression between the alcohol-preferring AA rat and its logical treatment of alcoholism. nonpreferring ANA counterpart, which precede any possible effects of ethanol, and thus may confer the innate alcohol MATERIALS AND METHODS preference in the AA line. Some of the detected differences Animals point to novel candidate systems. The major phenotypic Drug-naı¨ve, ethanol-preferring AA (Alko, Alcohol, National differences between the rat lines seem to be encoded by Public Health Institute, Helsinki, Finland), ethanol-nonpre- modest differences in brain gene expression, although the ferring ANA (Alko, Non-Alcohol) and regular Wistar (BK 35 microarray analysis may underestimate their magnitude. Universal, Sollentuna, Sweden) male rats were included in Quantitative real-time RT-PCR confirmation of differential the study (B300 g, n ¼ 12/group, standard housing condi- preproNPY expression indicates that differences of this tions). Animals were killed by decapitation, the brains were magnitude can be detected by the array analysis using the snap frozen in À401C isopentane and kept in À701C until present experimental conditions, and, perhaps more im- further dissection. The procedures were approved by Stock- portantly, the chosen statistical model. We conclude that holm South Animal Ethics Committee (permit S81–84/98). gene expression profiling with oligonucleotide microarrays is a feasible strategy to detect previously unknown differ- Tissue Preparation ences in basal gene expression between genetically deter- Four brain regions were used in the microarray analysis: mined phenotypes. This functional genomics approach is a amygdala, cingulate cortex, hippocampus and Nc. Accumbens.

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Bilateral samples (10–60 mg depending on region) were arrays on a Hewlett-Packard Gene Array scanner, data were obtained under a magnifying lens, using anatomical land- acquired with the Affymetrix MAS 5.0 software. Scanned marks.36 Amygdala, and hippocampus samples were pre- images were visually inspected to be free of specks or pared from a 2 mm thick coronal slice, taken in a Kopf brain scratches. Further quality assessment was carried out slicer by placing the rostral blade on the caudal edge of the according to the following criteria: low noise (RawQ o optic chiasm. For preparation of cingulate cortex and 1.6–2.6), low background (bgo120), low 30 to 50 ratio of accumbens, the rostral blade was placed 4 mm rostral to Gapd (ratioo2.3) and presence of control genes cre, BioD this landmark, and a second 2 mm coronal slice was and BioC. obtained. Cortical and hippocampal tissue was dissected out with a scalpel, while amygdala and accumbens tissue was obtained using a punch (2 mm diameter). Samples were Statistical Analysis of Microarray Data and Data Mining weighed, and stored at À701C until RNA was prepared. The Affymetrix MAS 5.0. scanner software provides indivi- dual probe readings. These were analysed with dChip 1.1 RNA Extraction and Purification (http://www.dchip.org) as well as with the Affymetrix MAS Total RNA was extracted with TRIzol reagent (Gibco BRL 5.0 software. The dChip software, developed by Li and 37 Life Technologies, Baltimore, MD, USA) followed by an Wong, fits a linear model across all chips. This allows the RNeasy (Qiagen, Hilden, Germany) clean-up step according variance in signal for each probeset to be partitioned into a to the manufacturer’s instructions. The yields of RNA specific hybridization-related signal vs noise, and does so were from about 6 to 30 mg depending on the region. with increasing power as chips are added to the analysis. The The RNA was prepared individually, in parallel and in approach also enables outliers to be flagged, providing a tool for quality control. Here, probe parameters were fitted to a mixed order. All RNA samples showed A260/280 ratios between 1.9 and 2.1. RNA integrity was determined using larger data set consisting of the chips of the presented study, an Agilent 2100 Bioanalyzer (Agilent Technologies, CA, as well as other experiments carried out under identical USA), and only material without signs of degradation conditions, for a total of 47 RN U34 array experiments was used. performed on rat forebrain tissue. Maximum array probe sets outlier accepted was 5%. On the basis of this criterion four Affymetrix Oligonucleotide Microarray Hybridization chips had to be excluded from the study. Total RNA samples from nine animals per experimental Two parameters were used for the analysis of expression group were chosen for microarray hybridization experi- data: probability of transcript detection and estimates of ments. To reduce individual variation and chip numbers transcript abundance. Calculation of the probability of required, samples from each strain were pooled (three transcript detection was based on the MAS 5.0 (which tests subjects/pool, 2–3 mg total RNA from each individual), specificity of the PM–MM pair), while the estimates of yielding three independent pools from each strain for each transcript abundance are based on dChip’s multichip region. Pooled RNAs were ethanol-precipitated together algorithm (which uses only PM values). with 0.5 ml Pellet Paint (Novagen, Madison, WI, USA). Target preparation and hybridization were according to the Assessment of region-specific gene expression manufacturer’s technical manual (Affymetrix, Santa Clara, CA, USA). Briefly, double-stranded cDNA was synthesized The signal from a probe set was accounted as present in a using the Superscript Choice System (Gibco BRL, Life particular region if it was flagged ‘present’ or ‘marginally

Technologies) with an HPLC-purified T7-(dT)24 primer present’ by MAS 5.0 on at least six of the eight arrays of that (Proligo, Boulder, CO, USA), starting with 6 mg of the pooled region, or on all chips of one rat line (these calls are based on total RNA. cDNA was then purified with Phase Lock Gel a probability of detection of Po0.04, and 0.04rPo 0.06, (Eppendorf-5 Prime, Boulder, CO, USA) and phenol/chloro- respectively). A probe set was scored as absent for a region if form (Ambion Inc., Austin, TX, USA) extraction, precipi- it was flagged ‘absent’ by MAS 5.0 on all chips of that region tated with ethanol (plus 0.5 ml Pellet Paint), and resuspended (based on probability of detection was P40.06). The signal in RNase-free water. Biotinylated cRNA targets were in vitro intensity threshold for an absent call (P40.06 probability of transcribed using the RNA Transcript Labeling Kit (Enzo detection) varies considerably (min–max: 39–4597, dChip Diagnostics, Farmingdale, NY, USA). The synthesized cRNA estimates) and is specific for each probe set. Additionally, was purified on an RNeasy column (Qiagen, Hilden, there is region-to-region variation in the mean signal Germany), yielding 50–80 mg labeled cRNA/target. The cRNA estimate of the absent calls. In order to ensure clear was fragmented to an average size of 35–200 bases. In total, distinction between region-based absent and present calls, 5 mg of fragmented cRNA was used in the hybridization a signal was only called region-specific if the signal estimate cocktail. Targets were hybridized for 14–16 h at 451Cto in the region with the present call was at least by 50% above oligonucleotide microarrays (Affymetrix Rat Neurobiology any region with an absent call. Furthermore, in cases where U34) containing probe sets for about 1000 genes. Chips the signal was called present in two or more regions we were washed and stained on an automated fluidic station tested for highly enriched gene expression defined as signal according to the procedure 2 protocol from Affymetrix, estimates at least two-fold above the levels of the other including antibody amplification. After scanning the regions with a present call.

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Candidate gene identification REFERENCES 1 Enoch MA, Goldman D. The genetics of alcoholism and alcohol abuse. Genes differentially expressed between the AA and ANA Curr. Psychiatry Rep 2001; 3: 144–151. lines were identified by a series of filtering steps. For each 2 Heilig M, Thorsell A. Brain neuropeptide Y (NPY) in stress and alcohol candidate gene were required: (1) a probability of differ- dependence. Rev. Neurosci 2002; 13: 85–94. 3 Lappalainen J, Kranzler HR, Malison R, Price LH, Van Dyck C, Rosenheck ential expression of Po0.05 from a t-test (AA vs ANA): (2) a RA et al. A functional neuropeptide Y Leu7Pro polymorphism associated probability of detection of Po0.06 on at least 50% of the with alcohol dependence in a large population sample from the United arrays; and (3) a 90% lower confidence bound (LCB) for the States. 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