Brain distribution of genes related to changes in locomotor activity

Physiology & Behavior 99 (2010) 618–626

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Physiology & Behavior j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / p h b

Brain distribution of genes related to changes in locomotor activity Pasquale Mignogna, Davide Viggiano ⁎ Department of Health Sciences, University of Molise, Campobasso, 86100, Italy

a r t i c l e

i n f o

Article history: Received 2 August 2009 Received in revised form 19 November 2009 Accepted 26 January 2010 Keywords: Knockout Mice Locomotor activity Exploration mRNA expression

a b s t r a c t The relationship between genes and behavior, and particularly the hyperactive behavior, is clearly not linear nor monotonic. To address this problem, a database of the locomotor behavior obtained from thousands of mutant mice has been previously retrieved from the literature. Data showed that the percent of genes in the genome related to locomotor hyperactivity is probably more than 1.56%. These genes do not belong to a single neurotransmitter system or biochemical pathway. Indeed, they are probably required for the correct development of a specific neuronal network necessary to decrease locomotor activity. The present paper analyzes the brain expression pattern of the genes whose deletion is accompanied by changes in locomotor behavior. Using literature data concerning knockout mice, 46 genes whose deletion was accompanied by increased locomotor behavior, 24 genes related to decreased locomotor behavior and 23 genes not involved in locomotor behavior (but important for other brain functions) have been identified. These three groups of genes belonged to overlapping neurotransmitter systems or cellular functions. Therefore, we postulated that a better predictor of the locomotor behavior resulting from gene deletion might be the brain expression pattern. To this aim we correlated the brain expression of the genes and the locomotor activity resulting from the deletion of the same genes, using two databases (Allen Brain Atlas and SymAtlas). The results showed that the deletion of genes with higher expression level in the brain had higher probability to be accompanied by increased behavioral activity. Moreover the genes that were accompanied by locomotor hyperactivity when deleted, were more expressed in the cerebral cortex, amygdala and hippocampus compared to the genes unrelated to locomotor activity. Therefore, the prediction of the behavioral effect of a gene should take into consideration its brain distribution. Moreover, data confirmed that genes highly expressed in the brain are more likely to induce hyperactivity when deleted. Finally, it is suggested that gene mutations linked to specific behavioral abnormalities (e.g. inattention) might probably be associated to hyperactivity if the same gene has elevated brain expression. © 2010 Elsevier Inc. All rights reserved.

1. Introduction The current tendency of biological psychiatry to focus on the genetic substrates of mental health and disease has driven much research to find gene mutations in different mental diseases, hoping to predict the risk to develop a mental illness or to find new pharmacological targets [1,2] (see the work by C. Lombroso in the last century for a more historical perspective about this approach [3,4]).

Abbreviations: CB, cerebellum; CTX, cerebral cortex; HIP, hippocampus; HPF, hippocampal formation; HY, hypothalamus; LSX, lateral septal complex; MB, midbrain; MY, medulla; OLF, olfactory regions; P, Pons; PAL, Pallidum; RHP, retrohippocampal region; STR, striatum; TH, thalamus; AMY, striatum-like amygdala nuclei; SN, substantia nigra; FC, frontal cortex; MOB, medial olfactory epithelium; SC, spinal cord. ⁎ Corresponding author. Dept. Health Sciences, Univ. of Molise, Via De Sanctis III Edificio Polifunzionale, 86100 Campobasso, Italy. Tel.: +39 0874 404965; fax: +39 0874 404763. E-mail address: [email protected] (D. Viggiano). 0031-9384/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.physbeh.2010.01.026

The recent technology of transgenic mice allowed to apply this paradigm through the study of the behavioral effects of deletions, insertions or mutations of single genes in mice. The main conclusion drawn from the large amount of data now available is that the relationship between behavioral tendency and gene mutation/ deletion is not linear nor monotonic, because the effects of multiple genetic changes may be completely different from the sum of the effects induced by individual genes, and therefore the results of multiple genetic modifications are often unpredictable [5,6]. Indeed, the number of transgenic mice produced up to now is very large: an Internet source lists at least 5283 different transgenic animals including animals with genes deletions (knockout mice; see http://www.informatics.jax.org/imsr/IMSRSearchForm.jsp). Interestingly, most of these animals have been behaviorally tested, but a database describing/comparing the behavioral pattern of each transgenic mouse is not yet available (however, see ref. [7] and the database of references describing individual knockout mice available at http://www.bioscience.org/knockout/knochome.htm). Such a database would allow to study the relationship between genes and behavior, and the identification of the animals that show a specific behavioral deficit

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within the entire set of transgenic models (metanalytical approach; see also Mouse Genome Informatics (MGI) projects [8] and the web site http://www.informatics.jax.org/phenotypes.shtml). The comparison of behavioral features of transgenic animals reported in different scientific articles should consider several problems, such as the differences in behavioral testing procedures (see e.g. [9]), the age and sex of the animals (see e.g. ref. [10,11]), sample size, rearing conditions such as number of animals per cage (see e.g. [12]) and the genetic background. All these parameters may affect the results and the reproducibility of data among laboratories [5]. A previous report classifying the behavioral activity of mutant mice based on numerous articles about transgenic mice, concluded that the number of genes linked to the increase of locomotor activity might be very high [13]. Specifically, data pertaining all transgenic mice with increased or decreased locomotor activity were retrieved and filtered to limit the effect of confounding variables. Unexpectedly, the results identified a very large number of genes involved in hyperactivity after exposure to a novel environment, which have been estimated to be at least 1.56% of the genes in the genome [13]. It is unclear why the mutation of so many genes can increase locomotor activity. Moreover, it was not possible to group all these genes in just one or few neurotransmitter systems or biochemical pathways [13]. Therefore, a working hypothesis suggested that all these genes were required for the correct development/functioning of a common neuronal network necessary to decrease a spontaneously occurring hyperactivity [13]. The present article tests this hypothesis through the analysis of brain expression of genes related to changes (increase/ decrease) in locomotor behavior. To this aim a database of knockout mice tested for locomotor activity in a novel environment has been realized from published studies, filtered on the basis of inclusion/ exclusion criteria. The knockout mice have been divided in hyperactive, hypoactive and normoactive groups on the basis of their locomotor behavior. Finally, the basal brain distribution of the genes knocked out in these groups using two databases available in Internet (Allen Brain Atlas and SymAtlas) has been studied.

2. Materials and methods The complete list of genes described in this paper is reported in Table 1. This list has been derived from an initial set of 15,806 abstracts containing key words “locomotor”, “activity”, “mice”, retrieved from PubMed (http://www.ncbi.nlm.nih.gov/sites/entrez/). This set was then filtered to include only the publications describing knockout mice and their locomotor behavior. These publications were then organized in a table containing: (i) the name of the gene knocked out, (ii) various parameters about the behavioral test, such as test duration, number of repetitions, size and shape of the arena, behavioral procedures, horizontal and vertical (rearing) activity, measurement system (photocells, video tracking etc), (iii) data about the sample, such as sample size, age and sex of the animals, type of control mice, genetic background, and (iv) statistical analysis (effect size expressed as % change compared to wt littermates and significance level). Finally, the animals in this first table have been selected according to the following inclusion criteria: (1) Age of animals from 2 to 6 months; (2) Minimum 7 animals per experimental group, each individually tested; (3) Experimental groups consisting of only males (no females); (4) Behavioral observations about horizontal locomotor activity (changes in rearing frequency were not considered); (5) Control mice consisting of wild type littermates; (6) Genes had to be expressed in the brain (this information has been retrieved from the Allen Brain Atlas and SymAtlas, as described below).

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The following exclusion criteria have been used: (1) The behavioral data did not discriminate male from female mice as these were grouped together; (2) Animals were not studied in a novel environment; (3) Behavioral changes occurred only for very short intervals (less than 5 min) or after very long exposure to novelty (more than 30 min) or only after repeated exposures to novelty; (4) Mice were prepuberal or aged; (5) Inappropriate control groups (no wt-littermates) or small experimental groups with less than seven individuals; (6) Genes were not expressed in the brain (this exclusion criterion was used to minimize the possibility that the alterations in locomotor behavior were due to systemic effects of the genetic deletion). The investigations that fulfilled all these requirements were then used to categorize the locomotor activity. The animals were divided in three groups, according their locomotor activity: (i) Increased activity or (ii) decreased activity, if locomotor activity changed with an effect size (increase or decrease respectively) greater than 20%; and (iii) normoactive animals, showing an effect size smaller than 10% compared to their wt littermate controls, which was not statistically significant (therefore animals showing no significant differences from controls but with an effect size greater than 10% were excluded too). Animals in the normoactive group satisfied the following additional criteria: 1) the targeted gene had no known “isoforms” which could replace its function, and 2) the targeted gene was involved in brain functions, since neurological/behavioral abnormalities (e.g. anxiety, memory deficit etc) were also reported. Afterwards, the brain expression pattern of the candidate genes has been retrieved from two different databases: the Allen Brain Atlas (http://mouse.brain-map.org), a database describing the mRNA brain expression pattern of mouse genes based on the in situ hybridization technique and the SymAtlas (now available through the BioGPS portal http://biogps.gnf.org/) which quantifies mRNA expression pattern based on microarray technique. Specifically, the Allen Brain Atlas has been used to retrieve two different mRNA quantifications from 17 different brain regions: the expression density and the expression level (http://mouse.brain-map. org/pdf/InformaticsDataProcessing.pdf) [14]. The expression level (L) is the product of the average pixel intensity (I) per total area of positive cells (ag), normalized by the area of all cells (amax): L = I ⁎ (ag/amax). The expression density (D) is the number of positive cells (ng) normalized by the total number of cells (nmax) in the same region: D = ng/nmax. The expressions L and D were already quantified by Allen Brain Atlas database for the following brain regions: cerebellum (CB), cerebral cortex (CTX), hippocampal region (HIP), hippocampal formation (HPF = HIP + subiculum), hypothalamus (HY), lateral septal complex (LSX), midbrain (MB), medulla (MY), olfactory areas (OLF = olfactory bulb, anterior olfactory nuclei, and pyriform cortex), Pons (P), Pallidum (PAL), retrohippocampal region (RHP), striatum (STR), thalamus (TH), striatum-like amygdalar nuclei (AMY= central+ anterior + medial amygdalar nucleus). Future studies will address possible subdivisions of these brain regions (in particular the cerebral cortex) in order to obtain spatially defined results. The SymAtlas database has been used to retrieve the mRNA expression value from the following brain regions: CB, CTX, HIP, HY, substantia nigra (SN), OLF, STR, AMY, frontal cortex (FC), medial olfactory epithelium (MOB), preoptic nucleus (PO), and spinal cord (SC). The database used (Mouse GNF1M Gene Atlas) reported the mRNA expression from multiple probes normalized with the Robust Multi-array Analysis (gcmrna algorithm) [15,16]. Data were submitted to two-way analysis of variance group × brain region separately for the two databases. Posthoc comparisons were

Calcium channel, voltage-dependent, beta 4 subunit (Cacnb4) [22] Dopamine beta hydroxylase (Dbh) [26,27] D site albumin promoter binding protein (Dbp) [30] Dopamine receptor 2 (Drd2) [33] Dopamine Receptor 4(Drd4) [36] Engrailed 1 (En1) [40] Engrailed 2 (En2) [40] Gastrin (Gast) [46] Glutamate receptor, metabotropic 8 (Grm8) [49] Orexin (Hcrt) [52] Hdc [55,56] Htr1a [59] Potassium inwardly rectifying channel, subfamily J, member 11, Kir 6.2 (Kcnj11) [61] Yamaguchi sarcoma viral (v-yes-1) oncogene homolog (Lyn) [64] Methyl CpG binding protein 2 (MeCP2) [67] Npy [70] Soluble adenylyl cyclase (sacy) [73] Solute carrier family 6 (neurotransmitter transporter, noradrenalin), member 2, NET (Slc6a2) [76,77] Serotonin Transporter, SERT (Slc6a4) [40,80–82] Somatostatin receptor-2 (sstr2) [85] Tyrosine Hydroxylase (Th) [89–93] Tyroid Hormone Receptor alpha (Thra) [96] Ubiquitin protein ligase E3 component n-recognin 1 (Ubr1) [98] Vitamin D receptor (Vdr) [101]

ATP-binding cassette, subfamily A (ABC1), member 2 (Abca2) [21] Adenylate cyclase activating polypeptide 1, PACAP (Adcyap1) [24,25] Adaptor-related protein complex 3, delta 1 subunit (Ap3d1) [29] Arylsulfatase A (Arsa or Asa) [32] ATPase, Na+/K + transporting, alpha 3 polypeptide (Atp1a3) [35] Calcium/calmodulin-dependent protein kinase II alpha (Camk2a) [39] Cholinergic receptor, muscarinic 1, CNS (Chrm1) [42,43] Cyclic nucleotide phosphodiesterase 1 (Cnp1) [45] Dopamine receptor D1A (Drd1a) [47,48] Fibroblast growth factor 1 and 2 (Fgf1 and Fgf2) [51] Fibroblast growth factor receptor 1 (Fgfr1) [54] Fragile X mental retardation syndrome 1 homolog (Fmr1) [58] Fragile X mental retardation gene 2, autosomal homolog (Fxr2h) [60]

Glast (Slc1a3) [79] glutamate receptor, ionotropic, AMPA1 (alpha 1) (Gria1) [84] Glutamate receptor, ionotropic, NMDA1 (zeta 1) (Grin1) [87,88] Glycogen synthase kinase 3 beta (Gsk3b) [95] 5-hydroxytryptamine (serotonin) receptor 2C (Htr2c) [18] Inositol (myo)-1(or 4)-monophosphatase 1 (Impa1) [100] Kv3.1, potassium voltage-gated channel, Shaw-related subfamily, member 1, Potassium channel (Kcnc1) [102,103] Kv3.3, potassium voltage-gated channel, Shaw-related subfamily, member 3 (Kcnc3) [102,103] GIRK2, potassium inwardly rectifying channel, subfamily J (Kcnj6) [17] Potassium voltage-gated channel, subfamily Q, member 2 (Kcnq2) [104] ERK1, mitogen activated protein kinase 3 (Mapk3) [105] Melanin-concentrating hormone receptor 1 (Mchr1) [106] Microtubule-associated protein 6 or Stable Tubule-only peptide (STOP) (Mtap6) [107,108] NFkB-p50 subunit (Nfkb1) [109] Nur77, Nuclear receptor subfamily 4, group A, member 1 (Nr4a1) [110] Nurr1, nuclear receptor subfamily 4, group A, member 2 (Nr4a2) [111–113] Heregulin (Nrg1) [114] Protein-L-isoaspartate (D-aspartate) O-methyltransferase 1 (Pcmt1) [115] p85alpha (Pik3r1)[116] Prion protein (Prnp) [117] Ryr3 [118] Slc2a8 [119] DAT1, solute carrier family 6 (neurotransmitter transporter, dopamine), member 3 (Slc6a3) [120–122] Synaptosomal-associated protein 25 (Snap25) [123–126] Synapsin2 (Syn2) [127] Tropomodulin 2 (Tmod2) [128] Tenascin R, (Tnr) [129]

Gamma-aminobutyric acid (GABA-B) receptor, 1 (Gabbr1) [63] Gamma-aminobutyric acid (GABA) B receptor 2 (Gabbr2) [66] Gamma-aminobutyric acid (GABA-A) receptor, subunit alpha 3 (Gabra3) [69] Growth associated protein 43 (Gap43) [72] Connexin 43, gap junction membrane channel protein alpha 1 (Gja1) [75]

Locomotor activity decreased more than 20% when the gene is deleted (group 2)

Locomotor activity increased more than 20% when the gene is deleted (group 1)

Table 1 Genes related to locomotor behaviour.

P2rx7 [83] Cyclophilin D (Ppid) [86] Relaxin3 (Rln3) [94] Solute carrier family 32 (GABA vesicular transporter), member 1 (Slc32a1) [97] Sv2a [99]

Connexin 36, gap junction membrane channel protein alpha 9 (Gja9) [65] Glucagon-like peptide 1 receptor (Glp1r) [68] G-substrate (Gsbs) [71] Nr cam (C130076O07Rik) [74] Neuropsin (Opn5) [78]

Acetylcholine esterase (AChE) [23] Adrenergic receptor, alpha 2a (Adra2a) [28] Calpstatin (Cast) [31] Cav1.3 (cacna1d) [34] Cell adhesion molecule with homology to L1CAM (Chl1) [37,38] Muscarinic receptor M2 (Chrm2) [41] Cholinergic receptor, nicotinic, beta 2 subunit (neuronal) (Chrnb2) [44] Claudin 14 (cldn 14) Aromatase (Cyp19a1) [50] Egr2 [53] Forkhead Box, Class O (Foxo3a) [57] Galanin (Gal) Galanin receptor 2 (Galr2) [62]

Locomotor activity changes smaller than 10% (not significant) when the gene is deleted (“control” group)

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done using LSD test for repeated comparisons. Rejection level was set at p b 0.05. 3. Results Using the inclusion/exclusion criteria described above 93 knockout mice have been selected: 46 knockout mice with increased locomotor behavior, 24 knockout mice with decreased locomotor behavior and 23 knockout mice with other types of neurological impairments but normal locomotor behavior (Table 1). Five additional knockout mice were excluded from the analysis because behavioral reports from the literature were not consistent (cnr1, cckbr and bdnf) or were identified as outliers on the basis of the brain expression level (Pde10A) or their involvement in behavioral abnormalities were probably mediated by systemic metabolic alterations (pah). In agreement with a previous report, genes related to hyperactive and hypoactive behavior could not be grouped into separate neurotransmitter classes. Similarly, genes of the control “normoactive” group belonged to neurotransmitters/neuropeptides (galanin) or structural proteins (Gja9, Nr CAM, and L1CAM), or different neurotransmitter systems (epinephrine, acetylcholine, and GABA) and thus could not be grouped in only one neurotransmitter or cellular system. Therefore, the knowledge of the function of a specific gene at cellular or neuronal level does not carry enough information to predict if its deletion might change locomotor behavior. In contrast, a better predictor of gene deletion effect on locomotor behavior might be the level of expression of the same gene in the brain (mRNA expression). To test this hypothesis the expression levels of specific genes were analyzed in different brain regions in order to have predictable indicators on locomotor behavior after gene deletion, using two different datasets. In the following description the term “group 1 genes” is referred to the group of genes that, after deletion, are accompanied by hyperactivity, “group 2 genes” is referred to the group of genes that, after deletion, are accompanied by hypoactivity and “control genes” will refer to the group of genes that, after deletion, are not accompanied by changes in locomotor activity. Since the genetic background was not the same for all KO animals selected, we tested if a bias in the background among the groups was present. The majority of the KO animals were raised in C57BL/6 or Sv 129 background or in a mixed C57BL/6 × Sv129 background. Few animals in our set were studied in other genetic backgrounds such as balb/c (n = 4), icr (n = 1), FVB (n = 2) or DBA (n = 2). Therefore, to test the homogeneity of the groups we focused on the three major backgrounds (C57BL/6Sv129 and mixed C57BL/6 × Sv129). As shown in Fig. 1, these backgrounds were similarly represented in the groups divided according the behavioral activity. In fact, a non-parametric χ2 test of the observed frequency distribution of the three backgrounds in the three behavioral groups was not statistically significant. The analysis of the brain expression pattern of these genes is shown in Fig. 1. Group 1 genes showed higher expression level and expression density in all brain regions, compared to group 2 genes (Figs. 1 and 2). The brain expression pattern of group 1 and group 2 genes were then compared to the group of control genes. This analysis showed that, when compared to the control genes, the genes of group 1 showed significantly higher expression (level and density) in all brain regions according to the Allen Brain Atlas (p b b 0.01 in all brain regions). However, using expression leves from the SymAtlas database, only in the following regions were significant (Fig. 1): (i) the cerebral cortex (CTX; p = 0.041, LSD test for repeated comparisons), (ii) the hippocampus (HIP, p = 0.035, LSD test for repeated comparisons), and (iii) the amygdala (AMY, p = 0.030, LSD test for repeated comparisons). The group 2 genes did not show significant changes from the control group in any brain region according to the Allen Brain Atlas dataset and the SymAtlas dataset.

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A finer analysis was then conducted to verify the relationship between the expression level of each gene in the hippocampus and the change in locomotor activity resulting from their deletion. To this aim, rather than classifying knockout animals in three groups (increased, decreased or normal locomotor activity), the locomotor activity of each knockout animal compared to the appropriate wild type control littermate (expressed as percent of basal value) was retrieved from literature data. The locomotor activity level was then plotted against the expression level in the hippocampus of each gene according to the Allen Brain Atlas and the Sym Atlas dataset. Fig. 1 shows a significant correlation between the expression density of different genes in the hippocampus and the locomotor activity level resulting after deletion of the same genes (r = 0.542 according to the Allen Brain Atlas and r = 0.502 according to the SymAtlas database). Thus, the higher the expression of a gene in the hippocampus, the higher the observed locomotor behavior when the same gene is deleted (Figs. 1 and 2). 4. Discussion This article describes the brain expression pattern of genes that are accompanied by changes in locomotor activity when deleted and compares it to the expression pattern of genes expressed in the brain, but whose deletion do not change the locomotor behavior in a novel environment (Fig. 2). The main finding is that the genes accompanied, after deletion, by increased locomotor activity (group 1 genes), are also much more expressed in all brain regions compared to genes accompanied by decreased locomotor behavior (group 2 genes). In order to understand if this effect was due to a lower expression level of group 2 genes or to a higher expression level of group 1 genes, both groups have been compared to a “control” group consisting of genes expressed in the brain, whose deletion do not alter locomotor activity. The comparative analysis of two brain atlases showed that group 1 genes were highly expressed in few brain regions, as the cerebral cortex, hippocampus and amygdala, compared to the “control” genes. Several aspects should be considered in the interpretation of the results. One important issue is the influence of experimental conditions in behavioral findings. As highlighted by previous articles (see e.g. [5]), laboratory conditions greatly change not only the effect size of a specific genetic mutation, but even the possibility to see a behavioral change. Indeed, most of the noise in correlation analysis showed in Fig. 1 is probably due to the differences among laboratories (for example lighting conditions might be very important for novelty-induced locomotor activity). However, the general conclusions — that is the higher the brain expression of a gene (and specifically the expression in the cerebral cortex and hippocampus) the higher the probability that its deletion will be accompanied by hyperactive behavior — appear to be quite robust notwithstanding this experimental noise. Specifically, the main conclusion remained unchanged even after the inclusion of new knockout animals in the database or after the exclusion of some of them due to inconsistencies in new publications or even using two independent gene atlases. A second issue is related to the study of hypoactive animals. As showed by Fig. 1, the maximum effect size in hypoactive animals is about half of the maximum effect size in hyperactive animals. This was expected, because hypoactivity can rapidly reach a minimum, consistent in the complete immobility of the animal (floor effect). This might challenge the possibility to detect hypoactivity, particularly if the wt littermates show already low levels of locomotor activity. Therefore, it is possible to hypothesize that genetic backgrounds with a higher basal locomotor activity (such as C57BL/6) might be more useful to detect hypoactive behavior (and, vice versa, as suggested by anonymous referee, the background Sv129 or FVB, which show lower

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Fig. 1. Brain distribution and level of expression of genes whose deletion is accompanied by changes in locomotor activity. A: distribution of the genetic background according to the change of the locomotor activity as percent of control animals (0 = no behavioral changes, + 100/− 100 = 100% increase/decrease of locomotor activity compared to wt littermates; each dot represent a different knockout line). B,C Expression density according to the Allen Brain Atlas (B) and expression level according to the SymAtlas (C) of genes whose deletion is accompanied by hyperactive (hyper) or hypoactive (hypo) behavior or does not change locomotor activity (normal) in different brain regions. Each point represents the average expression of the genes that, when deleted, are accompanied by hyperactivity/hypoactivity or do not change locomotor behavior (see Table 1 for a list of the genes); D: statistical significance (p-value using multiple LSD comparisons) of the increase in expression level according to the SymAtlas (horizontal axis) and Allen Brain Atlas (vertical axis) of hyperactive genes compared to control genes in various brain regions (each dot represent a brain region). D: Non-linear monotonic correlation between the locomotor activity (0 = normal behavior) of knockout animals and the expression density in the cerebral cortex of the genes knocked out (each dot represents a different gene). B,C data represent mean ± standard error. CB: cerebellum; CTX: cerebral cortex; HIP: hippocampus; HPF: hippocampal formation; HY: hypothalamus; LSX: lateral septel complex; MB: midbrain; MY: medulla; OLF: olfactory regions; P: Pons; PAL: Pallidum; RHP: retrohippocampal region; STR: striatum (dorsal/ventral); TH: thalamus; AMY: striatum-like amygdalar nuclei, SN: substantia nigra; MOB: medial olfactory epithelium; PO: preoptic; FC: frontal cortex; SC: spinal cord.

activity in a novel environment, might be useful to detect a hyperactive behavior due to gene deletion). We did not observe a particular bias of the genetic background used in the literature to observe hyperactive or hypoactive behavior (see Fig. 1). However, the smaller number of hypoactive animals might reflect a real difficulty to detect this type of behavior. Another issue is the consideration that most of the selected genes are also expressed in regions outside the brain, and therefore the behavioral effects of their deletion might be indirect, as metabolic changes. When more tissue-specific conditional knockout mice will be

available, this issue will be appropriately addressed. However, the results concerning the brain expression pattern of group 1 genes are consistent with data from lesion studies. In fact, cerebral cortex and hippocampal lesions have been shown to increase locomotor activity (reviewed in [13]). Therefore it is plausible that the deletion of genes highly expressed in these brain regions would also result in increased locomotor behavior. Accordingly, the deletion of a gene highly expressed in the cerebral cortex may account for an increase in locomotor activity, independently from its function at cellular/neuronal level. It should be noted that, if the

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Fig. 2. Brain distribution of representative genes whose deletion is accompanied by an increase (left column), a decrease (right column) of locomotor activity in novel environments or does not change locomotor activity (central column). Data from the Allen Brain Atlas, reconstructed using the Brain Explorer software.

lack of a specific gene is accompanied by hyperactivity, the “normal” function of the same gene would be to decrease locomotor activity. For example hyperactivity emerges when two genes highly expressed in the brain such as girk2 [17] or serotonin receptor 2C genes [18] are deleted, and therefore they should be expected to decrease locomotor activity in normal mice, when normally expressed. Therefore, a working hypothesis is that genes highly expressed in the brain, and particularly in the cerebral cortex, have larger probability to be necessary for the development of a neural network which normally reduces locomotor activity [13]. It should be expected that focal lesions of different portions in this neuronal network either by pharmacological interventions (see [13] for a review) either by deletion/mutation of genes highly expressed in the same brain regions might alter the computational properties of this structure, a prerequisite for the development of novelty-induced hyperactivity. This specific type of hyperactivity depends on the recognition of previously explored situations, because in normal animals the exploration of familiar environments causes a reduction of the exploratory activity (habituation). Thus, if the brain regions, such as the cerebral cortex, involved in environmental recognition and mapping were altered by genetic modifications or pharmacological interventions, their function would be impaired, with consequent lower recognition ability and slower habituation to a novel environment. This is in agreement with previous reports that a large number of transgenic animals show altered hippocampal-dependent spatial memory [19]. Moreover, this neural network is expected to be mature at very early phases of life, since the capability of rat pups to explore is similar to adult rats [20]. An unresolved issue is whether gene expression alterations could be related to behavioral mechanisms like altered fear, reactivity to

reinforces. Indeed, further studies are currently in progress to retrieve knockout animals with these behavioral abnormalities, in order to study the statistical association with locomotor hyper/hypoactivity in the entire set of knockout mice. These results have implications for the understanding of gene– behavior relationship and for research in human psychiatric diseases. In fact, it appears that the action mechanism of a specific gene is less important than its expression level in specific brain regions in the prediction of its relevance for behavioral processes. Secondly, the increased locomotor activity accompanying mental diseases such as schizophrenia and ADHD, might be due to the brain expression level of the genes involved in the main symptoms of the disease (e.g. hallucinations and inattention, respectively). Specifically, it is plausible that if the genes implicated in the lack of attention (like in ADHD) or in hallucinations (like in schizophrenia) are highly expressed in the cortex or hippocampus, this might give rise to hyperactivity as showed in the present paper. Therefore, the occurring of hyperactivity in several psychiatric diseases might be explained as a collateral symptom due to alteration of genes highly expressed in the cerebral cortex or in the hippocampus.

Acknowledgments I am grateful to my wife Giovanna, for the encouragement and for the revision of the paper (DV). We are grateful to Dr. A. Bartolomucci and Dr. R. Gainetdinov who gave very useful suggestions. We also acknowledge the anonymous referees who greatly helped to improve the manuscript with their comments. We thank The Allen Institute for Brain Science for the permission to use their data in this publication.

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Finally, we are grateful to Dr. D. Clement for useful discussions of the data, presented at the Academy of Sciences in Prague.

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