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Endocrinology, doi:10.1210/en.2007-0634
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Endocrinology Vol. 148, No. 11 5147-5161
Copyright © 2007 by The Endocrine Society

Expression of a Tumor-Related Gene Network Increases in the Mammalian Hypothalamus at the Time of Female Puberty

Christian L. Roth, Claudio Mastronardi, Alejandro Lomniczi, Hollis Wright, Ricardo Cabrera, Alison E. Mungenast, Sabine Heger, Heike Jung, Christopher Dubay and Sergio R. Ojeda

Division of Neuroscience (C.L.R., C.M., A.L., H.W., R.C., A.E.M., S.H., H.J., C.D., S.R.O.) and Genetics Resources and Informatics Program (H.W., C.D.), Oregon National Primate Research Center/Oregon Health and Science University, Beaverton, Oregon 97006

Address all correspondence and requests for reprints to: Sergio R. Ojeda, Division of Neuroscience, Oregon National Primate Research Center, Oregon Health and Science University, 505 Northwest 185th Avenue, Beaverton, Oregon 97006. E-mail: ojedas{at}ohsu.edu.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Much has been learned in recent years about the central mechanisms controlling the initiation of mammalian puberty. It is now clear that this process requires the interactive participation of several genes. Using a combination of high throughput, molecular, and bioinformatics strategies, in combination with a system biology approach, we singled out from the hypothalamus of nonhuman primates and rats a group of related genes whose expression increases at the time of female puberty. Although these genes [henceforth termed tumor-related genes (TRGs)] have diverse cellular functions, they share the common feature of having been earlier identified as involved in tumor suppression/tumor formation. A prominent member of this group is KiSS1, a gene recently shown to be essential for the occurrence of puberty. Cis-regulatory analysis revealed the presence of a hierarchically arranged gene set containing five major hubs (CDP/CUTL1, MAF, p53, YY1, and USF2) controlling the network at the transcriptional level. In turn, these hubs are heavily connected to non-TRGs involved in the transcriptional regulation of the pubertal process. TRGs may be expressed in the mammalian hypothalamus as components of a regulatory gene network that facilitates and integrates cellular and cell-cell communication programs required for the acquisition of female reproductive competence.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
DURING THE LAST few years, significant progress has been made toward elucidating the basic cellular and molecular mechanisms underlying the neuroendocrine control of mammalian puberty. Specific transsynaptic and glia-to-neuron communication pathways affecting the GnRH neuronal network have been identified, and the relative importance of each of these pathways in controlling the pubertal process has been demonstrated, along with some of their structural and functional interactions. The neuronal networks most critically involved in controlling GnRH release during sexual development have been shown to be those that use excitatory/inhibitory amino acids (reviewed in Ref. 1), and the recently identified neuropeptide metastin/kisspeptin (2, 3), for neurotransmission. Cell-cell signaling molecules that, produced in astroglial cells, facilitate GnRH secretion have been identified, and genetic approaches have been used to define the physiological contribution of these molecules to the pubertal process (reviewed in Ref. 4).

These efforts have also made clear that no isolated pathway or cellular subset is responsible for the neuroendocrine control of puberty. Instead, this control is likely exerted by complex regulatory gene networks composed of functional modules. A global approach for the system-level identification of such networks has never been attempted, essentially due to the lack of appropriate technology and the relative paucity of genetic and biochemical details that can be assimilated into a testable biological model. The emergence of high-throughput approaches and computational methods to organize, display, and analyze the plethora of results derived from such approaches is rapidly changing this landscape and giving us for the first time the opportunity of identifying functional genetic modules involved in the hierarchical control of puberty.

Although mathematical models for common mechanisms of gene regulation are available (see, for instance, Ref. 5), most current models of genetic network architecture derive from nonmammalian species in which single metabolic or developmental pathways have been analyzed (e.g. Refs. 6, 7, 8). The development of similar models to explain integrated functions of much more complex tissues, such as the hypothalamus, has been (and continues to be) exceedingly difficult because of the cellular heterogeneity of the nervous tissue, the lack of adequate sets of biochemical and genetic markers that can be used to build the network, the complexity of the biological processes at work in these tissues, and the deficiencies of computational methods capable of overcoming these difficulties. Thus, it would be fair to state that, despite some early successes [such as constructing a temporal gene expression map of the developing mouse spinal cord (9)], the identification of genetic networks operating in the nervous system is still in its embryonic stage. Recently, new methods have been proposed to elucidate gene networks based on steady-state expression measurements without prior knowledge of the network structure and function (10), gene coexpression profiling (11, 12), and statistical algorithms to define gene clustering and identify novel regulatory motifs (7).

We have now used some of these emerging methods, and a combination of DNA microarrays, guilt by association (13, 14), and retrospective approaches to identify the components of a gene network that may be involved in the neuroendocrine control of female puberty. The members of this network share the feature of having been earlier identified as involved in tumor suppression/tumor formation. In this report, we propose the initial framework for the concept that tumor-related genes (TRGs) form a functionally interactive network that, operating within neuronal and glial subsets of the hypothalamus, provide one of the system-wide control mechanisms underlying the pubertal activation of GnRH secretion. We also use systems biology approaches to define in silico the putative structure and general viability of the proposed TRG network.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Animals and tissue dissection
The use of nonhuman primates and rats was approved by the Oregon National Primate Research Center (ONPRC) Animal Care and Use Committee in accordance with the National Institutes of Health (NIH) guidelines for the use of animals in research.

Nonhuman primates.
Female rhesus monkeys (Macaca mulatta) were obtained through the Tissue Distribution Program of the Oregon National Primate Research Center. For DNA microarray analysis, we compared five juvenile (8.9 month to 1.8 yr old) with three early pubertal (2–3 yr old) and five midpubertal (3–4 yr old) animals. After euthanizing the animals with a sodium pentobarbital overdose, brain tissues were collected immediately. The medial basal hypothalamus (MBH) was dissected along the posterior border of the optic chiasm, a caudal cut immediately in front of the mammillary bodies, and two lateral cuts along the hypothalamic sulci. The cerebral cortex (CTX) was dissected as a shallow slice along the superior frontal gyrus. The thickness of both tissue fragments was about 4 mm. The tissues were placed in vials containing RNAlater solution (Ambion, Austin, TX) and left overnight at 4 C. The following day, they were frozen on dry ice and stored at –85 C until RNA extraction.

Rats.
Female rats of the Sprague Dawley strain purchased from Charles River Laboratories (Wilmington, MA) were used in these studies. They arrived at the laboratory at 21 d of age and were housed in a room with controlled photoperiod (14 h light, 10 h darkness, lights on from 0500 to 1900 h) and temperature (23–25 C), with free access to tap water and pelleted rat chow.

To determine the global changes in hypothalamic gene expression that may occur at the time of female puberty in this species, animals were euthanized at three different stages, juvenile (25 d of age), early puberty (30–35 d of age), and on the day of the first proestrus (32–37 d of age). According to criteria previously established (15), 25-d-old animals are in the midjuvenile phase of prepubertal development. At this time, the vagina is not yet patent and the uterine weight is 60 mg or less, with no accumulation of intrauterine fluid. Older rats showing a closed vagina, accumulation of intrauterine fluid, and a uterine weight less that 200 mg are considered to be in early puberty [stage previously termed early proestrous (15)]. Finally, rats still exhibiting a closed vagina but showing a uterus ballooned with fluid and a uterine weight of at least 200 mg are considered to be in midpuberty because they had not yet ovulated. This stage corresponds to the phase earlier described as late proestrus, i.e. the phase of puberty when the first preovulatory surge of LHRH and gonadotropins takes place. The first ovulation occurs the following day. All animals were killed between 1600 and 1700 h, and the MBH was immediately dissected, as previously described (16) before freezing the tissue on dry ice.

RNA extraction
Total RNA was extracted using TriReagent (MRC Inc., Cincinnati, OH), according to the manufacturer’s protocol (supplemental material, note 1, published as supplemental data on The Endocrine Society’s Journals Online web site at http://endo.endojournals.org.).

Linear amplification of monkey RNA
To maximize the yield of nonhuman mRNA for array analysis and because of scarcity of the hypothalamic tissue collected from these animals, the monkey RNA samples (both MBH and CTX) were subjected to T7-based linear RNA amplification (17) (supplemental material, note 2). This technique has been extensively validated by others (18, 19). We further determined the linearity of the RNA amplification and determined the absence of bias toward preferential amplification of high-abundance genes (supplemental Fig. 1).

Human cDNA microarrays
Human cDNA microarrays were prepared by the Spotted Microarray core of the Gene Microarray Shared Resource at Oregon Health and Science University, as described in supplemental material, note 3. The arrays were prepared from the I.M.A.G.E. Consortium human cDNA library (Research Genetics, now Invitrogen, Carlsbad, CA). Some information on this library and the specific protocol is available from the SMC Web site (http://www.ohsu.edu/gmsr/smc), and a more extensive data file can be provided on request. Not all clones in the human library are printed on SMC arrays. The array data have been deposited in the National Center for Biotechnology Information’s Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) and are accessible through Gene Expression Omnibus Series (accession no. GSE 8490).

Rat Affymetrix arrays
Microarray assays were performed in the Affymetrix Microarray Core, a unit of the Oregon Health and Science University Gene Microarray Shared Resource using procedures adapted from the Affymetrix GeneChip expression analysis technical manual (revision 3), as outlined in supplemental material, note 3. The array data are accessible through GEO Series (accession no. GSE 8310).

DNA cloning and real-time PCR
A group of monkey genes showing increased expression in the arrays was selected for real-time PCR verification. To generate monkey-specific primers for these assays, total RNA from the MBH and CTX was subjected to RT-PCR amplification to produce 400–550 bp cDNA fragments from each gene selected for analysis. The PCR products were cloned into the pGEM-T vector (Promega, Madison WI), and the cDNAs were sequenced on an ABI 3100 genetic analyzer DNA sequencer (PE Applied Biosystems, Inc., Foster City, CA) using M13 forward and reverse primers. The sequences were analyzed using DNAStar software (DNASTAR, Inc., Madison, WI) and submitted to the GenBank. The accession numbers for these sequences and the primers used for real-time PCR are shown in Table 1Go. The real-time PCR protocol used to quantify mRNAs has been previously described in detail (20, 21), and it is outlined in supplemental material, note 4.


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  		TABLE 1. Sequences of forward (F) and reverse (R) primers and fluorescent probes (P) used for real-time PCR of rhesus monkey TRGs

 
In situ hybridization
To localize the sites of expression of selected genes (FLJ22457, p53, DNMT1, and SASH1) in monkey hypothalamic sections, 35S-uridine 5-triphosphate (UTP)-labeled cRNA probes transcribed from the cDNA templates indicated above were used. The hybridization procedure used was that recommended by Simmons et al. (22) and previously used by us (23, 24). Control sections were incubated with a sense probe transcribed from the same plasmid, but linearized on the 3' end to transcribe the coding strand of the cDNA template. After an overnight hybridization at 55 C, the slides were washed and processed for cRNA detection as described (23, 24). After dehydration in graded alcohol, the slides were air dried and exposed for 72 h to β-max hyperfilm (Amersham, Piscataway, NJ) for initial assessment of the hybridization reaction. Thereafter the slides were dipped in nitroblue tetrazolium salt-2 emulsion and exposed to the emulsion for 3 wk at 4 C. At this time the slides were developed, counterstained with 0.1% thionin, quickly dehydrated in ascending concentrations of alcohol, and coverslipped for microscopic examination.

Network construction
To develop a draft model of a hypothalamic TRG network, we compiled a gene list from our cDNA and Affymetrix microarray experiments, and used guilt-by-association and retrospective approaches to incorporate into this list additional genes encoding either TRGs previously shown to be involved in the control of puberty or TRGs functionally connected to some members of the array-generated gene list. We then searched this expanded gene set for functional similarities between genes and potential modulators of coordinated coexpression. We first analyzed the set referenced to Gene Ontology database (25) annotations, BLOCKS database protein motifs (26), KEGG database and BioCarta pathway data (27), on-line mendelian inheritance in man (28) disease relationships, and other annotations found for the list in the Database for Annotation, Visualization, and Integrated Discovery (http://david.abcc.ncifcrf.gov/). The Database for Annotation, Visualization, and Integrated Discovery system calculates a significance (P value) for the clustering of these functional annotations vs. a reference gene set of identical size for the same species.

To identify the nodes for the transcriptional control network model, we generated a database that includes the mRNA, protein, and genomic sequences (both 10 kb upstream and downstream of each gene) for human, rat, and mouse along with links to EntrezGene (29) and GeneRIF (29) entries. To determine the presence or absence of common RNA level control elements, we scanned our gene set for known micro(mi)-RNA sequences present in and around gene transcripts using two databases: the Sanger miRBase (http://microrna.sanger.ac.uk/sequences/) and the Memorial Sloan Kettering Cancer Center micro-RNA targets database (http://www.microrna.org/). Comparison of proportion of miRNA targets found in the genes with the number of targets in the general population available in the Sanger miRNA database was used to find significantly overrepresented targets in the genes of interest, using Fisher’s exact test and false discovery rate correction in the R package (http://www.r-project.org/).

We refined our transcriptional control network model by limiting visualized interactions to those identified using the TransFac V10.4 database (30). To do this, we examined the genomic DNA sequences 10 kb upstream from the canonical transcription initiation site in the gene set for transcription factor binding sites using MATCH with the minimum false-positive profiles and made directional links among all genes coding for a transcription factor to all genes that contained a binding site for that transcription factor. These networks were visualized in CytoScape (http://www.expasy.org/) and rendered in a hierarchical format revealing organizational patterns.

Identification of transcription factor binding site clustering
After putative transcription factor binding motifs were identified with MATCH, we filtered the list of motifs occurring in our top five most connected genes in the TRG network, as well as OCT2 and TTF1, for the presence of binding motifs for each of these seven genes. After filtering, the list was ordered by position relative to the transcriptional start site for examination of homotypic or heterotypic spatial clustering of motifs that may indicate the presence of cis-regulatory modules and/or cross-regulation of the major TRG and non-TRG network hubs (31).

Statistical analysis
Upon merging the data of the cDNA arrays (OmniViz, Inc., Maynard, MA), the genes showing changes in expression were ranked according to consistency of the change across biological replicates, and genes showing a consistent developmental profile (increase or decrease across puberty) in at least 70% of the biological replicates were selected for further studies. Real-time PCR results are shown as mean ± SEM. Statistical analysis was performed using a one-way ANOVA, followed by the Student-Neuman-Keuls multiple comparison test for unequal replications. The Kruskal-Wallis test was used if normal distributions could not be assumed. Differences were considered significant if P was less than 0.05. The analysis was performed using the Prism program (GraphPad Software, Inc. San Diego, CA).


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
TRG expression increases in the nonhuman primate hypothalamus at the time of female puberty
To determine the changes in gene expression that occur in the female neuroendocrine brain of nonhuman primates at the time of puberty, we performed gene expression profiles on human cDNA microarrays using RNA isolated from the MBH of juvenile, early-pubertal, and midpubertal female monkeys (Macaca mulatta; see Materials and Methods), which had been euthanized for a variety of reasons and were made available through the ONPRC Necropsy Program. The animals were classified in these developmental stages according to well-established criteria (32) and based on the prevailing plasma LH levels (33). The CTX was used as a control tissue. Although this region undergoes important structural changes during adolescence (34), it is not directly involved in the neuroendocrine control of puberty. As such, it can be used to identify developmental changes in gene expression that are specific to the hypothalamus.

After normalization of the array data using the local linear least squares protocol (35), genes showing no differences in expression intensity (absence call) were removed from the analysis. A linear regression analysis of expression intensities observed between arrays comparing hypothalamic RNA from juvenile animals to that of early or midpubertal monkeys demonstrated a high degree of linearity and correlation for the vast majority of genes across low, medium, and high abundance classes of mRNAs (see supplemental Fig. 2).

To identify genes that are differentially expressed at these three developmental stages, genes showing a fold change less than 1.8 times in either direction between juveniles and early pubertal-midpubertal groups were removed from further analysis (36). Thereafter the data were merged using Omniviz software (Maynard, MA), and genes showing a similar expression pattern in early pubertal/midpubertal groups in comparison with juvenile animals were clustered and visualized via a K-means clustering algorithm using J-Express 2.0 software (De Nova, Vancouver, British Columbia, Canada). Genes showing changes in expression were ranked according to consistency of the change across biological replicates, and genes showing a relative consistent developmental profile (increase or decrease across puberty) in at least five of eight biological replicates were selected for further study.

There were 109 genes with increased hypothalamic (but not CTX) expression during puberty meeting this criterion. Analyzing the function of the encoded proteins using the Swiss Prot database (http://www.expasy.ch/), in addition to the GOMiner (http://discover.nci.nih.gov/gominer/) and IHOP (http://www.ihop-net.org/UniPub/iHOP/) tools, showed that 11 of the 109 genes (10%) were TRGs (Fig. 1Go). The changes in expression of each of these genes seen at the time of monkey puberty are shown in Table 2Go. Within this group, six genes were identified as tumor suppressor genes (TSGs), and five as oncogenes (Table 3Go). Based on their known function in oncogenesis or their novelty, four genes were selected for real-time PCR validation of the array results (primers and fluorescence probes listed in Table 1Go): 1) SASH1 (containing SAM And SH3 domains-1), previously shown to be down-regulated in a majority of breast cancer cases (37); like other proteins containing SH3 and SAM domains (including Eph receptors and ETS transcription factors), SASH1 appears to maintain differentiated functions via protein-protein interactions related to signal transduction (37, 38); 2) FLJ22457, encoding an hypothetical protein that belongs to a family of signaling proteins containing a DENN domain (differentially expressed in neoplastic vs. normal cells); some of these DENN-containing proteins are thought to suppress cell proliferation and enhance differentiation by regulating MAPK-dependent signaling pathways (39); 3) CUTL1 (CDP/cux), an evolutionary conserved homeobox gene that functions as a transcriptional repressor in several systems (40); Cutl1-null mutant exhibit a severe reduction in fertility (41) in addition to defects in skin and lung development (41, 42); genetic studies of human breast cancer have implicated CUTL1 as a tumor suppressor gene (43); and 4) CCND1 (cyclin D1), a positive regulator of the start checkpoint in the cell cycle (44); although deregulation of this vital checkpoint in oncogenesis results in unchecked cell growth and division, expression of cyclin D1 in the mature brain is associated with growth factor-dependent neuronal differentiation (45, 46). Noteworthy, there is no previous evidence that SASH1 or the novel gene FLJ22457 are expressed in the brain.


Figure 1
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  		FIG. 1. Physiological processes regulated by 109 genes with increased expression in the hypothalamus of female rhesus monkeys at the time of puberty, as determined by cDNA microarrays. TRGs (tumor-related genes and oncogenes) are overrepresented (10%) when compared with the absence of TRGs showing increased expression at puberty in the CTX, used as a control brain region. The miscellaneous category includes genes encoding proteins involved in cell adhesion, vesicle transport, ubiquitination, response to cellular stress, etc.

 

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  		TABLE 2. TRGs showing increased expression in the hypothalamus, but not the CTX, of female rhesus monkeys at the time of puberty, as determined by cDNA microarrays

 

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  		TABLE 3. Functional annotations of TRGs showing increased expression in the hypothalamus of female rhesus monkeys at the time of puberty

 
The hypothalamic content of each of these mRNAs was significantly greater in the pubertal groups than in juvenile animals, whereas no changes were detected in the CTX across pubertal development (Fig. 2Go), confirming the microarray results. A search of GenBank databases for SASH1- and FLJ22457-related sequences revealed that SASH1 is highly homologous (43% overall homology at the protein level) to a gene called SAMSN1/HACS1 (38, 47, 48), which has extensively conserved SH3 and SAM domains. FLJ22457, on the other hand, was found to have homology with a TSG known as HTS1 (Hela tumor suppression-1) (49) or ST5 (50). Real-time PCR analysis revealed that expression of neither of these two genes increases significantly in the hypothalamus at the time of puberty (data not shown), suggesting that the changes in SASH1 and FLJ22457 gene expression are gene specific.


Figure 2
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  		FIG. 2. The onset of female puberty in nonhuman primates is accompanied by increased expression of the TRGs SASH1 (A), FLJ22457 (B), CUTL1 (C), and CCND1 (D), in the MBH (upper panels) but not the CTX (lower panels), a brain region not directly involved in the neuroendocrine control of sexual development. In this and the following figure: Juv, juvenile; EP, early puberty; MP, midpuberty. The number of animals per group is: MBH Juv, n = 9; MBH EP, n = 5–6; MBH MP = 6–7; CTX-Juv, n = 5; CTX EP, n = 3; and CTX MP, n = 7. *, P < 0.05; **, P < 0.02; and * **, P < 0.01 vs. Juv group. Bars are means, and vertical bars represent SEM.

 
In addition to validating the results of the monkey arrays, we tested the possibility that changes in the expression of these four genes may reflect a more fundamental event taking place in the neuroendocrine brain at the time of puberty, i.e. the enhancement of differentiated functions by a cluster of functionally connected TRGs. Among the genes selected, based on retrospective examination of the literature and guilt-by-association analysis (13, 14), we examined by real-time PCR the expression profile of SynCAM1 (IGSF4), p53, and the DNA methylating enzyme DNMT1. We selected SynCAM1 for analysis because in other studies, we found that protein levels of SynCAM1, an immunoglobulin-like adhesion molecule recently described to play a critical role in synapse assembly (51), were strikingly decreased in the hypothalamus of mutant mice with delayed puberty caused by a defect in astrocytic erbB4 signaling (52). SynCAM1 has been previously described as tumor suppressor in lung cancer-1 (TSLC1) (53, 54); it has also been shown to be inactivated in stomach, lung, and breast tumors by promoter hypermethylation (55, 56). SynCAM1 mRNA abundance increased in the hypothalamus of peripubertal monkeys as compared with juvenile animals (Fig. 3AGo), indicating that, consistent with the loss of SynCAM1 expression detected in mice with delayed puberty, the onset of primate puberty is accompanied by hypothalamic activation of SynCAM1 synthesis.


Figure 3
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  		FIG. 3. The onset of female puberty in nonhuman primates is accompanied by increased hypothalamic expression of the TRGs SynCAM (A) and p53 (B), and decreased expression of DNMT1 (C) in the hypothalamus (upper panels) but not CTX (lower panels) of female monkeys undergoing puberty, as determined by real-time PCR. Bars are means and vertical bars represent SEM. Juv, Juvenile; EP, early puberty; MP, midpuberty. The number of animals per group is: MBH Juv, n = 9; MBH EP, n = 5–6; MBH MP = 6–7; CTX-Juv, n = 5; CTX EP, n = 3; and CTX MP, n = 7. For other details see Fig. 2Go.

 
We next searched for potential changes in p53 mRNA expression. Because p53 plays a central role in maintaining cellular differentiation by regulating the expression of hundreds of downstream genes (57, 58), an increase in its hypothalamic expression during puberty would, almost by definition, imply the existence of a TSG-containing regulatory gene network that contributes to the control of puberty. As shown in Fig. 3BGo, p53 mRNA levels increase in the monkey hypothalamus, but not the CTX, at puberty. Importantly, at the same time when these increases in TSG expression are taking place, the prevalence of DNMT1 mRNA, which encodes the most important enzyme in cytosine methylation-dependent TSG silencing (59), declines in the MBH, but not in the CTX (Fig. 3CGo). The primers and fluorescent probes used are listed in Table 1Go.

Metastasis suppressor genes play an important role in controlling the spread of cancerous cells. Among the eight best characterized metastasis suppressor genes, KiSS1 stands out because of its antimetastatic activity in both breast cancer and melanoma (60, 61). Proteolytic cleavage of the primary product encoded by KiSS1 generates a peptide termed metastin or kisspeptin that is recognized by a G protein-coupled receptor (GPR) known as GPR54 (62, 63). The KiSS1-GPR54 signaling system was recently shown to be a critical component required for the initiation of human and rodent puberty (2, 3) (reviewed in Ref. 64). In a study reported elsewhere (21), we found that the expression of KiSS1 and that of GPR54 increases during monkey puberty, indicating that, as is the case of the TSGs identified by the microarrays, expression of both KiSS1 and its receptor is developmentally regulated and in sync with the initiation and progression of the pubertal process.

TRG expression also increases in the rodent hypothalamus at the time of female puberty
To determine whether changes in TRG expression also occur in the rodent neuroendocrine brain at the time of puberty, we used Affymetrix arrays (Rat Genome 230 2.0) containing 31,000 probe sets that analyze the expression level of more than 28,000 annotated genes to interrogate the female rat hypothalamus during the juvenile-peripubertal transition. The expression of 594 annotated genes was found to increase in the hypothalamus of early pubertal and midpubertal animals in comparison with juvenile rats. From this total, 262 genes had functional annotations (obtained using the IHOP and GOMiner tools). Although there were differences with the monkey data in the relative fraction of genes encoding growth factors, transcription regulators, or proteins involved in immune responses, there was a close agreement in the percentage of genes encoding TRGs (10% in monkeys vs. 8% in rats), and genes encoding proteins involved in signal transduction (8 vs. 10% in rats), cell structure (5 vs. 7%), and metabolism (17 vs. 18%) (Fig. 4Go).


Figure 4
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  		FIG. 4. Physiological processes affected by 262 functionally annotated genes whose expression increases selectively in the hypothalamus at the time of puberty in female rats. As in the case of the monkey hypothalamus, TRGs are overrepresented (8%) when compared with the absence of TRGs showing increased expression in the CTX at puberty.

 
Three prominent members of the TRG group were the transcription factors forkhead box protein P1 (Foxp1), upstream stimulating factor 2 (Usf2), and Ying Yang 1 (YY1). Although the best-known function of Foxp1 is to promote development of the B cell lineage of the immune system (65); it is also expressed in the hypothalamus, in which it functions to increase food intake and body weight, and it is negatively regulated by leptin (66); Usf2 is a member of the evolutionary conserved family of basic-helix-loop-helix-leucine zipper transcription factors (67); recognized by an E-box binding motif present in various gene promoters, it plays an important role in the regulation of gene transcription by recruiting chromatin remodeling enzymes (67). An involvement of Usf2 in the control of reproductive function was recently shown by the finding that Usf2 controls the expression of the FSH receptor gene (68). FSH receptors mediate the actions of the gonadotropin FSH on the hypothalamic-pituitary-gonadal axis. Finally, YY1 affects transcription by recruiting chromatin remodeling enzymes to the promoters of target genes (69). YY1 not only controls the expression of imprinted genes (70) required for hypothalamic development (71, 72) but also up-regulates the promoter activity of Synaptotagmin XI, a candidate gene for susceptibility to schizophrenia (73). Schizophrenia is a neurodevelopmental disorder that becomes clinically evident at the time of puberty (34).

TRG mRNA expression is remarkable in cells of the neuroendocrine brain
The cellular sites of expression of selected TRGs were determined in the monkey and rat hypothalamus by hybridization histochemistry using homologous cRNA probes. The predicted gene FLJ22457 was found to be most abundantly expressed in cells of the periventricular region adjacent to the third ventricle, lateral arcuate nucleus (LARC), and lateral hypothalamus (LH) of female rhesus monkeys (Fig. 5AGo), and rats (not shown). FLJ22457 mRNA transcripts were more abundant in a subpopulation of cells of the LARC (Fig. 5CGo) and the lateral hypothalamus (Fig. 5Go, A, square box labeled LH, and D). No hybridization to a sense probe was detected in adjacent sections (Fig. 5Go, B and E). Higher-magnification images (Fig. 5FGo) showed that FLJ22457 mRNA-positive cells were scattered among both negative cells and cells containing low levels of FLJ22457 transcripts.


Figure 5
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  		FIG. 5. The novel TSG, FLJ22457, is expressed in cellular subsets of the female monkey hypothalamus. The mRNA transcripts were detected by hybridization histochemistry using a 35S-UTP-labeled rhesus monkey-specific FLJ22457 cRNA transcribed from a cDNA template obtained from the monkey hypothalamus by RT-PCR cloning. A, FLJ22457 mRNA is more abundantly expressed in periventricular and LH cell subsets (boxed) than surrounding dorsal and lateral brain regions. B, An adjacent section incubated with a sense RNA shows absence of specific hybridization. C and D, Higher-magnification images showing that FLJ22457 mRNA is abundant in subsets of hypothalamic cells located in the LARC (C) and LH (D). E, Lack of hybridization in an adjacent section incubated with the sense probe. F, The cells enriched in FLJ22457 mRNA in the periventricular region (rectangular box in A) are scattered (arrows) among FLJ22457 mRNA-negative cells and cells with low levels of FLJ22457 transcripts. 3V, Third ventricle; Thal, thalamus. Bars (C–E), 400 µm; (F), 20 µm.

 
As in the case of FLJ22457, cells containing p53 and DNMT1 mRNAs were more abundant in the hypothalamus than in surrounding brain structures (Fig. 6Go, A–F), including the thalamus (dorsal) and the caudate putamen/globus pallidus nuclei (lateral). Some cells appeared to contain particularly abundant levels of these mRNAs (Fig. 6Go, B and E). Examination at higher magnification revealed that these cells have both large nuclei (characteristically seen in neurons; Fig. 6Go, C and F, long arrows) and cells with small, dark nuclei (examples in 6, C and F, denoted by short arrows), indicating that p53 and DNMT1 are expressed in glial cells as well. A similar distribution was seen in the rat hypothalamus (not shown). SASH1 mRNA appeared to be abundant in glial cells of the ventral surface of the brain, endothelial cells adjacent to the external layer of the median eminence (Fig. 6Go, G and H, arrowheads), ependymal cells lining the third ventricle (Fig. 6Go, G and H, short arrows), and neurons of the arcuate nucleus (ARC) (Fig. 6Go, G and H, long arrows) in both monkeys (Fig. 6Go, G– I) and rats (not shown). In the ARC, SASH1 mRNA transcripts appeared to be mostly present in neurons (Fig. 6IGo, arrows).


Figure 6
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  		FIG. 6. The TSGs, p53 and SASH1, in addition to the mRNA encoding DNMT1, the DNA methylating enzyme involved in TSG transcriptional silencing, are expressed in the female monkey hypothalamus. The mRNA transcripts were detected by hybridization histochemistry using 35S-UTP-labeled rhesus monkey-specific cRNAs transcribed from cDNA templates obtained from the monkey hypothalamus by RT-PCR cloning. p53 (A) and DNMT1 (D) mRNAs are more abundant in cells of the hypothalamus than in surrounding dorsal and lateral brain regions. B and E, Closer view of the regions boxed in A and D. C and F, Higher-magnification view showing that p53 and DNMT1 transcripts are abundant in hypothalamic cells that appear to be neurons because of their large cell nuclei (arrows), but they are also expressed in glial cells that have small, dark cell nuclei (short arrows). G and H, SASH1 mRNA is most abundant in cells of the ARC (long arrows) and ependymal cells lining the third ventricle (small arrowheads) as well as in glial cells lining the ventral surface of the brain (arrowheads). I, Most cells expressing SASH1 mRNA transcripts in the ARC have large nuclei (examples denoted by arrows), suggesting that the SASH1 gene is mostly expressed in neurons, respectively. 3V, Third ventricle; Thal, thalamus. Bars (B, E, and H) 400 µm; (C, F, and I), 20 µm.

 
Construction of a TRG regulatory network
The basic mechanisms underlying the onset of puberty are essentially the same in both primates and rodents. Although primates (74), but not rodents (15), exhibit a juvenile hiatus in gonadotropin secretion, puberty is initiated in both cases by a diurnal increase in pulsatile GnRH release, and the activity of GnRH neurons is controlled by the same regulatory neuronal and glial networks (15, 74, 75). Based on these considerations, we examined as a single entity the TRG sets identified by microarrays in both species. Because this combined gene set contains several transcription factors, we reasoned that one or more of these transcriptional regulators may be controlling the expression of a majority of genes in the set and therefore may represent a hierarchy of genes controlling the network via multiple interactions. By definition, these top-level regulators or major hubs should be represented by a few nodes, highly connected to the entire network, but also highly interconnected to each other, providing the network with the necessary degree of biological redundancy (76). To identify these major hubs, we used the TransFac V10.4 database (30) to examine the genomic DNA sequence of each gene 10 kb upstream from the canonical transcription initiation site for sequences recognized by the transcription factors present in the network. Visualization of these interactions using the CytoScape software (77), which allows dynamic exploration of the network, revealed that five genes (CUTL1, USF2, YY1, MAF, and p53) are at the core of the network (Fig. 7AGo). Other transcription factors showing increased hypothalamic expression at puberty, such as STAT6, ATBF1, FOXP1, MEIS1, BHLB2, and PLAGL1, appear to play subordinate roles. Switching the CytoScape representation mode from organic to hierarchical allows one to visualize the hierarchical topography of the network, with the five major hubs clearly in a position of command (Fig. 7BGo). Consistent with the emerging general principles of biological networks (76), the hypothalamic TRG network is composed of a majority of nonconnected genes governed by a few highly connected hubs. The CytoScape rendering also allows visualization of what appears to be a minor subnetwork governed by the transcription factor MEIS1 (Fig. 7BGo, bottom).


Figure 7
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  		FIG. 7. TRGs are organized into a network in the hypothalamus of female rhesus monkeys and female rats undergoing puberty. A, Initial self-organized network (37 member gene set) constructed using the presence of binding sites for transcription factors (TFs) with TRG function within 10 kb of the 5' flanking region of each TRG found to have increased hypothalamic expression at the time of puberty in female monkeys and rats. Connections from genes coding for a TF to genes that contain a binding site for that TF are visualized as arrows. Five TFs were identified as major hubs controlling the network (red circles); other TFs playing more subordinate roles are shown in yellow. B, A hierarchical view of this network revealing tiered organization and identifying five major hubs showing the highest degree of connectivity: MAF, CUTL 1, p53, YY1, and USF2.

 
In previous publications, we provided evidence for the involvement of three transcriptional regulators in the neuroendocrine control of female puberty: OCT2, a Pit-Oct-Unc domain family homeodomain gene (78); TTF1 (33), a member of the Nkx homeodomain gene family; and EAP1 (79), a novel gene containing a really interesting new gene finger domain. To determine whether these genes are connected to the TRG network, we again used the TransFac database to search for TTF1 and OCT2 binding sites in the 5' flanking region of all members of the TRG network. We did not examine EAP1 because it is not known whether EAP1 binds directly to target sequences or it modifies promoter activity via protein-protein interactions. The results of this analysis showed that both OCT2 and TTF1 are highly connected to not only the five TSG main hubs but also most other subordinate members of the network (Fig. 8AGo). Because OCT2 and TTF1 also govern via transcriptional regulation the expression of a larger set of genes, which are not TRGs (Lomniczi, A., H. Wright, H. Dubay, and S. R. Ojeda, unpublished data), it would appear that hypothalamic TRGs are organized into a subnetwork, which is, in turn, hierarchically connected to a larger network(s) via multiple interactions that include its upstream controlling genes.


Figure 8
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  		FIG. 8. A, Hierarchical network view from Fig. 7BGo showing that the major hubs of the TRG hypothalamic gene network are strongly interconnected with TTF1 and OCT2, two non-TRGs found in other studies to be major hubs for a non-TRG gene network. B, Network showing a remarkable degree of interconnectivity between the upper-echelon TRG and non-TRG hubs. With the exception of OCT2, all other genes are subjected to autoregulation (semicircles).

 
To determine whether the five hubs of the TRG network and the non-TRG hubs TTF1/OCT2 are reciprocally connected, we again used the TransFac database to identify the existence of reciprocal binding sites in the 5' flanking region of these genes. As shown in Fig. 8BGo, there is a remarkable degree of interconnectivity among the seven genes. Strikingly, all of them, with the possible exception of OCT2, appear to be autoregulated. Of potential significance is the observation that CUTL1 and MAF are the only members of the group not directly targeted by p53. Additional searches, including potential miRNA or small interfering RNA coding motifs, did not reveal the existence of any overrepresented motifs in the full genomic DNA sequence of the TRG network.

The 5' flanking region of the TRG and non-TRG network upstream genes show a graded degree of heterotypic transcription factor binding site clustering
Examination of homotypic or heterotypic spatial clustering of transcription factor binding motifs in the proximal 3-kb segment upstream from the transcription start site of each TRG and non-TRG network upper-echelon gene revealed that the most heterotypically regulated gene (i.e. regulated proximally by a larger number of other upper echelon genes) is YY1, and the least heterotypically regulated gene is CUTL1 (Fig. 9AGo). Whereas the 5' flanking region of the YY1 gene contains the binding sites for each of the other hub genes within 3 kb of the transcriptional start site, the same region of CUTL1 contains no binding motifs for any upper-echelon gene. Instead, these sites were located upstream from the proximal 3-kb regulatory sequence. The most homotypically regulated gene was USF2 (containing a large cluster of MAF and YY1 binding sites near the proximal promoter) followed by p53 (containing mostly MAF binding sites) and MAF (with two CUTL1 sites and two YY1 sites). Of the two non-TRG genes, OCT2 was the most heavily controlled by the other upper-echelon genes, whereas TTF1 had two CUTL1 and two YY1 binding sites, in addition to a TTF1 binding site (Fig. 9BGo). Thus, it appears that the upper-echelon genes controlling the TRG network are subjected to different degrees and pattern of regulatory complexity.


Figure 9
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  		FIG. 9. Distribution of binding sites in the 5' flanking region of each of the five major hubs controlling the hypothalamic TRG network and two non-TRG genes interconnected with the network. A, The five TRG upper-echelon genes are arranged in ascending order of transcriptional regulatory independence from the other major hubs of the network. This independence is estimated based on the number of binding sites for other upper-echelon genes that are located within 3 kb from the transcription start site of each gene. The most heterotypically regulated gene (YY1) is shown on top, and the least heterotypically regulated gene (CUTL1) is shown last. B, similar arrangement for OCT2 and TTF1, the two non-TRG genes connected to the TRG network. For the sake of simplicity, this arrangement is based on binding sites present within 6 kb upstream of the putative transcription initiation site in each 5' flanking region.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
The results of this study demonstrate the existence of a network of genes that become activated in the mammalian hypothalamus at the time of female puberty. Although we used DNA arrays substantially different to interrogate the monkey and the rat hypothalamus (a limited number of human cDNA probes for monkeys and a comprehensive number of Affymetrix oligodeoxynucleotides probes for rats), the final outcome was similar in both cases: about 10% of the genes showing a hypothalamic-specific pubertal increase in expression were genes previously implicated in tumor suppression or tumor formation. Real-time PCR analysis of genes selected from those with increased expression in the array, genes with similar functions, and genes shown earlier to play a role in the hypothalamic control of puberty, suggests that region-specific activation of TRG expression does not occur in a vacuum, but instead it may constitute a more fundamental process of hypothalamic development associated with the acquisition of female reproductive competence.

In keeping with this notion is the finding that expression of p53, the most versatile TSG of the mammalian genome (80), and DNMT1, a gene required for cytosine methylation-dependent TSG silencing (59), changes in opposite directions in the hypothalamus at the time of puberty, with expression of p53 increasing and that of DNMT1 decreasing. Such a coordinated change in expression suggests the existence of epigenetic cues that, acting at more than one level of control, facilitate the hypothalamic expression of TRGs during the acquisition of reproductive maturity. Because each of these genes, including p53, participates in the physiological control of cellular processes during normal development, it is plausible that activation of their expression might be entirely dissociated from their tumor suppressor activities. However, the possibility also exists that as genes with tumor-promoting activity, such as those identified here, or others, that like erbB1 and erbB2 (4), become activated at puberty in the presence of hormonal influences (e.g. estrogen) favoring cell proliferation, there is a concomitant up-regulation of TSG expression to maintain the developmental process focused on differentiated functions, rather than on proliferative activity.

This notion may be at odds with the concept that the p53 gene network (and by inference other TSGs) is normally off, becoming activated only when the cells are stressed or damaged (58). Instead, our results suggest that coordinated activation of TRG expression does occur under physiological conditions and that TRGs may play a role in facilitating the attainment of specific developmental landmarks. Our results also indicate that attainment of reproductive capacity is one of the developmental events influenced by TRGs and that TRGs act within the hypothalamus, the brain region that controls the pubertal process, to exert their regulatory effects. The importance of TRGs in the control of the pubertal process was hinted by the loss of SynCAM1 expression in mice with delayed puberty (52) and made evident by the critical importance of the KiSS1/GPR54 signaling system in the control of human, nonhuman primate, and rodent puberty (2, 3, 21) (reviewed in Ref. 64). In close similarity to the changes in hypothalamic TSG expression we now report, expression of the KiSS1 gene was earlier shown to increase at the time of puberty in both rodents and nonhuman primates (21, 81).

Of interest is the finding that a well-conserved fraction (10%) of genes overexpressed in the hypothalamus of monkeys and rats at puberty is composed of TRGs, but the identity of individual genes is dissimilar. This discrepancy may be partially explained as due to methodological differences, such as array specificity (human/monkey vs. rat/rat) (82, 83); array completeness (8,500 vs. >30,000 probes); and physiological stages (elevated midpubertal LH secretion in monkey vs. midpubertal preovulatory LH levels in the rat). Nevertheless, the recent demonstration of a significant divergence in tissue-specific transcriptional regulation between humans and mice (84) suggests that the differences observed may also have biological bases.

The use of computational tools allowed us to demonstrate that the TRGs showing increased hypothalamic expression form a functionally related network and that this relationship is provided by cis-regulatory interactions exerted by selected members of the network with transcriptional regulatory capacity. Although the network contains 12 genes encoding transcription factors, only five of them have a degree of connectivity with the rest of the genes that identifies them as major hubs of the network. Interestingly, p53 does not appear to constitute a major hub. Instead, it forms part of a hierarchy of transcription factors that include CUTL1, MAF, YY1, and USF2. Analysis of the distribution of binding sites for each member of this hierarchy along the 5' flanking region of each member of the group suggests that CUTL1 is the gene most likely to function with a greater degree of independence from the other main hubs of the network because no binding sites for any of the other upper-echelon genes were found within 3 kb upstream from its transcription start site. It must be pointed out, however, that CUTL1 expression may still be controlled by the other members of the TRG hierarchy via sites located upstream from the proximal 3 kb because significant transcriptional regulation can occur via binding sites located at distances from the transcription start site much longer than 3 kb (85).

Further computational analysis of experimentally defined transcription factor binding sites (using the TransFac database) revealed that the TRG network is a subnetwork linked via cis-regulatory interactions with two non-TRGs, previously shown to play a role in the neuroendocrine control of female puberty, OCT2 (78) and TTF1 (33). This association brings up the issue of how relevant a cis-regulatory TRG network is to the overall neuroendocrine control of the pubertal process. The organization of the TRG network according to the general principles of complex biological networks, i.e. having a few, highly connected nodes playing a central role (76, 86), predicts that such hubs are essential for the functional integrity of the network (86, 87). Although not formally tested here, the results of studies dealing with two main hubs connecting the TRG with a non-TRG regulatory network are consistent with this prediction. Male mice carrying a targeted deletion of the Cutlike1 gene are infertile (41), and female mice subjected to conditional, Cre/loxP-mediated deletion of the Ttf1 gene from neurons (33) have delayed puberty, disrupted reproductive cyclicity, and a shortened reproductive life span by a mechanism involving loss of transcriptional control of at least one subordinate TRG (KiSS1).

Knockout (KO) models have also been generated for the other upper-echelon genes governing the TRG network: p53 (88), YY1 (89), c-MAF (90, 91), and USF2 (92), but these animals have not been informative in regard to reproductive phenotypes. Whereas YY1 KO mice die in early embryonic life, c-MAF KOs have been analyzed only during fetal life for defects in lens development. Mice lacking p53 and USF2 are reported to reproduce, but as it is usually the case for gene KOs intended to disrupt nonreproductive systems, no efforts have been made to determine whether these animals have deficiencies in reproductive capacity (which would be expected to be partial due to the redundancy of the network). Cutlike1 male KOs are infertile, but surprisingly, a female reproductive phenotype has not been characterized (41).

Our results do not answer a number of important questions, such as the cell and temporal context in which the hypothalamic TRG network becomes activated; the composition of the network in different populations of neurons and glial cells; the influence that metabolic and steroid signals may have on the functional capacity of the network during developmental milestones, such as puberty and menopause; and finally whether the greater impact of the network’s activation is exerted directly on GnRH neurons and/or via neuronal/glial populations functionally connected to these cells. Although it would appear unlikely that the full network operates in every cell of the hypothalamus, the five central nodes might conceivably be expressed in both glia and neurons, in which they would regulate not only the transcription of similar subordinate genes but also that of subordinate genes that are specifically expressed in particular neuronal and glial subsets. In addition to not providing an answer to these questions, the inferred network does not take into consideration protein-protein interactions that may be crucial to explain how KiSS1 can play such a decisive role in the control of puberty and yet not be directly involved in coordinating cis-regulatory control. It is also possible that KiSS1 plays an important role in controlling the network via cis-regulatory mechanisms activated by GPR54-dependent signaling. These mechanisms, if present, would have escaped detection by our study. Recognizing these drawbacks, in addition to those derived from the lack of more precise systems biology approaches to analyze complex mammalian cellular systems (93), our study provides for the first time evidence supporting the existence of a genetic network that operating within the neuroendocrine brain contributes to the control of a complex physiological process. Although imperfectly characterized, the TRG network we describe fulfills the fundamental requirements of gene-regulatory networks, such as the existence of a few major hubs controlling a gene set, a preferential interaction between these hubs, and the existence of a majority of less connected genes under the control of the major hubs of the network (8, 76, 94). Systems biology is based on iterative approaches, which should allow one to not only test experimentally the predictions of this first model but also provide cellular and temporal depth to the network. The observation of a highly conserved increase in expression of genes involved in cellular metabolism (17% in monkeys and 18% in rats) offers an additional avenue of research because metabolic networks are likely to work in coordination with transcriptional networks in the control of cellular functions.

For many years it has been assumed that the hypothalamic control of sexual maturation, a process critical for the preservations of our species, should be endowed with the highest degree of redundancy and combinatorial control. The remarkable degree of interconnectivity displayed by the major hubs of the hypothalamic TRG network, and their surprisingly strong interconnectivity with upstream members of a non-TRG network, suggests that the neuroendocrine control of female sexual development is exerted by a number of interactive hypothalamic regulatory networks organized to maintain a high degree of intra- and intercombinatorial redundancy.


   Acknowledgments
 
Hypothalamic sections for hybridization histochemistry were kindly provided by Dr. Cynthia Bethea (ONPRC). We thank Maria E. Costa for performing the in situ hybridization experiments.


   Footnotes
 
This work was supported by National Institutes of Health Grants HD050798, HD25123, MH65438, and U54 HD18185 through cooperative agreement as part of the Specialized Cooperative Centers Program in Reproduction and Infertility Research, National Institute of Child Health and Human Development/NIH, and Grant RR00163 for the operation of the Oregon National Primate Research Center (to S.R.O.), German Research Foundation DFG Grant RO 2220/3-1 (to C.L.R.), HE3151/3-1 (to S.H.), and European Society for Pediatric Endocrinology (to H.J. and C.L.R.).

Present address for C.L.R.: Children’s Hospital and Regional Medical Center, University of Washington, Seattle, Washington. Present address for C.M.: Department of Psychiatry, University of Miami, Miami, Florida 33101. Present address for R.C.: Laboratorio de Investigaciones Neuroquimicas y Endocrinas, Universidad de Cuyo, Mendoza, Argentina. Present address for A.E.M.: Department of Neuroscience, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104. Present address for S.H.: Department of Pediatric Endocrinology, Childrens Hospital Bult, Janusz-Korczak-Allee 12, 30173 Hannover, Germany. Present address for H.J.: Lilly Germany GmbH, Medical Department, Endocrinology D-61350 Bad Homburg, Germany.

Disclosure Statement: The authors have nothing to disclose.

First Published Online July 5, 2007

Abbreviations: ARC, Arcuate nucleus; CTX, cerebral cortex; GPR, G protein-coupled receptor; KO, knockout; LARC, lateral arcuate nucleus; LH, lateral hypothalamus; MBH, medial basal hypothalamus; ONPRC, Oregon National Primate Research Center; TRG, tumor-related gene; TSG, tumor suppressor gene; UTP, uridine 5-triphosphate.

Received May 14, 2007.

Accepted for publication June 22, 2007.


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 Introduction
 Materials and Methods
 Results
 Discussion
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Converging at Puberty's Hub
Endocrinology, November 1, 2007; 148(11): 5145 - 5146.
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