Schizophrenia genomics
Larry H. Bernstein, MD, FCAP, Curator
LPBI
Histone Methylation at H3K9; Evidence for a Restrictive Epigenome in Schizophrenia
Schizophrenia is conceptualized as a disorder of gene transcription and regulation. Consequently, chromatin is the ideal scaffold to examine this manifested pathophysiology of schizophrenia, as it constitutes the interface between the underlying genetic code and its surrounding biochemical environment. Through post-transcriptional modifications of histone proteins, gene expression can be either transcriptionally active in a ‘euchromatic’ environment, temporarily quieted in ‘facultative heterochromatin,’ or completely silenced in ‘constitutive heterochromatin’ (Zhang and Reinberg 2001). Post-translational modifications to lysine 9 of the H3 protein (H3K9) are uniquely able to reflect these three levels of transcriptional regulation. H3K9 modifications located in the promoter regions of actively transcribed genes are often acetylated (H3K9acetyl). Conversely, quieted transcription in gene-rich areas of the genome are often associated with mono- or dimethyl H3K9 (H3K9me2), while completely silenced areas of the genome are associated with trimethylated H3K9 (H3K9me3). In particular, the formation of H3K9me2 is catalyzed by histone methyltransferases (HMTs), including Eu-HMTase2 (G9a), Eu-HMTase1 (GLP), and SETDB1 (Krishnan et al. 2011) The different degrees of lysine methylation are possible due to the cooperation of these HMTs, which are able to form large heteromeric complexes (Fritsch et al. 2010).
H3K9 methylation has not been extensively studied in the brain, and until recently the regulation and role of the enzymes responsible for its formation were not known. Postnatal, neuronal-specific GLP/G9a knockdown produces a significant decrease in global H3K9me2 levels and inappropriate gene expression, leading to deficits in learning, reduction in exploratory behaviors and motivation in mice (Schaefer et al. 2009; Shinkai and Tachibana 2011;Tachibana et al. 2005;Tzeng et al. 2007). In humans, deletions or loss-of-function mutations of G9a results in Kleefstra Syndrome, characterized by a severe learning disability and developmental delay (Nillesen et al. 2011; Kleefstra et al. 2005). In humans, increased SETDB1 mRNA expression and resultant elevated H3K9me3 levels have been documented in Huntington Disease (HD) (Ryu et al. 2006; Fox et al. 2004).
A hallmark of schizophrenia is aberrant gene regulation, with the vast majority of studies reporting a down-regulation of gene transcription, suggesting that the epigenome of patients with schizophrenia is restrictive (Akbarian et al. 1995;Guidotti et al. 2000;Fatemi et al. 2005; Impagnatiello et al. 1998; Jindal et al. 2010). Postmortem brain studies indicate a reduction of an open histone modification, H3K4me3, and elevated expression of the histone deacetylase HDAC1 mRNA expression (Cheung et al. 2010; Sharma et al. 2008). The use of peripheral blood mononuclear cells as a reflection of overall chromatin state or at particular gene promoters has been successfully implemented in clinical studies of subjects afflicted depression, alcoholism, and schizophrenia. Peripheral blood cell studies have indicated that schizophrenia is associated with an abnormally condensed chromatin structure; (Issidorides et al. 1975; Kosower et al. 1995) specifically increased restrictive H3K9me2 and reduced H3K9 acetylation (Gavin et al. 2009b). Additionally, H3K9 acetylation in schizophrenia patients is less responsive to in vivo treatment with HDAC inhibitors when compared to both patients with bipolar disorder and nonpsychiatric controls (Sharma et al. 2006;Gavin et al. 2008). Finally, a correlation exists between age of onset of psychiatric symptoms of schizophrenia and baseline levels of H3K9me2 (Gavin et al. 2009b). It is the hypothesis of this paper that schizophrenia can be characterized by a restrictive epigenome, which is observable in both brain and peripheral blood, and has specific and observable effects on psychopathology. We have focused on levels of H3K9me2, indicative of facultative heterochromatin, and the enzymes that catalyze this modification, in patients with schizophrenia to examine their role in this illness.
3.1. mRNA Levels of HMT Gene Expression
We performed a multiple linear regression with each HMT gene of interest as the dependent variable. For postmortem brain tissue we examined sex, age, pH, RIN and diagnosis, whereas for lymphocytes we examined sex, age, and diagnosis as explanatory variables. In these two cohorts, we found that a diagnosis of schizophrenia is a significant predictor for GLP mRNA expression in both postmortem brain samples (β=0.44, F(1,24)=5.80, p<0.05), and in lymphocytes (β=−0.41, F(1,40)=7.91, p<0.01), indicating that patients with schizophrenia demonstrated increased levels compared to nonpsychiatric controls (Fig. 1a). Similarly, a diagnosis of schizophrenia is also a significant predictor for increased SETDB1 mRNA levels in both postmortem brain samples (β=0.39, F(1, 24)=4.33,p<0.05), and in lymphocytes (β=0.37, F(1,40)=6.19, p<0.05; Fig. 1b). A diagnosis of schizophrenia is not a significant predictor for elevated G9a mRNA levels in postmortem brain samples (β=0.22, F(1,24)=1.22, p=ns), but is for lymphocytes (β=−0.317, F(1,40)=4.46, p<0.05; Fig. 1c).
Interestingly, in both postmortem tissue (r=0.79, p<0.001) and lymphocytes (r=0.54, p<0.001), GLP and SETDB1 mRNA expression are positively correlated (data not shown).
To establish whether there exist differences in HMT mRNA among schizophrenic patients taking psychotropic medication, and those who were not, we performed a second multiple linear regression analysis on each individual cohort. The overall or type-specific use of antipsychotic, antidepressant or mood stabilizing medication are not significant predictors of HMT mRNA levels in either the postmortem or the lymphocyte cohorts.
3.2. H3K9me2 levels in the Postmortem Brain
In a previously published study we documented elevated global H3K9me2 levels in lymphocytes obtained from schizophrenia patients compared to nonpsychiatric controls (Gavin et al. 2009b). In the current study we attempted to discern whether this abnormality in a restrictive histone modification is present in brain tissue from the SFNC cohort as well. We performed a multiple linear regression with H3K9me2 levels as the dependent variable, with sex, age, and diagnosis as explanatory variables. We found that diagnosis of schizophrenia is a significant predictor of H3K9me2 levels extracted from postmortem brain tissue (β=0.40, F(1,24)=4.58, p<0.05; Fig. 2). GLP (r=0.65, p<0.001) and SETDB1 (r=0.44,p<0.05) are positively correlated with H3K9me2 levels, as discovered through a Pearson Correlation (data not shown).
Lymphocyte levels of G9a mRNA demonstrated a positive correlation with the PANSS negative subscale total (r=0.61, p<0.05; Fig. 3a), GLP mRNA is positively correlated with the PANSS general subscale total, (r=0.64, p<0.01; Fig. 3b), and SETDB1 mRNA is more highly expressed in patients with longer durations of illness compared to both normal controls and patients in the ‘first episode psychosis’ group (ANOVA, F(2,30)=3.66, p<0.01; Fig. 3c). Patients with a family history of schizophrenia also had significantly increased levels of lymphocyte SETDB1 mRNA (t18=2.52, p<0.05; Fig. 3d).
The current paper demonstrates an increase in GLP and SETDB1 mRNA in both postmortem parietal cortex and lymphocyte samples from patients with schizophrenia, as well as an increase in G9a mRNA in lymphocytes. G9a and GLP are responsible for the bulk of H3K9me2 modifications across the genome (Shinkai and Tachibana 2011; Tachibana et al. 2005), and SETDB1 is the only euchromatic HMT to specifically di- and tri-methylate H3K9 (Zee et al. 2010;Wang et al. 2003), but all three of these HMTs are able to form large heteromeric complexes, thus allowing for the sequential degrees of lysine methylation (Fritsch et al. 2010). Further, we demonstrate that the ultimate outcome of their catalytic activity, H3K9me2, is significantly increased in patients with schizophrenia as compared to nonpsychiatric controls. Moreover, GLP and SETDB1 mRNA are positively correlated with H3K9me2 levels. These findings add gravity to our previous demonstration of increased H3K9me2 levels in lymphocytes from schizophrenic patients (Gavin et al. 2009b).
Our investigations into the role of H3K9me2 in schizophrenia pathophysiology, as opposed to other H3K9 modifications, were motivated by the hypothesis that initial inactivation of gene promoter activity at various schizophrenia candidate genes can result in gradual entrenchment of the heterochromatin state as a result of disease chronicity and disuse (Sharma et al. 2012). Areas of H3K9me2 can then act as a platform for additional restrictive adaptors, thus resulting in the spreading of heterochromatin across previously unmodified gene rich areas. As such, the gene altering effects of medications are unable to overcome this restrictive burden, leading to repeated medication failures (Sharma et al. 2012). Support for this hypothesis has been previously demonstrated, (Sharma et al. 2008; Benes et al. 2007) including the finding that schizophrenia patients clinically treated for four weeks with the HDAC inhibitor, valproic acid, displayed no increase in peripheral blood cell acetylated histones 3 or 4 as compared to bipolar patients (Sharma et al. 2006). Here, we find an increase in both H3K9me2 levels and the enzymes which catalyze this modification, providing additional evidence supporting an increased heterochromatin state in schizophrenia.
The major role of the parietal cortex is to integrate and evaluate sensory information (Andersen & Buneo, 2003; Cohen & Andersen, 2002). It is one of the last areas of the human brain to fully mature, (Geschwind, 1965) thus early life environmental insults could have a profound effect. Disordered thought, a common symptom in schizophrenia, is most likely explainable through disruption of this system (Torrey, 2007). Patients with schizophrenia report either acute (McGhie & Chapman, 1961) or blunted (Freedman, 1974) sensitivity to sensory stimuli, and demonstrate overall impairment of sensory integration (Manschreck & Ames, 1984; Torrey, 1980). Similar patterns of transcriptional regulation are observed across the cortex, consequently, results from the parietal cortex likely reflect patterns of gene transcription in other brain regions (Hawrylycz et al., 2012).
Due to its heterogeneity, examining schizophrenia as a binary measurement of illness when examining biological relevancy can be limiting (Arango et al. 2000;Buchanan and Carpenter 1994). Through utilizing the PANSS, biological underpinnings that do not demarcate cleanly with diagnostic categories, can be correlated directly with specific symptomatology. Correlations between methyltransferase enzymes and clinical symptomatology indicate that these restrictive enzymes could contribute to specific facets of the illness, particularly negative and general symptoms, which are particularly resistant to improvement. Increased severity of negative symptoms are correlated with poorer disease prognosis, (Wieselgren et al. 1996) and are not alleviated through our current regimen of psychotropics.
Additionally, SETDB1 mRNA levels are also correlated with other markers of a worse disease prognosis, including a more chronic form of the illness, and a history of schizophrenia in the family. Pharmacological targeting of increased levels of SETDB1improves motor performance and extends survival in HD mice, indicating the promise of treatments that modulate gene silencing mechanisms in neuropsychiatric disorders (Ryu et al. 2006).
The main weakness of this current study was that clinical symptoms were correlated with mRNA extracted from peripheral tissue. Enzymes relating specifically to synaptic function were not examined, but rather overall mechanisms of epigenetic regulation that are not tissue specific. While postmortem investigations are able to serve as a useful snapshot at the time of death, the ability to measure and monitor histone marks over time as marker of disease progression, improvement, or as a predictor of pharmacological response are only possible using peripheral blood cells. A strong rationale for the use of blood chromatin ‘levels’ as a type of biosensor that registers the epigenetic milieu has been proposed elsewhere (Sharma 2012). Furthermore, previous studies have indicated the mRNA patterns of expression patterns in lymphocytes are capable of distinguishing between psychiatric diagnostic groups (Middleton et al. 2005).
The present study hypothesized that schizophrenia may be due to abnormal regulation of fundamental epigenetic mechanisms, thus, we chose to measure overall levels of H3K9me2 opposed to specific gene promoters, based on the assumption that while the individual genes silenced in the brain and blood may not be the same, similar global pathogenic processes may be occurring in both tissues.
The results of this paper indicate that chromatin is more restrictive in patients with schizophrenia, and may be significantly contributing to disease pathology. If, through pharmacological interventions, a reduction in this histone hyper-restrictive insult in schizophrenia can be relaxed, inducing a type of “genome softening,” then neuronal gene expression can be enhanced, thus allowing for increased plasticity and improved therapeutic response (Sharma 2005).
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Balancing Histone Methylation Activities in Psychiatric Disorders
Schizophrenia and depression are major psychiatric disorders that lack consensus neuropathology and, in a large majority of cases, a straightforward genetic risk architecture. Furthermore, many patients on the mood and psychosis spectrum show an incomplete response to conventional pharmacological treatments which are mainly aimed at monoamine signaling pathways in the brain (Box 1).
However, there is evidence that dysregulated gene transcription, indicative of compromised neural circuitry, contributes to disordered brain function in psychosis and mood spectrum disorder [1, 2]. While no single gene transcript is consistently affected, alterations in RNA levels contribute to defects in GABAergic inhibitory neurotransmission and more generally, synapse organization and function, metabolism and mitochondrial functions, and oligodendrocyte pathology [3–5]. While a number of transcriptional and post-transcriptional mechanisms may contribute to these changes, chromatin-associated proteins and epigenetic regulators invoked in sustained alterations of gene expression and function (Box 2) could play a critical role in the pathophysiology, or treatment of mental illness [6,7]. Indeed, there is evidence that changes in acetylation of histone lysine residues, which are broadly associated with active gene expression [8] and considered a potential therapeutic target for cancer and other medical conditions [9], also impact gene expression patterns in the brain and thereby influence emotional and cognitive functions. For example, mice or rats exposed to systemic treatment, or localized intracranial injections of class I/II histone deacetylase inhibitors (HDACi) exhibit behavioral changes reminiscent of those elicited by conventional antidepressant drugs [10–13]. The short chain fatty acid derivative valproic acid, widely prescribed for its mood-stabilizing and anticonvulsant effects, induces brain histone hyperacetylation at a select set of gene promoters when administered to animals at comparatively high doses [14]. Conversely, overexpression of selected HDACs in neuronal structures implicated in the neurobiology of depression, including the hippocampus, elicit a pro-depressant behavioral phenotype [12]. Similarly, animals treated with class I/II HDACi often show improved performance in learning and memory paradigms and furthermore, drug-induced inhibition or activation of class III HDAC (also known as sirtuins) elicits changes in motivational and reward-related behaviors [15]. Therefore, the orderly balance between histone acetyl-transferase and deacetylase activities is critical for cognitive performance and synaptic and behavioral plasticity [16]. Likewise, However, HDACs interfere with acetylation of many non-histone proteins in the nucleus and cytoplasm [16], and moreover, some of these drugs carry a significant side effect burden [9]. Therefore, in light of the emerging role of epigenetic mechanisms in the neurobiology of these and other psychiatric conditions [6], the therapeutic potential of chromatin modifying drugs, other than the HDACi, warrants further investigations. This review will focus on histone lysine methylation, one of the most highly regulated chromatin markings in brain and other tissues. Multiple methyltransferases (KMTs) and demethylases (KDMs) were recently implicated in emotional and cognitive disorders (Fig. 1), and these types of chromatin modifying enzymes could emerge as novel targets in the treatment of mood and psychosis spectrum disorders.
The methylation of lysine and arginine residues, like other histone PTM, define chromatin states and function [8, 17]. To date, more than 20 methyl-marks on K and R residues have been described [18, 19]. As it pertains to the lysines, the majority of studies focused on the regulation and methylation-related functions of six specific sites: H3K4, H3K9, H3K27, H3K36, H3K79 and H4K20 [18]. For H3K4 and H3K9/K27, there is additional complexity because specific information is also conveyed (i) for H3K4, the unmethylated lysine effectively serving as a DNA methylation signal [20, 21], and (ii) for H3K9/K27 acetylation as an alternative PTM [22, 23] (Fig. 1A). For the aforementioned H3/H4 residues, specific biological functions and their interrelations with functional chromatin states, including transcriptional initiation and elongation, heterochromatic silencing and other mechanisms, have been described for the trimethyl-, and for some of the mono- and dimethyl-modifications (Representative examples are provided in Fig. 1B. See ref [17] for a detailed description of the histone methylation code and its relation to other types of histone PTM).
The following examples further illustrate the complex regulation of histone lysine methylation. Monomethylation of histone H3-lysine 4 (H3K4me1) plays an important role in neuronal activity-induced transcription at enhancer sequences [24], but the related forms, H3K4me3/2 are primarily found at the 5′ end of genes, with H3K4me3 mostly arranged as distinct and sharp peaks within 1–2Kb of transcription start sites. The H3K4me3 mark provides a docking site at the 5′ end of genes for chromatin remodeling complexes that either facilitate or repress transcription [25]. Furthermore, mono-methyl-H4-K20 shows strong positive correlation with gene expression at promoters enriched with CpGs, which contrasts to the trimethylated form of the same residue which generally is associated with repressed chromatin [23]. Taken together, these examples illustrate that even closely related histone lysine methylation markings are potentially associated with very different chromatin states.
To date, H3K4, H4K9, H3K27 and H4K20 methylation signals were measured at specific loci and genome-wide in human brain, essentially confirming that each of these epigenetic markings defines the same type of chromatin as in the peripheral tissues or animal brain [26–30]. Interestingly, a subset of psychotherapeutic drugs including the mood-stabilizer valproate, the atypical antipsychotic clozapine and some monoamine oxidase inhibitors and stimulant drugs interfere with brain histone methylation (Table 1).
Molecular mechanisms of histone (lysine) methylation
A complex system of site-specific methyltransferases, which transfer the methyl-group of S-Adenosyl-Methionine (SAM) to lysine residues, has evolved in the vertebrate cell. There are an estimated 70 human genes harboring the Su(var)3–9,Enhancer of Zeste,Trithorax (SET) domain, which spans approximately 130 amino acids essential for KMT enzymatic activity [31]. The only known exception is the H3K79-specific methyltransferase, KMT4/DOT1L [31, 32], which lacks a SET. Each of the histone K residues discussed above is the preferential target of a distinct set of methyltransferase proteins (Fig. 1A)[19]. Of note, these histone-modifying enzymes are thought not to access histone substrates directly unless recruited by DNA-bound activators and repressors, a mechanism which could target each methyltransferase to a highly specific set of genomic loci [19].
An equally complex system exists for the site-specific lysine demethylases (Fig. 1A). There are at least two different mechanisms for active histone demethylation. The first enzyme type, represented by lysine-specific demethylase 1 (LSD1/KDM1A), contains an amine oxidase domain and requires flavin adenine dinucleotide (FAD) as a cofactor to demethylate di- and mono-methylated lysines. LSD1 and its homologue, LSD2, are primarily H3K4 demethylases, albeit depending on species and context, and activity against H3K9 also has been described [18]. Interestingly, monoamine oxidase inhibitors (MAOi) such as tranylcypromine or phenelzine — powerful antidepressants that exert their therapeutic effects mainly by elevating brain monoamine levels through inhibition of MAO-A/B — also block LSD1 type histone demethylases [18]. While LSD1 is thought to regulate histone methylation at promoters, LSD2 is bound to transcriptional elongation complexes and removes H3K4 methyl markings in gene bodies, thereby facilitating gene expression by reducing spurious transcriptional initiation outside of promoters [33]. The second type of demethylase, which in contrast to LSD1/LSD2 is capable of demethylating trimethyl markings, involves Fe2+-dependent dioxygenation by Jumonji-C (JmJC) domain-mediated catalysis [18]. Given that each of the KMTs and KDMs described has a different combinatorial set of functional domains and (protein) binding partners [18, 34], it is likely that the various site-specific methyltransferases and demethylases are largely non-redundant in function.
An increasing number of KMTs and KDMs are implicated in neurodevelopment and major psychiatric diseases (marked in red in Fig. 1A).
H3K4
The first histone lysine methyltransferase explored in the nervous system was KMT2A/MLL1, a member of the mixed-lineage leukemia (MLL) family of molecules. Mice heterozygous for an insertional (lacZ) loss-of-function Mll1mutation show distinct abnormalities in hippocampal plasticity and signaling [35], in conjunction with defects of learning and memory [36]. Of note, the hippocampus, and other portions of the forebrain including prefrontal cortex and ventral striatum, are frequently implicated in the neural circuitry of mood and psychosis spectrum disorders [1]. Furthermore, conditional deletion of Mll1resulted in defective neurogenesis during the early postnatal period [37]. While the full spectrum of MLL1 target genes in neurons and glia awaits further investigation, dysregulated expression of certain transcription factors such as DLX2, a key regulator for the differentiation of forebrain GABAergic neurons (which are essential for inhibitory neurotransmission and orderly synchronization of neural networks) [38], may contribute to the cognitive phenotype of the Mll1mutant mice. These observations may be relevant for the pathophysiology of schizophrenia, because some patients show in the prefrontal cortex a deficit in H3K4-trimethylation and gene expression at a subset of GABAergic promoters, including GAD1 encoding a GABA synthesis enzyme [28]. While the timing and age-of-onset for this ‘molecular lesion’ remains unknown, it is of interest that in the normal PFC, H3K4 methylation at the site of GABAergic genes progressively increases during the transition from fetal period to childhood to adulthood [28]. The epigenetic vulnerability of the Gad1 promoter during such prolonged developmental periods is further emphasized by recent animal studies demonstrating that Gad1-DNA methylation and histone acetylation are heavily influenced by the level of maternal care in the neonatal period/pre-weanling period [39].
There is additional evidence that epigenetic fine-tuning of the brain’s H3K4 methyl-markings is critical for orderly neurodevelopment. Of note, loss-of-function mutations in KDM5C/JARID1C/SMCX, an X-linked gene encoding a H3K4 demethylase, have been linked to mental retardation [40] and autism spectrum disorders [41]. The KDM5C gene product operates in a chromatin remodeling complex together with HDAC1/2 histone deacetylases and the transcriptional repressor REST, thereby poising neuron-restrictive silencer elements for H3K4 demethylation and decreased expression of target genes including synaptic proteins and sodium channels [40]. However, because this study was conducted with the HeLa cell line, it remains to be determined whether similar mechanisms operate in the nervous system.
In addition to its role in neurodevelopment, MLL-mediated H3K4 methylation could play a potential role for the treatment of psychosis. The atypical antipsychotic clozapine, which has a somewhat higher therapeutic efficacy when compared to conventional antipsychotics that function primarily as dopamine D2 receptor antagonists [42], upregulates H3K4 tri-methylation at the Gad1/GAD1GABA synthesis enzyme gene promoter. These effects were not mimicked in dopamine receptors D2/D3 (Drd2/3) compound null mutant mice, suggesting that blockade of dopamine D2-like receptors is not sufficient for clozapine-induced H3K4 methylation [28]. In the human PFC, GAD1-associated H3K4 methylation was increased in subjects exposed to clozapine, as compared to subjects treated with conventional antipsychotics. Conversely, mice heterozygous for the H3K4-specific KMT, mixed-lineage leukemia 1 (MLL1), exhibited decreased H3K4 methylation at brain Gad1 [28]. Therefore, it is possible that MLL1, which is highly expressed in GABAergic and other neurons of the adult cerebral cortex [28], will in the future emerge as a novel target for the treatment of psychosis. Questions that remain to be resolved include (i) the molecular pathways linking clozapine — a drug that impacts dopaminergic, serotonergic, muscarinic and other signaling pathways — to MLL1-mediated histone methylation, and (ii) whether or not the clozapine-induced changes in H3K4 methylation are restricted to GABAergic gene promoters or, alternatively, the reflection of more widespread epigenetic changes throughout the genome. Of note, clozapine’s effects on H3K4 methylation require intact brain circuitry and cannot be mimicked in cultured neurons differentiated from forebrain progenitor cells [43]. This finding is in good agreement with the recent observation that some of clozapine’s therapeutic effects require an intact serotonergic system, particularly its presynaptic components [44].
H3K9
The 9q34 subtelomeric deletion syndrome, which includes mental retardation and other developmental defects, is caused by deleterious mutations and haploinsufficiency of euchromatin histone methyltransferase 1 (EHMT1, also known as GLP and KMT1D) [45]. This gene encodes a H3K9-specific methyltransferase that operates in a multimeric complex that includes its closest homologue, G9a/KMT1C, and additional H3K9-specific HMTs [46]. Studies in mutant mice suggest that the GLP/G9a complex is important for suppression of non-neuronal and progenitor genes in mature neurons, and loss of this complex has deleterious effects on cognition and other higher brain functions [47]. Furthermore, G9a-mediated H3K9 methylation events within the reward circuitry, including the ventral striatum, are critical intermediates for the long-term effects of cocaine on reward behavior and neuronal morphology [48]. This would suggest that GLP/G9a, and proper regulation of H3K9 levels, is important for orderly brain function both in developing and mature brain.
Furthermore, changes in motivational and affective behaviors could be elicited by overexpression of the H3K9-HMT, SET domain bifurcated 1 (KMT1C/SETDB1/ESET), in adult forebrain neurons [49]. Interestingly, SETDB1 occupancy in neuronal chromatin is highly restricted, and may be confined to less than 0.75% of annotated genes [49]. However, among these are several NMDA and other ionotropic glutamate receptor subunit genes, including Grin2a/b (Nr2a/b)[49]. Mild to moderate inhibition of NMDA receptor-mediated (including Grin2b) neurotransmission elicits a robust improvement of depressive symptoms in some mood disorder patients [50], and, indeed, SETDB1-mediated H3K9 methylation and repressive chromatin remodeling at the Grin2b locus was associated with antidepressant-like behavioral phenotypes in the Setdb1 transgenic mice [49]. Of note, NMDA receptor antagonists, including GRIN2B-specific drugs, elicit significant therapeutic benefits even in subjects who failed multiple trials of selective serotonin reuptake inhibitors (SSRI) and other conventional antidepressants [50]. However, drugs directly acting at the NMDA receptor site have an unfavorable side effect profile, and therapeutic strategies aimed at SETDB1 expression and activity may therefore provide an alternative strategy.
Interestingly, mice with a genetic ablation of Kap1, encoding the SETDB1 binding partner KRAB-associated protein 1, also known as TRIM28/TIF1b/KRIP1)[51], show increased anxiety and deficits in cognition and memory [52], which are phenotypes that are broadly opposite from those observed in mice with increasedSetdb1 expression in brain [49]. These findings further speak to the therapeutic potential of the Kap1-Setdb1 repressor complex in the context of neuropsychiatric disease.
Finally, the H3K9-specific demethylase, KDM3A/Jmjd1A, showed increased H3K9-methylation at its own promoter in the ventral striatum of mice exposed to social defeat (a type of stressor associated with a depression-like syndrome in these animals), while mice that were treated with a conventional antidepressant or that were resilient to this type of stress did not show changes in KDM3A promoter methylation [53]. While it is unclear whether KDM3A or some other demethylase acitivity is altered in the depressed animals, the same study [53] reported widespread repressive histone methylation changes, including increased dimethyl-H3K9 and methylated H3K27 at hundreds of gene promoters in stress susceptible animals, which further emphasizes the importance of these PTMs for the epigenetics of mood disorder.
H3K27
The H3K27-selective methyltransferase, KMT6A, also known as Enhancer of zeste homolog2 (EZH2), is associated with the polycomb repressive chromatin remodeling complex 2 (PRC2) [54], and essential for cortical progenitor cell and neuron production. Consequently, loss of EZH2 function is associated with severe thinning of the cerebral cortex and a disproportionate loss of neurons residing in upper cortical layers I–IV [55]. Likewise, the H3K27-specific demethylase, JMJD3, is important for neurogenesis and neuronal lineage commitment [56]. Furthermore, H3K27 methylation is dynamically regulated in mature brain and involved in the neurobiology of major psychiatric disease. For example, changes in expression of brain-derived neurotrophic factor (Bdnf) in hippocampus of mice exposed to environmental enrichment or chronic stress are associated with opposite changes in the H3K27me3 mark at a subset of Bdnf gene promoters [12,57]. In addition, acute stress leads to an overall decrease in hippocampal H3K27me3 and H3K9me3 [58]. Furthermore, in the orbitofrontal cortex of suicide completers, alterations in H3K27 methylation were described at the TRKB gene, encoding the high affinity receptor for the nerve growth factor molecule, BDNF [27]. Changes in the balance between histone H3K4 and H3K27 methylation, or DNA cytosine and H3K27 methylation may also contribute to GABAergic gene expression deficits in schizophrenia [28, 43]. To date it remains unclear which of the various H3K27-specific KMTs and KDMs (Fig. 1) are involved in these disease-related alterations in postmortem brain tissue. Of note, the Jumonji and Arid containing protein 2 (JARID2), which by itself lacks catalytic activity but is crucial for subsequent H3K27 or H3K9 methylation by recruiting the polycomb PRC2 complex to its target genes [59, 60], is located within the schizophrenia susceptibility locus on chromosome 6p22 and confers genetic risk in multiple populations of different ethnic origin [61, 62]. While the biological functions of JARID2 have been studied primarily in the context of transcriptional regulation in stem cells [63, 64], this gene shows widespread expression in the mature nervous system [65], implying JARID2-mediated control over polycomb repressive chromatin remodeling in the adult brain.
H3K36 and H4K20
Epigenetic dysregulation of nuclear receptor-binding SET domain containing protein 1/KMT3B could play a role in some neuro- and glioblastomas [66], but like for other H3K36 and H4K20 regulating enzymes (Fig. 1), to date little is known about their role in neurodevelopment, cognition and psychiatric disease. Strikingly, however, KMT3A/HYPB/SETD2, a member of the SET2 family of KMTs mediating H3K36 methylation [67], is also known as huntingtin-interacting protein 1 (HIP-1) or huntingtin(yeast)-interacting protein B (HYPB) [68]. Huntington’s is a triplet repeat disorder and chronic neurodegenerative condition with motor symptoms and cognitive defects, and significant changes in mood and affect [69]. Whether or not there is altered H3K36 methylation in the neuronal populations that are at risk for degeneration is unclear. Furthermore, the huntingtin/KMT3A interaction has been documented for yeast [68] but not brain. Of note, wildtype huntingtin is a facilitator of polycomb complex PCR2-mediated H3K27 methylation [70], and furthermore, H3K4 and H3K9 methylation changes have been reported in preclinical model systems and postmortem brains with Huntington’s disease [71, 72]. Therefore, it is possible that transcriptional dysregulation in this condition is associated with aberrant methylation patterns of multiple lysine residues.
Given the emerging role of histone methylation in the neurobiology of psychiatric disease, the next obvious question is whether this type of PTM could provide a target for a new generation of psychotropic therapeutics. In principle, KMTs and KDMs should provide fertile ground for the development of novel drugs, because these enzymes are considered more specific than, for example, HDACs, because each HDAC enzyme is likely to affect a much larger number of histone residues as compared to KMTs/KDMs [73]. However, like for other histone modifying enzymes, the specificity of KMTs and KDMs is not limited to histones but includes the (de)methylation of lysines of non-histone proteins, including the p53 tumor suppressor protein and the VEGF growth factor [74]. Druggable domains within the KMTs and KDMs could involve not only their catalytic sites, such as the SET domain for the KMTs or the amino oxidase and JmjC domains for the LSD1 and JMJD subtypes of KDMs, respectively, but also some of the many other functional domains that are specific to subsets of these proteins [75]. One potential candidate would be the bromodomain of the MLLs and other H3K4-specific methyltransferases [75]. Bromodomains, which are present in many different types of nuclear proteins, bind to acetylated histones and small molecules interfering with some of these interactions recently emerged as powerful modulators of systemic inflammation [76].
The catalytic activity of the SET domain containing KMTs requires the universal methyl donor, S-adenosyl-methionine (also known as AdoMET). Crystallographic and functional studies revealed that the SAM binding pocket of KMTs is different from the SAM pockets of other proteins, which may increase the chance to develop compounds which specifically target histone methyltransferases but not other enzymes and proteins [31]. Currently, however, no KMT or KDM related drug is in clinical trials. However, several of these compounds show therapeutic promise in preclinical studies. For example, the S-adenosylhomocysteine hydrolase inhibitor, 3-deazaneplanocin A (DZNep) induces apoptosis in breast cancer cells [77]. This drug alters H3K27 and H4K20 trimethylation via interference with polycomb PRC2 repressive chromatin remodeling [73]. Antioncogenic effects were also observed with BIX-01294, a drug that downregulates H3K9 methylation levels by binding to the SET domain of the G9a/GLP(EHMT1) methyltransferases [73]. The same drug was shown to alter addictive behaviors and H3K9 methylation when infused locally into the brain of cocaine-exposed mice [48]. As discussed above, while tranylcypromine and other monoamine oxidase inhibitors used for the treatment of depression are weak inhibitors of the LSD1 type of KDM, recently several compounds emerged with much stronger activity against LSD1/LSD2 [18]. It will be extremely interesting to explore these drugs in preclinical models for mood and psychosis spectrum disorders. Finally, microRNA-based therapeutic strategies, aimed at decreasing levels and expression of chromatin remodeling complexes, including some of the histone modifying enzymes discussed here, are gaining increasing prominence in the field of cancer therapy [73] and may in the future emerge as a novel therapeutic option in the context of neuropsychiatric disease.
Emerging Concept in DNA Methylation: Role of Transcription Factors in Shaping DNA Methylation Patterns
CLAIRE MARCHAL AND BENOIT MIOTTO* Journal of Cellular Physiology Volume 230, Issue 4, http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-4652
DNA methylation in mammals is a key epigenetic modification essential to normal genome regulation and development. DNA methylation patterns are established during early embryonic development, and subsequently maintained during cell divisions. Yet, discrete site-specific de novo DNA methylation or DNA demethylation events play a fundamental role in a number of physiological and pathological contexts, leading to critical changes in the transcriptional status of genes such as differentiation, tumor suppressor or imprinted genes. How the DNA methylation machinery targets specific regions of the genome during early embryogenesis and in adult tissues remains poorly understood. Here, we report advances being made in the field with a particular emphasis on the implication of transcription factors in establishing and in editing DNA methylation profiles. J. Cell. Physiol. 230: 743–751, 2015.
DNA methylation is a well-studied epigenetic modification in mammalian genomes, discovered in 1948. It is involved in a number of essential cellular processes such as transcription regulation, cellular differentiation, cellular identity maintenance, X inactivation, gene imprinting, and the cellular response to environmental changes (Klose and Bird, 2006; Guibert and Weber, 2013; Smith and Meissner, 2013; Subramaniam et al., 2014). DNA methylation has proved to be a dynamic process, requiring continuous regulation and potentially having an important regulatory role for tissuespecific differentiation or cellular signaling. Indeed, the analysis of the distribution of DNA methylation at the genome scale, and nowadays at the single-base resolution, in different physiological and pathological states, unraveled that local changes in DNA methylation contribute to cell-type specific variation in gene expression. Furthermore, aberrant DNA methylation patterns are documented in a number of human diseases from Immunodeficiency, Centromere instability, and Facial anomalies (ICF) syndrome to cancer, and contribute to the onset or development of these diseases (Smith and Meissner, 2013; Weng et al., 2013; Subramaniam et al., 2014). Needless to say, these discoveries also fuel the promising idea that therapeutic strategies targeting DNA methylation can be used in the prevention and the treatment of cancer and other human diseases, including neuro-developmental disorders (Weng et al., 2013; Subramaniam et al., 2014). As an example, antipsychotic drugs clozapine and sulpiride, combined with histone deacetylase inhibitor valproate, have a beneficial action in schizophrenia and bipolar patients, maybe because they revert the aberrant DNA methylation status at GABAergic gene promoters (Dong et al., 2008). In 2004, 5-azacytidine (VidazaTM, Celgene Corporation, Summit, NJ). A drug blocking DNA methylation, received approval by the Food and Drug Administration for the treatment of myelodysplastic syndromes (Kaminskas et al., 2005).
Figure 1. Overview of the DNA methylation and demethylation pathway. (A) DNMT1 is responsible for the maintenance of DNA methylation during DNA replication. It recognizes hemi-methylated CpG, thanks to its interaction with co-factor UHRF1, and it adds methylation on the un-methylated strand. Black bubbles: methylated CpG. Empty bubbles: un-methylated CpG. (B) DNMT3A/B are responsible for de novo DNA methylation. They establish new patterns of methylation directly from unmethylated CpG-containing sequences. In the embryo, their activity is modulated by a catalytically inactive family member DNMT3L. (C) Passive demethylation occurs through loss of DNMT1/3 activity in actively dividing cells. Loss can be attributed to post-translational modifications, gene mutations, gene silencing or any other mechanism that will eventually lead to DNMT activity inhibition. (D) Active DNA demethylation is catalyzed by the TET family of enzymes. TET1, 2 and 3 can oxydate 5mC into 5hmC (represented in grey bubbles), and eventually oxidate 5hmC into 5-formylcytosine and 5-carboxy-cytosine. None of these bases is recognized by DNMTs causing loss of DNA methylation during DNA replication. In addition, these oxidated bases are recognized by the base-excision repair (BER) pathway and catalytically removed.
Figure 2. Summary of the nuclear factors and epigenetic marks involved in the maintenance of DNA methylation status in different regions of the genome. The table recapitulates our current knowledge on transcription factors, chromatin remodellers and histone marks contributing to the establishment of DNA methylation and its erasure. The information is presented according to genomic features, sharing common regulators, such as promoters/enhancers, tumor suppressor genes, germline gene promoters, imprinted regions, DNA repeats, and retroviral elements and peri-centromeric regions.
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t KAP1/DNMTs control the maintenance of DNA methylation, independently of DNA replication, on a number of genomic targets. Yet, DNMTs have been shown to be recruited onto the chromatin by other chromatin remodelers, such as SETDB1 or G9a, or secondary to gene silencing (Gibbons et al., 2000; Dennis et al., 2001; Guibert and Weber, 2013; Pacaud et al., 2014). Thus, only the identification of the full-spectrum of transcription factors involved in the regulation of DNA methylation will tell whether this function is predominantly confer to KRAB-ZNF factors. This systematic analysis might help understand why only a limited number of factors per family are involved in the shaping of DNA methylation. In the case of ZNF factors several explanations have been postulated. The resolution of the structure of the ZNF fingers of Zfp57 bound onto methylated DNA indicated that a specific amino-acid sequence in the DNA binding ZNF fingers might be required for the recognition and binding of methylated CpG sequences (Liu et al., 2012; BuckKoehntop and Defossez, 2013). Using this knowledge, researchers have postulated that ZNF factors containing this motif might likely contribute to shape DNA methylation profile (Liu et al., 2013). An alternative hypothesis rely on the observation that KRAB-ZNF factors are present uniquely in vertebrate genomes and have expanded quite dramatically in mammalian genomes. As DNA repeats sequences also quickly evolved in mammalian genomes, it is suggested that humanspecific KRAB-ZNF factors might primarily contribute in DNA repeats silencing (Lukic et al., 2014).
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DNA methylation plays an important role in the control of gene expression and cell fate in mammals. Its regulation and function has been upon intense scrutiny since its discovery in mid-1900s. Yet, how DNA methylation patterns are established during embryogenesis, and edited in adult tissue, remains a matter of intense debate. Profiling of DNA methylation in many cell type, species and environmental set up indicates that the DNA methylation profile is thighly correlated with the cell type and its environment. As a consequence, de novo methylation and DNA demethylation events are not randomly distributed but are actually targeted to particular regulatory DNA elements in the genome, including promoters, enhancers or repeated DNAs. For this latter reason researchers have focused on the role of transcription factor in these DNA methylation events. Yet, it is also recognized that non-coding RNAs, short and long, contribute to the establishment and editing of DNA methylation profiles in mammals. Non-coding RNAs may directly interact and control methylation and demethylation activities and, as a consequence, the pattern of DNA methylation in the genome (Di Ruscio et al., 2013; Arab et al., 2014; Castro-Diaz et al., 2014; Molaro et al., 2014; Turelli et al., 2014). For instance, antisense long non-coding RNA TARID (TCF21 antisense RNA inducing demethylation), activates TCF21 expression by inducing promoter demethylation. TARID sequence is complementary to the sequence of the TCF21 promoter. Its transcription causes the anchoring of GADD45A (growth arrest and DNA-damageinducible, alpha), a regulator of DNA demethylation, at the TCF21 promoter and its subsequent chromatin remodelling (Arab et al., 2014). Understanding the interplay between noncoding RNAs and transcription factors in the establishment and the maintenance of DNA methylation is therefore an important challenge for the future.
The Expanding Role of MBD Genes in Autism: Identification of a MECP2 Duplication and Novel Alterations in MBD5, MBD6, and SETDB1
There is growing evidence of the involvement of the methyl-CpG-binding domain (MBD) genes in neurological disorders. To date, pathogenic mutations have been found in patients with clinical features along the autism continuum for two genes in this family, methyl-CpG-binding domain protein 5 (MBD5) and methyl-CpG-binding protein 2 (MECP2). Both genes carry an MBD domain, the unifying feature for the family that includes nine additional genes; BAZ1A, BAZ1B, MBD1,MBD2, MBD3, MBD4, MBD6, SETDB1 and SETDB2 (Roloff et al., 2003). The MBD genes are involved in a variety of functions, including chromatin remodeling (BAZ1A, BAZ1B, MBD1, MBD2, MBD3, and MECP2), DNA damage repair (BAZ1A and MBD4), histone methylation (SETBD1 and SETDB2), and X chromosome inactivation (MBD2, Roloff et al., 2003, Bogdanovic & Veenstra, 2009). There is also functional interplay among members of this family as they have been found to bind at the same promoter regions (MBD1, MBD2, MBD3, andMECP2), partner with each other in complexes (MBD1 and SETBD1), or act in the same complexes in a mutually exclusive manner (MBD2 and MBD3, Sarraf & I. Stancheva 2004; Ballestar et al., 2005; Le Guezennec et al., 2006; Matarazzo et al., 2007). Little is known thus far about the functions of MBD5 and MBD6; they each encode proteins that localize to chromatin but fail to bind methylated DNA (Laget et al., 2010).
One specific disorder in the autism spectrum, Rett syndrome, is caused almost exclusively by alterations in MECP2 (Amir et al., 1999). Due to the location ofMECP2 on the X chromosome, mutations in females can lead to Rett syndrome while males with the same genetic changes typically present with neonatal encephalopathy (Moretti & Zoghbi 2006). Further investigations have demonstrated that MECP2 misregulation can lead to a wide range of clinical features including autism, Angelman-like symptoms, mental retardation with or without infantile seizures, mild learning disabilities, and schizophrenia (Watson et al., 2001; Klauck et al., 2002; Carney et al., 2003; Shibayama et al., 2004;Coutinho et al., 2007; Harvey et al., 2007; Lugtenberg et al., 2009). Our group previously evaluated the MECP2 gene in a dataset of female ASD patients and identified two mutations reported in classic Rett syndrome patients; an Arg294X mutation and a 41 base pair deletion (Leu386fs) predicted to generate a truncated protein (Carney et al., 2003). Furthermore, while point mutations in MECP2 were first recognized to result in abnormal clinical phenotypes, increased expression of the wild type protein due to gene duplication also results in neurodevelopmental disorders (Meins et al., 2005; Van Esch et al., 2005; del Gaudio et al., 2006;Ramocki et al., 2009).
A second gene in the MBD family, MBD5, was tied to neurodevelopmental disorders following the identification of microdeletions on chromosome 2q22–2q23 (Vissers et al., 2003; Koolen et al., 2004; de Vries et al., 2005; Wagenstaller et al., 2007; Jaillard et al., 2008; van Bon et al., 2009; Williams et al., 2009; Chung et al., 2011; Talkowski et al., 2011; Noh & J. M. Graham Jr 2012). The minimal region for these nonrecurrent deletions covers only a single gene, MBD5 (van Bon et al., 2009; Williams et al., 2009; Talkowski et al., 2011). This suggests that the common features of ASDs, delayed or impaired speech, intellectual disability, epilepsy, and stereotypic hand movements found across microdeletion patients manifest due to a decreased expression of this critical gene (van Bon et al., 2009;Williams et al., 2009; Talkowski et al., 2011). Notably, two cases of individuals with duplications across the critical MBD5 region also present with autistic features and developmental delay (Chung et al., 2012). This demonstrates that precise regulation of both MBD5 and MECP2 must be maintained as either increased or decreased expression of each gene can result in a range of neurodevelopmental disorders.
Supplementing clinical evidence, mouse models have reiterated the potential significance of the MBD family in autism etiology. Mbd1 and Mecp2 null models have abnormal neurobehavioral phenotypes including increased anxiety, and impaired social interactions and synaptic plasticity (Guy et al., 2001; Shahbazian et al., 2002b; Zhao et al., 2003; Allan et al., 2008). Furthermore, a transgenicSetdb1 model established a link between this gene and behavior (Jiang et al., 2010a). Additionally, Setdb1 plays a role in the repression of Grin2b, a gene linked to autism, bipolar disorder, intellectual disability, and schizophrenia (Avramopoulos et al., 2007; Allen et al., 2008; Endele et al., 2010; Jiang et al., 2010a; Myers et al., 2011; O’Roak et al., 2011).
Studies have demonstrated that each of the MBD genes are expressed in the brain, while their specific functions having only been determined for a subset of genes (Shahbazian et al., 2002a, Bogdanovic & Veenstra, 2009, Jiang et al., 2010b, Laget et al., 2010, Safran et al., 2010). MeCP2 is a transcriptional regulator believed to act in neuronal maturation as levels increase over time (Shahbazian et al., 2002a,Chahrour et al., 2008). Stable levels of MeCP2 are required through adulthood, as elimination of this protein in adult mice mimics features seen in knockout Mecp2mice (McGraw et al., 2011). The H3K9 methyltransferase SETDB1 acts both in early development as well as later stages of life (Jiang et al., 2010a, Cho et al., 2012). Removal of Setdb1 in mice results in peri-implantation lethality (Dodge et al., 2004). Studies in the forebrain of transgenic Setdb1 mice demonstrate that it targets the NMDA receptors Grin2a and Grin2b as well as the glutamate receptorGrid2 (Yang et al., 2002, Jiang et al., 2010a).
While there is clinical evidence of MECP2 and MBD5 playing a role in autism, only two studies to date have evaluated patients with ASD for mutations in additional MBD family members (Li et al., 2005; Cukier et al., 2010). Previous work in our laboratory analyzed the coding regions of MBD1, MBD2, MBD3, andMBD4 in over 200 individuals with ASD of African and European ancestry and identified multiple variants that altered the amino acid sequence, were unique to patients with autism, and concordant with disease in multiplex families (Cukier et al., 2010). In contrast, a study by Li and colleagues was restricted to a dataset of 65 Japanese autistic patients and reported only a single variation that might be related to autism (Li et al., 2005). We now expand our initial study of MECP2 to a larger dataset that includes male patients and perform the first study evaluating patients with ASD for alterations in four additional MBD family members: MBD5, MBD6, SETDB1 and SETDB2.
Sequencing across the five MBD genes in 287 patients with ASD and 288 ethnically matched control individuals identified a total of 186 unique variations (Table 1, Supplemental Tables 3–7). These variants included 177 single nucleotide polymorphisms (SNPs), five deletions and four insertions. Ninety (48.4%) of the variations have been previously reported in either the dbSNP 134 database (http://www.ncbi.nlm.nih.gov/projects/SNP/) or RettBASE (http://mecp2.chw.edu.au/), while the remaining 96 variants (51.6%) are novel. Fifty-six variations are predicted to alter the amino acid sequence. Fifty-three of the changes were found solely in patients with ASD and absent from controls. To determine variants most likely to contribute to ASD susceptibility, we prioritized changes that were either unique to affected individuals or that had an increased frequency in cases when compared to controls. The 17 most interesting variants were nonsynonymous and unique to our ASD population (Table 1). We utilized four distinct programs to characterize the variants; GERP (Cooper et al., 2005) and PhastCons (Siepel et al., 2005) to measure the level of amino acid conservation across species and PolyPhen (Adzhubei et al., 2010) and SIFT (Kumar et al., 2009) to predict which alterations might have the damaging consequences to protein function.
The mutational burden between cases and controls of African or European ancestry for each gene was not statistically significant by the chi-squared test (Supplemental Table 8). This was determined for the overall load of all variants as well as nonsynonymous alterations (Supplemental Table 9).
MBD5
Thirty-two changes were identified in MBD5, 18 of which have been previously reported (Supplemental Table 3). A distinct set of 11 alterations were nonsynonymous, four of which were only identified in patients with ASD (Val443Met, Ile1247Thr, Tyr1269Cys, and Arg1299Gln, Figure 1A–D, Table 1). Three of these four alterations (75%) are predicted to be damaging by SIFT, as compared to only two of seven nonsynonymous variants (28.6%) identified solely in control individuals (Supplemental Table 3). One alteration of high interest, MBD5 Tyr1269Cys, was inherited paternally in all three ASD children in multiplex family 7763 (Figure 1C). Two of the affected individuals (0001 and 0100) were intellectually impaired with measured IQ in the moderate to severe range (Full Scale IQ: 40 and 50, respectively), while the remaining brother with autism (0101) had borderline intellectual functioning (Full Scale IQ=78). Furthermore, all three siblings had a delay in language and displayed self-injurious behaviors. Two individuals presented with macrocephaly (0100 and 0101), and individual 0100 has a history of epilepsy (recurrent non-febrile seizures).
MBD6
A total of 44 alterations were detected in MBD6, two being single base pair insertions and the remainder of which were SNPs (Supplemental Table 4). Sixteen of the single nucleotide changes have been previously reported and 28 are novel. A subset of 17 alterations was identified only in individuals with ASD, seven of which are predicted to cause missense changes (Table 1, Figure 1E–K). While each of these changes was only identified in a single proband, three of the alterations have high PolyPhen and SIFT scores and are novel (Arg883Trp, Pro943Arg and Arg967Cys), suggesting a strong functional consequence. Furthermore, one of these alterations, Arg883Trp, was identified in multiplex family 7979 and passed maternally to both affected children (Figure 1I). Individual 0001 has a diagnosis of autism and is nonverbal with moderate intellectual disability. His sister (0100) has a diagnosis of Pervasive Developmental Disorder-Not Otherwise Specified and mild intellectual disability, displaying some phrase speech. Both siblings have a history self-injurious behavior. Their mother (1001), who also carries the alteration, was diagnosed with anxiety/panic disorders, depression, obsessive compulsive disorder, and has a history of epilepsy (adolescent onset seizures).
Along with novel variations of interest in MBD6, we found that two known SNPs occur at a higher frequency within our affected population compared to our control population. The first variation, rs61741508 (c.-2C>A), was recognized in sixteen patients with ASD and five controls and is located just upstream of the ATG start site in the Kozak consensus sequence. This variation also has high conservation scores (Supplemental Table 4). The second SNP, rs117084250 (c.2407-64C>T), falls within intron nine and was found in twelve individuals with ASD but only four controls. However, the conservation scores were relatively low, thereby making this a variant of lesser interest (Supplemental Table 4).
MECP2
Twenty-eight alterations were identified in MECP2 (Supplemental Table 5). Sixteen of these are currently in the dbSNP database and another one has been previously reported in RettBASE, leaving 11 novel variations. While none of the frequently recurring, classic Rett syndrome variations were identified in this study, there are two previously reported MeCP2 alterations of undetermined pathogenicity (Thr240Ser and Ala370Thr) that may cause clinical phenotypes. This first variation, MeCP2 Thr240Ser (rs61749738), was identified in two families of African ancestry (1072 and 17130) and absent in control individuals (Figure 2A,B). Further investigation into additional family members showed that the variation was inherited maternally in both cases and concordant with disease in multiplex family 1072. The second alteration, Ala370Thr (rs147017239), was also inherited maternally in a single proband of African ancestry (family18024, Figure 2C).
SETDB1
A total of 44 changes were found in SETDB1, comprised of 19 known and 25 novel alterations (Supplemental Table 6). Eight changes are predicted to be nonsynonymous, but only one of these, Pro1067del, was found solely in patients with ASD. This change is also the only ASD specific, nonsynonymous deletion identified in the entire study. The variant removes three nucleotides and predicts an in-frame deletion of a single amino acid. This deletion falls within the SET domain of the protein and was inherited maternally in both affected sons in family 17187 (Figure 3A).
Another novel variation of interest in SETDB1 that we identified in a high proportion of cases versus controls, Pro529Leu, was identified in five ASD families of European ancestry and only a single control (Figure 3B–F). This variant was inherited paternally in one family and maternally in the remaining four families. In family 37265, the variation was passed from the father, who has dyslexia, to both the female proband with autism (0001) who was diagnosed with developmental and language delays as well as her brother (0100) who presented with ADHD, anxiety/panic disorder, language delay and macrocephaly (Figure 3E). In two of the families with maternal inheritance (17663 and 37673), the mothers presented with anxiety/panic disorder. In family 17663, the mother also presented with a history of seizures, sleep disorder and self-reported depression, while the mother in family 37673 reported history of adolescent onset Anorexia Nervosa. The increased incidence of this alteration in cases versus controls, along with neuropsychiatric and neurodevelopmental disorders in parents carrying the alteration, suggests that this variation may confer a variety of clinical consequences.
SETDB2
Thirty-eight single base pair alterations were identified in the SETDB2gene, 21 of which have been previously reported and the remaining 17 are novel (Supplemental Table 7). Eight SNPs are predicted to alter amino acids and three of these were unique to affected individuals: Ile425Thr, Thr475Met and Pro536Arg (Table 1, Figure 3C,G,H). However, these alterations are not predicted to have a highly detrimental effect on the protein and occur within singleton families, making it difficult to determine whether they may play a pathogenic role in ASD.
Along with isolating additional variations in MBD5 and MECP2 that may contribute to neuropsychiatric disease, this study is the first to report prospective pathogenic variations in MBD6 and SETDB1. These include two novel, nonsynonymous alterations in MBD6 (Arg883Trp and Pro943Arg) and one more in SETDB1 (Pro1067del). Furthermore, the MBD6 Arg883Trp and SetDB1 Pro1067del variations each segregated with ASD in the multiplex families. Potential for SETDB1 to play a role in neurobehavioral phenotypes is supported by results from transgenic Setdb1 mice demonstrating a role in mood behaviors (Jiang et al., 2010a).
To date, MBD5 mutations have been identified in individuals presenting a range of clinical phenotypes including ASD, developmental delay, intellectual disability, epilepsy, repetitive movements, and language impairments (Vissers et al., 2003;Koolen et al., 2004; de Vries et al., 2005; Wagenstaller et al., 2007; Jaillard et al., 2008; van Bon et al., 2009; Williams et al., 2009; Chung et al., 2011; Talkowski et al., 2011; Noh & Graham Jr 2012). These results suggest a significant role for theMBD5 isoform 1, which presents with increased expression in the brain (Laget et al., 2010). It has been estimated that between microdeletions and point mutations of MBD5, this gene may play a contributing genetic role in up to 1% of individuals with ASD (Talkowski et al., 2011). Of the nonsynonymous alterations identified in this study, ASD specific changes were more likely to be predicted to be damaging as compared to those variations found in control individuals (Supplemental Table 3). MBD5 Tyr1269Cys is a strong potentially pathogenic change due to its co-segregation with ASD in a multiplex family of three affected children, high conservation of this amino acid across species and altered function in the luciferase transcriptional activation assay. While this alteration does not fall in a known protein domain, it is specific to isoform 1, the isoform predominately expressed in brain (Laget et al., 2010). It seems likely that most alterations inMBD5 related to disease will be rare and unique, as the one alteration previously reported to have an increased frequency in patients with ASD, Gly79Glu, was only identified in a single control in the current study (Talkowski et al., 2011).
The role of MECP2 in developmental disorders is undisputed (Samaco & Neul 2011). Our study supports the possible pathogenicity of two specific MeCP2 alterations: Thr240Ser and Ala370Thr. The first variant, Thr240Ser was identified in two male probands from families of African ancestry, including the multiplex family 1072 where the variant segregated with ASD (Figure 2A,B). The maternal inheritance in family 17130 and presence of an unaffected carrier sister suggests that the variation may only present with a clinical phenotype in a hemizygous state. This variant falls within the transcriptional repression domain and has been previously reported in four studies; three cases of males with intellectual disability and one female with Rett syndrome (Yntema et al., 2002; Bourdon et al., 2003;Bienvenu & J. Chelly 2006; Campos et al., 2007; Bunyan & D. O. Robinson 2008). The second alteration, Ala370Thr, was identified in a singleton family of African ancestry and previously reported in three Chinese individuals: one female with Rett syndrome, her unaffected mother and a male presenting with epileptic encephalopathy (Figure 2C, Li et al., 2007; Wong & Li 2007). Both of these alterations must be further evaluated to isolate their potential functional consequences.
Finally, while we did identify variants of interest in four of the genes studied,SETDB2 alterations did not appear to be related to the occurrence of ASDs.
This is the first study to evaluate the coding regions of MBD5, MBD6, SETDB1, and SETDB2 for rare alterations in individuals with ASD. We identified novel point mutations predicted to be damaging and concordant with disease in multiplex families, as well as a complex duplication encompassing MECP2. Additional studies, ideally both in patients and animal models, are required to determine the precise consequences of these alterations. The results described here compound the evidence of MECP2 and MBD5’s involvement in ASDs and neurodevelopmental disorders and provide the first examples of autistic patients carrying potentially detrimental alterations in MBD6 and SETDB1. This study demonstrates the expanding role MBD genes play in autism etiology.
PI3K/Akt: getting it right matters
T F Franke1 Oncogene (2008) 27, 6473–6488; http://dx.doi.org:/10.1038/onc.2008.313
The Akt serine/threonine kinase (also called protein kinase B) has emerged as a critical signaling molecule within eukaryotic cells. Significant progress has been made in clarifying its regulation by upstream kinases and identifying downstream mechanisms that mediate its effects in cells and contribute to signaling specificity. Here, we provide an overview of present advances in the field regarding the function of Akt in physiological and pathological cell function within a more generalized framework of Akt signal transduction. An emphasis is placed on the involvement of Akt in human diseases ranging from cancer to metabolic dysfunction and mental disease.
The molecular mechanisms of Akt regulation are summarized in Figure 1.
Figure 1.
Canonical schematic depicting the present state of our understanding of Akt activation and regulation of downstream biological responses. Autophosphorylation of RTKs induces the recruitment of p85 regulatory subunits leading to PI3K activation. Once activated, p110 catalytic subunits phosphorylate plasma membrane-bound phosphoinositides (PI-4-P and PI-4,5-P2) on the D3-position of their inositol rings. The second messengers resulting from this PI3K-dependent reaction are PI-3,4-P2and PI-3,4,5-P3 (also called PIP3). PIP3, in turn, is the substrate for the phosphoinositide 3-phosphatase PTEN, an endogenous inhibitor of PI3K signaling in cells. The phosphoinositide products of PI3K form high-affinity binding sites for the PH domains of intracellular molecules. PDK1 and Akt are two of the many targets of PI3K products in cells. Following binding of the Akt PH domain to PI3K products, Akt is phosphorylated by PDK1 on a critical threonine residue in its kinase domain. mTORC2 is the main kinase activity that through phosphorylation of a C-terminal HM serine residue locks Akt enzyme into an active conformation. Other kinases such as DNA-PK and ILK1 are also capable of phosphorylating Akt at the HM site but may do so in a cell- or context-dependent manner. Akt activation is blunted by phosphatases including PP2A and PHLPP that inhibit Akt activity by dephosphorylation. Studies examining Akt-interacting proteins such as CTMP or second messengers such as Ins(1,3,4,5)P4 suggest that this common pathway of Akt regulation may be further specified within certain functional contexts or during development. Once activated, Akt activation is channeled into a plethora of downstream biological responses reaching from angiogenesis, cell survival, proliferation, translation to metabolism.
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Consequences of Akt activation include diverse biological responses, ranging from primarily metabolic functions such as glucose transport, glycolysis, glycogen synthesis and the suppression of gluconeogenesis to protein synthesis, increased cell size, cell-cycle progression and apoptosis suppression.
Insights into the molecular consequences of increased Akt activation were derived from seminal studies that ultimately identified the ‘orphan’ proto-oncogene as an obligate intermediate downstream of PI3K in the insulin-dependent metabolic control of glycogen synthesis. When searching for kinases that could regulate GSK3, the groups of Brian Hemmings and Phil Cohen realized that Akt inhibited GSK3 activity in an insulin-stimulated and PI3K-dependent manner by direct phosphorylation of an N-terminal regulatory serine residue (Cross et al., 1995). By systematically permutating the amino-acid sequence surrounding the Akt phosphorylation site in GSK3, Alessi et al. (1996b) derived an optimal peptide sequence for Akt phosphorylation (R-X-R-X-X-S/T; where R is an arginine residue, S is serine, T is threonine and X is any amino acid). This Akt consensus motif is a common feature of known substrates of Akt, and its presence predicts reasonably well whether a given protein may be phosphorylated by Akt enzyme in vitro (for review, see Manning and Cantley, 2007). Experiments using randomized permutations on the basis of the motif to optimize substrate peptides have defined the requirement for optimal phosphorylation by Akt further (Obata et al., 2000). The preferred phosphoacceptor for Akt-dependent phosphorylation is a serine residue, but a synthetic substrate peptide with a threonine residue as the phosphoacceptor instead (R-P-R-A-A-T-F; P=proline, A=alanine, F=phenylalanine) is also easily phosphorylated. For achieving optimal phosphorylation efficiency, the phosphoacceptor is best followed by a hydrophobic residue with a large side-chain in the p+1 position, and preceded by a serine or threonine at the p−2 position.
One of the first targets of Akt to be identified that has direct implications for regulating cell survival is the pro-apoptotic BCL2-antagonist of death (BAD) protein. BAD regulation by Akt has exemplified the molecular pathways linking survival factor signaling to apoptosis suppression (for review, see Franke and Cantley, 1997). When BAD is not phosphorylated, it will inhibit Bcl-xL and other anti-apoptotic Bcl-2 family members by direct binding of its Bcl-2 homology domain to their hydrophobic grooves (Gajewski and Thompson, 1996). Once phosphorylated, these phospho-serine residues of BAD form high-affinity binding sites for cytoplasmic 14-3-3 molecules. As a result, phosphorylated BAD is retained in the cytosol where its pro-apoptotic activity is effectively neutralized (Zha et al., 1996). The importance of BAD as an integration point of survival signaling is underscored by the fact that it is a substrate for multiple independent kinase pathways in cells, not all of which phosphorylate BAD at the same site(s) as Akt (Datta et al., 2000). The mechanisms of 14-3-3-dependent regulation of BAD function hereby resemble the Akt-dependent inhibition of FoxO transcription factors that regulate the transcription of pro-apoptotic genes (Brunet et al., 1999).
The function of Akt extends beyond maintaining mitochondrial integrity to keep cytochrome c and other apoptogenic factors in the mitochondria (Kennedy et al., 1999). Akt activity also mitigates the response of cells to the release of cytochrome c into the cytoplasm. Although caspase-9 is an Akt substrate in human cells, where it may explain cytochrome c resistance (Cardone et al., 1998), it may not be the only, or even the most important, target because Akt-dependent cytochrome c resistance can be observed in animal species where caspase-9 lacks a potential Akt phosphorylation site (Fujita et al., 1999; Zhou et al., 2000). Not surprisingly, other components of the post-mitochondrial machinery such as the X-linked inhibitor of apoptotic proteins (XIAP) have been suggested as potential Akt substrates (Dan et al., 2004).
Another important class of Akt targets are proteins involved in the stress-activated/mitogen activated protein kinase (SAPK/MAPK) cascades. Growing experimental evidence points to a close functional relationship between the Akt survival pathway and SAPK/MAPK cascades that are activated by various cellular stresses and are linked to apoptosis. Increased Akt activity has been shown to suppress the JNK and p38 pathways (Berra et al., 1998; Cerezoet al., 1998; Okubo et al., 1998). It has been shown that apoptosis signal-regulating kinase 1 (ASK1) is regulated by Akt and contains an Akt-specific phosphorylation site (Kim et al., 2001). These findings have been confirmed independently by other groups (Yuan et al., 2003; Mabuchi et al., 2004). Thus, ASK1 is likely to be one of the points of convergence between PI3K/Akt signaling and stress-activated kinase cascades, although probably not the only one. Akt also phosphorylates the small G protein Rac1 (Kwon et al., 2000), the MAP2K stress-activated protein kinase kinase-1 (SEK1; also known as JNKK1 or MKK4) (Park et al., 2002) and the MAP3K mixed lineage kinase 3 (MLK3) (Barthwal et al., 2003; Figueroa et al., 2003). Using yeast-2-hybrid screens to identify interacting partners for Akt kinases, Figueroa et al. (2003) found binding of Akt2 to the JNK adaptor POSH. These authors showed that the binding of Akt2 to POSH results in an inhibition of JNK activity, and that this inhibition is mediated by phosphorylation of the upstream kinase MLK3 and leads to the disassembly of the JNK signaling complex. In turn, POSH is also an Akt substrate (Lyons et al., 2007). Taken together, these findings point to an intriguing model for the regulation of the JNK pathway by Akt, in which the Akt-dependent phosphorylation of specific components can block signal transduction through the stress-regulated kinase cascade. In spite of this, it has been reported that Akt also blocks the pro-apoptotic activity of other MAP3Ks such as MLK1 and MLK2 that act in parallel to MLK3 but do not contain a typical Akt consensus phosphorylation motif (Xu et al., 2001). Thus, phosphorylation-based mechanisms may be limited in explaining the role of Akt in blocking JNK signaling.
Although many of its substrates are involved in clearly defined biological functions within a circumscribed context such as cell proliferation, a more thorough analysis of Akt signaling has suggested that the boundaries between metabolic processes and apoptosis suppression may be artificial. For example, the Akt target GSK3 has been implicated both in the regulation of glucose metabolism and cell survival (Pap and Cooper, 1998). These findings suggest that the distinctions between cell growth, survival, metabolism and apoptosis regulation do not properly reflect functional interactions between concurrent biological processes in cells. This shift in perception has been fueled by studies from the Korsmeyer laboratory that have demonstrated a canonical function for the pro-apoptotic Bcl-2 family member BAD in the regulation of glucokinase activity (Danial et al., 2003). It is conceivable that findings of PKA-dependent regulation of BAD in glucose metabolism can be extrapolated to BAD inhibition by Akt. Still, a formal confirmation for a role of Akt in this process has yet to be presented (for review, see Downward, 2003).
The critical importance of Akt signaling for neuronal function is implied from several lines of in vitro evidence using neuronal cell lines and dispersed primary neuronal cultures that have demonstrated a requirement for Akt in the protection against trophic factor deprivation, oxidative stress and ischemic injury (Dudek et al., 1997; Salinas et al., 2001; Noshita et al., 2002). Dysregulation of Akt activity is observed in neurodegenerative diseases including Alzheimer’s disease (Rickle et al., 2004; Ryderet al., 2004), Parkinson’s disease (Hashimoto et al., 2004) and Huntington’s disease (Humbert et al., 2002), and it is also associated with the pathobiological mechanisms underlying spinocerebellar ataxia (Chen et al., 2003). A mechanistic involvement of impaired Akt signaling in neurodegeneration is further supported by the Akt-dependent phosphorylation of the disease-related proteins huntingtin (Humbert et al., 2002) and ataxin (Chen et al., 2003).
Other studies suggest that the involvement of Akt in brain function extends beyond the protection of neuronal cells against apoptotic insults. Indeed, pathological changes in Akt signal transduction have been described that are associated with mental diseases. Significantly decreased Akt1 expression has been reported in patients suffering from familial schizophrenia (Emamian et al., 2004). Decreased Akt1 levels are correlated with increased GSK3 activity, presumably because of the lack of the Akt-dependent inhibitory input on GSK3. In support of AKT1 being a susceptibility gene for schizophrenia, Akt1(−/−) mice exhibit increased sensitivity to the sensorimotor disruptive effect of amphetamine, which is partly reversed by the treatment of mutant mice with the antipsychotic drug haloperidol (Emamian et al., 2004). Additional support for a contribution of impaired Akt signaling in the pathogenesis of schizophrenia derives from the finding of mutant PI3K signaling in schizophrenia (for review, see Arnold et al., 2005). A direct involvement of Akt in dopaminergic action is indicated by the observation that Akt1(−/−) mutant mice exhibit a behavioral phenotype resembling enhanced dopaminergic transmitter function (Emamian et al., 2004). By interacting with the GSK3 pathway, Akt modulates the suppression of dopamine (DA)-associated behaviors after treatment with the mood stabilizer lithium (Beaulieu et al., 2004). Furthermore, a β-arrestin 2-mediated kinase/phosphatase scaffold of Akt and protein phosphatase A (PP2A) is required for the regulation of Akt downstream of DA receptors (Beaulieu et al., 2005). Still, the role of Akt in dopaminergic responses by far exceeds actions downstream of DA receptors: the insulin-dependent regulation of DA transporter also depends on Akt activity (Garcia et al., 2005).
Since the field of Akt signaling in psychiatric disorders is still emerging, it may be too early to speculate about the molecular involvement of Akt in regulating higher brain function. Possible functional outlets of Akt include some of the substrates mentioned above, including mTORC1 and GSK3. In addition, substrates of Akt related to synaptic plasticity and transmission have been described. One such novel substrate of Akt related to neuronal excitability is the β2-subunit of the type A γ-aminobutyric acid receptor (GABAA-R) (Lin et al., 2001). In support of a direct involvement of Akt in synaptic function, studies directed at working memory performance performed in Akt1(−/−) mice (Lai et al., 2006) and in healthy individuals carrying the AKT1 coding variation observed in familial schizophrenia (Tan et al., 2008) find a strong correlation with cognitive performance. Additional roles for Akt in higher brain function are suggested by studies from the Nestler laboratory that have explored the IRS2-Akt pathway during the development of tolerance to opiate reward (Russo et al., 2007). By using viral-mediated gene transfer to express mutant Akt in midbrain neurons, these authors demonstrate that downregulation of the IRS2-Akt pathway mediates morphine-induced decreases in cell size of DA neurons in brain regions that are critically involved in the reward circuitry and affected in individuals addicted to drugs of abuse.
Finally, TSC patients show an increased incidence of autism spectrum disorders (ASD) ranging from 25 to 50% (for review, seeWiznitzer, 2004). Individuals with macrocephaly due to Lhermitte–Duclos disease are prone to ASD and show a pronounced incidence of mutations in the PTEN tumor suppressor gene (Butler et al., 2005). Additional experimental support for a possible involvement of PTEN/Akt in ASD is provided by data from the Parada laboratory examining the morphology and behavior of mutant mice with neuron-specific knockout of PTEN (Kwon et al., 2006). Future studies will be required to clarify the function of Akt in cognition and characterize the underlying molecular mechanisms. In spite of this, these initial studies suggest a complex function of Akt in conditions affecting brain function and mental health.
The emerging involvement of Akt in higher brain function is summarized in Figure 2.
Figure 2.
Akt kinase regulates diverse aspects of neuronal cell function. Akt activation in neuronal cells follows similar mechanisms to those outlined in Figure 1, including activation of PI3K by RTKs including IGF-1/insulin and nerve growth factor (BDNF/NT-3) receptors. Other mechanisms governing Akt activity in neuronal cells include G-coupled receptors for the monoamine neurotransmitters serotonin (5-HT) (for review, see Raymond et al., 2001) and dopamine (DA) (for review, see Beaulieu et al., 2007). Depending on receptor type (D2-DA and 5-HT1A receptors vs D1-DA receptors), binding of 5-HT or DA decreases or increases the activity of adenylyl cyclase (AC), respectively. Changes in cAMP second messenger levels, in turn, alter PKA and PP2A activity. PP2A is inhibited by increased PKA activity, thus maintaining Akt in an activated state after 5-HT1Areceptor simulation (Hsiung et al., 2008). After binding of DA to D2-DA receptor, following initial inhibition of AC, a secondary internalization complex is formed between β-arrestin 2, PP2A and Akt leading to the inhibition of Akt. In neuronal cells, activated Akt regulates diverse targets that have been implicated in the regulation of protein translation and cell size (mTORC1), axonal outgrowth (GSK3), apoptosis suppression (BAD) and synaptic plasticity (GABAA-R). Details regarding functional consequences of Akt regulation for higher brain function are discussed in the text.
When considering the present understanding of all the signals leading to and from Akt, we face a growing complexity that is in part compounded by the intersection of multiple signaling cascades. Many substrates of Akt are shared with other kinases that have similar specificities. Moreover, signals originating from activated Akt do not simply lead to changes in the biological activity of specific downstream substrates, but affect entire signaling networks. In spite of this, there is hope that there is order to the far-reaching physiological involvement of Akt. One possibility is that differential regulation of the binding partners of Akt may determine cell- and context-specific signaling by Akt. Studies are now needed to elucidate the physiological functions of the binding partners of Akt in mammalian physiology.
A second challenge that the field is facing arises from the involvement of Akt in multiple areas of physiology. These now exceed cancer and diabetes and, as briefly outlined above, include higher brain functions related to cognition.
SETDB1 in Early Embryos and Embryonic Stem Cells
Yong-Kook Kang
The histone methyltransferase SETDB1 contributes to the silencing of local chromatin and the target specificity appears to be determined through various proteins that SETDB1 interacts with. This fundamental function endows SETDB1 with specialized roles in embryonic cells. Keeping the genomic and transcriptomic integrity via proviral silencing and maintaining the pluripotency by repressing the differentiation-associated genes have been demonstrated as the roles of SETDB1 in embryonic stem cells. In early developing embryos, SETDB1 exhibits characteristic nuclear mobilizations that might account for its pleiotropic roles in these rapidly changing cells as well. Early lethality of SETDB1-null embryos, along with other immunolocalization findings, suggests that SETDB1 is necessary for reprogramming and preparing the genomes of zygotes and pluripotent cells for the post-implantation developmental program.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3706629/
Exome sequencing of probands with autism have revealed broadly similar results:de novo mutations in a large set of genes occur in a significant fraction of patients, with relatively high OR’s for damaging mutations in genes expressed in the brain9,19–21. Most interestingly, CHD8, which like CHD7 reads H3K4me marks, is frequently mutated in autism22, raising the question of whether the H3K4me pathway may play a role in many congenital diseases. Among 249 protein-alteringde novo mutations in CHD (Supplementary Table 4) and 570 such mutations in autism9,19,20,23, there were two genes, CUL3 and NCKAP1, with damaging mutations in both CHD and autism and none in controls (P = 0.001, Monte Carlo simulation), and several others with mutations in both (e.g., SUV40H1 and CHD7). Similarly, rare copy number variants at 22q11.2, 1q21, and 16p11 are found in patients with autism, CHD or both diseases24–26. These observations suggest variable expressivity of mutations in key developmental genes. Identification of the complete set of these developmental genes and the full spectrum of the resulting phenotypes will likely be important for patient care and genetic counseling.
Context-specific microRNA function in developmental complexity
Adam P. Carroll1,2, Paul A. Tooney1,2 and Murray J. Cairns1,2,* http://jmcb.oxfordjournals.org/content/early/2013/03/01/jmcb.mjt004.full J Mol Cell Biol (2013) doi: 10.1093/jmcb/mjt004
Since their discovery, microRNAs (miRNA) have been implicated in a vast array of biological processes in animals, from fundamental developmental functions including cellular proliferation and differentiation, to more complex and specialized roles such as longterm potentiation and synapse-specific modifications in neurons. This review recounts the history behind this paradigm shift, which has seen small non-coding RNA molecules coming to the forefront of molecular biology, and introduces their role in establishing developmental complexity in animals. The fundamental mechanisms of miRNA biogenesis and function are then considered, leading into a discussion of recent discoveries transforming our understanding of how these molecules regulate gene network behaviour throughout developmental and pathophysiological processes. The emerging complexity of this mechanism is also examined with respect to the influence of cellular context on miRNA function. This discussion highlights the absolute imperative for experimental designs to appreciate the significance of context-specific factors when determining what genes are regulated by a particular miRNA. Moreover, by establishing the timing, location, and mechanism of these regulatory events, we may ultimately understand the true biological function of a specific miRNA in a given cellular environment.
It was once considered the central dogma of molecular biology that gene expression was regulated in a unidirectional manner whereby cellular instructions were encoded in DNA to be transcribed to produce RNA, which simply acted as a messenger molecule to produce the protein end-products that executed these cellular instructions. In fact, signs of a biological phenomenon whereby non-protein-coding RNA molecules could interfere with this very process were not even realized until the 1970s and early 1980s, when exogenous oligonucleotides complementary to ribosomal RNA were found to interfere with ribosome function (Taniguchi and Weissmann, 1978; Eckhardt and Luhrmann, 1979;Jayaraman et al., 1981). A number of experiments in both prokaryotes and eukaryotes further supported the notion of antisense RNA as an antagonist to RNA function (Chang and Stoltzfus, 1985; Ellison et al., 1985; Harland and Weintraub, 1985; Izant and Weintraub, 1985; Melton, 1985), and one such experiment elegantly demonstrated that the introduction of synthetic oligonucleotides complementary to 3′- and 5′-terminal repeats of Rous sarcoma virus 35S RNA not only attenuated viral replication and cell transformation, but also inhibited viral RNA translation in vitro (Stephenson and Zamecnik, 1978; Zamecnik and Stephenson, 1978).
In addition to this, the successful inhibition of thymidine kinase gene expression by antisense RNA in eukaryotic cells precipitated the concept of antisense RNA not only as an experimental tool, but also as a therapeutic design (Izant and Weintraub, 1984). Determining the functionality of a previously identified gene sequence without identifying, isolating, or characterizing the protein product; interfering with RNAs that are never translated; and silencing the expression of disease-associated transcripts in a sequence-specific manner: these were some very appealing prospects. By the late 1980s and early 1990s, a variety of techniques had evolved in the field of molecular and applied genetics whereby various antisense DNA and RNA construct designs were employed to efficiently downregulate target gene expression (Fire et al., 1991).
Meanwhile, the scientific community was also beginning to appreciate a role for endogenous antisense RNA. Short antisense transcripts were found to form an RNA–RNA duplex with the 5′ end of the replication primer of the ColE1 plasmid (Tomizawa et al., 1981; Tomizawa and Itoh, 1982). Endogenous antisense RNA control in prokaryotes was also linked with various biological processes such as plasmid replication, transposition, temporal bacteriophage development, and catabolite repression in bacteria (Light and Molin, 1983; Simons and Kleckner, 1983; Kumar and Novick, 1985). Evidence was also beginning to mount to implicate antisense control mechanisms in eukaryotic organisms (Adeniyi-Jones and Zasloff, 1985; Farnham et al., 1985; Heywood, 1986; Spencer et al., 1986; Williams and Fried, 1986; Stevens et al., 1987), including the demonstration that antisense transcripts in the bovine papillomavirus type 1 (BPV-1) genome prevented episomal replication (Bergman et al., 1986).
It was only a matter of time before phenomena of gene silencing began to unfold in animals. Previous work in the 1980s with Caenorhabditis elegans had established that mutations in the genes for lin-4, lin-14, lin-28, lin-29, and lin-41 altered the heterochronic lineage of developing larvae, resulting in a failure to control temporal aspects of post-embryonic development (Chalfie et al., 1981; Ambros and Horvitz, 1984; 1987; Ambros, 1989); thus, these genes were referred to as being ‘heterochronic’. However, in 1993 it was discovered that lin-4 was located within an intron and was thus unlikely to encode a protein. More significantly, two lin-4 transcripts ∼22 and 61 nucleotides in length were identified that exhibited complementarity to a repeat sequence element in the 3′ untranslated region (UTR) of lin-14 mRNA (Lee et al., 1993). With another report soon replicating this finding in C. elegans andCaenorhabditis briggsae (Wightman et al., 1993), the notion was set forth that the 22-nucloetide lin-4 transcript represented an active mature form of the 61-nucelotide transcript and functioned to control worm larval development by binding to the 3′-UTR of lin-14, thereby negatively regulating its function via an antisense RNA–RNA interaction. Furthermore, lin-4 exhibited complementarity to seven regions within the 3′-UTR of lin-14, demonstrating that gene expression was more potently inhibited as more of these non-coding transcripts bound to the mRNA (He and Hannon, 2004). Retrospectively, we can identify the lin-4 gene in C. elegans as the pioneer of a new class of small, non-coding RNAs called microRNA (miRNA) (Lee et al., 1993), which utilize the RNA interference (RNAi) pathway to regulate the expression of protein-encoding genes at post-transcriptional level (He and Hannon, 2004).
The following few years were somewhat quiet at the forefront of miRNA research, with lin-4 mechanism assumed to be a unique event. Meanwhile, RNAi was coming to prominence in 1998 with Fire and Mello (along with their colleagues) reporting double-stranded RNA (dsRNA) to be far more potent at mediating gene suppression in C. elegans than single-stranded antisense RNA (Fire et al., 1998). Interestingly, only small quantities of dsRNA were required to induce post-transcriptional gene silencing (PTGS), and it was hypothesized that an endogenous catalytic or amplification component was mediating mRNA degradation prior to translation (Montgomery et al., 1998). RNAi was soon thereafter reported as an ATP-dependent process in an in vitroDrosophila embryo lysate system where dsRNA was processed into 21–23-nucleotide species that appeared to guide sequence-specific mRNA cleavage (Zamore et al., 2000). When dsRNA was shown by the Tuschl laboratory to be processed into 21–22-nucleotide short interfering RNA (siRNA) by a ribonuclease III enzyme to mediate sequence-specific RNAi in human embryonic kidney HEK-293 cells, the prospect was set forth for exogenous 21–22-nucleotide siRNA to be developed as gene-specific therapeutic molecules (Elbashir et al., 2001a).
With incredible excitement surrounding the implications of RNAi, Ruvkun and colleagues discovered a second miRNA inC. elegans in 2000. Like lin-4, the newly discovered let-7 exhibited complementarity to the 3′-UTR of heterochronic genes, in this case lin-14, lin-28, lin-41, lin-42, and daf-12 (Reinhart et al., 2000). Moreover, they discovered that let-7 was highly conserved in its temporal regulation across phylogeny (Pasquinelli et al., 2000), refuting the widely believed concept that lin-4 and let-7 were a worm-specific oddity and propelling miRNA to significance as native endogenous clients of the RNAi machinery. This catalysed intense genome-wide searches for the discovery of more endogenous small regulatory RNAs in numerous species, to the point that miRBase Release 19 currently contains sequence data for 25141 mature miRNA products in 193 organism species (Kozomara and Griffiths-Jones, 2011).
The significance of non-coding RNA was further illuminated in 2001 when the completion of the human genome project revealed that <2% of the human genome encoded proteins (Lander et al., 2001). It has been realized that the ratio of non-coding to protein-coding DNA in the genome correlates with developmental complexity (Mattick, 2004), and a recent publication has reported on the exponential correlation of miRNA gene number and 3′-UTR length—but not 5′-UTR or coding sequence length—with morphological complexity in animals (Chen et al., 2012). This was measured according to the number of cell types within each organism, and also confirmed earlier observations that 3′-UTR length in housekeeping genes has remained short across organisms, thereby minimizing miRNA-binding site potential and reducing the complexity with which these constitutively expressed genes are regulated (Stark et al., 2005). Today we certainly have a stronger appreciation for RNA molecules to function not only as messengers of protein production, but also as complex regulatory molecules facilitating the intricate control of gene expression required for developmental complexity (Kosik, 2009).
When considering non-coding RNA function, miRNAs constitute one of the largest classes of endogenous, non-coding regulatory RNA molecules in animals. In their mature form they are ∼19–22 nucleotides in length, and they interact via Watson–Crick binding with regions of complementarity primarily within the 3′-UTR of mRNA transcripts. In doing so, miRNAs act as sequence-specificity guides for the RNAi machinery to mediate repression of target gene expression at post-transcriptional level by negatively regulating mRNA stability and/or protein translation.
miRNA biogenesis
miRNAs are typically transcribed by RNA polymerase II (pol II) as long primary miRNA (pri-miRNA) transcripts, which undergo sequential cleavage into a precursor miRNA (pre-miRNA) transcript before being cleaved again into the mature miRNA duplex (Figure 1). These pri-miRNA transcripts range in length from several hundred nucleotides to several kilobases, can contain either a single miRNA or clusters of several miRNAs, and originate from intronic regions of protein-coding and non-coding genes, as well as from intergenic and exonic regions (Rodriguez et al., 2004; Saini et al., 2007). The microprocessor complex is responsible for mediating pri-miRNA cleavage, with the dsRNA-binding protein DGCR8 (DiGeorge syndrome critical region gene 8) binding the pri-miRNA and positioning the catalytic site of Drosha—a ribonuclease III (RNase III) dsRNA-specific endonuclease—11 nucleotides from the base of the duplex stem to mediate nuclear processing to the pre-miRNA transcript (Denli et al., 2004; Han et al., 2006). This produces a pre-miRNA hairpin typically 55–70 nucleotides in length with a two-nucleotide 3′ overhang, characteristic of RNase III-mediated cleavage (Lee et al., 2003). This two-nucleotide overhang facilitates the subsequent exportation of the pre-miRNA from the nucleus to the cytoplasm by a RanGTP/Exportin5-dependent mechanism and is suspected to also facilitate subsequent cleavage by the RNase III endonuclease Dicer (Yi et al., 2003; Bohnsack et al., 2004; Lund et al., 2004). This cleavage requires the interaction of Dicer with the dsRNA-binding protein TRBP [HIV-1 transactivating response (TAR) RNA-binding protein] (Forstemann et al., 2005), and as a result of Dicer processing the terminal base pairs and the loop of the pre-miRNA are excised. This produces a 19–22-nucleotide mature miRNA duplex, which possess two-nucleotide overhangs at each 3′ end (Lee et al., 2002).
http://jmcb.oxfordjournals.org/content/early/2013/03/01/jmcb.mjt004/F1.medium.gif
Figure 1
A model for canonical miRNA biogenesis and function in animals. After their transcription by RNA polymerase II, pri-miRNAs are cleaved in the nucleus by Drosha, which forms a microprocessor complex with DGCR8. This generates the pre-miRNA, which is actively exported into the cytoplasm via a RanGTP/Exportin 5-dependent mechanism. In the cytoplasm, Dicer binds the base of the pre-miRNA stem defined in the nucleus by Drosha. Dicer cleavage liberates a mature miRNA duplex that exhibits imperfect complementarity. This miRNA duplex is assembled into the miRISC loading complex, in which the passenger strand is discarded. The miRNA guides the mature miRISC to regions of complementarity within mRNA transcripts, thereby mediating post-transcriptional gene silencing through translational repression and/or mRNA degradation.
miRISC loading
After their maturation into small RNA duplexes, miRNAs are loaded into ribonucleoprotein (RNP) complexes, often referred to as miRNA-induced silencing complexes (miRISCs), RISCs, or miRNPs. The signature components of each miRISC are the miRNA and an Argonaute (AGO) protein. In humans, there are four AGO proteins (AGO1-4), each consisting of the highly conserved P-element-induced wimpy testes (PIWI), middle (MID), and PIWI-AGO-Zwille (PAZ) domains, along with a less-conserved terminal domain. The loading of the miRNA into this protein complex has been proposed to occur in tandem with Dicer-mediated miRNA maturation (Gregory et al., 2005;Maniataki and Mourelatos, 2005) and requires ATP hydrolysis with additional chaperone proteins to create an open conformation to facilitate loading of the miRNA duplex (Liu et al., 2004; Yoda et al., 2010).
A key feature of miRNA is that while both strands of a small RNA duplex are capable of activating the miRISC, typically only one strand will induce silencing (Khvorova et al., 2003). This asymmetry is primarily governed by the relative thermodynamic properties of the RNA duplex, such that the miRISC-associated helicase preferentially unwinds the miRNA duplex from the end with least resistance in terms of inter-strand hydrogen bonding. The strand with its 5′ end at this less thermodynamically stable end is selected as the guide strand, and proteins such as TRBP or protein kinase, interferon-inducible dsRNA-dependent activator (PACT) are proposed to interact with Dicer to sense this thermodynamic asymmetry (Schwarz et al., 2003; Noland et al., 2011). In doing so, the guide strand is retained in the miRISC, while the other strand (the passenger, or the miRNA* strand) is discarded (Hutvagner, 2005; Matranga et al., 2005). miRNA strand selection also appears to be independent of Dicer processing polarity (Preall et al., 2006), where both ends of a duplex have similar thermodynamic properties, both the miRNA and miRNA* act as the guide strand with similar frequencies (Schwarz et al., 2003). However, strand selection does not always occur according to the axiom of thermodynamic strand asymmetry, with tissue-specific factors appearing to play a role in enabling both the miRNA and miRNA* strands to co-accumulate and function as the guide strand (Ro et al., 2007). For this reason, miRNA nomenclature has advanced beyond the miRNA* system, with the adoption of miRNA-5p and -3p names to indicate whether the mature miRNA sequence is derived from the 5′ or 3′ end of the pre-miRNA transcript.
Once the mature miRNA strand has been isolated in the mature miRISC, the AGO protein functions as an interface for the miRNA to interact with its mRNA targets. Recent characterization of human AGO2 has revealed that the 3′ hydroxyl of the miRNA inserts into a hydrophobic pocket of AGO such that the terminal nucleotide stacks against the aromatic ring of a conserved phenylalanine residue in the AGO PAZ domain (Jinek and Doudna, 2009). Meanwhile, the MID domain forms a binding pocket that anchors the miRNA 5′ phosphate such that this terminal nucleotide is distorted and does not interact with the target mRNA (Ma et al., 2005; Parker et al., 2005).
…….
Since being discovered as regulators of developmental timing in C. elegans, it has become widely established that miRNA-mediated regulation of gene expression is a fundamental biological phenomenon required to facilitate key developmental processes such as cellular proliferation, programmed cell death, and cell lineage determination and differentiation (Bartel, 2009; Ambros, 2011). Their significance is such that 60% of the human genome is predicted to be regulated by miRNA function (Friedman et al., 2009), each miRNA estimated to regulate around 200 target genes (Krek et al., 2005).
http://jmcb.oxfordjournals.org/content/early/2013/03/01/jmcb.mjt004/F2.medium.gif
Figure 2
Characteristic miRNA associated with the proliferation and differentiation of specialized cell types. A number of distinct miRNAs are expressed at specific stages through development to play a vital role in mediating cell proliferation, specification, and differentiation. A number of miRNAs involved in the establishment of specialized cell types are illustrated for neurogenesis (Smirnova et al., 2005;Makeyev et al., 2007; Shen and Temple, 2009; Shi et al., 2010; Zhao et al., 2010), myogenesis (Chen et al., 2006; Kim et al., 2006), haematopoiesis (Chen et al., 2004; Georgantas et al., 2007;Vasilatou et al., 2010), oligodendrocyte differentiation (Lau et al., 2008; Dugas et al., 2010), as well as induced pluripotent stem (iPS) cell reprogramming (Miyoshi et al., 2011).
miRNAs play a central role in establishing the spatiotemporal gene expression patterns required to establish specialized cell types and promote developmental complexity. The inherent complexity of miRNA function, however, requires a scientific approach in which context-specific miRNA function must be acknowledged if advancements are to be made in understanding how these small regulatory RNA molecules function in various developmental and pathophysiological processes. While this requires an appreciation for mechanistic aspects such as non-redundant miRISC function and the dynamic regulatory outcomes this facilitates, arguably the greatest challenge facing miRNA biology is the identification of the many genes that each miRNA targets and an understanding of the context-specific factors that determine when and how these genes are regulated.
2012pharmaceutical
Amandeep Kaur
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Alan F. Kaul, PharmD., MS, MBA, FCCP
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