, 2012). Our findings add further support to the growing number of studies implicating changes in DNA methylation in response to neuronal

activation across diverse experimental paradigms (Feng et al., 2010a, Feng et al., 2010b, Guo et al., 2011a, Guo et al., 2011b, Lubin et al., 2008, Ma et al., 2009, Miller et al., 2010 and Miller and Sweatt, 2007). We observed that injection of an AAV virus expressing the TET1 catalytic domain resulted in a dramatic increase in global levels of 5hmC, as was shown previously (Guo et al., 2011b). Moreover, using an accurate and sensitive HPLC/MS method, we also observed a decrease in global 5mC and a significant increase in the fraction of unmodified cytosines compared to either control or TET1m-infected find more samples (Figures 3D–3F). Together, these data provide evidence for an active DNA demethylation process at the global level, driven by TET1 hydroxylase activity and utilizing 5hmC as an intermediate. Trichostatin A clinical trial In agreement with this general model, we also observed a significant increase in the expression levels of several genes involved in TET-hydroxylase-mediated DNA demethylation, including Tdg, Apobec1, Smug1, and Mbd4, after TET1 manipulation ( Figure 3G). These findings suggest that the transcription of these genes may be coupled to changes in 5hmC as part of a transcriptionally coordinated system

in neurons. TET1 expression has been shown to induce increases in the expression of Bdnf and the brain-specific Fgf1B while providing no effect on the developmentally expressed Fgf1G, indicating target specificity ( Guo et al., 2011b). Similarly, gene expression analysis of our survey of memory-related genes in this study not only confirmed that Bdnf is positively regulated by TET1 but also revealed significant regulation of many other IEGs, including Arc, Egr1, Fos, Homer1, and Nr4a2 ( Figure 3G). Interestingly, TET1 did not have any significant effect on the expression of other genes we examined including reference genes, genes involved in synaptic plasticity, and genes generally thought to negatively regulate memory. Unexpectedly,

we found that the same set of genes whose expression was promoted by TET1 were also significantly elevated L-NAME HCl in response to the catalytically inactive TET1m, suggesting that TET1 regulates the expression of these genes, at least in part, independently of 5mC to 5hmC conversion. These findings are contradictory to those previously reported by Guo et al., where TET1m had no effect on the expression of Bdnf or Fgf1B in the dentate gyrus ( Guo et al., 2011b). One distinct possibility for this difference may include our targeting of pyramidal cells in area CA1 in comparison to the previous study’s focus on granule cells in the dentate gyrus, which exhibit different gene expression profiles and, thus, differences in the regulation of their transcriptomes ( Datson et al.

Counterstaining with fluorescence Nissl confirmed tdT expression in cell bodies (Figure 3L), suggesting transsynaptic transport from RGCs. tdT expression was also detected in layer

4 of area 17 of the visual cortex (Figures 3M–3O, arrow), which receives input from the dLGN (Frost and Caviness, 1980 and Simmons et al., 1982). A few tdT-positive cells were also found in area 18a, which is located rostrolaterally to area 17 (Figure 3N), indicating transport of the virus across at least four synapses from “starter” Cre-expressing Ruxolitinib research buy RBCs. The lack of detectable tdT expression in layer 5 or 6 of V1, cells of which project to the LGN or SC (Brumberg et al., 2003, Kozloski et al., 2001 and Simmons et al., 1982), suggests an absence of retrograde labeling of these cortical neurons, further supporting an anterograde-specific spread of H129ΔTK-TT (Sun et al.,

1996). The most abundant direct subcortical retinal projection is to the superior colliculus (SC) in the midbrain (Dräger, 1974 and Provencio et al., 1998). In intravitreally injected PCP2/L7-Cre mice, robust tdT expression was seen in the SC at 7 DPI (Figures 3P–3R, arrow). tdT labeling was also observed in pretectal nuclei Baf-A1 mw (PT), such as the posterior pretectal nucleus (PPT), the nucleus of the optic tract (NOT), and the olivary pretectal nuclei (OPN), which receive direct input from the retina (Pak

et al., 1987) (Figure 3K, asterisk; Figures S3A–S3C), as well as in accessory optic tract terminal nuclei such as the medial terminal nucleus (MTN) tetrandrine (Pak et al., 1987) (Figures S3D–S3F). RGCs project to a number of hypothalamic targets, including the suprachiasmatic nucleus (SCN) (Millhouse, 1977) and anterior hypothalamic nucleus (AH) (Hattar et al., 2006). We observed abundant tdT expression in both of these structures (Figures 3S–SU), as well as in the perisupraoptic nucleus (pSON) (Hattar et al., 2006) (Figures S3G–S3I). tdT-positive cells were also detected in a variety of other hypothalamic nuclei including the PVH (Figures S3J–S3LL and data not shown). Prominent expression of tdT was also seen in the lateral septum ventral (LSV) (Figures S3M–S3O, arrow), a structure which, like the PVH, has been implicated in stress and anxiety (Sheehan et al., 2004). Other structures in which tdT was detected included the medial amygdalar (MEA) and posteromedial cortical amygdalar nuclei (PMCO), and hippocampal layer CA1 (Table S3b and data not shown). Overall, approximately 4.4% (37/836) of brain substructures (Franklin and Paxinos, 2008) contained tdT label in animals analyzed between 5 and 8 DPI (Table S3b). On average, between 5% and 15% of total Nissl-positive cells in a 20× field were tdT positive in each region surveyed (Figure S5B).

For instance, the number of cases of Alzheimer’s disease (AD) and other dementias, including Lewy body disease and frontotemporal dementia, was estimated by the World Health Organization in 2005 at almost 25 million individuals worldwide, with ∼5 million new cases annually, and is projected SCH727965 to more than double by 2025. Existing approved medicines provide only symptomatic relief, and their chronic use is often associated

with deleterious side effects; none appear to modify the natural course of the diseases. Clearly, the development of effective therapies is hindered by our limited knowledge of the molecular mechanisms underlying these conditions. Despite the phenotypic diversity of neurodegenerative disorders, insights gained in the last decade into small molecule library screening their pathophysiology, especially through genetics, have begun to reveal some underlying themes. These include disturbances in cellular quality control mechanisms (e.g., endoplasmic reticulum [ER] stress, defects in proteasomal and autophagic function, and accumulation and/or aggregation of misfolded proteins), oxidative stress, neuroinflammation, and impaired subcellular

trafficking. Another pathogenic theme that has come to prominence, and which is the focus of this review, is the role of impaired mitochondrial function, not only as it pertains to defects in mitochondrial energy production, but also to mitochondrial dynamics (i.e., organellar shape, size, distribution, movement, and anchorage), communication with other organelles, and turnover. Of necessity, we have substrate level phosphorylation limited our discussion to a subset of neurodegenerative disorders (Table 1), focusing on those that best illustrate our central points. We recognize that this selection introduces a bias, yet the diseases we have chosen encompass the vast majority of patients afflicted with neurodegenerative disease, and thus should

provide a faithful picture of the state of affairs regarding the role of mitochondria in neurodegeneration. Many of the prominent adult-onset neurodegenerative disorders, such as AD, Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS), are primarily sporadic, i.e., they occur in the absence of any genetic linkage. However, in rare instances they can be inherited. The phenotypes of both the sporadic and familial forms of these diseases are essentially indistinguishable, implying that they might share common underlying mechanisms. We believe that this similarity justifies the analysis of rare genetic forms of a common sporadic disorder, as it could well illuminate the pathogenesis of both. Moreover, the familial counterparts of all of the common sporadic neurodegenerative disorders are due to mutations not just in a single gene, but in multiple distinct and often ostensibly dissimilar genes.

Slices were incubated in GMEM medium containing pCMV-EGFP retrovirus (1 to 5.105 pi/ml), for 2 to 3 hr at 37°C. Slices were then mounted on on laminin/poly-lysine-coated 0.4 μm Millicell culture inserts in a drop of type I collagen and cultured at

37°C, 7.5% CO2, in 6-well plates in GMEM supplemented with 1% sodium pyruvate, 7.2 μM beta-mercaptoethanol, 1% nonessential amino acids, 2 mM glutamine, 1% penicillin/streptomycin, and 10% click here FCS. Primary antibodies used were rabbit anti-Ki67 (Neomarker, 1:400), rabbit anti-Ki67 FITC conjugated (Neomarker, 1:100), mouse anti-NeuN (Milipore 1/100), mouse anti-Pax6 (DSHB, 1/1,000), rabbit anti-Tbr2 (Abcam 1/4,000), sheep anti-EOMES (R&D 1:800), chicken anti-GFP (Invitrogen, 1:1,000), rabbit anti-Geminin (Santa-Cruz, 1:400), and mouse anti-PCNA (Dako, 1/100). We performed 6,003.3 hr (i.e., ∼250 days) of recording in this study. Images were taken every 1 to 1.5 hr for up to 15 days. A cell was considered proliferative if it underwent division during the recording period. DNA Synthesis inhibitor It was designated as a neuron if it started radial migration

with typical migrating neuron morphology or when it was observed nondividing for a duration exceeding 1.5 times the average cell-cycle length of the zone and age under consideration (E48 > 67 hr, E65 > 101 hr and 108 hr, at E78 > 69 hr and 74 hr in the VZ and OSVZ, respectively). We examined 1,071 cells (56 cells at E48; 50 at E67; 71 at E75, two hemispheres; 335 at E65; 559 at E78, four hemispheres). We analyzed 487 divisions (22 at E48; 142 at E65; 31 at E67; 45 at E75; 247 at E78). Quantitative data are presented as the mean ± SEM from representative experiments. Statistical

analyses were performed using the R software. The tests and the corresponding p values are indicated in the out figure legends. For data involving proportions of small number of data points, the Fisher’s exact test was used. Nonparametric statistical tests were preferred because the data did not follow a normal distribution. Wilcoxon test was performed for mean comparison, Kruskal-Wallis test for one-way ANOVA. p < 0.05 was considered statistically significant. The hierarchical clustering (Figure 1J) was performed using the factoMineR package of R (Lê et al., 2008). We thank K. Knoblauch for invaluable and expert guidance in R statistics. We are grateful to M. Valdebenito, M. Seon, F. Piollat, and B. Beneyton for excellent animal care. We are indebted to N. Doerflinger, S. Zouaoui, P. Misery, and C. Lamy for technical assistance and to P. Giroud and J.P. Laigneau for help with the iconography. Administrative and logistic support from C. Nay, N. Kolomitre, and J. Beneyton is acknowledged.

For each sample, Lumacaftor research buy serial sections (20 μm) were collected from the cortex through to the cervical spinal cord. Every fifth section was costained with PKCγ (which marks the corticospinal tract), as well as NeuN and Hoescht to assist with matching levels between samples. Matched images corresponding to two regions were selected for analysis: (1) caudal to the basilar pons and (2) caudal to the pyramidal decussation. Images were analyzed in Metamorph. A constant threshold was applied to all images and the dorsal funiculus was masked. We then computed the area above threshold, which was normalized to the

area observed in wild-type mice. All measurements were conducted blind to genotype. Phylogenetic trees of murine Bhlhb5- and Prdm8-related proteins were created using the amino acid sequences of each murine protein and the ClustalW algorithm, with MyoD and G9A as the outgroups,

respectively. Apart from Zfp488, which we added based on our discovery of high similarity in protein sequences between Prdm8 and Zfp488 (E-value 3e-28), the decision of which family members to include in the phylogenetic analysis was based on previous analyses for bHLH (Ledent et al., 2002, Ledent and Vervoort, 2001 and Stevens et al., 2008) and Prdm families (Fumasoni et al., 2007). We thank M. Takeichi for supplying the Cdh11 mutant mice; A. Cano for supplying the HA-tagged E2-2B expression vector; MK-2206 E.C. Griffith for critical readings of the manuscript; D. Harmin for help with statistical analysis; P. Zhang for assistance with mouse colony management; the Intellectual and Developmental Disabilities Research Center (IDDRC) Gene Manipulation Core (M. Thompson, 4-Aminobutyrate aminotransferase Y. Zhou, and H. Ye); the Harvard Medical School Rodent Histopathology Core (R.T. Bronson), and the IDDRC Molecular Genetics Core. This work was supported by a Jane Coffin Childs Fellowship and a

Dystonia Medical Research Foundation Fellowship to S.E.R., NIH grant NS028829 to M.E.G., and the Developmental Disabilities Mental Retardation Research Center grant NIH-P30-HD-18655. “
“Adenosine-to-inosine (A-to-I) RNA editing is a versatile posttranscriptional mechanism that allows pinpoint recoding of transcripts at the resolution of single nucleotides. This mechanism can drastically impact both the expression levels and functional properties of resulting proteins, thereby expanding the repertoire of protein customization (Keegan et al., 2001). The underlying chemistry involves ADAR enzymes (adenosine deaminases acting on RNA) that catalyze the deamination of adenosine (A) to generate inosine (I) at certain nucleotide positions within RNA. Because inosine is decoded as guanosine (G) during translation, resulting protein products feature exquisitely customized amino acid composition.

Experiments were initiated by establishing a whole-cell recording from an FS interneuron, then testing its connectivity with as many neighboring MSNs as possible until the presynaptic interneuron was lost. Typically 1–6 (average 2.4) MSNs were sampled per interneuron. The probability of finding a synaptic connection between FS-D1 MSN pairs was not changed by dopamine depletion. Connection probability was 0.60 in saline-injected selleck chemicals llc mice (average distance between pairs, 113 ± 49 μm) and 0.53 in 6-OHDA-injected mice (average distance between pairs, 105 ± 50.1 μm) (p = 0.60) (Figure 1A). In contrast, dopamine depletion

significantly increased the probability of finding a synaptic connection between FS-D2 MSN pairs. In saline-injected mice, connection probability was 0.39 (average distance between pairs, 116 ± 46 μm) but was nearly 2-fold higher, 0.77, in 6-OHDA-injected mice (average distance between pairs, 101 ± 48 μm) (p = 0.0004). Changes in FS connectivity occurred rapidly after dopamine depletion, with increased connectivity to D2 MSNs already present at 3 days after dopamine depletion (Figures 1B and 1C). Importantly, the observed change in connection probability was not due to a difference in the number of healthy “patchable”

D1 versus Lumacaftor purchase D2 MSNs in the slice after dopamine depletion. In 6 slices from a total of two 6-OHDA-injected mice, we counted 43 ± 7 patchable D1 MSNs and 40 ± 8 patchable D2 MSNs surrounding FS interneurons. In 6 slices

from 2 saline-injected mice, we counted 43 ± 10 patchable D1 MSNs and 42 ± 6 D2 patchable MSNs surrounding FS interneurons. As shown in Figures 1D–1G, dopamine depletion did not change the properties of unitary inhibitory postsynaptic currents (uIPSCs) recorded in MSNs. Action potentials evoked in presynaptic FS interneurons with brief somatic current injections (5 ms, typically ∼1 nA) reliably elicited uIPSCs in postsynaptic MSNs (Figure 1D). Amplitudes of uIPSCs were similar from trial to trial for a given pair but varied widely across the population (Figure 1E). The amplitudes of uIPSCs were not significantly different across conditions (pD1 = 0.94; pD2 = 0.20, Wilcoxon). These data demonstrate that postsynaptic GABA receptors at FS-MSN synapses are not altered after dopamine Oxyphenisatin depletion. To determine whether aspects of presynaptic function were affected by dopamine depletion, action potentials were elicited in presynaptic FS interneurons at frequencies of 10, 20, 50, or 100 Hz (Figures 1F and 1G). Short-term dynamics were measured as the change in amplitude of uIPSCs that accumulated during trains of ten action potentials at each frequency. Synapses exhibited frequency-independent depression, to 20%–40% their initial amplitudes, across all frequencies tested. The extent of this depression was similar in D1 and D2 MSNs and did not differ significantly between saline- and 6-OHDA-injected mice (p > 0.05 at all frequencies) (Figure 1G).

5 but is substantially decreased by E12.5 ( Figures 1A–1D; data not shown). Consistent with previous studies showing a requirement for GDE2 in interneuron generation, Gde2 transcripts extend dorsally from E10.5, coincident with the timing of ventral and dorsal interneuron formation ( Figures 1B and 1C; Yan et al., 2009). Similarly, GDE2 protein is expressed in postmitotic somatic motor neurons from E9.5 and is detected dorsally from E10.5 ( Figures 1E and 1F). Examination of GDE2 expression in relation to columnar-specific

motor neuron markers at fore- and hindlimb levels of the spinal cord shows that GDE2 is localized to newly differentiating motor neurons and to MMC and lateral and medial LMC motor neurons ( Figures 1E–1G’; Tsuchida et al., 1994; data not shown). By E12.5, GDE2 protein is reduced within motor neuron Antidiabetic Compound Library cell bodies but is enriched within motor axons, suggesting that GDE2 may have later roles in postmitotic motor neuron development ( Figures 1H and 1I). Thus, GDE2 is expressed in somatic motor

neuron cell bodies coincident with the period of motor neuron neurogenesis. To test the requirement for GDE2 in regulating motor selleck compound neuron generation, we generated stable mouse lines that lack functional GDE2 (Gde2−/−) using Cre-lox technology (see Figure S1 available online). We confirmed GDE2 ablation using a combination of PCR, direct sequencing, western blot, Chlormezanone and immunohistochemical analyses ( Figure 7C; Figure S1). Examination of Gde2−/− and wild-type (WT) littermates at the onset of motor neuron differentiation at E9.5 showed an approximately 50% loss of Isl1/2+ and HB9+ motor neurons ( Figures 2A, 2B, 2D, 2E, and 2G; Nornes and Carry, 1978). However, the number of Olig2+ motor neuron progenitors and the dorsal-ventral patterning of spinal progenitors were not affected ( Figures 2C, 2F, and 2G; Figure S2). No increase in TUNEL

staining was detected in Gde2−/− animals, suggesting that the loss of GDE2 does not compromise motor neuron survival but instead disrupts motor neuron formation ( Figure S2). Consistent with this model, Gde2 null mutants showed a decrease in the number of progenitors exiting the cell cycle ( Figures 2J, 2M, and 2N). Although no changes in the proportion of cells in S phase and M phase were detected, the total number of cells in S phase after a 16 hr BrdU pulse was increased, suggesting that the length of the cell cycle is extended in the absence of GDE2 ( Figures 2H–2N; Yan et al., 2009). These data collectively support previous findings in the chick showing that GDE2 is required to regulate motor neuron generation but does not affect progenitor patterning and specification ( Rao and Sockanathan, 2005). Some motor neurons are generated in the absence of GDE2, suggesting that GDE2 function might be redundant with its family members Gde3 and Gde6 ( Nogusa et al., 2004 and Yanaka et al., 2003).

Extensive research has been performed over the years to investigate why humans choose one particular manner of performing a task out of the infinite number possible. Initially, this has focused on reaching trajectories that tend to exhibit roughly straight-line paths with bell-shaped speed profiles, although certain movements have some path curvature depending on gravitational constraints (Atkeson and Hollerbach, 1985) or visual feedback (Wolpert et al., 1994). The majority of planning models have been placed within the framework of optimizing a cost. The idea is that a scalar value, termed cost, is associated with

each way of achieving a task, allowing all possible solutions to be ranked and the one ERK inhibitor with the lowest cost selected. Different costs then make different predictions

about the movement trajectory. For example, models that have been able to account for behavioral data include minimizing the rate of change of acceleration of the hand—the so-called minimum jerk model (Flash and Hogan, 1985)—or minimizing the rates of change of torques at the joints—the minimum torque change model (Uno et al., 1989). In these models, the end result is a desired movement. Although noise and environmental disturbances can act to disturb this process, the role of feedback is simply to return the movement back to this desired trajectory. Selinexor solubility dmso Although able stiripentol to account for many features of the empirical trajectories, these models have several features that make them somewhat unattractive in terms of explanatory power. First, it is not clear why the sensorimotor systems should care about costs such as the jerkiness of the hand. Second, even if it did, to optimize this would require measurement of third derivatives of positional information, and for this

to be summed over the movement is not a trivial computation. Third, these models often do not provide information as to what should happen in a redundant system because they only specify endpoint trajectories. Finally, it is hard to generalize these models to arbitrary tasks such as a tennis serve. In an effort to reexamine trajectory control and counter these four problems, a model was developed based on the assumption that there was one key element limiting motor performance, i.e., noise. In particular, motor noise over a reasonable range of motor activity is signal dependent, with the standard deviation of the noise scaling with the mean level of the signal—a constant coefficient of variation. Therefore, for faster, more forceful movements, the noise is greater than for slow movements, naturally leading to the speed-accuracy trade-off.

, 2010). Future studies will aim to test the role of complement in microglia-synapse interactions in other CNS regions known to undergo activity-dependent synaptic remodeling. In addition to relevance in global remodeling of circuits

in the healthy brain, our findings have important implications for understanding mechanisms underlying synapse elimination in the diseased brain. Consistent with this idea, abnormal microglia function and complement cascade activation have been associated with neurodegeneration of the CNS (Alexander et al., 2008, Beggs and Salter, 2010, Rosen and Stevens, 2010, Schafer and Stevens, 2010 and Stephan et al., 2012). Indeed, in a mouse model selleck screening library of glaucoma, a neurodegenerative disease associated with RGC loss and gliosis, C1q and C3 are highly upregulated and deposited on retinal synapses and C1q deficiency or microglial “inactivation” with minocycline provide significant neuroprotection (Howell et al., 2011, Steele et al., 2006 and Stevens et al., 2007). In addition to diseases associated with neurodegeneration, recent data from genome-wide association studies and analyses of postmortem human brain tissue have suggested that microglia and/or the complement cascade may also be involved in the development

and pathogenesis of neurodevelopmental and psychiatric disorders (e.g., autism, obsessive compulsive disorder, schizophrenia, etc.) (Chen et al., 2010, Håvik et al., 2011, Monji et al., 2009, Pardo et al., 2005 and Vargas et al., check details 2005). Thus, an intriguing possibility remains that microglia and/or complement dysfunction may be directly involved in diseases associated with synapse loss, dysfunction, and/or development. Together, our data offer insight into mechanisms underlying activity-dependent synaptic pruning in the developing CNS, provide a role for microglia in the healthy brain, and provide important mechanistic insight into microglia-synapse interactions in the healthy and diseased CNS. Selleck Afatinib All experiments were reviewed and overseen by the institutional animal use and care committee in accordance

with all NIH guidelines for the humane treatment of animals. See Supplemental Experimental Procedures for details. Mice, except tdTomato-expressing mice (CHX10-cre::tdTomato), received intraocular injections of anterograde tracers at P4. All mice were sacrificed at P5 and brains were 4% PFA fixed overnight (4°C). Only those brains with sufficient dye fills were analyzed (see Supplemental Experimental Procedures for details). P4 CX3CR1::EGFP heterozygotes were anesthetized with isoflurane and given an intraocular injection of drug (0.5 μM TTX or 10mM forskolin) and vehicle (saline or DMSO) into the left and right eyes, respectively. Injection volume was approximately 200 nl. Four to five hours after first injection, mice received a second intraocular injection of CTB 594 and 647 into the left and right eyes, respectively. Mice were sacrificed at P5 for analysis.

In contrast, we found that MGE-derived cells obtained from IN-Cxcr7

mutants fail to respond to Cxcl12 ( Figures 5D–5F). Thus, Cxcr7 is necessary for the chemotaxis of cortical interneurons in response to Cxcl12. The previous results were unexpected, since most MGE-derived cells express both Cxcr4 and Cxcr7 receptors (Figure 2) and Cxcr4 mediates the Cxcl12-dependent migration of these neurons (Li et al., 2008, López-Bendito et al., 2008, Stumm et al., 2003 and Tiveron et al., 2006). A possible explanation might be that both chemokine receptors cooperate in migrating interneurons and that one receptor alone is not sufficient to elicit a response to Cxcl12. Alternatively, Cxcr7 might be required for normal Cxcr4 function. To distinguish

between both possibilities, we examined whether Cxcr4 signaling was impaired in the absence of Cxcr7. To this end, Selleckchem BMS-387032 we prepared cultures from the ventral telencephalon of control and Cxcr7 mutant embryos, and stimulated them with recombinant Cxcl12. As expected from previous reports on Cxcr4 signaling ( Li and Ransohoff, 2008), stimulation with Cxcl12 strongly promoted the phosphorylation of the extracellular signal-regulated kinases 1 and 2 (Erk1/2) in control cells ( Figures 5G and 5H). In contrast, Cxcl12 stimulation failed to elicit phosphorylation of Erk1/2 in cells obtained from Cxcr7 mutants ( Figures 5G and 5H). The previous experiments reinforced SP600125 clinical trial the hypothesis that Cxcr4 function is compromised in the absence of Cxcr7. One possible mechanism could be that Cxcr7 is required for normal Cxcr4 expression. To test this idea, Cell press we analyzed the distribution of Cxcr4-expressing cells in the cortex of control and IN-Cxcr7 mutant embryos. We found that Cxcr4 mRNA is normally expressed in the absence of Cxcr7. However, as predicted from the MGE coculture experiments, Cxcr4-expressing neurons were found to distribute abnormally in the cortex of IN-Cxcr7 mutant embryos ( Figures 6A and 6D). Indeed, the distribution of Cxcr4-expressing

cells closely resembled that observed for Lhx6-expressing cells in IN-Cxcr7 mutant embryos. We next wondered whether the levels of Cxcr4 protein were normal in Cxcr7 mutant interneurons. We found that Cxcr4 immunoreactivity was reduced in the subpallium of Cxcr7 mutant embryos compared with controls ( Figures 6B and 6E). Most strikingly, Cxcr4 immunoreactivity was almost entirely absent from the cortex of IN-Cxcr7 mutant embryos ( Figures 6B, 6B′, 6E, and 6E′). These defects were also obvious in Cxcr7 null mutants ( Figures S2A–S2D). Because the antibody used to detect Cxcr4 in these experiments does not recognize the activated, phosphorylated form of Cxcr4 ( Figures S2E and S2F), these results indicate that either all Cxcr4 present in Cxcr7-deficient interneurons has been phosphorylated, or that Cxcr4 is indeed absent from these cells.