
==== Front
101573691
39703
Cell Rep
Cell Rep
Cell reports
2211-1247

39018245
10.1016/j.celrep.2024.114503
nihpa2019503
Article
Synaptic plasticity in human thalamocortical assembloids
Patton Mary H. 15
Thomas Kristen T. 15
Bayazitov Ildar T. 1
Newman Kyle D. 1
Kurtz Nathaniel B. 2
Robinson Camenzind G. 2
Ramirez Cody A. 1
Trevisan Alexandra J. 1
Bikoff Jay B. 1
Peters Samuel T. 3
Pruett-Miller Shondra M. 34
Jiang Yanbo 1
Schild Andrew B. 1
Nityanandam Anjana 1
Zakharenko Stanislav S. 16*
1 Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
2 Cell and Tissue Imaging Center, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
3 Center for Advanced Genome Engineering, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
4 Department of Cell and Molecular Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
5 These authors contributed equally
6 Lead contact
AUTHOR CONTRIBUTIONS

Conceptualization: M.H.P., K.T.T., and S.S.Z. Electrophysiology: M.H.P., I.T.B., and Y.J. Molecular biology: K.T.T., A.N., and A.B.S. Two-photon imaging: I.T.B. hiPSC line maintenance, organoid differentiation, and assembloid preparation: A.N. and K.D.N. Electron microscopy: N.B.K. and C.G.R. snRNA-seq sample preparation: A.J.T. and J.B.B. snRNA-seq analysis: C.A.R. and K.T.T. Design and production of hiPSC reporter lines: S.T.P. and S.M.P.-M. Visualization: M.H.P. and K.T.T. Funding acquisition: S.S.Z. Supervision: S.S.Z. Writing – original draft: M.H.P. and K.T.T. Writing – review & editing: S.S.Z.

* Correspondence: stanislav.zakharenko@stjude.org
12 9 2024
27 8 2024
16 7 2024
17 9 2024
43 8 114503114503
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (https://creativecommons.org/licenses/by-nc/4.0/).
SUMMARY

Synaptic plasticities, such as long-term potentiation (LTP) and depression (LTD), tune synaptic efficacy and are essential for learning and memory. Current studies of synaptic plasticity in humans are limited by a lack of adequate human models. Here, we modeled the thalamocortical system by fusing human induced pluripotent stem cell-derived thalamic and cortical organoids. Single-nucleus RNA sequencing revealed that >80% of cells in thalamic organoids were glutamatergic neurons. When fused to form thalamocortical assembloids, thalamic and cortical organoids formed reciprocal long-range axonal projections and reciprocal synapses detectable by light and electron microscopy, respectively. Using whole-cell patch-clamp electrophysiology and two-photon imaging, we characterized glutamatergic synaptic transmission. Thalamocortical and corticothalamic synapses displayed short-term plasticity analogous to that in animal models. LTP and LTD were reliably induced at both synapses; however, their mechanisms differed from those previously described in rodents. Thus, thalamocortical assembloids provide a model system for exploring synaptic plasticity in human circuits.

In brief

Human organoids are often used to model diseases with synaptic pathology; however, few studies have examined synaptic function via single-cell or single-synapse recordings. Patton et al. fused human thalamic and cortical organoids into assembloids to examine synaptic transmission and short- and long-term synaptic plasticity in human thalamocortical and corticothalamic circuits.

Graphical abstract
==== Body
pmcINTRODUCTION

Synaptic transmission through the release of neurotransmitter and subsequent activation of postsynaptic receptors is the fundamental mode of communication between neurons. Synaptic plasticity enhances or diminishes synaptic transmission in an activity-dependent manner in response to environmental cues. Although the chemical synapse is evolutionarily conserved,1 the molecular mechanisms underlying synaptic plasticity differ across species.2–6 Aberrant synaptic plasticity is well documented in animal models of autism, schizophrenia, and other psychiatric disorders,7–10 but full insight into these disorders requires a human model system.

Ex vivo human model systems are currently limited to post-mortem samples, which are often in a state of uncertain tissue quality, and biopsy samples, which are almost exclusively from individuals with epilepsy, brain tumors, or other neuropathologies.11 Neither provides adequate material for mechanistic studies. Human induced pluripotent stem cell (hiPSC)-derived organoids provide a promising in vitro model system that is accessible to experimental manipulation and recapitulates human-specific features of neural development and function.12–18 Moreover, organoids are widely used to model synaptopathies (i.e., neurologic and psychiatric disorders associated with synaptic dysfunction).19–25 However, previous work documenting synaptic plasticity in organoids exclusively relied on multielectrode array (MEA) recordings,26 which measure extracellular spike and local field activities from heterogeneous cell populations. Properties of synaptic transmission and synaptic plasticity differ across brain regions and neuronal subtypes.2,27–29 Reflecting this cellular heterogeneity, MEA recordings in organoids detected long-term potentiation (LTP), long-term depression (LTD), and bidirectional short-term synaptic plasticity in response to identical induction protocols.26 We hypothesized that single-cell recordings between defined neuronal populations might induce consistent, robust synaptic plasticity, which is a necessary precursor for mechanistic studies.

To build a minimal circuit, human cortical organoids (hCOs) can be fused with human thalamic organoids (hThOs) to produce thalamocortical (TC) assembloids.30–32 The thalamus is a primary relay center for incoming sensory information that sends widespread, yet highly organized, glutamatergic projections to various cortical regions based on the sensory modality.33–36 The cortex, in turn, sends glutamatergic projections back to thalamic nuclei to integrate and update sensory, motor, and cognitive information.37,38 Collectively, synaptic transmission within the thalamo-cortico-thalamic circuit creates cognitive representations of the outside world based on diverse incoming sensory inputs and provides the foundation for dynamic executive functioning.39–42 Synaptic plasticity within this system is critical to learning and underlies the expression of sensorimotor behaviors, attention, and perceptual and working memory.42–47 TC assembloids are capable of modeling TC and corticothalamic (CT) axonogenesis30,32 and synaptic transmission,31 but TC or CT synaptic plasticity has not been described.

Here, we describe a human assembloid system containing functional glutamatergic TC and CT synapses that undergo short- and long-term synaptic plasticity detected by whole-cell patch-clamp electrophysiology. We then use this system to reveal the molecular mechanisms underlying synaptic plasticity in human neurons.

RESULTS

hThOs contain functional glutamatergic thalamic neurons

To build optimal hThOs, we generated a reporter line from an hiPSC line derived from a neurotypical male subject with normal karyotype (Figure S1). Specifically, the tdTomato-coding sequence was inserted into the endogenous TCF7L2 locus (Figure 1A). We then modified a previously reported protocol48 to increase the efficiency of glutamatergic neuron generation. After differentiation into hThOs, we performed bulk RNA sequencing (RNA-seq) and VoxHunt deconvolution. High tdTomato RNA levels identified hThOs with high representation of diencephalon (a structure that contains the thalamus) and low representation from contaminating structures (Figure 1A). In hThOs from five hiPSC lines, TCF7L2 positively predicted the expression of the thalamic neural precursor genes OLIG3 and OTX2 and the thalamic neuron genes GBX2 and LHX9 (Figure S2). Visual assessment was sufficient to identify hThOs with high tdTomato, as differential expression analysis comparing hThOs with high TCF7L2-tdTomato fluorescence to hCOs revealed significant enrichment of thalamic markers in the hThOs (Figures S3A and S3B). All subsequent experiments were performed with TCF7L2-tdTomato+ hThOs.

At 60 days after the start of differentiation (D60), hThOs contained OTX2+ and SOX2+ neural progenitor domains surrounded by TUBB3+ neurons (Figure 1B). By D92, most cells expressed markers consistent with glutamatergic thalamic neurons, specifically LHX2, FOXP2, and GBX2; GABA immunoreactivity was observed in a small subset of cells (Figure S3C). At D70–D90, synaptic gene expression increased, and precursor and mitotic gene expression decreased in hThOs (Figures S3D and S3E).Whereas previous protocols generated hThOs containing ~25%–50% glutamatergic neurons,30,31 single-nucleus RNA-seq (snRNA-seq) analysis of our D90 hThOs revealed that the majority (~89%) of cells were glutamatergic neurons found primarily in excitatory neuron 1–4 (ExN1–4) clusters (~83% of all cells) (Figures 1C–1F). Applying VoxHunt mapping to BrainSpan and Allen Brain Atlas references, we found that clusters ExN1–4 mapped to the human mediodorsal thalamus (Figure 1D) and embryonic day (E) 15 mouse caudal thalamus (Figure 1G), which produces the glutamatergic neurons of the mature thalamus. Consistent with thalamic neurons, ExN1–4 neurons primarily expressed SLC17A6 (or VGLUT2); SLC17A7 (or VGLUT1) was sparsely expressed (Figure 1F). Neurons in clusters ExN1–4 expressed additional thalamic markers of interest, including GBX2, SHOX2, FOXP2, CADM1, and NTNG1 (Figure S3F). In line with reports from the mouse thalamus,49 a subset of ExN cells also expressed SOX2 (Figure S3F). One cluster (PT/ZLI/rTh) mapped to E15 mouse pretectum (PT) (Figure 1H) but also contained cells expressing markers of the thalamic organizer zona limitans intrathalamica (ZLI) and rostral thalamus (rTh) (Figure 1I). A small subset of SLC17A6+ glutamatergic neurons (~6%) and all GAD1+ GABAergic neurons (~1.5%) were found in this cluster.

To verify that the predominant cells in hThOs were functional putative neurons, we used whole-cell patch-clamp electrophysiology to investigate the membrane properties of individual cells. Action potentials (APs) were evoked in response to depolarizing current injections (Figure 1J). The resting membrane potential, membrane capacitance, input resistance, and AP properties measured in hThO cells were consistent with neurons (Figures S4A–S4H). Transmission electron microscopy (TEM) revealed numerous asymmetric and symmetric synapses (Figures S4Q and S4R). Some presynaptic terminals contained dense core vesicles (Figure S4S).

Finally, we examined the non-neuronal cell populations in our hThOs (~9% of cells). Pseudotime (Figure 1K) and cell-cycle analyses (Figures 1L–1N) revealed a small cluster of precursor cells undergoing mitosis (i.e., cycling progenitors cluster). The remaining TNC+ progenitors were labeled radial glia. Most of the remaining cells were GFAP+ astrocytes within the glia cluster (Figure 1O). Pseudotime analysis also revealed differences in glutamatergic neuron maturity, with the ExN4 cluster containing the least mature and the ExN2 cluster containing the most mature thalamic neurons (Figure 1K).

Thus, our hThO protocol generated functional glutamatergic thalamic neurons with high efficiency, and these neurons formed synaptic connections.

TC assembloids form functional glutamatergic TC and CT synapses

To form TC assembloids, we also required optimal hCOs. We generated an isogenic hiPSC reporter line by inserting the tdTomato-coding sequence into the endogenous SLC17A7 (VGLUT1) locus (Figures 2A and S1). We then generated hCOs via a previously reported protocol.50 VoxHunt deconvolution of bulk RNA-seq data demonstrated that VGLUT1-tdTomato+ hCOs exhibited high representation of the pallium (a structure that contains the cerebral cortex) and low representation of contaminating structures (Figure 2A). High expression of tdTomato RNA predicted increased expression of cortical markers relative to hThOs (Figures S3A and S3B) and VGLUT1-tdTomato– hCOs (Figure S5A). All subsequent experiments were performed with VGLUT1-tdTomato+ hCOs.

The snRNA-seq analysis of D90 hCOs revealed that most cells (~85%) fell within a trajectory that began with neural precursors and ended with differentiated neurons expressing markers of upper-layer (UL) or deep-layer (DL) excitatory cortical neurons (UL ExNs and DL ExNs, respectively) (Figures 2B and S5). Using VoxHunt, we found that clusters within this trajectory mapped to human neocortical structures (Figure S5B) and E15 mouse neocortex (Figure 2C). Consistent with reports in rodent models,51 SLC17A6 was expressed in intermediate progenitors, but expression declined with neuronal maturation (Figure 2E). Mature neurons in hCOs exclusively expressed SLC17A7 (Figure 2E). The remaining cells (~15%) included unidentified glutamatergic neurons (Un.ExN1 and Un.ExN2 clusters), glia, and cells resembling those in choroid plexus (Figures S5I and S5J). Overall, glutamatergic neurons constituted ~78% of cells in hCOs.

During development, thalamic axons form synapses within the cortical subplate before transitioning to cortical layer IV.52 Conversely, subplate neurons project to several thalamic nuclei.53 Thus, cortical subplate neurons are critical to TC and CT circuitry development. We identified a cluster in hCOs (subplate/DL ExN) that exhibited enriched expression of markers of human cortical subplate54 (Figure 2B) and contained the most mature neurons based on pseudotime analysis (Figure 2D), which was consistent with this cluster containing subplate-like neurons.55 We then applied NeuronChat56 to our snRNA-seq data to determine the likelihood of neuronal communication between cell clusters in the hThOs and hCOs. We found that the hThO ExN clusters exhibited the highest probability of TC communication with the hCO cycling progenitor and subplate/DL ExN clusters (Figure S6A). Conversely, subplate/DL ExNs exhibited a higher probability of CT communication with hThO ExN clusters than exhibited by other hCO clusters (Figure S6B). Interactions between thalamic axons and cortical progenitors in mice are well-documented but are not driven by synaptic connections.57–59 The hThO ExNs exhibited a high probability of TC communication by NRXN signaling with the hCO cycling progenitor and subplate/DL ExN clusters (Figure S6C). However, hThO ExNs exhibited a higher probability of glutamatergic communication with subplate DL/ExNs (Figure S6D). Together, these analyses suggest that hCOs contain neurons capable of forming glutamatergic TC and CT synapses.

Next, we investigated the firing properties of hCO cells using whole-cell patch-clamp electrophysiology. Delivering depolarizing current injections to hCO cells evoked AP firing (Figure 2F and S4L–S4P). These cells displayed typical neuronal properties (Figures S4I–S4P), consistent with previous reports of hCOs.60–62 TEM revealed asymmetric and symmetric synapses (Figures S4Q and S4R). A subset of presynaptic terminals contained dense core vesicles (Figure S4S).

We then fused hThOs with hCOs to form TC assembloids. Prior to fusion, hCOs were transduced with hSyn-GFP lentivirus to facilitate their identification within the assembloid (Figure 2G). GFP+ axons from the hCO were detectable within the hThO within 5 days post-fusion (dpf). Two-dimensional fusion assays confirmed that hThOs and hCOs sent reciprocal axonal projections (Figure 2H).

We then identified TC and CT synapses within assembloids. We transduced either the hThO or hCO with hSyn-V5-Mito-APEX2 lentivirus, which localized the V5-tagged peroxidase APEX2 to the mitochondrial matrix in neurons, enabling the identification of the hThO or hCO origin of the presynaptic terminal.63 APEX2+ hThOs were fused with APEX2− hCOs (or vice versa) to form TC assembloids. Light microscopy and immunolabeling identified V5+ puncta that co-localized with neurons expressing hSyn-GFP (Figure 2I). Reaction with DAB produced strong contrast in the matrix of APEX2+ mitochondria in TEM images. TEM images revealed APEX2+ mitochondria in presynaptic terminals from the hThO that formed TC synapses within the hCO after fusion (Figure 2J). Conversely, we observed APEX2+ mitochondria in presynaptic terminals from the hCOs that formed CT synapses within the hThOs after fusion (Figure 2K). Thus, assembloids contained TC and CT synapses.

Whole-cell patch-clamp electrophysiology recordings confirmed that TC and CT synapses were functional. Electrical stimulation of the hThO (Figure 3A) or hCO (Figure 3B) evoked excitatory postsynaptic currents (EPSCs) in cells recorded in the hCO or hThO, respectively. The likelihood of evoking a synaptic response varied among assembloids; on average, the chance of cells responding to electrical stimulation of the opposite organoid was 61% and 58% for TC and CT synapses, respectively (Figure 3B). Next, we calculated the paired-pulse ratio (PPR) of EPSCs, a measure of presynaptic short-term plasticity. In response to a pair of stimuli applied to a presynaptic neuron, TC synapses exhibited paired-pulse depression, wherein the second postsynaptic response was weaker than the first. In contrast, CT synapses exhibited paired-pulse facilitation, wherein the second response was stronger than the first (Figure 3C). Both results resemble previous observations in animal models.64–70

Evoked TC and CT EPSCs showed typical glutamatergic ionotropic properties comprising a fast α-amino-3-hydroxy-5-methyl-4-isoxazoleproprionic acid receptor (AMPAR)-mediated component blocked by the AMPAR inhibitor NBQX (3 μM) (86.7% ± 3.3% AMPAR current reduction for TC synapses [Figures 3D and 3F]; 82.2% ± 3.8% for CT synapses, [Figures 3G and 3I]) and a slow N-methyl-D-aspartate receptor (NMDAR)-mediated component blocked by the NMDAR inhibitor AP5 (50 μM) (84.0% ± 4.6% NMDAR current reduction for TC synapses [Figures 3E and 3F]; 78.4% ± 2.9% for CT synapses [Figures 3H and 3I]).

Using electrophysiology and two-photon Ca2+ imaging, we detected synaptically evoked Ca2+ transients in hCO cells upon stimulation of hThOs (Figures 3J–3M). Postsynaptic sites resembled dendritic spines described in cortical neurons of animal models (Figure 3K).71 Stimulation of the hThO evoked stronger Ca2+ transients in dendritic spines than in parent dendritic shafts (Figures 3L and 3M). Ca2+ transients in dendritic spines were blocked by AP5 (82.4% ± 5.2% reduction [Figure 3N]), indicative of glutamatergic synaptic transmission.

TC and CT synapses undergo LTP in assembloids

We then tested whether TC and CT synapses undergo long-term synaptic plasticities in assembloids. TC LTP was reliably induced by high-frequency (40-Hz) tetanization of thalamic inputs (Figure 4A), which increased EPSC amplitudes to 168.2% ± 19.3% of baseline (Figures 4B and 4C). We then induced spike-timing-dependent plasticity (STDP)72–74 by stimulating presynaptic inputs and directly depolarizing the postsynaptic cell. Following a short (×1) STDP-induction protocol, the amplitude of TC EPSCs increased to 144.4% ± 17.8% of baseline (Figures 4D–4F). Following a long (×3) STDP-induction protocol, EPSC amplitudes increased to 223.9% ± 24.4% of baseline (Figures 4G–4L). This TC LTP was observed in all tested (9/9) cells, from six separate assembloids, across three batches of differentiation (Figure 4H). TC LTP was not caused by changes in series resistance (Figure 4I); thus, it represents a true activity-dependent potentiation of synaptic strength.

Next, we investigated the mechanisms underlying TC LTP in assembloids. Bath application of the metabotropic glutamate receptor 5 (mGluR5) antagonist MPEP (10 μM) blocked TC LTP, but AP5 (50 μM) did not (Figures 4J and 4K). TC LTP also required postsynaptic Ca2+. When we included the Ca2+ chelator BAPTA (20 mM) in the internal pipette solution (iBAPTA), the long STDP protocol failed to induce LTP and instead reduced the EPSC amplitude (Figures 4J and 4K). We then tested if TC LTP was expressed presynaptically by measuring changes in PPR after LTP induction. PPR decreased (suggesting increased probability of presynaptic glutamate release) compared to baseline in control and AP5 conditions, and this change was blocked by MPEP (Figures S7A and S7B). In summary, TC synapses undergo LTP via multiple induction protocols, with the long STDP-evoked LTP induced postsynaptically and expressed, at least partially, presynaptically through mGluR5-dependent mechanisms.

CT synapses also underwent LTP after the long STDP-induction protocol. LTP occurred in 12/14 cells from nine assembloids across two differentiation batches (Figure 5B). On average, EPSC amplitudes increased to 158.3% ± 15.2% of baseline after LTP induction (Figures 5C and 5E). CT LTP was not caused by changes in series resistance (Figure 5D). CT LTP was blocked by iBAPTA and by separate application of MPEP and AP5 (Figures 5C and 5E). PPR was unchanged across all conditions (Figures S7C and S7D), suggesting that CT LTP does not involve changes in release probabilities. We concluded that the long STDP-evoked LTP is induced and expressed postsynaptically through mGluR5- and NMDAR-dependent mechanisms at CT synapses in assembloids.

TC and CT synapses undergo LTD in assembloids

The activity-dependent weakening of synaptic transmission through LTD is a key component of learning.75 We tested whether TC and CT synapses in assembloids undergo LTD. Delivering low-frequency (1-Hz) stimulation to the hThO depressed EPSCs in 8/9 hCO cells recorded in nine assembloids from three differentiation batches (Figures 6A and 6B). On average, TC EPSC amplitudes decreased to 59.4% ± 8.1% of baseline (Figures 6C–6F). TC LTD was blocked by iBAPTA or bath-applied MPEP or AP5 (Figures 6C and 6E). PPR was unchanged across all conditions (Figures S7E and S7F). These findings demonstrate that LTD in the TC pathway is induced and expressed postsynaptically and depends on both mGluR5 and NMDARs.

Low-frequency stimulation of hCO inputs to hThO cells also reliably induced LTD, as it was observed in 10/10 cells recorded in nine assembloids across two differentiation batches (Figures 7A and 7B). On average, CT EPSC amplitudes decreased to 65.8% ± 5.2% of baseline (Figures 7C–7F). CT LTD was blocked by iBAPTA or bath application of MPEP or AP5 (Figures 7C and 7E). PPR was unchanged across all conditions (Figures S7G and S7H). Neither TC LTD nor CT LTD occurred due to changes in series resistance (Figures 6D and 7D). These data suggest that CT LTD is induced and expressed postsynaptically and requires both mGluR5 and NMDARs. Reversing the order of pre-synaptic stimulation and postsynaptic depolarization in the long STDP protocol did not induce TC or CT LTD (data not shown).

Finally, snRNA-seq revealed that neurons in hThOs and hCOs contain transcripts encoding group 1 mGluRs (predominantly GRM5, which encodes mGluR5) and NMDAR subunits, the direct targets of MPEP and AP5 (Figures S7I and S7J). Neither the age of the individual organoid nor assembloid dpf affected the expression of TC or CT LTP/LTD (Figure S7K). Table S1 provides the number of batches of organoids used for each experimental condition.

DISCUSSION

Here, we describe an hiPSC-derived TC assembloid system for exploring synaptic plasticity in a minimal human neural circuit. Within assembloids, hThOs and hCOs form reciprocal glutamatergic synapses capable of short- and long-term synaptic plasticity. By measuring electrically evoked synaptic currents in single postsynaptic cells, we found that the vast majority (92.9%) of cells underwent LTP or LTD during the respective induction protocols. Furthermore, these synapses displayed a degree of specificity, as one established induction protocol (reverse long STDP) failed to induce LTD. Together, our findings suggest that synaptic plasticity is robust, highly replicable, and selective in TC assembloids.

We created a minimal neural circuit primarily consisting of glutamatergic neurons to study human synaptic plasticity mechanisms in these cell types. Our snRNA-seq data indicate that most cells in hThOs and hCOs are glutamatergic thalamic neurons and glutamatergic cortical neurons, respectively. This is likely due in part to our reporter line screening strategy, which limited contamination from off-target brain structures. Furthermore, our acute pharmacology experiments demonstrate that the postsynaptic currents we measured occur through AMPA and NMDA receptors. We also report paired-pulse depression and facilitation at human assembloid TC and CT synapses, respectively, consistent with observations at these synapses in rodents.64–70 Therefore, we believe TC recordings arise from cortical neurons receiving synaptic inputs from glutamatergic thalamic neurons, and CT recordings arise from thalamic neurons receiving synaptic inputs from glutamatergic cortical neurons. To our knowledge, only a few studies have measured synaptic transmission within a defined circuit in human brain organoids as we do here.76–78 More commonly, the properties of spontaneously released neurotransmitters onto single cells have been characterized,79–81 but the presynaptic sources of that transmission were not defined. Notably, none of these previous studies examined synaptic plasticity.

The field of synaptic physiology routinely studies defined circuits in heterogeneous systems. In rodent studies, we simplify complex neural networks by using molecular profiling, anatomical mapping, opto- and chemogenetics, and patch-clamp electrophysiology. Decades of research have generated databases of molecular, morphological, and functional characteristics of various neuronal subtypes that enable their identification by present-day researchers. However, in hiPSC-derived organoids, most of these characteristics remain poorly defined. Thus, we intentionally established a minimal neural circuit for our synaptic physiology experiments. Accordingly, it is important to note that our organoids lack some cells, e.g., endothelial cells and microglia, and contain a smaller number of other cells, e.g., astrocytes and GABAergic neurons, which are abundant in brain tissue. It is unclear whether these cells might influence synaptic plasticity in assembloids as they do in vivo. In the present study, the scarcity of cells that were not glutamatergic neurons suggests their influence was negligible. Future studies might build upon the foundation of our minimal circuit and systematically introduce other hiPSC-derived cell types of interest.

Although there are some similarities between our LTP/LTD findings from human assembloids and those from rodents, specifically the high prevalence for NMDAR-mediated LTP and LTD,82 in general, the mechanisms underlying LTP/LTD in the rodent TC and CT pathways are distinct from what we report here.83–85 In mouse auditory and somatosensory TC pathways, LTP depends on postsynaptic group 1 mGluRs, whereas LTP in the barrel cortex requires postsynaptic NMDAR activation and subsequent Ca2+ entry.86–90 Rodent CT LTP is expressed presynaptically and requires a rise in presynaptic Ca2+,91 but it does not involve NMDARs or mGluRs.91 In mice, somatosensory cortical LTD is mediated by NMDARs,92 and barrel cortical LTD requires type 1 cannabinoid receptors.88 In contrast, we found that three of the four types of long-term synaptic plasticity we measured required both mGluR5 and NMDARs. A functional link between group 1 mGluRs and NMDAR activity is seen in various brain regions.83,84 In mouse cortical neurons, the activation of mGluR1 potentiates NMDAR-mediated currents through downstream signaling.85 A similar mGluR5-dependent mechanism may exist in human-derived TC assembloids.

Our results may reflect differences between rodents and humans in the expression and maintenance of long-term synaptic plasticity. However, as noted above, the mechanisms underlying rodent LTP and LTD differ across cortical regions and thalamic nuclei, and it is unclear which of these specific pathways TC assembloids resemble most closely. Future studies will derive organoids that better model specific nuclei of the thalamus. (In fact, a recent report described hThOs resembling the thalamic reticular nucleus.93) In the developing brain, thalamic inputs mold the laminar, columnar, and functional organization of the cortex.57,94 Similarly, more specialized thalamic inputs might promote organizational maturation in hCOs. More organized TC assembloids might better model the diversity of synaptic plasticity mechanisms observed across TC sensory pathways.

Alternatively, the differences we identified between human and rodent synaptic plasticity may be due to the developmental age of the assembloids. Organoids resemble fetal brain more closely than postnatal structures,95 and most rodent studies of synaptic physiology are conducted in postnatal animals. Synaptic plasticity in fetal brains (human or rodent) has not been described, so it is unclear whether differences arise between fetal and early postnatal development. Synaptic plasticity in sensorimotor pathways is also different at early postnatal ages compared to adults, with the pathways undergoing a developmentally distinct critical period of synaptic plasticity before becoming gated.96–98 Thus, we should be cautious of drawing conclusions about adult synaptic plasticity mechanisms based on organoid studies. However, deriving organoids that model later stages of development might provide a framework to study these developmental transitions in human neurons.

Studies performed in animal models have greatly enhanced our knowledge of TC and CT synaptic plasticity mechanisms. However, the human thalamus and cortex differ markedly from rodent models in not only size and complexity but also cellular composition, synaptic protein composition, and functional organization.99–103 Despite their current limitations, hiPSC-derived organoids currently provide the only means of exploring species differences in synaptic plasticity, and we demonstrate here that hiPSC-derived organoids are suitable for the mechanistic experiments needed to identify these differences. Finally, human neurons express genes that have undergone evolutionary divergence from animal models and undergo disease-causing mutations whose functional significance can only be fully explored in cells with a human genome. Thus, we anticipate that organoids and assembloids derived from patient hiPSCs (or hiPSCs carrying disease-associated mutations introduced through genome editing) will provide a particularly useful model system for exploring synaptic pathology in human disorders. We expect that TC assembloids will be particularly useful in this respect, as functional abnormalities in many thalamic nuclei are linked to psychiatric disorders, including schizophrenia.104

Limitations of the study

Although we discuss the relevance of our results with regard to the human TC system, we acknowledge that organoids, like all model systems, are not perfect. In their current state, organoids do not completely replicate the gene expression, cellular composition, structural organization, or developmental trajectory of human brain tissue. Additionally, there is a degree of uncertainty regarding which ExN clusters comprise the pre- and postsynaptic cell populations in TC and CT recordings. While we believe our electrophysiological recordings arise from monosynaptic inputs from thalamic or cortical projections, we cannot rule out the possible polysynaptic contributions of local networks. However, similar recurrent activation of local interneurons from incoming synaptic connections occurs in rodent TC and CT circuits, and care was taken in our electrophysiological analyses to consider only the initial monosynaptic component. Moreover, tetanization of presynaptic inputs may indeed cause potentiation of polysynaptic responses, but STDP induction minimizes polysynaptic contribution. Nonetheless, we believe the integration of standard whole-cell patch-clamp electrophysiology methods that we use here with the rapidly evolving organoid field will strengthen future studies in human neurons and continue providing insights into human brain function.

STAR★METHODS

RESOURCE AVAILABILITY

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Stanislav S. Zakharenko (stanislav.zakharenko@stjude.org).

Materials availability

Plasmids, viruses, and cell lines generated in this study are available from the lead contact with a completed materials transfer agreement.

Data and code availability

The snRNA-seq data that support the findings of this study have been deposited in SRA: PRJNA999219. Bulk RNA-seq data have been deposited in SRA: PRJNA1001283.

Code used for the analysis of snRNA-seq data is available at Github: https://github.com/ZakharenkoLab/Thalamic_and_Cortical_Organoid_snRNASeq and archived at Zenodo: https://doi.org/10.5281/zenodo.12559453. Additional R code is available from the lead contact upon request.

Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

The use of hiPSCs for the generation of organoids was approved by the St. Jude Institutional Review Board. TP-190a and TP-189 were derived from dental pulp cells from neurotypical male and female subjects, respectively, with normal karyotypes. Cells were reprogrammed using episomal plasmids (ALSTEM LLC). The 2242 (i.e., 2242–1), 1205 (i.e., 1205–4), and 8858 (i.e., 8858–3) lines/clones were previously published.105

METHOD DETAILS

Human iPSC culture

All hiPSC lines were maintained in culture on human ES-qualified Matrigel (5264004, Corning) in complete mTeSR Plus (100–0276, STEMCELL Technologies) at 5% O2, 37°C, and 5% CO2. The cultures were passaged with Versene (15040066, ThermoFisher). Genetically modified reporter hiPSC lines were validated before differentiation (Figure S1). Specifically, six assays were performed: (1) Colonies were immunostained for six pluripotency markers126 (Stemlight Pluripotency Antibody Kit 9656S, Cell Signaling); (2) Expression of five additional pluripotency markers126 was assayed using a Custom TaqMan RT-qPCR assay designed in-house (manufactured by ThermoFisher); (3) G-banding; (4) Copy number variation at the seven most frequently aberrant chromosomal locations127–129 was assayed using a custom TaqMan RT-qPCR assay designed in-house (manufactured by ThermoFisher); (5) Global methylation analysis (Infinium MethylationEPICv1.0 850K Beadchip) was performed to identify methylation status at select epigenetic markers,130,131 and results were then compared to established and previously published human embryonic stem cell and hiPSC lines132; (6) Trilineage assay (STEMdiff Trilineage Differentiation Kit 05230, STEMCELL Technologies) was performed, and markers of interest126 were analyzed using a Custom TaqMan RT-qPCR assay designed in-house (manufactured by ThermoFisher).

Generating reporter lines

Genome-edited TP-190a hiPSCs were generated using CRISPR-Cas9 technology. Briefly, hiPSCs were pretreated with StemFlex (Thermo-Fisher Scientific) supplemented with 1× RevitaCell (ThermoFisher Scientific) for 1 h. Then, approximately 106 cells were transiently transfected with precomplexed ribonuclear proteins consisting of 250 pmol chemically modified single-guide RNA (sgRNA; Synthego), 165 pmol Cas9 protein (St. Jude Protein Production Core), 500 ng pMaxGFP (Lonza), and 3 μg ssODN donor (for deletion) or 1 μg dsDNA donor (for tagging) via nucleofection (Lonza, 4D-Nucleofector X-unit) using solution P3 and program CA-137 in a large (100-μL) cuvette, according to the manufacturer’s recommended protocol. Five days postnucleofection, cells were single-cell sorted by FACS for GFP+ (transfected) cells and plated onto Vitronectin XF (Stem Cell Technologies)-coated plates into prewarmed (37°C) StemFlex media supplemented with 1× CloneR (Stem Cell Technologies).

Clones were screened for the desired modification via targeted deep sequencing using gene-specific primers with partial Illumina adapter overhangs on a Miseq Illumina sequencer, as previously described,133 or by junction PCR followed by sequencing. Briefly, cell pellets of approximately 10,000 cells were lysed and used to generate gene-specific amplicons with partial Illumina adapters in PCR#1. Amplicons were indexed in PCR#2 and pooled with targeted amplicons from other loci to create sequence diversity. Additionally, 10% PhiX Sequencing Control V3 (Illumina) was added to the pooled amplicon library prior to running the sample on a Miseq Sequencer System (Illumina) to generate paired 2 × 250-bp reads. Samples were de-multiplexed using the index sequences, fastq files were generated, and next-generation sequencing (NGS) analysis of clones was performed using CRIS.py.134 Correctly edited clones were identified, expanded, and sequence confirmed. Final clones were authenticated using the PowerPlex Fusion System (Promega), which was performed at the St. Jude Hartwell Center and tested for mycoplasma by using the MycoAlertTMPlus Mycoplasma Detection Kit (Lonza). Editing-construct sequences and relevant primers are listed in Table S2.

Thalamic organoid generation

The hThOs were generated from the TP-190a-TCF7L2-tdTomato reporter hiPSC line, except for indicated organoids in Figure S2. For differentiation, cryovials were plated and maintained in culture in mTeSR1 (85850, STEMCELL Technologies). At 80% confluency, they were dissociated into single cells with Accutase (AT-104, Innovative Cell Technologies) and plated into low-attachment 96-well V-bottom plates (MS-9096VZ, Sbio) at 10,000 cells/well, in gfCDM media ([1:1 IMDM (12440053, Thermofisher]: Ham’s F12 [12–615F, Lonza], 1× lipid concentrate [11905031, Thermofisher], 1× antibiotic-antimycotic [15240062, Gibco], 450 μM monothioglycerol [M6145, Sigma], 15 μG/mL apotransferrin [T1428, Sigma], 5 mg/mL BSA [50–255-465, Fisher Scientific]) supplemented with 5 μM SB-431542 (TGFβ inhibitor, 1614, Tocris), 1 μg/mL insulin (I9278, Sigma), 1% v/v growth factor–reduced (GFR) Matrigel (354230, Corning), and 2 μM thiazovivin (72254, STEMCELL Technologies). On Day (D) 2, half the media was replaced with the same media supplemented with 4 μM dorsomorphin (3093, Tocris). On D4 and D6, half of the media was replaced with gfCDM supplemented with 5 μM SB-431542, 100 nM Smoothened agonist (73414, STEMCELL Technologies), and 20 ng/mL Fgf8b (100–25, PeproTech). In some differentiations, Matrigel was added on D2 instead of D0, but no difference was detected in the resulting organoids. On D8, D10, and D12, three-fourths of the media was replaced with the same but further supplemented with 30 ng/mL BMP7 (354BP010, R&D Systems) and 1 μM MEKi PD0325901 (S1036, R&D Systems). On D14, D16, and D18, half the media was replaced with the same, but gfCDM was substituted with thalamic N2 media (DMEM:F12, 10% ES-FBS (ES-009-C, SIGMA), 1× N2 supplement (17502–048, Gibco), 1× Glutamax (35050061, Gibco), and 1× antibiotic-antimycotic.

On D20, all organoids were transferred to a magnetic stir bioreactor (BWS-S03N0S-6, ABLE Corporation, Tokyo) in thalamic N2 media and agitated at 40 rpm. On D22 and D24, half the media was replaced with thalamic N2 supplemented with 1× B27 without vitamin A (12587–010, Gibco), 20 ng/mL heat-stable bFGF (PHG0367, ThermoFisher), and 20 ng/mL EGF (AF-100–15-100UG, Peprotech). On D26 and D28, half the media was replaced with the same, but the concentrations of bFGF and EGF were reduced to 10 ng/mL. On D30 and D32, all the media was replaced with thalamic N2 supplemented with 1× B27 without vitamin A.

Starting D35, full media was replaced every 4 days with BrainPhys (05790, STEMCELL Technologies) supplemented with 1× N2, 1× B27 without vitamin A, 10% ES-FBS, 10 ng/mL BDNF (450–02, Peprotech), and 10 ng/mL GDNF (450–10, Peprotech). Starting D70, all the media was changed to BrainPhys supplemented with 1× N2, 1× B27 without vitamin A, 1× glutamax, 1× NEAA (11140050, Gibco), 1× antibiotic-antimycotic, 200 μM ascorbic acid (A4403, Sigma), 100 μM dibutyryl cAMP (D0627, Sigma), 1% ES-FBS, 10 μM DAPT (2634, Tocris), 20 ng/mL BDNF, and 20 ng/mL GDNF. Starting D82, the concentration of BDNF and GDNF was reduced to 10 ng/mL. In addition, after D30, large organoids were pinched into two halves using a pair of ultra-fine clipper scissors (15300–00, Fine Science Tools) every 5–7 days to avoid large necrotic centers.

Cortical organoid generation

The hCOs were generated from the TP-190a-VGLUT1-tdTomato reporter iPSC line. At 80% confluency, cell cultures were dissociated into single cells with Accutase (AT-104, Innovative Cell Technologies) and plated into low-attachment 96-well V-bottom plates (MS-9096VZ, Sbio) at 9000 cells/well, in EB media (DMEM:F12, 20% knockout serum replacement [KSR] [10828, Life Technologies], 3% ES-FBS, 1× Glutamax, 1× β-mercaptoethanol [2020–07-30, Gibco], 1× antibiotic-antimycotic) supplemented with 5 μM SB-431542 (TGFβ inhibitor, 1614, Tocris), 2 μM dorsomorphin (3093, Tocris), 3 μM IWR1e (Wnt inhibitor, 681669, EMD Millipore), 1% v/v GFR-Matrigel, and 2 μM thiazovivin.

In some differentiations, 0% or 0.5% v/v GFR-Matrigel was added on D0, but no difference in the resulting organoids was detected. On D2, half the media was replaced with the same but without Matrigel. On D4 and D6, half the media was replaced with GMEM KSR media (GMEM, 20% KSR, 1× NEAA (Gibco), 1× sodium pyruvate (11360070, Gibco), 1× β-mercaptoethanol, 1× antibiotic-antimycotic) supplemented with 5 μM SB-431542, 3 μM IWR1e, 2.5 μM cyclopamine (72074, STEMCELL Technologies), and 2 μM thiazovivin. On D8, half the media was replaced with GMEM KSR media supplemented with 5 μM SB-431542, 3 μM IWR1e, and 2.5 μM cyclopamine. On D10, D12, D14, and D16, half the media was replaced with GMEM KSR media supplemented with 5 μM SB-431542 and 3 μM IWR1e. On D18 and D20, half the media was replaced with CBO N2 media (DMEM:F12, 1× chemically defined lipid concentrate (11905–031, Life Technologies), 1× N2 supplement (17502–048, Gibco) and 1× antibiotic-antimycotic) supplemented with 1× B27 supplement without vitamin A (12587–010, Gibco), 20 ng/mL heat-stable bFGF, and 20 ng/mL EGF. On D22, organoids were transferred to a magnetic stir bioreactor (BWS-S03N0S-6, ABLE Corporation) in CBO N2 media supplemented with 1× B27 supplement without vitamin A, 20 ng/mL heat-stable bFGF and 20 ng/mL EGF, and agitated at 40 rpm. Half the media was replaced with the same on D24, D26, and D28. On D30, the media was changed to CBO FBS media (DMEM:F12, 1× chemically defined lipid concentrate [11905–031, Life Technologies], 1× N2 supplement, 10% ES-FBS, 5 μg/mL heparin and 1× antibiotic-anti-mycotic) supplemented with 1× B27 supplement without vitamin A. Full media was replaced every 4 days. On D42 and D46, the media was changed to CBO FBS media supplemented with 1× B27 supplement without vitamin A, 10 ng/mL BDNF (450–02, Peprotech), and 10 ng/mL GDNF (450–10, Peprotech). Starting D50, all the media was replaced every 4 days with BrainPhys (05790, STEMCELL Technologies) supplemented with 1× N2 supplement, 1× B27 supplement without vitamin A, 10% ES-FBS, 10 ng/mL BDNF and 10 ng/mL GDNF. Starting D70, media was changed to BrainPhys supplemented with 1× N2, 1× B27 without vitamin A, 1× glutamax, 1× NEAA, 1× antibiotic-antimycotic, 200 μM ascorbic acid, 100 μM cAMP, 1% ES-FBS, 10 μM DAPT, 20 ng/mL BDNF, and 20 ng/mL GDNF. Starting D82, the concentration of BDNF and GDNF was reduced to 10 ng/mL. In addition, after D30, large organoids were pinched into two halves using a pair of ultra-fine clipper scissors every 5–7 days to avoid large necrotic centers.

Generation of thalamocortical assembloids

Between D90 and D120, TCF7L2-tdTomato+ hThOs were paired with VGLUT1-tdTomato+ hCOs of similar age. Each pair was transferred to a well of a low-attachment, 24-well plate in 500 mL Fusion media (BrainPhys supplemented with 1× N2, 1× B27 without vitamin A, 1× glutamax, 1× NEAA, 1× antibiotic-antimycotic, 200 μM ascorbic acid, 100 μM cAMP, 1% ES-FBS, 10 μM DAPT, 20 ng/mL BDNF, 20 ng/mL GDNF, and the CEPT cocktail (50 nM Chroman 1 [HY-15392, MedChem Express], 5 μM emricasan [S7775, Selleckchem], 0.7 μM trans-ISRIB (#5284, Tocris), and polyamine supplement [#P8483, Sigma-Aldrich135]) supplemented with 0.5% v/v GFR-Matrigel. The plate was left tilted and undisturbed in the incubator. After 3 days, 60% of the media in each well was replaced with fusion media. This was done slowly, while keeping the plate tilted with minimal disturbance to the “fused” organoid pair in each well. The same was done on D6 and D9. Subsequently, 80% of the media was replaced every 3 days. On D4, the plate was transferred to an orbital shaker at 80 rpm. The shaker speed was increased to 90 rpm on D5, 100 rpm on D6, and starting D7, the assembloids were kept at 110 rpm. Between 5 and 10 weeks postfusion, assembloids were harvested for electrophysiological experiments.

Plasmids and lentiviruses

Synapsin-EGFP (hSyn-GFP) lentiviruses with the VSV-G pseudo-type were generated using the pHR-hSyn-eGFP plasmid106 (Addgene: 114215, a gift from Xue Han) by the St. Jude Viral Vector Core. For APEX2 experiments, pLenti-hSyn-V5-COX4-APEX2 plasmid was generated by cloning the V5-COX4-APEX2 sequence from pAAV-COX4-dAPEX263 (Addgene: 117176, a gift from David Genty) into the pLenti backbone containing the human SYN promoter. Briefly, pAAV-COX4-APEX2 was digested with BspE1 and EcoR1, and pLenti-hSyn-nucGFP136 (Addgene: 140190, a gift from Lorenz Studer) was digested with EcoRI and AgeI to remove the nucGFP-coding sequence. Insert containing the V5-COX4-APEX2 sequence was then ligated into the pLenti-hSyn backbone. The resulting plasmid sequence was confirmed by Sanger sequencing. Lenti-hSyn-V5-COX4-APEX2 (hSyn-V5-Mito-APEX2) lentiviruses with the VSV-G pseudo-type were generated by the St. Jude Viral Vector Core.

Lentiviral vectors prepared at 1–3bn TU/mL were added to organoids in the bioreactor at 200×. For vectors at lower titer, 2 μg/mL Polybrene was also added to the media. After 18–20 h, organoids were washed twice with DMEM:F12 and fed fresh media. Media changes were continued according to the protocol. Lentiviral expression was detected at 72 h posttransduction.

Immunofluorescence and light microscopy

Organoids were briefly rinsed in phosphate-buffered saline (PBS) and then fixed in 4% paraformaldehyde in PBS overnight at 4°C. Following rinses in PBS, organoids were cryoprotected by incubation overnight in 30% sucrose in PBS. Organoids were then mounted in Optimal Cutting Temperature (O.C.T.) Compound (Tissue-Tek). Samples were stored at −80°C until cryosectioning. Cryosectioning was performed on a Leica CM 3050 cryostat set to −20°C. Serial sections of 20-μm thickness were mounted onto FisherBrand Superfrost Plus microscope slides and stored at −20°C.

Slides were briefly rehydrated with PBS and then blocked for 1 h at room temperature in blocking buffer (PBS, 5% normal donkey serum, 0.2% Triton X-100, 0.02% sodium azide, filter sterilized). Slides were incubated overnight at 4°C in primary antibodies diluted in blocking buffer, washed with PBS-Tween (0.1%), and incubated 1 h at room temperature in secondary antibodies diluted 1:500 in blocking buffer. Slides were then washed with PBS-Tween (0.1%), and nuclei were labeled with DAPI. Excess DAPI was removed by washing with PBS, and slides were dried and mounted for imaging using Prolong Diamond (ThermoFisher, P36961). Images were acquired on a Zeiss Axio Imager M2 equipped with a 20× Plan-Apochromat Objective (Zeiss, 0.8× NA), 40× EC Plan-NeoFluar Objective (Zeiss, 1.3× NA), and Apotome.2 (Zeiss). Images including GABA were acquired using the 40× objective. All other images were acquired using the 20× objective. During imaging, exposure times were kept below saturation, and imaging conditions were constant within experiments. For images acquired with the Apotome.2, z series were acquired at software-recommended intervals, and image stacks were then deconvolved using ZEN software and a constrained iterative algorithm. Images are shown as maximum-intensity projections prepared in Zeiss ZEN 3.7 software.

The following primary antibodies and dilutions were used: TCF7L2 (Cell Signaling Technologies 2569, 1:1000), OTX2 (R&D Systems AF1979, 1:100), TUBB3 (Abcam Ab107216, 1μg/mL), SOX2 (R&D Systems MAB2018, 1:200), V5 (Invitrogen R960–25, 1:1000), FOXP2 (Abcam ab16046, 1:250), LHX2 (Sigma ABE1402,1:250), GBX2 (R&D Systems AF4638, 1:250), and GABA (Sigma A2052, 1:5000). The following f(ab′)2 secondary antibodies from Jackson Immunoresearch were used: donkey anti–rabbit Alexa Fluor (AF) 488 (711–546-152), donkey anti–goat AF 647 (705–606-147), donkey anti–mouse AF 488 (715–546-150), donkey anti–mouse AF 647 (715–606-150), and donkey anti–chicken AF 647 (703–606-155).

Bulk RNA-seq

Each sample consisted of 2–3 pooled organoids from the indicated condition. Total RNA was isolated using the Direct-zol RNA Microprep Kits (Zymo, R2061), and DNA contamination was removed using the DNA-free DNA Removal Kit (Thermo Fisher, AM1906). RNA was quantified using the Quant-iT RiboGreen RNA assay (ThermoFisher) and quality checked by the 2100 Bioanalyzer RNA 6000 Nano assay (Agilent) or 4200 TapeStation High Sensitivity RNA ScreenTape assay (Agilent) prior to library generation. Libraries were prepared from total RNA with the TruSeq Stranded mRNA Library Prep Kit, according to the manufacturer’s instructions (Illumina PN 20020595). Libraries were analyzed for insert-size distribution using the 2100 BioAnalyzer High Sensitivity kit (Agilent), 4200 TapeStation D1000 ScreenTape assay (Agilent), or 5300 Fragment Analyzer NGS fragment kit (Agilent). Libraries were quantified using the Quant-iT PicoGreen ds DNA assay (ThermoFisher) or by low-pass sequencing with a MiSeq nano kit (Illumina). Paired-end 100-cycle sequencing was performed on a NovaSeq 6000 (Illumina) in the St. Jude Hartwell Center Genome Sequencing Core.

RT-qPCR

RNA was isolated and DNase-treated, as described above. Reverse transcription was performed using 100 ng RNA and the iScript cDNA Synthesis Kit (Bio-Rad, 1708891). A qPCR analysis was then performed using SYBR Green Master Mix (Thermo Fisher, 4309155) and a C1000 Touch Thermal Cycler (Bio-Rad). The following primers were used: GAPDH Forward 5′-AATCCCATCACCATCTTCCA-3′, GAPDH Reverse 5′-TGGACTCCACGACGTACTCA-3′, TCF7L2 Forward 5′-GAATCGTCCCAGAGTGATGTCG-3′, TCF7L2 Reverse 5′-TGCACTCAGCTACGACCTTTGC-3′, OLIG3 Forward 5′-TGAGGCTGAAGATCAACGGACG-3′, OLIG3 Reverse 5′-AGTTTCTGGCGAGCAGGAGTGT-3′, GBX2 Forward 5′-GCGGAGGACGGCAAAGGCTTC-3′, GBX2 Reverse 5′-GTCGTCTTCCACCTTTGACTCG-3′, LHX9 Forward 5′-ACCTGCTTTGCCAAGGACGGTA-3′, LHX9 Reverse 5′-TGACCATCTCCGAGGCGGAAAT-3′, OTX2 Forward 5′-GGAAGCACTGTTTGCCAAGACC-3′, OTX2 Reverse 5′-CTGTTGTTGGCGGCACTTAGCT-3′, FOXG1 Forward 5′-GTATG TGGTCACTAACAGGTC-3′, and FOXG1 Reverse 5′-ACCACAGTATCACAATCAAG-3′.

Preparation and sequencing of the snRNA-seq library

Two independent biological replicates were performed per the differentiation protocol (either cortical or thalamic), each containing 36 organoids pooled together. The hThOs were D91 or D96; the hCOs were D91. All organoids were flash frozen in liquid nitrogen and stored at −80°C until dissociation. Nuclei dissociation was performed as previously described.137 Briefly, frozen tissue was mechanically dissociated with a Dounce homogenizer in detergent lysis buffer containing 0.32 M sucrose, 10 mM HEPES (pH 8.0), 5 mM CaCl2, 3 mM magnesium acetate, 0.1 mM EDTA, 1 mM DTT, and 0.1% Triton X-100. The resulting homogenate was filtered through a 40-μm strainer and washed with the same solution described, without the Triton X-100 added. Nuclei were then centrifuged at 3200 ×g for 10 min at 4°C, and the supernatant was decanted. A sucrose-dense solution containing 1 M sucrose, 10 mM HEPES (pH 8.0), 3 mM magnesium acetate, and 1 mM DTT was carefully layered underneath the remaining supernatant and then spun at 3200 ×g for 20 min at 4°C. The supernatant was discarded, and the final remaining nuclei were resuspended in 0.4 mg/mL BSA and 0.2 U/μL Lucigen RNAse inhibitor (catalog number 30281–1) diluted in PBS. Between 5000 and 10,000 nuclei were inspected and counted on a hemacytometer before loading onto the 10× Chromium Controller (10× Genomics, catalog number 1000171). The snRNA-seq libraries were prepared using the 10× Genomics Chromium Next GEM Single Cell Kit, version 3.1 single index gene expression profiling assay, according to the manufacturer’s instructions.

Libraries were analyzed for insert-size distribution by using the 2100 BioAnalyzer High Sensitivity kit (Agilent), 4200 TapeStation D1000 ScreenTape assay (Agilent), or 5300 Fragment Analyzer NGS fragment kit (Agilent). Libraries were quantified using the Quant-iT PicoGreen ds DNA assay (ThermoFisher) or by low-pass sequencing with a MiSeq nano kit (Illumina). Paired-end 100-cycle sequencing was performed on a NovaSeq 6000 (Illumina) in the St. Jude Hartwell Center Genome Sequencing Core.

Electron microscopy for DAB-labeled samples

Prior to fusion, TCF7L2-tdTomato+ thalamic and VGLUT1-tdTomato+ hSyn-GFP+ cortical organoids were separately transduced in low-attachment 6-well plates with 107 TU/mL Lenti-hSyn-V5-COX4-APEX2 lentiviral vector. After 18–20 h, organoids were washed twice with DMEM:F12 and fed fresh media. After 3 days, APEX2-transduced thalamic organoids were fused with cortical organoids, and APEX2-transduced cortical organoids were fused with thalamic organoids to generate the assembloids described above. At 6–7 weeks postfusion, the assembloids were prepared for electron microscopy analysis. Specifically, each assembloid was embedded at the center of a UV-sterilized Nunc Thermanox plastic coverslip (Thermo Fisher, 174950) in 5 μL GFR-Matrigel for 1 h at 37°C. They were then transferred to the fusion media in 6-well plates and placed in the incubator overnight. The following day, a sterile blade was used to cut a V-shaped notch out of the coverslip on the side containing the APEX2+ half of the assembloid. DAB labeling was then performed using an adapted protocol.138

Briefly, after 1 additional day at 37°C, assembloids were fixed for 1 h in 2% glutaraldehyde in 0.1 M sodium cacodylate at room temperature, after which the fixative was replaced, and samples were incubated 1 h at 4°C. The samples were then washed thrice for 5 min in ice-cold wash solution (0.1 M sodium cacodylate). Next, the samples were incubated 5 min in 20 mM glycine in 1× sodium cacodylate, then washed thrice for 5 min on ice. The samples were preincubated in 0.5 mg/mL DAB in 0.1 M sodium cacodylate for 30 min on ice. The samples then underwent DAB staining in 0.5 mg/mL DAB and 50 mM H2O2 in 0.1 M sodium cacodylate on ice. The reaction was terminated by washing the samples thrice for 5 min on ice in wash solution.

After the DAB labeling developed, samples were postfixed in 2% osmium tetroxide in 0.1 M cacodylate buffer on ice for 30 min. Samples were subsequently washed 5 times for 2 min in ice-cold water, and then they were contrasted with 2% uranyl acetate overnight at 4°C. Samples were washed five times for 2 min in ice-cold water. Samples were dehydrated on ice by an ascending series of ethanol to 100%, followed by 100% propylene oxide at room temperature. Samples were infiltrated with EmBed-812 and polymerized at 60°C. Embedded samples were sectioned at ~70 nm on a Leica ultramicrotome and examined in a ThermoFisher Scientific TF20 transmission electron microscope at 80 kV. Digital micrographs were captured with an Advanced Microscopy Techniques imaging system. Unless otherwise indicated, all reagents were from Electron Microscopy Sciences.

Identification of synapses by transmission electron microscopy

Individual organoids were harvested between D102 and D121 for electron microscopy imaging. Samples were fixed in 0.1 M cacodylate buffer containing 2.5% glutaraldehyde and 2% paraformaldehyde. Samples were postfixed in reduced osmium tetroxide and contrasted with aqueous uranyl acetate. Dehydration was by an ascending series of ethanol to 100%, followed by 100% propylene oxide. Samples were infiltrated with EmBed-812 and polymerized at 60◦C. Embedded samples were sectioned at ~70 nm on a Leica ultramicrotome and examined in a ThermoFisher Scientific TF20 transmission electron microscope at 80 kV. Digital micrographs were captured with an Advanced Microscopy Techniques imaging system. Unless otherwise indicated, all reagents were from Electron Microscopy Sciences.

Fusion of 2-dimensional organoids

TCF7L2-tdTomato+ hThOs and VGLUT1-tdTomato+ hSyn-GFP+ hCOs were halved using a pair of ultra-fine clipper scissors and plated in a culture-insert 2-well in μ-dish 35 mm (81176, Ibidi). Specifically, each half chamber was first coated with human ES-qualified Matrigel diluted 1:200 in DMEM:F12, for 1 h at room temperature. The coating solution was aspirated and 100 μL fusion media was added to each half. One hThO half was placed in one chamber and 1–2 hCO halves were placed in the other and allowed to attach and extend neural processes for 5 days. On D5, the barrier was removed using sterilized blunt forceps, and the organoids were maintained in culture with media changes every 7 days. The barrier region in each dish was imaged every 3–7 days, from D9 to D61, at the same exposure time on a Zeiss AxioObserver D1.

Whole-cell patch-clamp electrophysiology

Whole-cell recordings were made in individual organoids between D90 and D141 or in assembloids between D19 and D78 postfusion. Whole, unsliced organoids were placed in a recording chamber mounted on a two-photon laser-scanning microscope (Bruker) and superfused (2–3 mL/min) with aCSF containing the following solution: 125 mM NaCl, 2.5 mM KCl, 2 mM CaCl2, 2 mM MgCl2, 1.25 mM NaH2PO4, 26 mM NaHCO3, and 20 mM glucose at 300–310 mOsm, equilibrated with 95% O2/5% CO2 at 32°C.

Cells were visualized under two-photon guidance by using PrairieView v5.5 software. Whole-cell voltage- or current-clamp recordings were made from visually identified thalamic or cortical cells approximately 2–5 cell layers (20–100 μm) from the organoid surface. In assembloids, recordings were made 400–800 μm from the TC border. Short-term synaptic plasticity, 1-Hz LTD, and 40-Hz LTP experiments were recorded in voltage-clamp mode (VHold = −60 mV), with borosilicate glass pipettes (Sutter, 3–6 MΩ open pipette resistance) containing the following solution: 125 mM CsMeSO3, 2 mM CsCl, 10 mM HEPES, 0.1 mM EGTA, 4 mM ATP-Mg2, 0.3 mM GTP-Na, 10 mM creatine phosphate-Na2, 5 mM QX-314 chloride, and 5 mM TEA-Cl at pH 7.4 and 290–295 mOsm.

For investigating membrane properties and LTP induced by the STDP protocol, the internal solution contained 115 mM potassium gluconate (KGlu), 20 mM KCl, 10 mM HEPES, 4 mM MgCl2, 0.1 mM EGTA, 4 mM ATP-Mg2, 0.4 mM GTP-Na, and 10 mM creatine phosphate-Na2 at pH 7.4 and 290–295 mOsm. Recordings were obtained using a Multiclamp 700B amplifier (Axon Instruments). Signals were digitized with an Axon Digidata 1550B (Axon Instruments) at 20 kHz and filtered at 2 kHz using Clampex 10.7 software. The liquid-junction potential was calculated to be −10 mV and was corrected for in each recording.

In current-clamp experiments, the rheobase was measured by first injecting a hyperpolarizing current step (−20 pA), followed by a depolarizing ramp (from −20 pA to +200 pA) into cells. The current at which the first AP was generated was recorded and averaged across cells. A series of hyperpolarizing and depolarizing step currents were injected into cells in current-clamp mode (+10 pA steps from −50 pA to +240 pA for 1 s) to measure input resistance and evoked firing rates.

In voltage-clamp experiments, synaptic currents were evoked using a bipolar concentric stimulating electrode (World Precision Instruments) or a homemade 2-prong stimulating electrode connected to a stimulus-isolation unit (Iso-Flex, A.M.P.I.) positioned in either the thalamic or cortical side of assembloids. Stimulus intensities were adjusted prior to each experiment to elicit measurable EPSCs in cortical or thalamic neurons. Because of the variability between assembloids, the amplitudes of evoked EPSCs ranged from −20 pA to −300 pA. PPRs were measured by delivering 2 stimuli 50, 100, 200, 500, or 1000 ms apart for both TC and CT synapses.

TC LTP was induced by high-frequency stimulation: 10 trains of 40-Hz stimulation for 200 ms every 5 s, repeated 3× every 5 min.90 Additional TC LTP and CT LTP were induced via an STDP protocol: a single presynaptic electrical stimulation preceded four post-synaptic APs by 10 s. Postsynaptic APs were induced by four somatic current injections of 2 nA (2-ms duration) at 40 Hz. This protocol was repeated 50 times (at 1 Hz) every 5 min, for a total of three times (long STDP-induction protocol).139 In a subset of experiments, the STDP protocol was delivered only 1× (short STDP-induction protocol). LTD was induced at TC and CT synapses by delivering electrical low-frequency stimulation at 1 Hz for 900 pulses.140 In all long-term synaptic plasticity induction protocols, cells were current-clamped at −60 mV. EPSC peak amplitudes were measured before and after synaptic plasticity induction in voltage-clamp mode (Vhold = −60 mV) using paired electrical stimulation (10 Hz) delivered every 20 s for a 5-min baseline period and a 30-min postinduction period.

All electrophysiological experiments were analyzed offline using Clampfit 10.7 software. For all long-term synaptic plasticity experiments, raw EPSC amplitudes were measured, averaged per minute, and expressed as a percent change from baseline. The amplitude of the first EPSC peak was measured if a polysynaptic response was elicited. To determine a change in synaptic strength after the plasticity-induction protocols, the full postinduction time periods of all the cells in the experiment were averaged and compared to a theoretical baseline of 100% by using a one-sample t test (GraphPad Prism 8.4.2), unless noted. To compare between experimental drug conditions, a one-way ANOVA with Dunnett’s multiple comparisons post-hoc test was used. PPR was calculated by measuring the peak amplitude of the evoked EPSC from both pulses and dividing the EPSC2 peak amplitude by the EPSC1 peak amplitude. The PPR for each ISI of each synapse was compared against 1.0 by using a one-sample t test and between TC and CT synapses by using an unpaired two-tailed t test.

Two-photon calcium imaging

Two-photon calcium imaging was performed as described previously.71 Briefly, two-photon laser-scanning microscopy was performed using an Ultima imaging system (Bruker), a Ti:sapphire Chameleon Ultra femtosecond-pulsed laser (Coherent, 820 nm) and 60× [0.9 numerical aperture] water-immersion infrared objectives (Olympus). Fluo-5F (300 μM) and Alexa 594 (10–25 μM) were included in the internal solution containing 115 mM KGlu, 20 mM KCl, 10 mM HEPES, 4 mM MgCl2, 0.1 mM EGTA, 4 mM ATP-Mg2, 0.4 mM GTP-Na, 5 mM QX-314 chloride, and 10 mM creatine phosphate-Na2 at pH 7.4 and 290–295 mOsm. Synaptically evoked changes in fluorescence of both fluorophores were measured in line-scan mode in a dendritic spine and the parent dendritic shaft. Line scans were analyzed as a ratio of normalized green (G) (Fluo-5F) fluorescence to normalized red (R) (Alexa Fluor 594) fluorescence (G/R). A line-scan was performed through every visible dendritic spine on a targeted dendritic branch, in an orientation that was parallel to the dendritic spine neck and orthogonal to the dendritic shaft.

Drugs

All salts for aCSF were purchased from Sigma-Aldrich. QX-314 chloride was purchased from Hello Bio. DL-AP5 and MPEP were purchased from Tocris Bioscience. To create stock solutions, MPEP was dissolved in DMSO and DL-AP5 was dissolved in water; both were kept frozen at −20°C until dilution in aCSF to the final concentration. For iBAPTA experiments, BAPTA tetra-potassium salt and BAPTA tetra-cesium salt were included in KGlu- and Cs-based intracellular solutions, respectively, at 20 mM.

QUANTIFICATION AND STATISTICAL ANALYSIS

Bulk RNA-seq

For tdTomato-expression analysis, we built a custom reference genome by adding the tdTomato sequence to the human genome (hg38, gencode v31). The tdTomato sequence was also added to the gene-annotation gtf file (gencode v31). Read alignment to the custom genome was performed with STAR (version 2.7) software.107 Gene-level read count was determined using RSEM (version 1.3.1).108

For differential gene expression analysis, only protein-coding genes validated at GENECODE confidence level 1 to 3 were considered. To remove genes that were lowly expressed, we first calculated the cutoff as 10 read counts per million library size, where the library size was defined as the median library size in the dataset. We then kept genes with expression level (counts per million) equal to or above the cutoff in a minimum number of samples, where the number of samples was chosen according to the minimum group sample size. The data were then normalized by TMM function in edgeR package,109 followed by the limma package with its voom method, linear modeling, and empirical Bayes moderation to assess differential expression.110

Markers of interest were identified by performing a differential-expression analysis using BrainSpan Developmental Transcriptome data. Thalamic structures (mediodorsal nucleus of the thalamus and dorsal thalamus) were compared with all cortical structures. The top 100 up- or down-regulated genes in thalamic vs. cortical structures were identified as “thalamic” or “cortical” markers, respectively.

Deconvolution of bulk RNA-seq data was performed using the VoxHunt (v1.0.1)111 R package using the default workflow (https://quadbio.github.io/VoxHunt/articles/deconvolution.html). Allen Brain Atlas data derived from E13 mouse brain were used as a reference. The “broad” gene set contained the top 50 markers for each region of interest. The top 15 markers were then used as input for the deconvolution tool.

GO term enrichment analysis was performed using g:Profiler.112 For all analyses, a custom background was uploaded containing genes detected in the dataset of interest. Driver terms containing fewer than 300 genes were selected for graphing. All graphs, except heatmaps, were prepared in R using ggplot2 (v3.4.0).113 Heatmaps were prepared using the ComplexHeatmap (v2.10.0) R package.114,115

RT-qPCR

Data were analyzed using the 2−ΔΔCq method [previously known as the 2−ΔΔCt method, first described in the Applied Biosystems User Bulletin 2 (P/N 4303859)].141 Transcripts of interest were normalized first to GAPDH (within sample), then to the mean ΔCq of the hThO samples with high tdTomato that were previously used for bulk RNA-seq. Regression analyses were performed in R using normalized values and graphed using the ggscatter function from ggpubr (v0.5.0). For all transcripts, except FOXG1, r and p were calculated using the Pearson correlation method, where r represents the correlation coefficient and p represents the p-value, and lines were fit using linear regression. Due to the presence of extreme outliers, for FOXG1 the rs and p-value were calculated using the Spearman correlation method, in which rs represents the correlation coefficient, p represents the p-value, and the nonlinear curve is fit using the Loess local polynomial-regression method.

snRNA-seq

Sequences from each Illumina-sequencing dataset were de-multiplexed using bcl2fastq v2.20.0.422 (Illumina). The sequencing data were aligned to the human reference genome GRCh38 (10× Genomics, v2020-A) using the CellRanger “count” algorithm (10× Genomics, v7.0.0); however, the “–force-cells” option was set to the estimated number of cells loaded for each sample (snCBO1: 6,000; snCBO2: 8,000; snTha1: 8,000; snTha2: 10,000). From the gene expression matrix, the downstream analysis was carried out in R (v4.2.1). First, the ambient RNA signal was removed using the default SoupX (v1.6.2) workflow (autoEstCounts and adjustCounts; github.com/constantAmateur/SoupX).116

Each dataset was initially filtered so that genes that were expressed in at least three cells, and cells that expressed at least 200 genes were included. Additionally, cells with fewer than 300 genes (presumed to be droplets or cellular debris), fewer than 500 UMIs, more than 1% unique transcripts derived from mitochondrial genes, or more than 3 median absolute deviations (MADs) from the median number of unique transcripts derived from mitochondrial genes were removed. Afterward, cells with more than 3 MADs from the median number of genes expressed were removed.

Samples were then preprocessed using the standard Seurat (v4.3.0) workflow (NormalizeData, ScaleData, FindVariables, RunPCA, FindNeighbors, FindClusters, and RunUMAP; github.com/satijalab/Seurat).117–120 Datasets were individually log-normalized using Seurat’s NormalizeData with default parameters. Cell cycle scoring was conducted using the associated S- and G2M-phase gene list from Tirosh et al.142 and the CellCycleScoring command in Seurat. We calculated 3000 features exhibiting high cell-to-cell variation in the dataset by using Seurat’s FindVariableFeature function. Next, we scaled the data by linear regression against the number of reads by using Seurat’s ScaleData function with default parameters. The variable genes were projected onto a low-dimensional subspace by performing principal component analysis using Seurat’s RunPCA function with default parameters. The number of principal components (n = 30) was selected based on inspection of the plot of variance explained.

Datasets were integrated using Harmony (v 0.1.1) with default parameters.121 A shared-nearest-neighbor graph was constructed based on the Euclidean distance in the low-dimensional subspace using Seurat’s FindNeighbors with dims = 1:30 and default parameters. Integrated datasets then underwent nonlinear dimensional reduction and visualization using UMAP. Clusters were identified using a resolution of 0.4 and the Leiden algorithm for the integrated datasets. Pseudotime analysis was conducted using Monocle3 (v1.3.1) with default parameters.122–125 Trajectory starting points were manually selected based on the expression of mitotic markers (e.g., MKI67) and/or neural precursor markers (e.g., TNC). Mapping of snRNA-seq datasets onto Allen Brain Atlas and BrainSpan reference datasets was performed using the VoxHunt (1.0.1) R package with the suggested workflows (https://quadbio.github.io/VoxHunt/articles/getting_started.html; https://quadbio.github.io/VoxHunt/articles/other_references.html).111 For Allen Brain Atlas comparisons, data derived from E15 mouse embryos were used. For BrainSpan comparisons, data derived from human fetal tissue 13–24 postconception weeks (pcw) were used. Neural communication patterns were predicted and visualized using the NeuronChat (v1.0.0) R package with the suggested workflow (https://github.com/Wei-BioMath/NeuronChat/blob/main/vignettes/NeuronChat-Tutorial.html).56

Cell types were assigned to each cell/cluster based on marker expression and cell cycle analysis. For hThO annotation, markers of interest were identified based on a comparison to previously published scRNA-seq or snRNA-seq studies in developing mouse thalamus or diencephalon.143,144 Additional markers were identified based on previously published in situ studies examining embryonic rodent thalamus. For example, within the mouse thalamus49 and hThOs, SOX2 is expressed in a subset of postmitotic neurons. For hCO cluster annotation, markers of interest were identified using a previously published scRNA-seq study that examined human neocortex at midgestation.54 Additional markers were identified based on previously published in situ studies examining embryonic rodent cortex.

Electrophysiology

Statistical tests were performed using Prism (Graphpad) or Sigmaplot (Systat) software. Statistical comparisons are noted in the text or figure legends. Unless otherwise noted, distributions were tested for normality (Shapiro-Wilk test) and equal variance (Brown-Forsythe test). If the distribution passed, a paired or unpaired t test was performed. If it failed, a rank-sum test or signed-rank test was performed. To compare more than two distributions, a one-way or repeated-measures ANOVAs was performed. Significance was designated as p < 0.05. All data are presented as the mean ± SEM, and the sample size (n) is presented as the number of cells per the number of assembloids.

Supplementary Material

1

ACKNOWLEDGMENTS

We thank Yiping Fan, Dale Hedges, and Daniel Estevez Prado (St. Jude Center for Applied Bioinformatics) for assistance with bulk RNA-seq analysis; Lawrence Reiter for providing the TP-190a and TP-189 dental pulp stem cells; Sergiu Pasca for providing the 2242, 1205, and 8858 hiPSC lines; Angela McArthur for manuscript editing; and Zakharenko lab members for constructive comments. This work was funded, in part, by the National Institutes of Health grants R01MH097742 and R01DC012833 (S.S.Z.), K99MH129617 (M.H.P.), the Stanford Maternal and Child Health Research Institute Uytengsu-Hamilton 22q11 Neuropsychiatry Research Program grants UH22-QEXTFY21 and UH22QEXTFY23 (S.S.Z.), the National Cancer Institute grant P30CA021765, and the American Lebanese Syrian Associated Charities. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or other granting agencies.

Figure 1. hThOs contain functional glutamatergic thalamic neurons

(A) Reporter cell line validation for hThOs. Top: schematic of TCF7L2 exon 1 in the TP-190a-TCF7L2-tdTomato reporter line. Bottom: VoxHunt deconvolution of bulk RNA-seq data from D69-D70 hThOs using E13 mouse brain data from the Allen Brain Atlas as a reference. TPMs: transcripts per million. n = 27 bulk RNA-seq samples, with each sample derived from 2 to 3 pooled hThOs.

(B) Immunofluorescence images of TCF7L2, TUBB3, OTX2, and SOX2 labeling in D60 hThOs. Nuclei are indicated by DAPI (cyan). TCF7L2-tdTomato fluorescence is indicated in magenta. Images were acquired from serial sections of the same organoid. Scale bars: 200 μm (whole section), 100 μm (insets).

(C) UMAP plot with cluster annotations indicated by color.

(D) VoxHunt mapping of snRNA-seq clusters to BrainSpan reference (human fetal tissue, 13–24 pcw). Excitatory neuron (ExN) clusters exhibit the highest correlations with mediodorsal nucleus of the thalamus (MD). A1C, primary auditory cortex; AMY, amygdala; CB, cerebellum; CBC, cerebellar cortex; DFC, dorsolateral prefrontal cortex; HIP, hippocampus; IPC, posteroventral (interior) parietal cortex; ITC, inferolateral temporal cortex; M1C, primary motor cortex; M1C-S1C, primary motor-sensory cortex; MFC, anterior (rostral) cingulate (medial prefrontal) cortex; OFC, orbital frontal cortex; S1C, primary somatosensory cortex; STC, posterior (caudal) superior temporal cortex; STR, striatum; V1C, primary visual cortex; VFC, ventrolateral prefrontal cortex.

(E) Bar plot showing the number of nuclei per cluster, with clusters indicated by fill color.

(F) UMAP plots of glutamatergic markers SLC17A6 (VGLUT2) and SLC17A7 (VGLUT1). Color indicates normalized transcript level.

(G) VoxHunt correlation analysis mapping clusters ExN1–4 onto the E15 mouse brain.

(H) VoxHunt correlation analysis mapping the PT/ZLI/rTh cluster onto the E15 mouse brain.

(I) UMAP plots of the PT/ZLI/rTh cluster, demonstrating the expression of markers associated with the PT, ZLI, and rTh. Transcript information is indicated by color. The relative locations of these structures within the developing diencephalon are shown in the schematic. cTh, caudal thalamus; eTh, epithalamus; preTh, prethalamus; PT, pretectum; ZLI, zona limitans intrathalamica; rTh, rostral thalamus.

(J) Example traces showing voltage and AP responses to current injections in an hThO cell.

(K) Pseudotime ordering of cells.

(L) UMAP plot of the neural progenitor marker TNC. Color indicates the normalized transcript level.

(M and N) UMAP plots of cell cycle analysis results for the cycling progenitor, radial glia, and glia cell clusters. Color indicates S score (M) or G2M score (N).

(O) UMAP plot of the astrocyte marker GFAP in the cycling progenitor, radial glia, and glia cell clusters. Color indicates the normalized transcript level.

Data in (C)–(I) and (K)–(O) were produced by snRNA-seq analysis of 15,363 nuclei from D90 hThOs. See Figures S1–S3 for additional data validating hiPSC lines and hThOs. See Figure S4 for additional data related to electrophysiological properties and synapses.

Figure 2. Fusing hThOs and hCOs produces assembloids that form reciprocal synapses

(A) Reporter line validation for hCOs. Top: schematic of SLC17A7 (VGLUT1) exon 12 in the TP-190a-VGLUT1-tdTomato reporter line. Bottom: VoxHunt deconvolution of bulk RNA-seq data from D70 hCOs using E13 mouse brain data from the Allen Brain Atlas as a reference. Organoids were visually categorized as positive or negative for tdTomato fluorescence prior to sequencing. The tdTomato RNA level for each sample is indicated in TPMs. Each stacked bar indicates one bulk RNA-seq sample derived from 2 to 3 pooled hCOs.

(B) The snRNA-seq analysis of hCOs. Left: UMAP plot with cluster annotations. ExN, excitatory neuron; DL, deep layer; UL, upper layer; Un., unknown. Right: dot plot showing subplate marker expression by cluster. Avg Exp, normalized average expression; % cells, percentage of cells expressing a marker within a cluster.

(C) VoxHunt analysis mapping hCOs (all clusters) onto the E15 mouse brain.

(D) Pseudotime analysis of the neural cell trajectory (cycling progenitors to UL ExNs, DL ExNs, and subplate/DL ExNs) from hCOs.

(E) UMAP plots of glutamatergic markers SLC17A6 (VGLUT2) and SLC17A7 (VGLUT1). Color indicates normalized transcript level.

(F) Traces showing the voltage and AP responses to current injections in an hCO cell.

(G) Fluorescence and bright-field image of a TC assembloid at 5 days post-fusion (dpf).

(H) Representative fluorescence images for 2-dimensional fusion assay. Thalamic neurons (magenta, right) and cortical neurons (green, left) extend processes from their respective chambers, across the barrier region (dashed yellow lines), and into the opposite chamber starting at D9. Elaborate processes extending from the opposite sides are seen in both halves by D61.

(I) Fluorescence image of an hCO co-transduced with hSyn-GFP and hSyn-V5-Mito-APEX2 lentiviruses.

(J) Schematic and TEM image of an APEX2+ mitochondrion (circled in magenta) in a TC synapse. Pre, presynaptic compartment; post, postsynaptic compartment.

(K) Schematic and TEM image of an APEX2+ mitochondrion (circled in green) in a CT synapse. APEX2– mitochondria are indicated by asterisks (*). Data in (B)–(E) were produced by snRNA-seq analysis of 12,008 nuclei from D90 hThOs.

See Figures S1 and S5 for additional data validating the TP-190a-VGLUT1-tdTomato reporter line and hCOs. See Figure S4 for additional data related to electrophysiological properties and synapses. See Figure S6 for NeuronChat analysis.

Figure 3. Assembloids contain glutamatergic TC and CT synapses

(A) Left: schematic of the recording configuration for the TC pathway. Right: bar graph of the percentage of responsive (green) and unresponsive (gray) cells in 11 assembloids. The numbers of cells recorded per assembloid are shown in white.

(B) Left: schematic of the recording configuration for the CT pathway. Middle: the percentages of hThO cells that responded (magenta) or did not respond (gray) to hCO stimulation across 10 assembloids. Right: bar graph of the average percentage of responsive cells for TC and CT synapses, based on (A) and (B).

(C) Line graph of paired-pulse ratios (PPRs) across five interstimulus intervals (ISIs) in CT (magenta) and TC (green) synapses (one-sample t test: μ = 1, #p < 0.05, ##p < 0.01, n = 18–23 cells/9–13 assembloids [TC], n = 8–24/7–12 [CT]). Differences between CT and TC synapses were evaluated by unpaired t test (**p < 0.01). Inset: sample traces depicting PPRs in CT and TC synapses.

(D) Average TC EPSC amplitude (holding potential [Vh] −70 mV) in the presence of NBQX (3 mM) is decreased compared to control aCSF conditions (paired t test: **p = 0.009, n = 5/2).

(E) The average TC EPSP amplitude (Vh +40 mV) in NBQX and AP5 (50 mM) is lower than in aCSF (paired t test: *p = 0.038, n = 5/3).

(F) Traces of evoked TC AMPAR- and NMDAR-mediated currents in aCSF and in NBQX or NBQX and AP5, respectively.

(G) Average CT EPSC amplitude (Vh −70 mV) in NBQX is decreased compared to aCSF conditions (paired t test: *p = 0.012, n = 5/3).

(H) The average CT EPSC amplitudes (Vh +40 mV) are reduced in NBQX and AP5 compared to aCSF (paired t test: ***p = 0.0006, n = 5/3).

(I) Example traces of evoked CT AMPAR- and NMDAR-mediated currents in aCSF and in NBQX or NBQX and AP5, respectively.

(J) Schematics of two-photon Ca2+ imaging in postsynaptic dendritic spines of hCO cells upon hThO stimulation. Alexa Fluor 594: AF-594 (R), magenta; Fluo-5F (G), green.

(K) Image of an hCO dendrite. Line scans (white line) were performed across a dendritic spine (Sp) and parent dendritic shaft (Sh).

(L) Left: representative changes in G/R of Sp and Sh responses over time to a single synaptic stimulation (arrowhead and black line). Right: representative line scans of Sp (light) and Sh (dark).

(M) Average changes in synaptically evoked G/R (paired t test: **p = 0.002, n = 9/4).

(N) Average changes in synaptically evoked Sp G/R in aCSF and in AP5 (paired t test: *p = 0.018, n = 7/5).

Data in (D), (E), (G), (H), (M), and (N) are shown as the mean values with individual responses overlaid. Grouped data (C) are shown as mean ± SEM. n = cells/assembloids. Circles in (C), (F), and (I) represent stimulus artifacts.

See Figure S7 for snRNA-seq data supporting glutamatergic communication.

Figure 4. TC synapses in assembloids undergo LTP

(A) Left: schematic of the recording configuration. Right, top: 40-Hz electrical stimulation LTP-induction protocol. Right, bottom: representative trace of a response.

(B) Left: time course data demonstrating that 40-Hz stimulation repeated three times (arrows) induces LTP in TC assembloids (n = 9 cells/9 assembloids). Right: representative traces from the first 5 min (1, dark) and final 5 min (2, light) of the experiment.

(C) Bar graph of group data after 40-Hz induction from (B) shows EPSC amplitudes differ from baseline values (one-sample t test, μ = 100 versus full postinduction time period, ##p = 0.0077).

(D) Top: spike-timing-dependent plasticity (STDP) was induced by stimulating presynaptic hThO inputs (Pre) then delivering four current injections (2 nA) to the postsynaptic cell (Post), 50 times. Bottom: representative trace of a response.

(E) Left: time course data demonstrating that the short STDP protocol (arrow) in TC assembloids induces LTP (n = 7/3). Right: representative traces from the first (dark) and final (light) 5 min of the experiment.

(F) Bar graph of group data following the ×1 STDP induction from (E) shows that EPSC amplitudes differ from baseline values (one-sample t test, μ = 100 versus full postinduction time period, #p = 0.04).

(G) Top: long STDP-induction protocol, as in (D) but repeated ×3 every 5 min. Bottom: representative trace of a response.

(H) Bar graph showing the average responses of nine cells from six assembloids after TC LTP induction. Shades of gray indicate different batches of assembloids; vertical lines denote separate assembloids.

(I) Time course of series resistance (Rs) normalized to the 5-min baseline period demonstrating TC LTP is not due to changes in Rs.

(J) Time course demonstrating the 33 STDP protocol (arrows) induces LTP in TC synapses (black, n = 9/6). MPEP (blue, n = 6/5) or iBAPTA blocked LTP (orange, n = 6/4). AP5 did not block TC LTP (green, n = 6/3). Shaded area depicts the presence of bath-applied drugs.

(K) Bar graph of group data following ×3 STDP induction from (J). Differences from baseline were evaluated by one-sample t test (μ = 100 versus full postinduction time period, ##p < 0.01). Differences between treatments and aCSF were evaluated by one-way ANOVA, p < 0.0001. Dunnett’s test: ***p = 0.0001, ****p < 0.0001.

(L) Example traces from the first (1) and final (2) 5 min of the experiment across conditions.

Data shown are mean ± SEM in (B), (E), (I), and (J), with individual data points overlaid as dots in (C), (F), and (K). n = cells/assembloids. Circles in (B), (E), and (L) represent stimulus artifacts.

See Figure S7 for additional supporting data.

Figure 5. CT synapses in assembloids undergo LTP

(A) Left: schematic of the recording configuration. Right: the long (33) STDP-induction protocol and example response.

(B) Bar graph showing the average responses in 14 cells from 9 assembloids after CT LTP induction in aCSF. Colors indicate different batches of assembloids; vertical lines denote separate assembloids.

(C) Time course demonstrating that ×3 STDP delivery (arrows) induces LTP in CT synapses (black, n = 14 cells/9 assembloids). MPEP (blue, n = 8/6), AP5 (green, n = 15/7), or iBAPTA (orange, n = 7/3) blocked LTP. Shaded area depicts the presence of bath-applied drugs. The first (1) and final (2) 5 min of the experiment are noted.

(D) Time course of Rs.

(E) Bar graph of group data from (C). Differences from baseline were evaluated by one-sample t test (μ = 100 versus full postinduction time period, ##p < 0.01). Differences between treatments and aCSF were evaluated by one-way ANOVA, p = 0.0053. Dunnett’s test: **p < 0.01.

(F) Example traces from the first (1) and final (2) 5 min of the experiment across conditions.

Data shown are mean ± SEM in (C), (D), and (E) with individual data points overlaid in (E). n = cells/assembloids.

See Figure S7 for additional supporting data.

Figure 6. TC synapses in assembloids undergo LTD

(A) Left: schematic of the recording configuration to induce TC LTD. Right, top: electrical stimulation was delivered at 1 Hz for 900 pulses. Bottom: example responses to a subset of the 900 pulses; dark-to-light traces depict the responses as the number of pulses progressed (from pulse [p] 1 to p900).

(B) Bar graph showing the average responses of 10 cells from 10 assembloids after TC LTD induction in aCSF. Colors indicate different batches of assembloids; vertical lines denote separate assembloids.

(C) Time course data demonstrating that 1-Hz electrical stimulation (thick dashed line) induces LTD in TC synapses (black, n = 10 cells/10 assembloids). MPEP (blue, n = 7/5), AP5 (green, n = 6/5), or iBAPTA (orange, n = 5/4) blocked LTD. Shaded area depicts the presence of bath-applied drugs. The first (1) and final (2) 5 min of the experiment are noted.

(D) Time course of Rs normalized to the 5-min baseline period.

(E) Bar graph of group data after 1-Hz stimulation from (C). Differences from baseline were evaluated by one-sample t test (μ = 100 versus full postinduction time period, ###p < 0.005). Differences between treatments and aCSF were evaluated by one-way ANOVA, p = 0.0046. Dunnett’s test: **p < 0.01.

(F) Example traces from the first (1) and final (2) 5 min of the experiment across conditions. Circles indicate electrical stimulation.

Data shown are mean ± SEM in (C), (D), and (E), with individual data points overlaid in (E). n = cells/assembloids.

See Figure S7 for additional supporting data.

Figure 7. CT synapses in assembloids undergo LTD

(A) Schematic of the experimental condition for CT LTD induction, the 1-Hz LTD-induction protocol, and an example response.

(B) Bar graph of the average responses of 10 cells from 9 assembloids after CT LTD induction in aCSF. Colors indicate different batches of assembloids; vertical lines denote separate assembloids.

(C) Time course data show that 1-Hz stimulation (thick dashed line) induced LTD in CT synapses (black, n = 10 cells/9 assembloids). MPEP (blue, n = 6/6), AP5 (green, n = 5/4), or iBAPTA (orange, n = 4/4) blocked LTD. Shaded area depicts the presence of bath-applied drugs. The first (1) and final (2) 5 min of the experiment are noted.

(D) Time course of Rs normalized to the 5-min baseline period.

(E) Bar graph of group data after 1-Hz stimulation from (C). Differences from baseline were evaluated by one-sample t test (μ = 100 versus full postinduction time period, ###p < 0.001). Differences between treatments and aCSF were evaluated by one-way ANOVA, p = 0.0004. Dunnett’s test: ***p < 0.001.

(F) Example traces from the first (1) and final (2) 5 min of the experiment across conditions. Circles indicate electrical stimulation.

Data shown are mean ± SEM in (C), (D), and (E), with individual data points overlaid in (E). n = cells/assembloids.

See Figure S7 for additional supporting data.

KEY RESOURCES TABLE REAGENT or RESOURCE	SOURCE	IDENTIFIER	
	
Antibodies	
Rabbit monoclonal anti-TCF7L2	Cell Signaling Technologies	Cat# 2569; RRID:AB_2199816	
Goat polyclonal anti-OTX2	R&D Systems	Cat# AF1979; RRID:AB_2157172	
Chicken polyclonal anti-TUBB3	Abcam	Cat# ab107216; RRID:AB_10899689	
Mouse monoclonal anti-SOX2	R&D Systems	Cat# MAB2018; RRID:AB_358009	
Mouse monoclonal anti-V5	Invitrogen	Cat# R960–25; RRID:AB_2556564	
Rabbit polyclonal anti-FOXP2	Abcam	Cat# ab16046; RRID:AB_2107107	
Rabbit polyclonal anti-LHX2	Sigma	Cat # ABE1402; RRID:AB_2722523	
Goat polyclonal anti-GBX2	R&D Systems	Cat# AF4638; RRID:AB_2109492	
Rabbit polyclonal anti-GABA	Sigma	Cat# A2052; RRID:AB_477652	
Donkey anti-rabbit Alexa Fluor 488	Jackson Immunoresearch	Cat# 711–546-152; RRID:AB_2340619	
Donkey anti-goat Alexa Fluor 647	Jackson Immunoresearch	Cat# 705–606-147; RRID:AB_2340438	
Donkey anti-mouse Alexa Fluor 488	Jackson Immunoresearch	Cat# 715–546-150; RRID:AB_2340849	
Donkey anti-mouse Alexa Fluor 647	Jackson Immunoresearch	Cat# 715–606-150; RRID:AB_2340865	
Donkey anti-chicken Alexa Fluor 647	Jackson Immunoresearch	Cat# 703–606-155; RRID:AB_2340380	
Chemicals, peptides, and recombinant proteins	
DL-AP5	Tocris Bioscience	Cat# 0105	
MPEP hydrochloride	Tocris Bioscience	Cat# 1212	
NBQX disodium salt	Tocris Bioscience	Cat# 1044	
BAPTA tetra-potassium salt	Invitrogen	Cat# B1204	
BAPTA tetra-cesium salt	Invitrogen	Cat# B1212	
Deposited data	
snRNA-seq	This paper	SRA: PRJNA999219	
Bulk RNA-seq	This paper	SRA: PRJNA1001283	
R code for snRNA-seq analysis	This paper	Github: https://github.com/ZakharenkoLab/Thalamic_and_Cortical_Organoid_snRNASeq; Zenodo: https://doi.org/10.5281/zenodo.12559453	
Experimental models: Cell lines	
Human iPSC line TP-190a-TCF7L2-tdTomato	This paper	N/A	
Human iPSC line TP-190a-VGLUT1-tdTomato	This paper	N/A	
Human iPSC line TP-189	This paper	N/A	
Human iPSC line 2242–1	Sloan et al.105	N/A	
Human iPSC line 1205–4	Sloan et al.105	N/A	
Human iPSC line 8858–3	Sloan et al.105	N/A	
Recombinant DNA	
pHR-hSyn-eGFP	Keaveney et al.106	Addgene Plasmid 114215; RRID:Addgene_114215	
Lenti-hSyn-V5-COX4-APEX2	This paper	N/A	
Software and algorithms	
pClamp	Molecular Devices	RRID:SCR_011323	
PrairieView	Bruker	N/A	
Prism	GraphPad	RRID:SCR_002798	
SigmaPlot	Systat	RRID:SCR_003210	
RStudio	Posit	RRID: SCR_000432	
STAR v2.7	Dobin et al.107	RRID: SCR_004463	
RSEM v1.3.1	Li et al.108	RRID: SCR_000262	
edgeR	Robinson et al.109	RRID: SCR_012802	
limma	Ritchie et al.110	RRID: SCR_010943	
VoxHunt v1.0.1	Fleck et al.111	RRID: SCR_023829	
g:Profiler	Raudvere et al.112	RRID: SCR_006809	
ggplot2	Wickham113	RRID: SCR_014601	
ComplexHeatmap v2.10.0	Gu114; Gu et al.115	RRID: SCR_017270	
bcl2fastq v2.20.0.422	Illumina	RRID: SCR_015058	
CellRanger v7.0.0	10xGenomics	RRID: SCR_017344	
SoupX v1.6.2	Young and Behjati116	RRID: SCR_019193	
Seurat v4.3.0	Satija Lab117–120	RRID: SCR_016341	
Harmony v 0.1.1	Korsunsky et al.121	RRID: SCR_022206	
Monocle3 v1.3.1	Trapnell Lab122–125	RRID: SCR_018685	
NeuronChat v1.0.0	Zhao et al.56	N/A	

Highlights

Human thalamic organoids consist of mostly (>80%) glutamatergic projection neurons

Thalamocortical assembloids form reciprocal glutamatergic synapses

Synapses are functional and undergo short-term plasticity resembling animal models

Long-term potentiation and depression reveal mechanisms distinct from rodents

DECLARATION OF INTERESTS

The authors declare no competing interests.

SUPPLEMENTAL INFORMATION

Supplemental information can be found online at https://doi.org/10.1016/j.celrep.2024.114503.
==== Refs
REFERENCES

1. Ryan TJ , and Grant SGN (2009). The origin and evolution of synapses. Nat. Rev. Neurosci. 10 , 701–712. 10.1038/nrn2717.19738623
2. Hensch TK (2004). Critical period regulation. Annu. Rev. Neurosci. 27 , 549–579. 10.1146/annurev.neuro.27.070203.144327.15217343
3. Zha C , and Sossin WS (2022). The molecular diversity of plasticity mechanisms underlying memory: An evolutionary perspective. J. Neurochem. 163 , 444–460. 10.1111/JNC.15717.36326567
4. Szegedi V , Paizs M , Csakvari E , Molnar G , Barzo P , Tamas G , and Lamsa K (2016). Plasticity in single axon glutamatergic connection to GABAergic interneurons regulates complex events in the human neocortex. PLoS Biol. 14 , e2000237. 10.1371/JOURNAL.PBIO.2000237.27828957
5. Ataman B , Boulting GL , Harmin DA , Yang MG , Baker-Salisbury M , Yap EL , Malik AN , Mei K , Rubin AA , Spiegel I , (2016). Evolution of Osteocrin as an activity-regulated factor in the primate brain. Nature 539 , 242–247. 10.1038/NATURE20111.27830782
6. Qiu J , McQueen J , Bilican B , Dando O , Magnani D , Punovuori K , Selvaraj BT , Livesey M , Haghi G , Heron S , (2016). Evidence for evolutionary divergence of activity-dependent gene expression in developing neurons. Elife 5 , e20337. 10.7554/ELIFE.20337.27692071
7. Mould AW , Hall NA , Milosevic I , and Tunbridge EM (2021). Targeting synaptic plasticity in schizophrenia: insights from genomic studies. Trends Mol. Med. 27 , 1022–1032. 10.1016/j.molmed.2021.07.014.34419330
8. Appelbaum LG , Shenasa MA , Stolz L , and Daskalakis Z (2023). Synaptic plasticity and mental health: methods, challenges and opportunities. Neuropsychopharmacology 48 , 113–120. 10.1038/s41386-022-01370-w.35810199
9. Bourgeron T (2015). From the genetic architecture to synaptic plasticity in autism spectrum disorder. Nat. Rev. Neurosci. 16 , 551–563. 10.1038/nrn3992.26289574
10. Goto Y , Yang CR , and Otani S (2010). Functional and Dysfunctional Synaptic Plasticity in Prefrontal Cortex: Roles in Psychiatric Disorders. Biol. Psychiatr. 67 , 199–207. 10.1016/j.biopsych.2009.08.026.
11. Lee K , Park TI-H , Heppner P , Schweder P , Mee EW , Dragunow M , and Montgomery JM (2020). Human in vitro systems for examining synaptic function and plasticity in the brain. J. Neurophysiol. 123 , 945–965. 10.1152/jn.00411.2019.31995449
12. Kanton S , Boyle MJ , He Z , Santel M , Weigert A , Sanchís-Calleja F , Guijarro P , Sidow L , Fleck JS , Han D , (2019). Organoid single-cell genomic atlas uncovers human-specific features of brain development. Nature 574 , 418–422. 10.1038/S41586-019-1654-9.31619793
13. Pollen AA , Bhaduri A , Andrews MG , Nowakowski TJ , Meyerson OS , Mostajo-Radji MA , Di Lullo E , Alvarado B , Bedolli M , Dougherty ML , (2019). Establishing cerebral organoids as models of human-specific brain evolution. Cell 176 , 743–756.e17. 10.1016/J.CELL.2019.01.017.30735633
14. Agoglia RM , Sun D , Birey F , Yoon SJ , Miura Y , Sabatini K , Pașca SP , and Fraser HB (2021). Primate cell fusion disentangles gene regulatory divergence in neurodevelopment. Nature 592 , 421–427. 10.1038/S41586-021-03343-3.33731928
15. Velasco S , Kedaigle AJ , Simmons SK , Nash A , Rocha M , Quadrato G , Paulsen B , Nguyen L , Adiconis X , Regev A , (2019). Individual brain organoids reproducibly form cell diversity of the human cerebral cortex. Nature 570 , 523–527. 10.1038/S41586-019-1289-X.31168097
16. Lancaster MA , Renner M , Martin CA , Wenzel D , Bicknell LS , Hurles ME , Homfray T , Penninger JM , Jackson AP , and Knoblich JA (2013). Cerebral organoids model human brain development and microcephaly. Nature 501 , 373–379. 10.1038/NATURE12517.23995685
17. Mora-Bermúdez F , Badsha F , Kanton S , Camp JG , Vernot B , Köhler K , Voigt B , Okita K , Maricic T , He Z , (2016). Differences and similarities between human and chimpanzee neural progenitors during cerebral cortex development. Elife 5 , e18683. 10.7554/ELIFE.18683.27669147
18. Li Y , Muffat J , Omer A , Bosch I , Lancaster MA , Sur M , Gehrke L , Knoblich JA , and Jaenisch R (2017). Induction of expansion and folding in human cerebral organoids. Cell Stem Cell 20 , 385–396.e3. 10.1016/J.STEM.2016.11.017.28041895
19. Li C , Fleck JS , Martins-Costa C , Burkard TR , Themann J , Stuempflen M , Peer AM , Vertesy Á , Littleboy JB , Esk C , (2023). Single-cell brain organoid screening identifies developmental defects in autism. Nature 621 , 373–380. 10.1038/s41586-023-06473-y.37704762
20. Wulansari N , Darsono WHW , Woo H-J , Chang M-Y , Kim J , Bae E-J , Sun W , Lee J-H , Cho I-J , Shin H , (2021). Neurodevelopmental defects and neurodegenerative phenotypes in human brain organoids carrying Parkinson’s disease-linked DNAJC6 mutations. Sci. Adv. 7 , eabb1540. 10.1126/sciadv.abb1540.33597231
21. Paulsen B , Velasco S , Kedaigle AJ , Pigoni M , Quadrato G , Deo AJ , Adiconis X , Uzquiano A , Sartore R , Yang SM , (2022). Autism genes converge on asynchronous development of shared neuron classes. Nature 602 , 268–273. 10.1038/s41586-021-04358-6.35110736
22. Sebastian R , Jin K , Pavon N , Bansal R , Potter A , Song Y , Babu J , Gabriel R , Sun Y , Aronow B , and Pak C (2023). Schizophrenia-associated NRXN1 deletions induce developmental-timing- and cell-type-specific vulnerabilities in human brain organoids. Nat. Commun. 14 , 3770. 10.1038/s41467-023-39420-6.37355690
23. Notaras M , Lodhi A , Dündar F , Collier P , Sayles NM , Tilgner H , Greening D , and Colak D (2022). Schizophrenia is defined by cell-specific neuropathology and multiple neurodevelopmental mechanisms in patient-derived cerebral organoids. Mol. Psychiatr. 27 , 1416–1434. 10.1038/s41380-021-01316-6.
24. Liu C , Fu Z , Wu S , Wang X , Zhang S , Chu C , Hong Y , Wu W , Chen S , Jiang Y , (2022). Mitochondrial HSF1 triggers mitochondrial dysfunction and neurodegeneration in Huntington’s disease. EMBO Mol. Med. 14 , e15851. 10.15252/emmm.202215851.35670111
25. Kathuria A , Lopez-Lengowski K , Jagtap SS , McPhie D , Perlis RH , Cohen BM , and Karmacharya R (2020). Transcriptomic Landscape and Functional Characterization of Induced Pluripotent Stem Cell-Derived Cerebral Organoids in Schizophrenia. JAMA Psychiatr. 77 , 745–754. 10.1001/jamapsychiatry.2020.0196.
26. Zafeiriou MP , Bao G , Hudson J , Halder R , Blenkle A , Schreiber MK , Fischer A , Schild D , and Zimmermann WH (2020). Developmental GABA polarity switch and neuronal plasticity in Bioengineered Neuronal Organoids. Nat. Commun. 11 , 3791. 10.1038/s41467-020-17521-w.32728089
27. Magee JC , and Grienberger C (2020). Synaptic plasticity forms and functions. Annu. Rev. Neurosci. 43 , 95–117. 10.1146/ANNUREV-NEURO-090919-022842.32075520
28. Reha RK , Dias BG , Nelson CA , Kaufer D , Werker JF , Kolbh B , Levine JD , and Hensch TK (2020). Critical period regulation across multiple timescales. Proc. Natl. Acad. Sci. USA 117 , 23242–23251. 10.1073/PNAS.1820836117.32503914
29. Citri A , and Malenka RC (2008). Synaptic plasticity: multiple forms, functions, and mechanisms. Neuropsychopharmacology 33 , 18–41. 10.1038/SJ.NPP.1301559.17728696
30. Xiang Y , Tanaka Y , Cakir B , Patterson B , Kim K-Y , Sun P , Kang Y-J , Zhong M , Liu X , Patra P , (2019). hESC-Derived Thalamic Organoids Form Reciprocal Projections When Fused with Cortical Organoids. Cell Stem Cell 24 , 487–497.e7. 10.1016/j.stem.2018.12.015.30799279
31. Kim J , Miura Y , Li M-Y , Revah O , Selvaraj S , Birey F , Meng X , Thete MV , Pavlov SD , Andersen J , (2023). Human assembloids reveal the consequences of CACNA1G gene variants in the thalamocortical pathway. Preprint at bioRxiv, 2023.03.15.530726. 10.1101/2023.03.15.530726.
32. Shin D , Kim CN , Ross J , Hennick KM , Wu S-R , Paranjape N , Leonard R , Wang JC , Keefe MG , Pavlovic BJ , (2024). Thalamocortical organoids enable in vitro modeling of 22q11.2 microdeletion associated with neuropsychiatric disorders. Cell Stem Cell 31 , 421–432.e8. 10.1016/j.stem.2024.01.010.38382530
33. Abramson BP , and Chalupa LM (1985). The laminar distribution of cortical connections with the tecto- and cortico-recipient zones in the cat’s lateral posterior nucleus. Neuroscience 15 , 81–95. 10.1016/0306-4522(85)90125-3.4010937
34. Rockland KS , Andresen J , Cowie RJ , and Robinson DL (1999). Single axon analysis of pulvinocortical connections to several visual areas in the Macaque. J. Comp. Neurol. 406 , 221–250. 10.1002/(SICI)1096-9861(19990405)406:2&lt;221::AID-CNE7&gt;3.0.CO;2-K.10096608
35. Halassa MM , and Sherman SM (2019). Thalamocortical circuit motifs: a general framework. Neuron 103 , 762–770. 10.1016/j.neuron.2019.06.005.31487527
36. Nakajima M , and Halassa MM (2017). Thalamic control of functional cortical connectivity. Curr. Opin. Neurobiol. 44 , 127–131. 10.1016/j.conb.2017.04.001.28486176
37. Briggs F , and Usrey WM (2008). Emerging views of corticothalamic function. Curr. Opin. Neurobiol. 18 , 403–407. 10.1016/J.CONB.2008.09.002.18805486
38. Sherman SM (2016). Thalamus plays a central role in ongoing cortical functioning. Nat. Neurosci. 19 , 533–541. 10.1038/NN.4269.27021938
39. Takahashi N , Moberg S , Zolnik TA , Catanese J , Sachdev RNS , Larkum ME , and Jaeger D (2021). Thalamic input to motor cortex facilitates goal-directed action initiation. Curr. Biol. 31 , 4148–4155.e4. 10.1016/J.CUB.2021.06.089.34302741
40. Hwang K , Shine JM , Cole MW , and Sorenson E (2022). Thalamo-cortical contributions to cognitive task activity. Elife 11 , e81282. 10.7554/ELIFE.81282.36537658
41. Saalmann YB , Pinsk MA , Wang L , Li X , and Kastner S (2012). The pulvinar regulates information transmission between cortical areas based on attention demands. Science 337 , 753–756. 10.1126/SCIENCE.1223082.22879517
42. Wimmer RD , Schmitt LI , Davidson TJ , Nakajima M , Deisseroth K , and Halassa MM (2015). Thalamic control of sensory selection in divided attention. Nature 526 , 705–709. 10.1038/NATURE15398.26503050
43. Biane JS , Takashima Y , Scanziani M , Conner JM , and Tuszynski MH (2016). Thalamocortical projections onto behaviorally relevant neurons exhibit plasticity during adult motor learning. Neuron 89 , 1173–1179. 10.1016/J.NEURON.2016.02.001.26948893
44. Audette NJ , Bernhard SM , Ray A , Stewart LT , and Barth AL (2019). Rapid plasticity of higher-order thalamocortical inputs during sensory learning. Neuron 103 , 277–291.e4. 10.1016/J.NEURON.2019.04.037.31151774
45. Scott GA , Liu MC , Tahir NB , Zabder NK , Song Y , Greba Q , and Howland JG (2020). Roles of the medial prefrontal cortex, mediodorsal thalamus, and their combined circuit for performance of the odor span task in rats: analysis of memory capacity and foraging behavior. Learn. Mem. 27 , 67–77. 10.1101/LM.050195.119.31949038
46. Phillips JM , Kambi NA , Redinbaugh MJ , Mohanta S , and Saalmann YB (2021). Disentangling the influences of multiple thalamic nuclei on prefrontal cortex and cognitive control. Neurosci. Biobehav. Rev. 128 , 487–510. 10.1016/J.NEUBIOREV.2021.06.042.34216654
47. Blundon JA , Roy NC , Teubner BJW , Yu J , Eom T-Y , Sample KJJ , Pani A , Smeyne RJ , Han SB , Kerekes RA , (2017). Restoring auditory cortex plasticity in adult mice by restricting thalamic adenosine signaling. Science 356 , 1352–1356. 10.1126/science.aaf4612.28663494
48. Xiang Y , Tanaka Y , Cakir B , Patterson B , Kim K-Y , Sun P , Kang Y-J , Zhong M , Liu X , Patra P , (2019). hESC-derived thalamic organoids form reciprocal projections when fused with cortical organoids. Cell Stem Cell 24 , 487–497.e7. 10.1016/j.stem.2018.12.015.30799279
49. Vue TY , Aaker J , Taniguchi A , Kazemzadeh C , Skidmore JM , Martin DM , Martin JF , Treier M , and Nakagawa Y (2007). Characterization of progenitor domains in the developing mouse thalamus. J. Comp. Neurol. 505 , 73–91. 10.1002/cne.21467.17729296
50. Rai M , Coleman Z , Curley M , Nityanandam A , Platt A , Robles-Murguia M , Jiao J , Finkelstein D , Wang YD , Xu B , (2021). Proteasome stress in skeletal muscle mounts a long-range protective response that delays retinal and brain aging. Cell Metabol. 33 , 1137–1154.e9. 10.1016/J.CMET.2021.03.005.
51. De Gois S , Schä fer MK-H , Defamie N , Chen C , Ricci A , Weihe E , Varoqui H , and Erickson JD (2005). Homeostatic scaling of vesicular glutamate and GABA transporter expression in rat neocortical circuits. J. Neurosci. 25 , 7121–7133. 10.1523/JNEUROSCI.5221-04.2005.16079394
52. Herrmann K , Antonini A , and Shatz CJ (1994). Ultrastructural evidence for synaptic interactions between thalamocortical axons and subplate neurons. Eur. J. Neurosci. 6 , 1729–1742. 10.1111/j.1460-9568.1994.tb00565.x.7874312
53. Viswanathan S , Sheikh A , Looger LL , and Kanold PO (2017). Molecularly Defined Subplate Neurons Project Both to Thalamocortical Recipient Layers and Thalamus. Cerebr. Cortex 27 , 4759–4768. 10.1093/cercor/bhw271.
54. Polioudakis D , de la Torre-Ubieta L , Langerman J , Elkins AG , Shi X , Stein JL , Vuong CK , Nichterwitz S , Gevorgian M , Opland CK , (2019). A single-cell transcriptomic atlas of human neocortical development during mid-gestation. Neuron 103 , 785–801.e8. 10.1016/j.neuron.2019.06.011.31303374
55. Kanold PO , and Luhmann HJ (2010). The subplate and early cortical circuits. Annu. Rev. Neurosci. 33 , 23–48. 10.1146/annurev-neuro-060909-153244.20201645
56. Zhao W , Johnston KG , Ren H , Xu X , and Nie Q (2023). Inferring neuron-neuron communications from single-cell transcriptomics through NeuronChat. Nat. Commun. 14 , 1128. 10.1038/s41467-023-36800-w.36854676
57. Monko T , Rebertus J , Stolley J , Salton SR , and Nakagawa Y (2022). Thalamocortical axons regulate neurogenesis and laminar fates in the early sensory cortex. Proc. Natl. Acad. Sci. USA 119 , e2201355119. 10.1073/pnas.2201355119.35613048
58. Sato H , Hatakeyama J , Iwasato T , Araki K , Yamamoto N , and Shimamura K (2022). Thalamocortical axons control the cytoarchitecture of neocortical layers by area-specific supply of VGF. Elife 11 , e67549. 10.7554/eLife.67549.35289744
59. Gerstmann K , Pensold D , Symmank J , Khundadze M , Hübner CA , Bolz J , and Zimmer G (2015). Thalamic afferents influence cortical progenitors via ephrin A5-EphA4 interactions. Development (Camb.) 142 , 140–150. 10.1242/dev.104927.
60. Saleem A , Santos AC , Aquilino MS , Sivitilli AA , Attisano L , and Carlen PL (2023). Modelling hyperexcitability in human cerebral cortical organoids: Oxygen/glucose deprivation most effective stimulant. Heliyon 9 , e14999. 10.1016/j.heliyon.2023.e14999.37089352
61. Wu W , Yao H , Dwivedi I , Negraes PD , Zhao HW , Wang J , Trujillo CA , Muotri AR , and Haddad GG (2020). Methadone Suppresses Neuronal Function and Maturation in Human Cortical Organoids. Front. Neurosci. 14 , 593248. 10.3389/fnins.2020.593248.33328864
62. Khan TA , Revah O , Gordon A , Yoon S-J , Krawisz AK , Goold C , Sun Y , Kim CH , Tian Y , Li M-Y , (2020). Neuronal defects in a human cellular model of 22q11.2 deletion syndrome. Nat. Med. 26 , 1888–1898. 10.1038/s41591-020-1043-9.32989314
63. Zhang Q , Lee W-CA , Paul DL , and Ginty DD (2019). Multiplexed peroxidase-based electron microscopy labeling enables simultaneous visualization of multiple cell types. Nat. Neurosci. 22 , 828–839. 10.1038/s41593-019-0358-7.30886406
64. Beierlein M , and Connors BW (2002). Short-term dynamics of thalamocortical and intracortical synapses onto layer 6 neurons in neocortex. J. Neurophysiol. 88 , 1924–1932.12364518
65. Rose HJ , and Metherate R (2005). Auditory thalamocortical transmission is reliable and temporally precise. J. Neurophysiol. 94 , 2019–2030.15928054
66. Bayazitov IT , Westmoreland JJ , and Zakharenko SS (2013). Forward suppression in the auditory cortex is caused by the Ca(v)3.1 calcium channel-mediated switch from bursting to tonic firing at thalamocortical projections. J. Neurosci. 33 , 18940–18950. 10.1523/JNEUROSCI.3335-13.2013.24285899
67. Viaene AN , Petrof I , and Sherman SM (2011). Properties of the thalamic projection from the posterior medial nucleus to primary and secondary somatosensory cortices in the mouse. Proc. Natl. Acad. Sci. USA 108 , 18156–18161. 10.1073/pnas.1114828108.22025694
68. Gil Z , Connors BW , and Amitai Y (1999). Efficacy of thalamocortical and intracortical synaptic connections: quanta, innervation, and reliability. Neuron 23 , 385–397.10399943
69. Stratford KJ , Tarczy-Hornoch K , Martin KA , Bannister NJ , and Jack JJ (1996). Excitatory synaptic inputs to spiny stellate cells in cat visual cortex. Nature 382 , 258–261.8717041
70. Beierlein M , Fall CP , Rinzel J , and Yuste R (2002). Thalamocortical bursts trigger recurrent activity in neocortical networks: layer 4 as a frequency-dependent gate. J. Neurosci. 22 , 9885–9894.12427845
71. Richardson RJ , Blundon JA , Bayazitov IT , and Zakharenko SS (2009). Connectivity patterns revealed by mapping of active inputs on dendrites of thalamorecipient neurons in the auditory cortex. J. Neurosci. 29 , 6406–6417. 10.1523/JNEUROSCI.0258-09.2009.19458212
72. Debanne D , and Inglebert Y (2023). Spike timing-dependent plasticity and memory. Curr. Opin. Neurobiol. 80 , 102707. 10.1016/j.conb.2023.102707.36924615
73. Feldman DE (2012). The spike-timing dependence of plasticity. Neuron 75 , 556–571. 10.1016/j.neuron.2012.08.001.22920249
74. Dan Y , and Poo MM (2004). Spike timing-dependent plasticity of neural circuits. Neuron 44 , 23–30.15450157
75. Collingridge GL , Peineau S , Howland JG , and Wang YT (2010). Long-term depression in the CNS. Nat. Rev. Neurosci. 11 , 459–473. 10.1038/NRN2867.20559335
76. Jo J , Xiao Y , Sun AX , Cukuroglu E , Tran HD , Göke J , Tan ZY , Saw TY , Tan CP , Lokman H , (2016). Midbrain-like Organoids from Human Pluripotent Stem Cells Contain Functional Dopaminergic and Neuromelanin-Producing Neurons. Cell Stem Cell 19 , 248–257. 10.1016/j.stem.2016.07.005.27476966
77. Miura Y , Li M-Y , Birey F , Ikeda K , Revah O , Thete MV , Park J-Y , Puno A , Lee SH , Porteus MH , and Pașca SP (2020). Generation of human striatal organoids and cortico-striatal assembloids from human pluripotent stem cells. Nat. Biotechnol. 38 , 1421–1430. 10.1038/s41587-020-00763-w.33273741
78. Pasca AM , Sloan SA , Clarke LE , Tian Y , Makinson CD , Huber N , Kim CH , Park JY , O’Rourke NA , Nguyen KD , (2015). Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture. Nat. Methods 12 , 671–678. 10.1038/nmeth.3415.26005811
79. Muguruma K , Nishiyama A , Kawakami H , Hashimoto K , and Sasai Y (2015). Self-organization of polarized cerebellar tissue in 3D culture of human pluripotent stem cells. Cell Rep. 10 , 537–550. 10.1016/j.celrep.2014.12.051.25640179
80. Sakaguchi H , Kadoshima T , Soen M , Narii N , Ishida Y , Ohgushi M , Takahashi J , Eiraku M , and Sasai Y (2015). Generation of functional hippocampal neurons from self-organizing human embryonic stem cell-derived dorsomedial telencephalic tissue. Nat. Commun. 6 , 8896. 10.1038/ncomms9896.26573335
81. Mariani J , Coppola G , Zhang P , Abyzov A , Provini L , Tomasini L , Amenduni M , Szekely A , Palejev D , Wilson M , (2015). FOXG1-Dependent Dysregulation of GABA/Glutamate Neuron Differentiation in Autism Spectrum Disorders. Cell 162 , 375–390. 10.1016/j.cell.2015.06.034.26186191
82. Lüscher C , and Malenka RC (2012). NMDA receptor-dependent long-term potentiation and long-term depression (LTP/LTD). Cold Spring Harbor Perspect. Biol. 4 , a005710. 10.1101/cshperspect.a005710.
83. Pisani A , Gubellini P , Bonsi P , Conquet F , Picconi B , Centonze D , Bernardi G , and Calabresi P (2001). Metabotropic glutamate receptor 5 mediates the potentiation of N-methyl-D-aspartate responses in medium spiny striatal neurons. Neuroscience 106 , 579–587. 10.1016/s0306-4522(01)00297-4.11591458
84. Benquet P , Gee CE , and Gerber U (2002). Two distinct signaling pathways upregulate NMDA receptor responses via two distinct metabotropic glutamate receptor subtypes. J. Neurosci. 22 , 9679–9686. 10.1523/JNEUROSCI.22-22-09679.2002.12427823
85. Heidinger V , Manzerra P , Wang XQ , Strasser U , Yu S-P , Choi DW , and Behrens MM (2002). Metabotropic glutamate receptor 1-induced upregulation of NMDA receptor current: mediation through the Pyk2/Src-family kinase pathway in cortical neurons. J. Neurosci. 22 , 5452–5461. 10.1523/JNEUROSCI.22-13-05452.2002.12097497
86. Fox K , Schlaggar BL , Glazewski S , and O’Leary DD (1996). Glutamate receptor blockade at cortical synapses disrupts development of thalamocortical and columnar organization in somatosensory cortex. Proc. Natl. Acad. Sci. USA 93 , 5584–5589. 10.1073/pnas.93.11.5584.8643619
87. Schlaggar BL , Fox K , and O’Leary DD (1993). Postsynaptic control of plasticity in developing somatosensory cortex. Nature 364 , 623–626. 10.1038/364623a0.8102476
88. Itami C , Huang J-Y , Yamasaki M , Watanabe M , Lu H-C , and Kimura F (2016). Developmental switch in spike timing-dependent plasticity and cannabinoid-dependent reorganization of the thalamocortical projection in the barrel Cortex. J. Neurosci. 36 , 7039–7054. 10.1523/JNEUROSCI.4280-15.2016.27358460
89. Crair MC , and Malenka RC (1995). A critical period for long-term potentiation at thalamocortical synapses. Nature 375 , 325–328. 10.1038/375325a0.7753197
90. Chun S , Bayazitov IT , Blundon JA , and Zakharenko SS (2013). Thalamocortical long-term potentiation becomes gated after the early critical period in the auditory cortex. J. Neurosci. 33 , 7345–7357. 10.1523/JNEUROSCI.4500-12.2013.23616541
91. Castro-Alamancos MA , and Calcagnotto ME (1999). Presynaptic long-term potentiation in corticothalamic synapses. J. Neurosci. 19 , 9090–9097. 10.1523/JNEUROSCI.19-20-09090.1999.10516326
92. Feldman DE , Nicoll RA , Malenka RC , and Isaac JT (1998). Long-term depression at thalamocortical synapses in developing rat somatosensory cortex. Neuron 21 , 347–357. 10.1016/s0896-6273(00)80544-9.9728916
93. Kiral FR , Cakir B , Tanaka Y , Kim J , Yang WS , Wehbe F , Kang Y-J , Zhong M , Sancer G , Lee S-H , (2023). Generation of ventralized human thalamic organoids with thalamic reticular nucleus. Cell Stem Cell 30 , 677–688.e5. 10.1016/j.stem.2023.03.007.37019105
94. Antón-Bolaños N , Sempere-Ferràndez A , Guillamón-Vivancos T , Martini FJ , Pérez-Saiz L , Gezelius H , Filipchuk A , Valdeolmillos M , and López-Bendito G (2019). Prenatal activity from thalamic neurons governs the emergence of functional cortical maps in mice. Science 364 , 987–990. 10.1126/science.aav7617.31048552
95. Amiri A , Coppola G , Scuderi S , Wu F , Roychowdhury T , Liu F , Pochareddy S , Shin Y , Safi A , Song L , (2018). Transcriptome and epigenome landscape of human cortical development modeled in organoids. Science 362 , eaat6720. 10.1126/science.aat6720.30545853
96. Hensch TK (2005). Critical period plasticity in local cortical circuits. Nat. Rev. Neurosci. 6 , 877–888. 10.1038/nrn1787.16261181
97. Patton MH , Blundon JA , and Zakharenko SS (2019). Rejuvenation of plasticity in the brain: opening the critical period. Curr. Opin. Neurobiol. 54 , 83–89. 10.1016/j.conb.2018.09.003.30286407
98. Zhang LI , Bao S , and Merzenich MM (2001). Persistent and specific influences of early acoustic environments on primary auditory cortex. Nat. Neurosci. 4 , 1123–1130. 10.1038/nn745.11687817
99. Wei JR , Hao ZZ , Xu C , Huang M , Tang L , Xu N , Liu R , Shen Y , Teichmann SA , Miao Z , and Liu S (2022). Identification of visual cortex cell types and species differences using single-cell RNA sequencing. Nat. Commun. 13 , 6902. 10.1038/s41467-022-34590-1.36371428
100. Letinic K , and Rakic P (2001). Telencephalic origin of human thalamic GABAergic neurons. Nat. Neurosci. 4 , 931–936. 10.1038/nn0901-931.11528425
101. Bakken TE , van Velthoven CT , Menon V , Hodge RD , Yao Z , Nguyen TN , Graybuck LT , Horwitz GD , Bertagnolli D , Goldy J , (2021). Single-cell and single-nucleus RNA-seq uncovers shared and distinct axes of variation in dorsal LGN neurons in mice, non-human primates, and humans. Elife 10 , e64875. 10.7554/eLife.64875.34473054
102. Xue JR , Mackay-Smith A , Mouri K , Garcia MF , Dong MX , Akers JF , Noble M , Li X , Zoonomia C† , Lindblad-Toh K , (2023). The functional and evolutionary impacts of human-specific deletions in conserved elements. Science 380 , eabn2253. 10.1126/science.abn2253.37104592
103. Bayés À , Collins MO , Croning MDR , van de Lagemaat LN , Choudhary JS , and Grant SGN (2012). Comparative Study of Human and Mouse Postsynaptic Proteomes Finds High Compositional Conservation and Abundance Differences for Key Synaptic Proteins. PLoS One 7 , e46683. 10.1371/journal.pone.0046683.23071613
104. Jiang Y , Patton MH , and Zakharenko SS (2021). A case for thalamic mechanisms of schizophrenia: perspective from modeling 22q11.2 deletion syndrome. Front. Neural Circ. 15 , 769969. 10.3389/fncir.2021.769969.
105. Sloan SA , Darmanis S , Huber N , Khan TA , Birey F , Caneda C , Reimer R , Quake SR , Barres BA , and Paşca SP (2017). Human astrocyte maturation captured in 3D cerebral cortical spheroids derived from pluripotent stem cells. Neuron 95 , 779–790.e6. 10.1016/j.neuron.2017.07.035.28817799
106. Keaveney MK , Tseng H-A , Ta TL , Gritton HJ , Man H-Y , and Han X (2018). A microRNA-based gene-targeting tool for virally labeling interneurons in the rodent cortex. Cell Rep. 24 , 294–303. 10.1016/j.celrep.2018.06.049.29996091
107. Dobin A , Davis CA , Schlesinger F , Drenkow J , Zaleski C , Jha S , Batut P , Chaisson M , and Gingeras TR (2013). STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29 , 15–21. 10.1093/bioinformatics/bts635.23104886
108. Li B , and Dewey CN (2011). RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinf. 12 , 323. 10.1186/1471-2105-12-323.
109. Robinson MD , McCarthy DJ , and Smyth GK (2010). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26 , 139–140. 10.1093/bioinformatics/btp616.19910308
110. Ritchie ME , Phipson B , Wu D , Hu Y , Law CW , Shi W , and Smyth GK (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43 , e47. 10.1093/nar/gkv007.25605792
111. Fleck JS , Sanchís-Calleja F , He Z , Santel M , Boyle MJ , Camp JG , and Treutlein B (2021). Resolving organoid brain region identities by mapping single-cell genomic data to reference atlases. Cell Stem Cell 28 , 1148–1159.e8. 10.1016/j.stem.2021.02.015.33711282
112. Raudvere U , Kolberg L , Kuzmin I , Arak T , Adler P , Peterson H , and Vilo J (2019). g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update). Nucleic Acids Res. 47 , W191–W198. 10.1093/NAR/GKZ369.31066453
113. Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag).
114. Gu Z (2022). Complex heatmap visualization. iMeta 1 , e43. 10.1002/imt2.43.38868715
115. Gu Z , Eils R , and Schlesner M (2016). Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 32 , 2847–2849. 10.1093/bioinformatics/btw313.27207943
116. Young MD , and Behjati S (2020). SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data. GigaScience 9 , giaa151. 10.1093/gigascience/giaa151.33367645
117. Hao Y , Hao S , Andersen-Nissen E , Mauck WM , Zheng S , Butler A , Lee MJ , Wilk AJ , Darby C , Zager M , (2021). Integrated analysis of multimodal single-cell data. Cell 184 , 3573–3587.e29. 10.1016/j.cell.2021.04.048.34062119
118. Stuart T , Butler A , Hoffman P , Hafemeister C , Papalexi E , Mauck WM , Hao Y , Stoeckius M , Smibert P , and Satija R (2019). Comprehensive integration of single-cell data. Cell 177 , 1888–1902.e21. 10.1016/j.cell.2019.05.031.31178118
119. Butler A , Hoffman P , Smibert P , Papalexi E , and Satija R (2018). Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36 , 411–420. 10.1038/nbt.4096.29608179
120. Satija R , Farrell JA , Gennert D , Schier AF , and Regev A (2015). Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol. 33 , 495–502. 10.1038/nbt.3192.25867923
121. Korsunsky I , Millard N , Fan J , Slowikowski K , Zhang F , Wei K , Baglaenko Y , Brenner M , Loh P-R , and Raychaudhuri S (2019). Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 16 , 1289–1296. 10.1038/s41592-019-0619-0.31740819
122. Trapnell C , Cacchiarelli D , Grimsby J , Pokharel P , Li S , Morse M , Lennon NJ , Livak KJ , Mikkelsen TS , and Rinn JL (2014). The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32 , 381–386. 10.1038/nbt.2859.24658644
123. Qiu X , Mao Q , Tang Y , Wang L , Chawla R , Pliner HA , and Trapnell C (2017). Reversed graph embedding resolves complex single-cell trajectories. Nat. Methods 14 , 979–982. 10.1038/nmeth.4402.28825705
124. Qiu X , Hill A , Packer J , Lin D , Ma Y-A , and Trapnell C (2017). Single-cell mRNA quantification and differential analysis with Census. Nat. Methods 14 , 309–315. 10.1038/nmeth.4150.28114287
125. Cao J , Spielmann M , Qiu X , Huang X , Ibrahim DM , Hill AJ , Zhang F , Mundlos S , Christiansen L , Steemers FJ , (2019). The single-cell transcriptional landscape of mammalian organogenesis. Nature 566 , 496–502. 10.1038/s41586-019-0969-x.30787437
126. Tsankov AM , Akopian V , Pop R , Chetty S , Gifford CA , Daheron L , Tsankova NM , and Meissner A (2015). A qPCR ScoreCard quantifies the differentiation potential of human pluripotent stem cells. Nat. Biotechnol. 33 , 1182–1192. 10.1038/nbt.3387.26501952
127. Assou S , Girault N , Plinet M , Bouckenheimer J , Sansac C , Combe M , Mianné J , Bourguignon C , Fieldes M , Ahmed E , (2020). Recurrent genetic abnormalities in human pluripotent stem cells: definition and routine detection in culture supernatant by targeted droplet digital PCR. Stem Cell Rep. 14 , 1–8. 10.1016/j.stemcr.2019.12.004.
128. Baker D , Hirst AJ , Gokhale PJ , Juarez MA , Williams S , Wheeler M , Bean K , Allison TF , Moore HD , Andrews PW , and Barbaric I (2016). Detecting genetic mosaicism in cultures of human pluripotent stem cells. Stem Cell Rep. 7 , 998–1012. 10.1016/j.stemcr.2016.10.003.
129. Martins-Taylor K , Nisler BS , Taapken SM , Compton T , Crandall L , Montgomery KD , Lalande M , and Xu R-H (2011). Recurrent copy number variations in human induced pluripotent stem cells. Nat. Biotechnol. 29 , 488–491. 10.1038/nbt.1890.21654665
130. Nishino K , Toyoda M , Yamazaki-Inoue M , Fukawatase Y , Chikazawa E , Sakaguchi H , Akutsu H , and Umezawa A (2011). DNA methylation dynamics in human induced pluripotent stem cells over time. PLoS Genet. 7 , e1002085. 10.1371/journal.pgen.1002085.21637780
131. Johannesson B , Sagi I , Gore A , Paull D , Yamada M , Golan-Lev T , Li Z , LeDuc C , Shen Y , Stern S , (2014). Comparable frequencies of coding mutations and loss of imprinting in human pluripotent cells derived by nuclear transfer and defined factors. Cell Stem Cell 15 , 634–642. 10.1016/j.stem.2014.10.002.25517467
132. Norrie JL , Nityanandam A , Lai K , Chen X , Wilson M , Stewart E , Griffiths L , Jin H , Wu G , Orr B , (2021). Retinoblastoma from human stem cell-derived retinal organoids. Nat. Commun. 12 , 4535. 10.1038/s41467-021-24781-7.34315877
133. Sentmanat MF , Peters ST , Florian CP , Connelly JP , and Pruett-Miller SM (2018). A survey of validation strategies for CRISPR-Cas9 editing. Sci. Rep. 8 , 888. 10.1038/s41598-018-19441-8.29343825
134. Connelly JP , and Pruett-Miller SM (2019). CRIS.py: a versatile and high-throughput analysis program for CRISPR-based genome editing. Sci. Rep. 9 , 4194. 10.1038/s41598-019-40896-w.30862905
135. Chen Y , Tristan CA , Chen L , Jovanovic VM , Malley C , Chu P-H , Ryu S , Deng T , Ormanoglu P , Tao D , (2021). A versatile polypharmacology platform promotes cytoprotection and viability of human pluripotent and differentiated cells. Nat. Methods 18 , 528–541. 10.1038/s41592-021-01126-2.33941937
136. Miller JD , Ganat YM , Kishinevsky S , Bowman RL , Liu B , Tu EY , Mandal PK , Vera E , Shim J , Kriks S , (2013). Human iPSC-based modeling of late-onset disease via progerin-induced aging. Cell Stem Cell 13 , 691–705. 10.1016/j.stem.2013.11.006.24315443
137. Matson KJE , Sathyamurthy A , Johnson KR , Kelly MC , Kelley MW , and Levine AJ (2018). Isolation of adult spinal cord nuclei for massively parallel single-nucleus RNA sequencing. J. Vis. Exp. 140 , 58413. 10.3791/58413.
138. Martell JD , Deerinck TJ , Lam SS , Ellisman MH , and Ting AY (2017). Electron microscopy using the genetically encoded APEX2 tag in cultured mammalian cells. Nat. Protoc. 12 , 1792–1816. 10.1038/nprot.2017.065.28796234
139. Garad M , Edelmann E , and Leßmann V (2021). Impairment of spike-timing-dependent plasticity at Schaffer collateral-CA1 synapses in adult APP/PS1 mice depends on proximity of Ab plaques. Int. J. Mol. Sci. 22 , 1378. 10.3390/ijms22031378.33573114
140. Blundon JA , Bayazitov IT , and Zakharenko SS (2011). Presynaptic gating of postsynaptically expressed plasticity at mature thalamocortical synapses. J. Neurosci. 31 , 16012–16025. 10.1523/JNEUROSCI.3281-11.2011.22049443
141. Livak KJ , and Schmittgen TD (2001). Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25 , 402–408. 10.1006/meth.2001.1262.11846609
142. Tirosh I , Izar B , Prakadan SM , Wadsworth MH , Treacy D , Trombetta JJ , Rotem A , Rodman C , Lian C , Murphy G , (2016). Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352 , 189–196. 10.1126/science.aad0501.27124452
143. Govek KW , Chen S , Sgourdou P , Yao Y , Woodhouse S , Chen T , Fuccillo MV , Epstein DJ , and Camara PG (2022). Developmental trajectories of thalamic progenitors revealed by single-cell transcriptome profiling and Shh perturbation. Cell Rep. 41 , 111768. 10.1016/j.celrep.2022.111768.36476860
144. Guo Q , and Li JYH (2019). Defining developmental diversification of diencephalon neurons through single cell gene expression profiling. Development 146 , dev174284. 10.1242/dev.174284.30872278
