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The autism-associated gene SYNGAP1 regulates human cortical neurogenesis

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The autism-associated gene SYNGAP1 regulates human cortical neurogenesis

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Content Copyright 2023 Ashley Nicol Del Dosso
The autism-associated gene SYNGAP1 regulates human cortical
neurogenesis

By

Ashley Del Dosso

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(DEVELOPMENT, STEM CELLS, AND REGENERATIVE MEDICINE)

December 2023

ii

Acknowledgements

First and foremost, I would like to thank my mentor, Dr. Giorga Quadrato for her guidance
throughout my graduate career. Her encouragement has pushed my growth as a scientist
tremendously and I will be forever grateful for that.

I would like to thank my friends, specifically Rosanna and Ariel, for their unwavering support as
I navigated this process. I would also like to thank my partner, Taylor, who has made such a
difference in my life during the latter portion of my graduate career. Whether it be handling meal
prep and cleaning when there were early mornings and late nights or being a shoulder to cry on
when things got a little too stressful, I cannot thank him enough and I am anxious to see where
the next chapter of my career will take us. My family has also been instrumental in my success,
providing me with the confidence and security to take on the endeavor of a doctoral degree. My
lab mates, J.P. and Alec, have been a wonderful emotional and intellectual support network as
well and I could not have thrived in the lab without them.

Lastly, I would like to thank my committee members Marcelo Coba, Justin Ichida and Jianfu
Chen. Their generosity in time and resources lent to me throughout this process has been
overwhelming. Their academic guidance and unique perspectives on my work have taken it to a
level I never thought possible.

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Table of Contents

Acknowledgements ...................................................................................................................... ii
List of Figures............................................................................................................................. iv
Abstract ...................................................................................................................................... v
Chapter 1: Introduction .............................................................................................................. 1
SYNGAP1 Related Intellectual Disability ................................................................................. 1
The Role of ASD Risk Genes Across Developmental Timelines and Distinct Cell Types .............. 7
Stem cell derived brain organoids to model human brain development. ....................................10
Methods for elucidation of cell type specific developmental trajectories ....................................13
Thesis Goals ..............................................................................................................................19
Chapter 2: The autism associated gene SynGAP1 regulates human cortical neurogenesis .............20
Abstract .................................................................................................................................20
Introduction ...........................................................................................................................21
Results ...................................................................................................................................24
SYNGAP1 is expressed in human ventricular radial glia and colocalizes with the tight junction
protein TJP1 .................................................................................................................................................................. 24
SYNGAP1 plays a role in the cytoskeletal organization in hRGCs ....................................................... 26
SYNGAP1 haploinsufficiency disrupts the organization of the developing cortical plate ........... 28
SYNGAP1 haploinsufficiency affects the division mode of human radial glial progenitors ....... 29
Decrease in SYNGAP1 levels leads to asynchronous cortical neurogenesis in vitro and in vivo.
............................................................................................................................................................................................. 31
Syngap haploinsufficient organoids exhibit accelerated maturation of cortical projection
neurons. ........................................................................................................................................................................... 32
Discussion ..............................................................................................................................34
Figures ...................................................................................................................................39
Chapter 3. Future Directions ......................................................................................................70
The role of SYNGAP1 in the developing human cerebellum .....................................................70
Tools for tracing the lineage of distinct progenitor cell types through development. ..................77
Conclusions ...............................................................................................................................80
References .................................................................................................................................83
Appendices ................................................................................................................................94
Methods and Materials ...........................................................................................................94

iv

List of Figures

Figure 5-1. Mechanism of action for SYNGAP1 in the post synaptic density ............................... 1
Figure 5-2. SYNGAP1 mutations are highly heterogenous and do not exhibit genotype to
phenotype correlation...................................................................................................................... 7
Figure 5-3. Development-inspired strategies to recapitulate early human brain regionalization. 10
Figure 5-4. Accessibility and available experimental readouts for organoid models ................... 13
Figure 7-1 ...................................................................................................................................... 21
Figure 7-2. SynGAP1 is expressed in human radial glial progenitors and colocalizes with the
tight junction protein TJP1............................................................................................................ 39
Figure 7-3. SYNGAP1 plays a role in the cytoskeletal organization of human radial glia. ......... 41
Figure 7-4. SYNGAP1 haploinsufficiency disrupts the organization of the developing cortical
plate. .............................................................................................................................................. 44
Figure 7-5. SYNGAP1 affects the division mode of human radial glial progenitors. .................. 48
Figure 7-6. Decrease in SYNGAP1 levels lead to asynchronous corticogenesis. ........................ 50
Figure 7-7. SYNGAP1organoids exhibit accelerated maturation of cortical projection neurons. 52
Figure S7-8................................................................................................................................... 56
Figure S7-9.................................................................................................................................... 58
Figure S7-10.................................................................................................................................. 59
Figure S7-11.................................................................................................................................. 61
Figure S7-12.................................................................................................................................. 63
Figure S7-13.................................................................................................................................. 65
Figure S7-14.................................................................................................................................. 68
Figure 8-1 ...................................................................................................................................... 70
Figure 8-2. In-vitro development and characterization of human iPSC derived cerebellar
organoids. ...................................................................................................................................... 72
Figure 8-3. Deciphering the developmental trajectory of distinct cell types of the cerebellum. .. 73
Figure 8-4. SYNGAP1 haploinsufficient cerebellar neurons display a more mature state. ......... 75
Figure 8-5 ...................................................................................................................................... 77

v

Abstract
Autism spectrum disorder (ASD) is a genetically heterogeneous disorder linked with rare,
inherited and de novo mutations occurring in two main functional gene categories: gene
expression regulation and synaptic function. Accumulating evidence points to dysregulation in
cortical neurogenesis as a convergent mechanism in ASD pathophysiology. While asynchronous
development has been identified as a shared feature among ASD-risk genes in the category of
gene expression regulation, it remains unknown whether this phenotype is also associated with
ASD-risk genes in the synaptic function category. The recent advent of human derived brain
organoids has allowed for the longitudinal modeling of neurodevelopmental diseases while
preserving the patient’s unique genetic architecture. In this thesis, I present our efforts to show
the expression and function of the synaptic Ras GTP-ase activating protein 1 (SYNGAP1), one
of the top ASD risk genes, in human cortical progenitors (hCPs) using a human brain organoid
model system. Using this model, we were able to demonstrate key neurodevelopmental
phenotypes associated with SYNGAP1 haploinsufficiency. Overall, the discovery of the
expression and function of SYNGAP1 in cortical progenitor cells reframes our understanding of
the pathophysiology of SYNGAP1-related disorders and, more broadly, underscores the
importance of dissecting the role of synaptic genes associated with neurodevelopmental
disorders in distinct cell types across developmental stages.

1
Chapter 1: Introduction
SYNGAP1 Related Intellectual Disability
Figure 0-1. Mechanism of action for SYNGAP1 in the post synaptic density
2

Under normal conditions the induction of neuronal activity causes a dispersion of SYNGAP from the MAGUK
scaffold. This dispersion releases the ‘brake’ that SYNGAP has on the RAS mediated signaling cascade. Once this
brake is released RAS goes on to activate the Raf/Rac/MEK/ERK signaling cascades leading to actin polymerization
and the addition of AMPA receptors to the membrane, promoting long term potentiation. When SYNGAP levels are
reduced this RAS activated pathway continues unchecked, despite fluctuations in neuronal activity leading to
occluded LTP. This figure is adapted from (Gamache, Araki et al. 2020)

Autism Spectrum Disorder (ASD) is a genetically and phenotypically heterogeneous
neurodevelopmental disorder. Comorbidities such as Intellectual Disability (ID), Developmental
Delay (DD), and Epilepsy are common among ASD patients ((Khachadourian, Mahjani et al.
2023). Symptoms of these disorders may present at birth or in the years following shortly after
and can potentially have a devastating effect on patients' lives. The prevalence of ASD is on the
rise globally, currently affecting roughly 4% of the world’s population (Baio, Wiggins et al.
2018). While there have been major recent scientific breakthroughs in understanding the
pathophysiology of these disorders, there has been little development in clinical interventions,
mainly due to the genetic complexity of ASD and the lack of a relevant human specific model
system. There are many risk factors implicated in the development of ASD including both
environmental and genetic. Among the genetic risk factors there are two major categories of risk
genes, those belonging to the functional category of neuronal transmission and those belonging
to the functional category of gene expression regulation (De Rubeis, He et al. 2014). While
dysregulation in the latter has been shown to contribute to asynchronous neurogenesis (Mariani,
Coppola et al. 2015, Schafer, Paquola et al. 2019, Urresti, Zhang et al. 2021, Jourdon, Wu et al.
2022, Paulsen, Velasco et al. 2022, Villa, Cheroni et al. 2022), the role of the former has been
less well characterized, leaving a large gap in knowledge. SYNGAP1 is a major autism risk gene
belonging to the category of neuronal transmission (Satterstrom, Kosmicki et al. 2020). The
characterization of SYNGAP1 as an ASD risk gene has been limited to its role in the post
synaptic density of mature glutamatergic neurons. Throughout this section I aim to briefly
3

describe the currently known functions of SYNGAP1 at the PSD and the resulting clinical
manifestations of SYNGAP1 mutations.
Within the brain, information is transferred from one neuron to another by the diffusion of
neurotransmitters at the junction of two neurons, termed the synapse. The release of
neurotransmitters from the pre-synaptic neuron is the result of electrical activity, or an action
potential. These released neurotransmitters are then taken up by appropriate receptors at the post
synaptic dendritic membrane and facilitate the modulation of downstream signaling networks
capable of changing the structure and function of the neuron. The repetition of this process can
lead to the enlargement of the dendritic spine and the addition of receptors to the membrane, a
process known as long-term potentiation (LTP) (Nicoll 2017).
There is a high degree of regulation within biological signaling networks, involving many
governing proteins. A key upstream protein in many signaling networks are small GTPases
which serve as a molecular on/off switch depending on whether they are bound to GTP or GDP,
respectively (Bourne, Sanders et al. 1990). The propensity of a GTPase to have bound GDP or
GTP is dependent on the activity nucleotide exchange factors (GEFs) which promote the binding
of GTP and GTPase-activating proteins which promote the hydrolysis of GTP to form GDP. To
appropriately regulate the large number of small GTPases there exist a multitude of GAPs and
GEFs capable of responding to a variety of stimuli and directing their output to a specific small
GTPases (Raaijmakers and Bos 2009, Cherfils and Zeghouf 2013).
SYNGAP1 is a Ras/Rap GTPase activating protein (GAP) abundant at the post synaptic
density of excitatory glutamatergic neurons and has been identified as a major autism risk gene
(Chen, Rojas-Soto et al. 1998, Kim, Liao et al. 1998, Satterstrom, Kosmicki et al. 2020). It
functions as both a scaffolding protein and as a signal transducer, having the ability to bind PSD-
4

95 and SAP-102, key scaffolding proteins of the PSD that are physically linked to N-methyl D-
aspartate receptors (NMDARs), which together form a key signaling complex (Chen, Rojas-Soto
et al. 1998, Kim, Liao et al. 1998).
SYNGAP1 is a complex protein that regulates and is regulated by several large signaling
networks. SYNGAP1 has the ability to dually regulate Ras and Rap small GTPases whose roles
in neuronal physiology have opposing effects. While Ras is activated by NMDAR-dependent
CaMKII activation, Rap is activated by lower levels of Ca2+ influx and promotes the removal of
AMPARs from the synapse (Zhu, Qin et al. 2002). In turn, the GAP activity of SYNGAP can be
altered by port translational modifications, mainly by phosphorylation at roughly 20 distinct sites
by several synaptic protein kinases (Walkup, Mastro et al. 2016). The phosphorylation of these
sites by CaMKII favors Rap1 GAP activity over Ras GAP activity (Walkup, Mastro et al. 2016),
while phosphorylation of SYNGAP by CDK5 produces the opposite effect. Additionally, when
Polo-like kinase 2 (Plk2) phosphorylates SYNGAP, GAP activity towards H-Ras is favored over
Rap1 (Walkup Ward G. 2018).
The SynGAP protein is expressed in various structural isoforms due to differential
transcriptional start sites and post-transcriptional processing (Li, Okano et al. 2001). These
isoforms display individual brain-region and cell-type specific expression profiles. Three N-
terminal isoforms (A-C) have been identified and result from alternative transcriptional start site
usage, while at least four C-terminal SynGAP splice variants (α1, α2, β, and γ) are currently
known (Li, Okano et al. 2001). SynGAP isoforms display distinct distribution patterns in
neuronal subcellular compartments and differentially regulate synaptic strength in cultured
neurons (McMahon, Barnett et al.). The mechanisms underlying these differences remain
unclear, however it has been shown that the α1 isoform is the only isoform that contains the C-
5

terminal PBM, which allows SynGAP to bind PDZ-domain-containing MAGUK family proteins
in the PSD, allowing for its high degree of enrichment at the PSD of excitatory glutamatergic
neurons as compared to other isoforms (Li, Okano et al. 2001).
Under normal baseline conditions, SYNGAP1 remains associated with PSD-95 at the
post synaptic density and carries out its GAP activity, serving to limit the degree of Ras/Rac
activity and their related downstream pathways. However, when there is sufficient calcium influx
after depolarization calmodulin-dependent protein kinase II (CaMKII) becomes activated and is
then able to phosphorylate SYNGAP1 thereby decreasing the affinity of SYNGAP1 for PSD-95
and prompting the rapid dispersion of SYNGAP1 from the PSD (Araki, Zeng et al. 2015). The
resulting absence of SYNGAP1 from the PSD allows for Ras and Rac mediated signaling
pathways to continue without obstruction leading to activation of downstream signaling
pathways involving Erk and mTOR which function to promotes protein synthesis and the
trafficking of α-amino-3-hydroxyl-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) to
the synapse (Zhu, Qin et al. 2002, Rumbaugh, Adams et al. 2006, Wang, Held et al. 2013). The
increased presence and activity of AMPARs at the synaptic membrane after persistent synaptic
activity is indicative of synaptic maturation and promotes long term potentiation (LTP) while in
turn suppressing synaptic plasticity. In the case of SYNGAP1 halploinsufficiency, which is a
common result of many pathogenic SYNGAP1 variants, the continuous lack of SYNGAP1 and
therefore continuously elevated Ras and Rac signaling pathways leads to erroneous induction of
LTP (Figure 5-1). This loss of synaptic plasticity can adversely affect neuronal signaling
networks and may be able to explain, in part, the prevalence of seizures in SYNGAP1 patients.
SYNGAP1 mutations are almost exclusively de novo and currently account for roughly
1% of all genetic cases of intellectual disability (Hamdan, Gauthier et al. 2009, Berryer, Hamdan
6

et al. 2013). There are a wide array of reported pathogenic variants (Figure 5-2), most leading to
haploinsufficiency of the protein, yet there has been no identified genotype to phenotype
correlation. Despite a patient’s particular genotype, they can present with an array of symptoms
with varying degrees of severity (Jimenez-Gomez, Niu et al. 2019, Zhang H 2021). These
symptoms can include intellectual disability, autism spectrum disorder, global developmental
delay, behavioral disorders, and seizures. There is currently no treatment for SYNGAP1 aside
from the treatment of individual symptoms through behavioral therapy and targeted
pharmaceutical intervention. Because of the complex nature of the SYNAP1 signaling network
the current therapeutic focus for SYNGAP1 treatment is in promoting increased expression of
SYNGAP1 through gene therapy (Creson, Rojas et al. 2019).

7

SYNGAP1 mutations are generally de novo and comprise a wide variety of pathogenic alterations to the gene
including splice mutations frame shifted mutations, and nonsense mutations that often lead to truncation of the
protein. All SYNGAP1 patients, regardless of their mutation, present with varying degrees of intellectual disability
and developmental delay. A subgroup of patients additionally present with either seizures, autism spectrum disorder
(ASD) or both. To date, characterization of patient genetics and clinical presentations has not identified and
genotype to phenotype correlation. This figure is adapted from (Zhang H 2021) and shows the genotype and clinical
phenotype of 13 SYNGAP1 patients.
The Role of ASD Risk Genes Across Developmental Timelines and Distinct
Cell Types
Accumulating evidence points to dysregulation in cortical neurogenesis as a convergent
mechanism in Autism Spectrum Disorder (ASD) pathophysiology (De Rubeis, He et al. 2014,
Mariani, Coppola et al. 2015, Jourdon, Wu et al. 2022, Paulsen, Velasco et al. 2022, Villa,
Cheroni et al. 2022). Many human genetic studies of neurodevelopmental diseases including
ASD have found enrichment of mutations in genes encoding classically defined synaptic proteins
(Camp, Badsha et al. 2015, Quadrato, Nguyen et al. 2017, Velasco, Kedaigle et al. 2019,
Trevino, Sinnott-Armstrong et al. 2020, Wang, Zhang et al. 2020, De Jong, Llapashtica et al.
2021, Gordon, Yoon et al. 2021) Currently, most studies of Syngap and other postsynaptic
proteins have been done in rodent models and within the context of mature synapses (Gamache,
Araki et al. 2020). Indeed, the lack of a reliable model to study the stage-specific functions of
ASD risk genes during human brain development has limited our understanding of their
functional role, confining it to rudimentary functional categories.
Recently there has been interest in the contribution of classically defined synaptic proteins
to the proliferation and differentiation of neural progenitors during early stages of corticognesis
and their potential contribution to neurodevelopmental disorders within this context. A recent
study in xenopus has supported to idea of SYNGAP1, along with several other neuronally
Figure 0-2. SYNGAP1 mutations are highly heterogenous and do not exhibit genotype to
phenotype correlation.
8

associated large effect autism genes, as contributing to convergent vulnerability during
neurogenesis. It was additionally revealed that the region’s most highly affected during the
neurogenic period were the cortical plate and subventricular zone. Within these regions, after
SYNGAP1 knocked via CRISPR, there was a significant reduction in both ventricle size and
telencephalon size, suggesting that processes related to proliferation and differentiation are
adversely affected during early stages of neurogenesis (Willsey, Exner et al. 2021). This data
further highlights the dual role of SYNGAP1 within progenitor and neuronal populations and
reaffirms the need to assess the spatiotemporal contributions of autism risk genes. In line with
these findings, another recent study in a murine model has identified DLGAP4, a membrane-
associated guanylate kinase found at the postsynaptic density of neuronal cells, as a regulator of
ventricle organization and radial glial progenitor migration (Romero, Poirier et al. 2022).
Interestingly, DLGAP4 belongs to a membrane-associated guanylate kinase family known to
function in glutamatergic synapses and like SYNGAP1, associates with the Membrane
Associated Guanylate Kinase (MAGUK) superfamily. The proper functioning of synapses relies
heavily on the precise spatial organization of the presynaptic and postsynaptic apparatuses, as
well as the close alignment of their respective membrane compartments. To achieve this specific
arrangement, cells employ a protein network situated in the submembrane region, which is
constructed around scaffold proteins. Among these scaffold proteins, the membrane-associated
guanylate kinase (MAGUK) family stands out as a highly expressed and evolutionarily
conserved group that plays a fundamental role in the establishment and control of this
scaffolding process (C, P et al. 2012, Chen, Levy et al. 2015, Oliva and Sierralta 2018) .
Considering the importance of this protein interaction network at the synapse and the potential
conservation of this network in radial glial progenitors, further interrogation of the
9

spatiotemporal roles of these proteins across diverse human genetic background will be
imperative to better understand the origins of neurodevelopmental disorders.

Currently there have been several human genetic studies of neurodevelopmental disorders
that have found enrichment of mutations in genes encoding PSD proteins(Kirov, Pocklington et
al. 2012, O’Roak, Vives et al. 2012, Peça and Feng 2012, De Rubeis, He et al. 2014, Fromer,
Pocklington et al. 2014, Genovese, Fromer et al. 2016, Satterstrom, Kosmicki et al. 2020). In the
synapses of the adult mouse brain, Syngap is a major hub in the PSD PIN, and proteins
associated with NDD are Syngap protein interactors

(Wilkinson, Li et al. 2017). During my pre-
doctoral studies using human iPSC derived brain organoids I found expression of multiple
components of the postsynaptic density in my proteomic analysis and have shown that some of
those proteins are interactors of Syngap in cortical progenitors. It is tempting to speculate that the
complex controlling structural integrity at the PSD of excitatory neurons is also important in
regulating the scaffolding properties of human radial glia. Radial glia, particularly apical radial
glia, give rise to additional progenitor cells, including intermediate progenitors found in the
subventricular zone (SVZ), as well as basal RGs (bRGs) predominantly located in the outer
SVZ(Götz and Huttner 2005). Because of the affect radial glial cells can impart on all cell
derived from them, future studies will be imperative to characterize whether disruption of
proteins classically considered important for maintenance of the PSD scaffold in neurons may
represent a point of convergence for neurodevelopmental disorders in humans.
10

Stem cell derived brain organoids to model human brain development.
Protocols for human brain organoid generation take inspiration from in vivo patterning processes to recapitulate
aspects of brain development in a dish. Morphogen gradients within the neural tube are critical in determining the
rostro-caudal and dorsal-ventral axis of the developing brain and contribute to the formation of discrete
regionalization. Several key signaling centers present in the neural tube including the Roof Plate (RP) and Floor
Plate (FP) are a prominent source of BMP (bone morphogenic protein), WNT and SHH (sonic hedgehog),
respectively. Brain organoids can now be generated that are reminiscent of specific brain regions including
organoids of the dorsal and ventral forebrain, hippocampus, hypothalamus, anterior pituitary, thalamus, midbrain,
cerebellum, midbrain and spinal cord.

Human brain development occurs in a tightly regulated series of events governed by long-range
morphogen-driven gradients combined with local cell-cell and cell-extracellular matrix (ECM)
interactions that continuously evolve through positive and negative feedback regulation over the
course of gestation. These complex and intricate regulatory networks allow for the formation of
discrete structures and cellular stratification that contribute to the vast processing power of the
human brain. Complex neurodevelopmental disorders have been notoriously difficult to study
due to lack of available postmortem human tissue, the simplicity of 2D cultures and the inability
Figure 0-3. Development-inspired strategies to recapitulate early human brain
regionalization.
11

to fully recapitulate human disorders in animal models. Brain organoids have recently emerged
as a human specific alternative model for the tractable interrogation of developmental processes.
Human brain organoids are human pluripotent stem cell (hPSC)-derived self-organizing 3D
structures that resemble the developing human fetal brain. Protocols for human brain organoid
generation have taken inspiration from in vivo patterning processes to recapitulate
neurodevelopment in a dish (Figure 5-3). Current organoid protocols are divided into two major
categories, patterned and self-patterned. Generally, in both approaches, dissociated PSCs are
aggregated into 3D spheres or embryoid bodies to generate self-organizing 3D neuroectodermal
structures. Self-patterned protocols utilize basic fibroblast growth factor (bFGF) and retinoic acid
during hPSC reaggregation to generate whole-brain organoids. These protocols leverage the
default bias of early ectoderm to generate dorsal forebrain fates (Espuny-Camacho, Michelsen et
al. 2013). Patterned protocols have been shown to improve regional accuracy and cellular
reproducibility have emerged as a widely used alternative in the field. A unifying characteristic
among most patterned protocols is an initial inhibition of the SMAD pathway (Chambers, Fasano
et al. 2009). The SMAD family of proteins act as signal transducers downstream of TGF-β
superfamily ligand binding to promote the generation of epidermis over neural ectoderm.
Patterned protocols have generally employed the use of partial or dual SMAD inhibition through
administration of small-molecule inhibitors of the TGF-β type I receptor and/or administration of
inhibitors that target the activity of bone morphogenetic proteins (BMPs). Additionally, WNT
inhibition during early stages of organoid generation is often employed to repress the
mesodermal lineage and, in turn, promote the production of anterior neuroectoderm (ten Berge,
Koole et al. 2008). Despite patterning and culturing differences, cortical organoids across
protocols can develop neural-tube-like neuroepithelial structures that follow a similar temporal
12

developmental trajectory as in vivo. These structures give rise to a diverse range of cortical cell
types as seen in the endogenous human forebrain including, inner and outer radial glia,
intermediate progenitors, deep- and upper-layer cortical neurons, astroglia, and oligodendroglia
precursor cells. Cortical organoids are widely used because of their relevance to human
neurodevelopmental disorders, as defects in higher-order cognitive abilities predominately stem
from dysregulation within this brain region.
The ability of these organoids to recapitulate the key developmental aspects of diverse cell types
from regions of the brain highly susceptible to NDDs makes them an ideal model system.
Additionally, this system is able to maintain a patient’s unique genetic background while being
amenable to genetic manipulation and large samples sizes. These advantages have allowed for
the interrogation of human specific mechanisms of NDD etiology and pathophysiology through
the interrogation of organoids carrying a variety of NDD associated mutations including those
implicated in Autism Spectrum Disorder (ASD), Bipolar Disorder (BD) Rett Syndrome (RTT)
and Fragile X Syndrome (FXS) (Mariani, Coppola et al. 2015, Mellios, Feldman et al. 2018,
Schafer, Paquola et al. 2019, Gomes, Fernandes et al. 2020, Sawada, Chater et al. 2020, Xiang,
Tanaka et al. 2020, De Jong, Llapashtica et al. 2021, Kang, Zhou et al. 2021, Urresti, Zhang et al.
2021) .

13

Methods for elucidation of cell type specific developmental trajectories

Figure 0-4. Accessibility and available experimental readouts for organoid models
Organoid systems allow for the longitudinal tracking of cell fate and functionality. Because of its in vitro nature, the
tissue generated is easily accessible and can be removed from culture for fixation and further processing at the
researcher’s discretion, preserving tissue quality.

Over the past decade, there has been incredible momentum within the field of brain organoids
that has led to the establishment and improvement of a wide variety of protocols for their
generation. As brain organoids have become more complex, the technology used to analyze them
has been appropriately matched in complexity. Classical techniques that provide transcriptional
information, such as bulk RNA sequencing (RNA-seq) and qPCR, have been used extensively to
characterize organoids but do not provide enough resolution to resolve the complexity of human
brain development (Figure 5-4). As technology has progressed, single-cell resolution at the
functional and molecular level has been achieved. Single-cell RNA-seq (scRNAseq), in
particular, has been used extensively to characterize brain organoids across protocols and in
reference to the developing fetal brain (Birey, Andersen et al. 2017, Quadrato, Nguyen et al.
2017, Xiang, Tanaka et al. 2017, Madhavan, Nevin et al. 2018, Tanaka, Tanaka et al. 2018,
Cakir, Xiang et al. 2019, Giandomenico, Mierau et al. 2019, Kanton, Boyle et al. 2019, Klaus,
14

Kanton et al. 2019, Marton, Miura et al. 2019, Pollen, Bhaduri et al. 2019, Velasco, Kedaigle et
al. 2019, Xiang, Tanaka et al. 2019, Bhaduri, Sandoval-Espinosa et al. 2021, Eze, Bhaduri et al.
2021). These studies have demonstrated cellular diversity in patterned and self-patterned brain
organoid protocols (as reviewed in (Atamian, Cordón-Barris et al. 2021). Brain organoids give us
for the first time the opportunity to investigate the emergence of cellular diversity and lineage
relationships in human tissue. With scRNA-seq, several computational approaches have been
developed to infer lineage relationships based on transcriptomic high-dimensional data. A
detailed comparison of these methods and guidelines for users was recently provided by(Saelens,
Cannoodt et al. 2019). In brain organoids, several papers have implemented different iterations
of the Monocle package to construct pseudotime trajectories (Camp, Badsha et al. 2015, Marton,
Miura et al. 2019, Velasco, Kedaigle et al. 2019, Ziffra, Kim et al. 2021). As these computational
approaches rely on making inferences, combining single cell sequencing with lineage tracing
systems would improve the robustness of future cell lineage findings and allow for direct tracing
of neuronal ontogeny within organoids. Broadly speaking, lineage tracing techniques can be
categorized by their tagging system. Currently cell ontogeny can be traced based on somatic
mutations, reporter systems, cell barcoding, and dynamic lineage tracing (Frieda, Linton et al.
2017, Alemany, Florescu et al. 2018, Chatterjee, Sullivan et al. 2018, Raj, Wagner et al. 2018,
Spanjaard, Hu et al. 2018, Mckenna and Gagnon 2019). A detailed description of the advantages
and considerations of emerging lineage tracing approaches that can be combined with scRNA-
seq are reviewed by (Wagner and Klein 2020). Recently, scRNA-seq has been combined with an
inducible CRISPR/Cas9-based barcoding system to reconstruct dynamic lineage trees within
microdissected self-patterned organoids for the first time. This elegant approach, called iTracer
(He, Maynard et al. 2022), integrates the sleeping beauty transposon system (Ivics, Hackett et al.
15

1997) with an inducible iCRISPR system (González, Zhu et al. 2014). Using this approach,
progenitor-neuron lineage relationships were reconstructed revealing a clonal accumulation bias
of iPSCs towards distinct brain regions. Ideally, in the future similar approaches will emerge and
become commonplace for the analysis of patterned organoids in healthy and disease states.
Similarly, just as lineage tracing can be leveraged to determine neuronal ontogeny, spatial
transcriptomics will allow for the probing of cellular spatial relationships during human brain
organoid development. Several techniques that incorporate fluorescence in situ hybridization
have emerged to identify and spatially resolve specific transcripts at the single cell level
(Codeluppi, Borm et al. 2018, Salmén, Ståhl et al. 2018, Wang, Moffitt et al. 2018, Eng, Lawson
et al. 2019, Chen, Lu et al. 2020). Recently, the 10X Visium platform was used to perform
spatial transcriptomics of iTracer (barcoded and scarred) cells within cerebral organoids (He,
Maynard et al. 2022). This analysis confirmed previously discussed findings of iPSC clonal bias
in distinct brain organoid regions and marks the first use of spatial transcriptomics in the brain
organoid field. The future incorporation of spatial registration combined with transcriptomic and
epigenomic techniques will be critical in the analysis of brain organoids as they do not
reproducibly recapitulate in vivo stereotypic anatomy.
Refinement of culture conditions has allowed for the protracted development of
organoids and opened the door to understanding the functional physiological properties of
neurons within organoids. Dendritic spines and structurally defined synaptic connections have
been identified in both patterned and self-patterned protocols suggesting that 3D cultures favor
the development of structural features characteristic of mature neurons. Given the presence of
these mature neuronal populations, it is unsurprising that brain organoids can develop
spontaneous neural network activity as evidenced by calcium fluxes as well as intracellular and
16

extracellular recordings (Mariani, Coppola et al. 2015, Muguruma, Nishiyama et al. 2015, Paşca,
Sloan et al. 2015, Sakaguchi, Kadoshima et al. 2015, Jo, Xiao et al. 2016, Qian, Nguyen et al.
2016, Birey, Andersen et al. 2017, Quadrato, Nguyen et al. 2017, Cakir, Xiang et al. 2019,
Marton, Miura et al. 2019, Song, Yuan et al. 2019, Qian, Su et al. 2020). Whole-cell patch-
clamp, voltage clamp, and current clamp have been utilized extensively to characterize neurons
in organoids, typically in sliced cultures or organoid edges where functional connectivity
between neurons has been detected (Mariani, Coppola et al. 2015, Muguruma, Nishiyama et al.
2015, Paşca, Sloan et al. 2015, Sakaguchi, Kadoshima et al. 2015, Qian, Nguyen et al. 2016,
Birey, Andersen et al. 2017, Xiang, Tanaka et al. 2017, Marton, Miura et al. 2019, Smits,
Reinhardt et al. 2019, Song, Yuan et al. 2019, Qian, Su et al. 2020). Though intracellular patch-
clamp provides important information on the electrical properties and functional connectivity of
neurons, it is not a high throughput approach, which is necessary to comprehensively
characterize the complex neuronal network behaviour for the large number of neuronal subtypes
present in organoids. The standard microelectrode arrays (MEAs) approach for extracellular
recordings of in vitro assays uses planar electrodes arranged in grids. While these 2D MEAs are
useful for detecting spikes in mono-layers and have been used extensively in the organoid field,
they are limited to capturing the activity of neurons in the outer layers of the organoid
(Giandomenico, Mierau et al. 2019, Schmunk, Kim et al. 2020). High density silicon
microelectrodes are an emerging technology that allows for insertion of probes into 3D tissue
and can provide single cell resolution by leveraging the simultaneous recordings of each ‘spike’,
across multiple spatially distributed channels, to improve the clustering of ‘spikes’ that originate
from the same neuron. Simultaneously, it is also possible to record network burst activity
indicated by recordings of neurons in multiple probes that fire coordinated bursts of action
17

potentials in a temporal manner. In Quadrato et al (2017) this technology has been successfully
used to characterize network behaviour in 8 months old self-patterning brain organoids.
However, this technology is difficult to implement for high throughput experiments that require
simultaneous recording of multiple organoids. Several studies have used calcium indicators to
record transient calcium waves that arise during depolarization (Lancaster, Renner et al. 2013,
Sakaguchi, Kadoshima et al. 2015, Birey, Andersen et al. 2017, Lancaster, Corsini et al. 2017,
Xiang, Tanaka et al. 2017, Park, Wetzel et al. 2018, Xiang, Tanaka et al. 2019, Samarasinghe,
Miranda et al. 2021). Calcium imaging is more amenable to large scale studies as compared to
MEA technology and represents a powerful tool for the extraction of temporal information on
neuronal firing patterns. However, currently there is no effective method to monitor the activity
of a large number of neurons over long periods of time in organoids although this has been
accomplished in vivo. Typically, imaging is performed at the organoid surface, yet with two-
photon and light-sheet microscopy it is possible to acquire data from deeper organoid layers and
eventually perform 4D imaging (Chen, Legant et al. 2014, Lavagnino, Sancataldo et al. 2016,
Schöneberg, De Lorenzi et al. 2018) Lineage tracking of early formed embryoid bodies (EBs)
was recently performed using 4D light-sheet microscopy to visualize how single nuclei give rise
to spatially restricted daughter cells, which only migrate short distances from parent cells (He,
Maynard et al. 2022). The development of miniscopes to perform long-term calcium imaging in
freely moving rodents, suggest the exciting possibility that similar approaches could be adapted
to perform much needed long-term recordings of neuronal activity in organoids (Gonzalez,
Zhang et al. 2019). The major drawback compared to other techniques result from the decaying
dynamics of the calcium indicators and resolving signal over noise, which becomes increasingly
difficult to distinguish at single-cell resolution as neuronal firing rates increase. A powerful yet
18

low-throughput technique that enables correlation of transcriptomic and functional data at the
single cell level to simultaneously combine functional and molecular profiling of neurons is
Patch-seq (Cadwell, Palasantza et al. 2016, van den Hurk M 2018) which combines whole-cell
patch-clamp recordings with scRNA-seq and morphological characterization. This recently
developed method, in which a single neuron can be targeted by a microelectrode, recorded for its
electrical function and thereafter aspired and prepared for sequencing, is critical for investigating
how electrophysiological properties in neurons correlate to cell subtype specific transcriptomes.
Application of this powerful technique to the analysis of brain organoids will provide the field
with much needed understanding of the molecular determinants of human neuronal diversity and
it will facilitate and improve the classification of neural cell types across different stages of
neural development in a human cellular context. This knowledge will also be pivotal for the cell-
type specific characterization of disease states.

19

Thesis Goals
In this thesis I am to reveal the presence and function of SYNGAP1 in human cortical
progenitors. When I first joined Georgia’s laboratory, I began working with our collaborators Dr.
Marcelo Coba and Dr. Brent Wilkinson to generate SYNGAP1 patient iPSC derived brain
organoids. Using this model system, we discovered that SYNGAP1 is expressed within the
apical domain of human radial glia cells (hRGCs) where it lines the wall of the developing
cortical ventricular zone colocalizing with the tight junction-associated protein and MAGUK
family member TJP1. Additionally, through immunohistochemistry (IHC), RNA sequencing and
proteomics we show dysregulated cytoskeletal dynamics that impair the scaffolding and division
plane of hRGCs. This altered division mode resulted in disrupted lamination of the cortical plate
and accelerated maturation of cortical projection neurons, shown through electrophysiological
experiments lead by Dr. Birtele.
In summary, with great help and support from my mentor Dr. Giorgia Quadrato and my co-
author Dr. Marcella Birtele, we have identified the presence of SYNGAP1 in human cortical
progenitors and discovered that within this cell type SYNGAP1 functions as a regulator of
cytoskeletal dynamics. These findings highlight important aspects of disease pathology and the
pleiotropic nature of synaptic proteins, providing insight for the future development of
therapeutics.

20

Chapter 2: The autism associated gene SynGAP1 regulates human cortical
neurogenesis
Abstract
Autism spectrum disorder (ASD) is a genetically heterogeneous disorder linked with rare,
inherited and de novo mutations occurring in two main functional gene categories: gene
expression regulation and synaptic function (De Rubeis, He et al. 2014). Accumulating evidence
points to dysregulation in cortical neurogenesis as a convergent mechanism in ASD
pathophysiology

(Mariani, Coppola et al. 2015, Schafer, Paquola et al. 2019, De Jong,
Llapashtica et al. 2021, Urresti, Zhang et al. 2021, Jourdon, Wu et al. 2022, Paulsen, Velasco et
al. 2022, Villa, Cheroni et al. 2022). While asynchronous development has been identified as a
shared feature among ASD-risk genes in the category of gene expression regulation, it remains
unknown whether this phenotype is also associated with ASD-risk genes in the synaptic function
category. Here we show for the first time the expression of the synaptic Ras GTP-ase activating
protein 1 (SYNGAP1), one of the top ASD risk genes (Satterstrom, Kosmicki et al. 2020), in
human cortical progenitors (hCPs). Interestingly, we found that multiple components of the
postsynaptic density (PSD) of excitatory synapses, of which SYNGAP1 is one of the most
abundant components (Chen, Rojas-Soto et al. 1998, Kim, Liao et al. 1998), are enriched in the
proteome of hCPs. Specifically, we discover that SYNGAP1 is expressed within the apical
domain of human radial glia cells (hRGCs) where it lines the wall of the developing cortical
ventricular zone colocalizing with the tight junction-associated protein and MAGUK family
member TJP1. In a cortical organoid model of SYNGAP1 haploinsufficiency, we show
dysregulated cytoskeletal dynamics that impair the scaffolding and division plane of hRGCs,
resulting in disrupted lamination of the cortical plate and accelerated maturation of cortical
projection neurons. Overall, the discovery of the expression and function of SYNGAP1 in
21

cortical progenitor cells reframes our understanding of the pathophysiology of SYNGAP1-
related disorders and, more broadly, underscores the importance of dissecting the role of synaptic
genes associated with neurodevelopmental disorders in distinct cell types across developmental
stages.

Graphical Abstract

Figure 0-1
Introduction
Exome sequencing analyses have identified two major functional categories of genes
associated with Autism Spectrum Disorder (ASD): gene expression regulation and synaptic
function

(De Rubeis, He et al. 2014). SYNGAP1 is a top ASD genetic risk factor (Satterstrom,
Kosmicki et al. 2020) and one of the most abundant proteins found at the postsynaptic density
22

(PSD) of excitatory synapses (Chen, Rojas-Soto et al. 1998, Kim, Liao et al. 1998). Within the
PSD, SYNGAP1 functions as a RAS GTPase-activating (RASGAP) protein that regulates
synaptic plasticity (Chen, Rojas-Soto et al. 1998, Kim, Liao et al. 1998, Komiyama, Watabe et
al. 2002, Zhu, Qin et al. 2002, Kim, Lee et al. 2003, Araki, Zeng et al. 2015). Through its
RASGAP domain, SYNGAP1 limits the activity of the mitogen-activated protein kinase 1
(Mapk1/Erk2), whereas through its PDZ-binding domain, SYNGAP1 helps assemble the core
scaffold machinery of the PSD (Walkup, Mastro et al. 2016, Zeng, Shang et al. 2016, Kilinc M
2022). Despite its classification as a synaptic protein, several lines of evidence suggest a
potential role for SYNGAP1 at early stages of cortical neurogenesis. First, homozygous deletion
of Syngap1 in embryonic mice leads to early developmental lethality (Knuesel, Elliott et al.
2005). Second, decreased syngap1 levels have been shown to affect the ratios of neural
progenitor cells to mature neurons in Xenopus tropicalis (Willsey, Exner et al. 2021). Third,
disruption of the Syngap1 signaling complex in embryonic mice results in deficits in the
tangential migration of GABAergic interneurons (Su, Lai et al. 2019). Lastly, in addition to
being an ASD genetic risk factor, de novo mutations in SYNGAP1 have been found in patients
with intellectual disability, epilepsy, neurodevelopmental disability, and global developmental
delay (Berryer, Hamdan et al. 2013, Kilinc, Creson et al. 2018, Gamache, Araki et al. 2020).
This evidence, combined with the high frequency and penetrance of pathogenic SYNGAP1
variants, indicates a major and unique role for SYNGAP1 in human brain development.
However, as with other components of the scaffold machinery of the PSD, it remains unclear if
SYNGAP1 is expressed in early cortical progenitors and how it affects cortical neurogenesis.
To address these questions, we used 3D cultures of human brain organoids. Derived from
human embryonic or induced pluripotent stem cells (hPSCs), organoids have emerged as an
23

effective way to model genetic architecture and cellular features of human brain development
and disease (Lancaster, Renner et al. 2013, Bershteyn, Nowakowski et al. 2017, Kanton, Boyle et
al. 2019, Klaus, Kanton et al. 2019, Esk, Lindenhofer et al. 2020, Khan, Revah et al. 2020,
Samarasinghe, Miranda et al. 2021, Jourdon, Wu et al. 2022, Tidball, Niu et al. 2022, Villa,
Cheroni et al. 2022). These reproducible models of the human forebrain are capable of
generating cellular diversity and epigenetic states that follow the developmental trajectory of the
corresponding endogenous cell types (Camp, Badsha et al. 2015, Quadrato, Nguyen et al. 2017,
Velasco, Kedaigle et al. 2019, Trevino, Sinnott-Armstrong et al. 2020, Gordon, Yoon et al. 2021,
Paulsen, Velasco et al. 2022), allowing for the functional characterization of ASD-risk genes in a
longitudinal modeling and human cellular context.
Here, we show for the first time the expression of SYNGAP1 protein in human radial glia
cells (hRGCs). Mechanistically, we find that SYNGAP1 regulates cytoskeletal remodeling of
subcellular and intercellular components of hRGCs, with haploinsufficiency leading to disrupted
organization of the developing cortical plate. By performing single-cell transcriptomics coupled
with structural and functional analysis of mutant organoids, we discovered that SYNGAP1
regulates the timing of hRGCs differentiation with haploinsufficient organoids exhibiting
accelerated maturation of cortical projection neurons. Additionally, we show that reduction in
SynGAP1 levels affects cortical neurogenesis in a murine model suggesting that SynGAP1
function in cortical progenitors is conserved across species. Altogether, these findings reveal a
novel function for the classically defined synaptic protein SYNGAP1 at early stages of human
cortical neurogenesis, providing a new framework for understanding ASD pathophysiology.
24

Results
SYNGAP1 is expressed in human ventricular radial glia and colocalizes with
the tight junction protein TJP1
Syngap1 expression has been reported to be largely restricted to the PSD of mature
excitatory synapses (Chen, Rojas-Soto et al. 1998, Kim, Liao et al. 1998) of mouse cortical
projection neurons, where it has a cell type-specific function (Aceti, Creson et al. 2015,
Michaelson, Ozkan et al. 2018). To investigate the expression of SYNGAP1 in distinct human
cortical cell types, we took advantage of a recently published single cell RNA-seq data set of
early human fetal telencephalic/cortical development from post-conception days (PCD) 26 to 54
(Eze, Bhaduri et al. 2021). We compared SYNGAP1 expression and distribution across all
developmental stages with the expression of well-known gene markers for neuroepithelial/radial
glial cells (PAX6), radial glial cells (HES5), and intermediate progenitor cells (IPC)
(EOMES/TBR2). Within the data set, SYNGAP1 expression was detected throughout the age
range. Interestingly, SYNGAP1’s expression levels were enriched in hRGCs (Suppl. Fig 7-7a-c),
pointing to a novel function of SYNGAP1 in human cortical progenitors.
To further validate SYNGAP1 protein expression at this stage of development, we
performed a proteome profiling of human cortical organoids (D.I.V. 7), which are entirely
composed of SOX2+ and PAX6+ progenitors at this stage of development (Suppl. Fig. 7-7d).
Using this pipeline, we were able to identify a total of 8690 proteins (Suppl. Table 1), including
24 unique peptides for SYNGAP1. Interestingly, 793 of these proteins belonged to the SynGO
ontology term ‘Synapse’ (Suppl. Table 2), with enrichment in components of the postsynaptic
density, pointing to an unappreciated role of classically defined postsynaptic proteins in
progenitor biology (Fig. 7-1a). Within 2-month-old organoids, the Ventricular Zone (VZ) is
delineated by radially aligned SOX2+ neural stem cells surrounding the apical junctional belt,
25

which is composed of adherens and tight junction proteins such as TJP1. Immunofluorescence
using a SYNGAP1 antibody (Suppl. Fig 7-7f-g) revealed that SYNGAP1 expression was
enriched at the apical end feet of the VZ cells (Fig. 7-1b) as well as in MAP2+ neurons (Fig. 7-
1d). Notably, SYNGAP1 and TJP1 co-localize (Fig. 7-1b). Through a series of
immunohistochemical analyses of micro-dissected VZ and SVZ specimens of human cortex at
gestational week 17 (GW17) (Fig. 7-1f) and mouse cortex at E13.5 (Suppl. Fig. S7-7e), we
confirmed the same pattern of SYNGAP1 expression in the apical end feet of ventricular radial
glia cells. Moreover, SYNGAP1 immunoprecipitation and mass spectrometry analysis shows
that TJP1 is part of the SYNGAP1 interactome (Fig. 7-1c, Suppl. Table 3). The PDZ ligand
domain of SYNGAP1 is known to mediate localization of the protein to the PSD via binding to
MAGUK proteins such as Dlg4 in mature rodent neurons

(Li, Zhang et al. 2017).TJP1 is a
MAGUK family member and shares the modular-domain composition of other MAGUK
proteins, and therefore can associate to SYNGAP1 through a PDZ domain. Therefore, we
hypothesize that SYNGAP1 interacts with TJP1, a PDZ domain containing protein, in a similar
manner (Fig. 7-1e). The capacity of SYNGAP1 to associate to proteins containing PDZ domains
is isoform-dependent (Walkup, Mastro et al. 2016, Araki Y 2020). To address whether hRGCs
express the SYNGAP1 isoform alpha 1 (id: A0A2R8Y6T2), the isoform with the capacity to
associate to PDZ domains, we designed a parallel reaction monitoring experiment based on high
resolution and high precision mass spectrometry. This assay allowed us to show that similarly to
what occurs in mature rodent synapses (Walkup, Mastro et al. 2016, Araki Y 2020), SYNGAP1
has the capacity to associate to PDZ containing proteins in hRGCs cells (Fig. 7-1e, Suppl. Fig. 7-
8a-b).

26

SYNGAP1 plays a role in the cytoskeletal organization in hRGCs
To determine the function of SYNGAP1 in hRGCs, we developed an early cortical
organoid model (D.I.V. 7) from a patient carrying a SYNGAP1 truncating (p.Q503X) mutation.
This patient presented with intellectual disability, developmental delay, autistic features and
epilepsy. For this, we generated iPSC lines from the patient and the correspondent corrected
isogenic control (Suppl. Fig. 7-9b,c,g,h Suppl. Table 4-5). The characterization of the patient-
derived iPSC cell line shows that the p.Q503X mutation produces a haploinsufficent model of
SYNGAP1 disfunction with a 51.6% decrease in SYNGAP1 total protein levels and not
detectable protein fragments as evidenced by WB and quantitative Mass Spectrometry assays
(Suppl. Fig. 7-9d-f)
To start to address the role of SYNGAP1 in hRGCs we performed bulk RNA sequencing of 7
D.I.V. organoids from the Patient
p.Q503X
and Patient
Corrected
lines, and our Gene Ontology (GO)
analyses found terms for biological processes related to cytoskeletal remodeling and migration to
be significantly enriched within our gene list (P value = 1.02e-03) (Fig. 7-2a; Suppl. Table 6). In
addition, GO analysis of the SYNGAP1 interactome revealed that the predicted set of molecular
functions regulated by SYNGAP1 clustered within the functional categories of cytoskeletal
organization and regulation (Suppl. Fig. 7-9a).
hRGCs have a bipolar shape with distinct apical and basolateral domains and include a
process terminating at the ventricular surface and another process reaching the pial surface. To
monitor the effect of SYNGAP1 haploinsufficiency on the shape and polarity of hRGCs
processes, we employed a standardized single neural rosette protocol (GT, BF et al. 2018) that
allows high-throughput generation and analysis of rosette formation (Fig. 7-2b, Suppl. Video 1).
We found homogeneous expression of the cortical progenitor markers PAX6 and SOX2 with
radially organized acetylated tubulin networks in rosettes derived from the Patient
Corrected
line
27

(Fig. 7-2c,d, Suppl. Fig. 7-10a). However, these structures were less organized in SYNGAP1
haploinsufficient tissues, and their formation was less frequent than in corrected rosettes (Fig. 7-
2e-h, Suppl. Fig. 7-10b). Through a high throughput analysis of the localization tight-junction
marker TJP1 in single rosettes tissues, we found that SYNGAP1 haploinsufficient rosettes
exhibited apico-basal polarity from a wider, more irregular TJP1 positive region, while corrected
individual rosettes had a tighter and more circular TJP1 ring (Fig. 7-2i, Suppl. Fig. 7-10d-e).
To understand the contribution of the patient's genetic background to the observed
phenotypes, we repeated this assay in rosettes derived from a new line that we generated to carry
the truncating p.Q503X mutation in the control 03231 background (Wilkinson, Evgrafov et al.
2019) (Suppl. Fig. 7-9j, m-o). Importantly, single rosettes generated from this line displayed the
same phenotypes as Patient
p.Q503X
(Fig. 7-2j-p; Suppl. Fig. 7-10c,f,g,i). This indicates that the
SYNGAP1 haploinsufficiency phenotype is not influenced by the individual genomic context.
This finding is consistent with the high penetrance of pathogenic SYNGAP1 variants in patients.
The ability of SYNGAP1 to partake in cytoskeletal remodeling in mature neurons has been
attributed to enzymatic activity from its RAS GTPase-activating domain (Chen, Rojas-Soto et al.
1998, Kim, Liao et al. 1998, Tomoda, Kim et al. 2004, Carlisle, Manzerra et al. 2008, Aceti,
Creson et al. 2015). To assess if SYNGAP1’s enzymatic function is conserved in hRGCs, we
edited the 03231 iPSC line to carry a homozygous non-functional RASGAP domain. We named
this RASGAP-Dead line 03231
RGD
(Suppl. Fig. 7-9 i-l; Suppl. Table 4) and compared it to its
isogenic control iPSC line. We observed a more marked effect compared to the SYNGAP1
haploinsufficient phenotype, with the tissue generated from the RASGAP-Dead (RGD) line
displaying fully disrupted apico-basal polarity and a reduced central TJP1 positive luminal space
(Fig. 7-2q-s; Suppl. Fig.7-10h,j). Importantly, these profound defects lead to the loss of about
28

90% of the 03231
RGD
organoids

over 2 months preventing a thorough characterization of
organoids at later stages of development (Suppl. Fig. 7-10k). These data indicate that impairment
in the cytoskeletal architecture of apical end feet, as well as disruption of radial elongation of the
basal process of hRGCs are present in both SYNGAP1 haploinsufficient and RGD-derived
tissues, indicating that this function is dependent on the RASGAP domain of SYNGAP1.
However, we cannot exclude that misfolding effects or changes in SYNGAP1 protein
localization and interaction occur following mutation of the RASGAP domain in the RGD line,
affecting the function of other functional sites in the SYNGAP1 protein. Further experiments
will need to be performed to prove the necessity of the enzymatic function of the RASGAP
domain in regulating cytoskeleton dynamics of hRGCs.
Altogether, these data show that SYNGAP1 regulates a dynamic cytoskeletal network that
influences the subcellular and intercellular organization of ventricular radial glia.

SYNGAP1 haploinsufficiency disrupts the organization of the
developing cortical plate
hRGCs control the generation and organization of a proper VZ by tightly connecting to
each other via an AJ belt at their apical endfeet (Aaku-Saraste E 1996); through their basal
process, they guide newly born neurons across the entire thickness of the developing cortex,
serving as a central organizer for the assembly of cortical neuronal columns, layers, and circuitry
(P 1971, P 1972, Edmondson and Hatten 1987). To assess SYNGAP1’s function during cortical
plate formation, we analyzed 2-month-old haploinsufficient and corrected cortical organoids. At
this stage, organoids form robust VZs and the surrounding regions are populated with both upper
and deep layer cortical projection neurons (Velasco, Kedaigle et al. 2019). The VZs, which are
29

defined by highly dense SOX2 positive areas, serve as the germinal niche for the organoids;
these regions were significantly reduced in size, number, and organization in SYNGAP1
haploinsufficient organoids derived from two independent genetic backgrounds (Patient
p.Q503X

and 03231
p.Q503X
) (Fig. 7-3a-h). The sizable presence of MAP2+ cells within the VZ of
haploinsufficient organoids indicates a potentially impaired ability of neuroblasts to migrate
away from the ventricular zone towards the cortical plate or an imbalance in direct neurogenesis
(Fig. 7-3i-n). This is also consistent with the disorganization of radial glial progenitors seen in
SYNGAP1 haploinsufficient rosettes, which are known to serve as migratory scaffolding for
neuroblasts in vivo. Consistent with these results, binning analysis of BrdU labeling experiments
in 2-month-old organoids treated for 2 hours with BrdU followed by 24 hours chase revealed the
presence of a higher number of BrdU+/ NeuN+ neurons in bins closer to the ventricular wall in
SYNGAP1 haploinsufficient organoids (Fig. 7-3o-t, Suppl. Fig. 7-11a-d). This further highlights
the role of SYNGAP1 in controlling neuronal positioning and the overall organization of the
cortical plate during human neurogenesis. In addition, we observed that dividing cells, in
haploinsufficient organoids, have a higher propensity to differentiate into NeuN+ neurons while
control organoids maintained a larger BrdU+/SOX2+ progenitor pool (Fig 7-3.o,r-t, Suppl. Fig.
7-11a-d), suggesting a potential impairment in the division mode of hRGCs.

SYNGAP1 haploinsufficiency affects the division mode of human radial
glial progenitors
The precise spatiotemporal regulation of RGCs division and differentiation (P 1978,
Nowakowski, Pollen et al. 2016) is critical for proper lamination and microcircuit assembly in
the developing human cortex. During ventricular RGC division, mitotic spindle orientation
30

determines the cleavage plane and predicts cell fate decisions that result in either symmetric
proliferative or asymmetric differentiative divisions (Chenn and Mcconnell 1995, Shitamukai,
Konno et al. 2011). To better characterize the observed imbalance in the ratio of progenitors to
neurons, we analyzed the division planes of ventricular radial glia and found an increased
proportion of cells undergoing differentiative divisions in haploinsufficient organoids (Fig. 7-4a-
e). This data suggests an earlier depletion of the progenitor pool due to premature loss of the
proliferative potential of the hRGCs in haploinsufficient organoids derived from two
independent genetic backgrounds (Patient
p.Q503X
and 03231
p.Q503X
).
To analyze this phenotype at higher resolution, we preformed single-cell RNA-
sequencing analysis on a total of 50,592 cells from 6 individual organoids at 2 months (3
corrected and 3 haploinsufficient). To systematically perform cell type classification, we
clustered cells from all organoids and compared signatures of differentially expressed genes with
a pre-existing human fetal cortex single cell dataset (Nowakowski, Bhaduri et al. 2017). This
defined 9 main transcriptionally distinct cell types (Figure 7-4f; Suppl. Table 7), which included
a large diversity of progenitors (apical radial glia, outer radial glia, and intermediate progenitor
cells) and neuronal cell types (inhibitory neurons, corticofugal neurons and callosal projection
neurons) representing all the main cell types of the endogenous human fetal cortex. Importantly
we found that individual organoids were highly reproducibly in cell type composition consistent
with previous reports (Velasco, Kedaigle et al. 2019, Paulsen, Velasco et al. 2022) (Figure 7-4g-
h). This high level of reproducibility allowed us to preform differential gene expression analysis
between Patient
Corrected
and Patient
p.Q503X
apical radial glia. In agreement with the observed
increase in the differentiative division mode observed in haploinsufficient organoids we found an
enrichment in terms related to neuronal differentiation, synapses and neuronal projection
31

development. This was coupled with a downregulation of terms related to mitotic cell cycle
process, cell division, mitotic spindle formation and centrosomes (Figure 7-4i-l).
Overall, these data suggests that SYNGAP1 haploinsufficiency affect the balance of self-
renewing versus differentiative division in apical radial glia cells.

Decrease in SYNGAP1 levels leads to asynchronous cortical
neurogenesis in vitro and in vivo.
We next analyzed whether impairment in the division mode of hRGPs would affect the relative
ratio of progenitor to neurons in 2-month-old SYNGAP1 haploinsufficient organoids. In line,
with the observed acceleration in the timing of hRGCs differentiation, we found that the total
percentage of SOX2+ cells were decreased in haploinsufficient organoids (Figure 5a, c; Suppl.
Fig. 6a-b) and analysis of the percentage of NeuN+ cells showed an increase in the proportion of
neurons generated (Figure 7-5b,d; Suppl. Fig. 7-12a,c). Interestingly, the percentage of TBR2+
cells remained consistent between genotypes (Suppl. Fig.7-12d-e)
As an additional line of evidence, we analyzed Syngap1 Het and KO mice at late
embryonic stages (E18.5) to understand whether the developmental phenotype reported in
organoids is conserved in vivo and across species. We stained sections from E18.5 mouse brains
for the neural progenitor marker Sox2 and as found in organoids (Fig. 7-5e) we detected a
reduction in the thickness of the size of the VZ in the Syngap1 Het and KO mice in comparison
to WT littermates (Fig. 7-5g,i; Suppl. Fig. 7-12f-g). NeuN staining revealed a clear increase in
the cortical thickness of the Syngap1 Het and KO mice illustrating an imbalance in the
maintenance of radial glia and the production of cortical neurons compared to WT mice (Fig. 7-
5f,h,j). Interestingly, as observed in organoids, Tbr2 staining did not reveal any difference
32

between genotypes (Suppl. Fig. 7-12h-j). Overall, the phenotypes observed in mice were in line
with what was observed in organoids derived from patients with SYNGAP1 haploinsufficiency,
indicating that a reduction in SynGAP1/SYNGAP1 protein levels impairs cortical neurogenesis
in vivo as well as in vitro leading to the accelerated production of neurons. Interestingly, these
changes in cell type composition did not significantly affect the overall organoid size over time
(Suppl. Fig. 7-12k-l). This is consistent with the Patient
p.Q503X
donor regularly scoring within the
lower end of the normal head circumference size range according to the WHO child growth
standard for males aged 0 to 2 years (Suppl. Fig. 7-12m). This lack of a clear microcephaly
phenotype suggests that there are complex compensatory mechanisms at play in distinct
progenitor populations at different developmental stages. Elucidation of this phenotype will
require extensive characterization through lineage tracing approaches that can precisely
reconstruct cell population dynamics and lineage relationships over time from individual cell
types.

Syngap haploinsufficient organoids exhibit accelerated maturation of
cortical projection neurons.
As additional evidence of the accelerated developmental trajectory in haploinsufficient
organoids, we analyzed structural and functional features of neurons in intact 4-month-old
organoids. Structural analysis of dendritic complexity in individual neurons showed a more
developed dendritic tree arborization with an increase in the number of dendrites in
haploinsufficient organoids (Fig. 7-6a-f). The higher degree of complexity in dendritic
arborization was also supported by scRNA-seq data from 4-month-old Patient
Corrected
and
Patient
p.Q503X
organoids (Suppl. Fig. 7-13c-e; Suppl. Table 8), showing in CFuPNs an
33

upregulation of transcripts related to the functional categories of neuronal projection regulation
and axon development including genes such as CNTN1, DCX, and SYT4 (Fig. 7-6g-h). CPNs
showed enrichment in the transcription of genes including GRIN2B, DCX, and SLITRK5 with
an overall upregulation of genes regulating neuronal projection morphogenesis and axon
development (Fig. 7-6i-j). SLITRK5, a gene encoding for a protein known to suppress neurite
outgrowth, was found to be downregulated, further supporting evidence of increased dendritic
complexity. Importantly, upregulation in functional categories indicative of enhanced neuronal
maturation was also observed in CFuPNs and CPNs within scRNA-seq data from 2-month-old
Patient
Corrected
and Patient
p.Q503X
organoids, suggesting that this phenotype can be reproducibly
detected across different batches and time points (Suppl. Fig. 7-13a-b; Suppl. Table 7).
Functional neuronal maturation was monitored through recording of spontaneous neuronal
activity using an Adeno-Associated Virus driving GCaMP6f as a proxy of intracellular calcium
dynamics. Patient
Corrected
and 03231
Control
organoids displayed limited spontaneous basal calcium
waves; however, haploinsufficient organoids showed an increase in network bursts, with faster
transients, and coordinated bursts across distant GCaMP-positive soma (Fig. 7-6k-n, Suppl.
Fig.7-13f,h; Suppl. Video 3-6). Action potential (AP) generation and propagation were
specifically blocked by tetrodotoxin (TTX), a voltage-gated sodium channel antagonist, and AP
firing rate was found to be increased after bath application of glutamate, indicating that
registered calcium waves are a result of glutamatergic synaptic connections (Suppl. Fig.7-13g,i).
In line with previous evidence demonstrating precocious structural and functional maturation of
SYNGAP1-deficient human glutamatergic neurons in 2D cultures

(Llamosas, Arora et al. 2020),
these results indicate that haploinsufficient organoids exhibit higher levels of spontaneous
activity and a more mature synchronized network.
34

Collectively, these data show that SYNGAP1 expression in hRGCs is required for precise
control of their division mode, for the structural integrity and organization of the VZ, timing of
neurogenesis, and proper cortical lamination. Finally, SYNGAP1 haploinsufficiency ultimately
results in asynchronous cortical neurogenesis and accelerated maturation of cortical projection
neurons.
Discussion
Many human genetic studies of neurodevelopmental diseases including ASD have found
enrichment of mutations in genes encoding classically defined synaptic proteins (O'Roak,
Deriziotis et al. 2011, Kirov, Pocklington et al. 2012, O’Roak, Vives et al. 2012, Peça and Feng
2012, De Rubeis, He et al. 2014, Fromer, Pocklington et al. 2014, Genovese, Fromer et al. 2016,
Satterstrom, Kosmicki et al. 2020). Currently, most studies of SYNGAP1 and other synaptic
proteins have been done within the context of mature synapses in rodent models (Gamache,
Araki et al. 2020). Indeed, the lack of a reliable model to study the stage-specific functions of
ASD risk genes during human brain development has limited our understanding of their role to
rudimentary functional categories. Here, we leveraged 3D human brain organoids to perform
longitudinal modeling and functional characterization of SYNGAP1, a top risk gene for ASD in
the functional category of synaptic function. We detected SYNGAP1 in hRGCs and identified it
as a key regulator of human cortical neurogenesis.
One advantage of using cultures of human cortical organoids is that, at early stages, they
are composed by a relatively pure population of cortical progenitors. Analysis of the SYNGAP1
interactome within this population suggests an association between SYNGAP1 and the tight
junction protein TJP1, which is a PDZ domain containing protein belonging to the MAGUK
family. In neurons, SYNGAP1’s interaction with MAGUK proteins is key for protein
35

localization within the PSD machinery(Walkup, Mastro et al. 2016, Zeng, Shang et al. 2016,
Zeng, Bai et al. 2017).Our results suggest a similar role of TJP1 in localizing SYNGAP1
function in the apical domain of radial glial progenitors. SYNGAP1 might regulate cytoskeletal
organization in hRGCs through its RASGAP domain and its localization and assembly in
macromolecular complexes through its PDZ ligand domain. This is particularly intriguing when
considering the critical role of tight junctions and their association with the cytoskeleton in
forming and preserving the apical junctional belt, which maintains radial glial apico-basal
polarity and neuroepithelial cohesion(Aaku-Saraste E 1996). As apical radial glial cells begin to
differentiate, there is a downregulation of junctional proteins and a constriction of the apical
junctional ring, which enables detachment from the ventricular wall and migration away from the
VZ (Kawaguchi 2021). The disruption of junctional complexes regulating this delamination
process has been shown to result in the collapse of apical RGCs morphology, disruption of the
ventricular surface, and cortical lamination defects due to failed neuronal migration (Kadowaki
M 2007, Cappello, Böhringer et al. 2012, Gil-Sanz, Landeira et al. 2014, Yoon, Nguyen et al.
2014). These phenotypes are consistent with several of our findings in SYNGAP1
haploinsufficient organoids, including disrupted ventricle formation and cortical lamination and
the accelerated developmental trajectory of radial glial progenitors. Consistent with the high
penetrance of pathogenic SYNGAP1 variants in patients, this phenotype was detected across two
different genetic backgrounds and two different mutations.
Importantly, we also provide evidence for the expression and function of SynGAP1 in RGCs in
vivo by exploring the earlier effects of the decrease in the level of SynGAP1 on the cortical
progenitor dynamics in an embryonic mouse model of Syngap1 mutation. Although murine
neuronal progenitor biology differs from human(Hansen, Lui et al. 2010), we similarly observed
36

an increased ratio of neurons to radial glial progenitors. Interestingly, decrease in SYNGAP1
levels have also been shown to regulate the ratios of neural progenitor cells to mature neurons in
Xenopus tropicalis (Willsey, Exner et al. 2021), suggesting that Syngap1 controls the timing of
cortical neurogenesis in vitro, in vivo, and across species.
As previously reported, developing neurons in SynGAP1 heterozygous mice exhibit
accelerated structural and functional maturation, which have been linked to altered neural circuit
connectivity and dysregulated network activity (Clement, Aceti et al. 2012, Clement, Ozkan et
al. 2013, Ozkan, Creson et al. 2014, Aceti, Creson et al. 2015). While it has been observed that
SynGAP1 re-expression in adulthood can ameliorate certain relevant phenotypes induced by
Syngap1 heterozygosity (Ozkan, Creson et al. 2014, Creson, Rojas et al. 2019), many core
behavioral phenotypes in SynGAP1 haploinsufficient mice are not improved through adult-
initiated gene restoration(Clement, Ozkan et al. 2013). This phenomenon has been attributed to
pleiotropic and temporally specific functions of the SYNGAP1/Syngap1 gene (Creson, Rojas et
al. 2019). These current findings are consistent with this hypothesis because many of the
Syngap1-related phenotypes described here are specific to early stages of brain development.
A growing body of literature suggests that a dysregulated neurogenesis program may lead
to impaired neuronal wiring. This is because establishing proper neuronal circuits requires the
spatiotemporally precise control of neuronal positioning, neurogenesis, and afferent and efferent
synaptic connectivity(Noctor, Martínez-Cerdeño et al. 2004, He, Li et al. 2015). Therefore, the
impairment in neuronal excitability observed in SYNGAP1 patients may in part be explained by
a disruption in microcircuit formation, driven by an altered developmental trajectory of cortical
progenitors. Thus, our finding that cortical projection neurons in SYNGAP1 haploinsufficient
organoids display accelerated development reshapes the current framework for therapeutic
37

interventions, which could target not only the well-known alterations in synaptic transmission,
but also the early developmental defects. The dual function of SYNGAP1 in progenitors and
neuronal synapses underscores the importance of dissecting the role of ASD risk genes in
specific cell types across developmental stages and suggests that a similarly nuanced approach
may have broader relevance for studying other neurodevelopmental disorders (NDD). This is
even more important considering that alterations in developmental trajectories during cortical
neurogenesis are emerging as major contributors to the etiology of autism (Mariani, Coppola et
al. 2015, Schafer, Paquola et al. 2019, De Jong, Llapashtica et al. 2021, Urresti, Zhang et al.
2021, Jourdon, Wu et al. 2022, Paulsen, Velasco et al. 2022, Villa, Cheroni et al. 2022).
In addition, human genetic studies have found enrichment of mutations in genes encoding
PSD proteins (O'Roak, Deriziotis et al. 2011, O’Roak, Vives et al. 2012, Peça and Feng 2012, De
Rubeis, He et al. 2014, Fromer, Pocklington et al. 2014, Genovese, Fromer et al. 2016,
Satterstrom, Kosmicki et al. 2020), which generally form large protein interaction networks that
are considered risk factors for NDD (J, B et al. 2016, Li, Zhang et al. 2017, Coba, Ramaker et al.
2018). In the synapses of the adult mouse brain, Syngap1 is a major hub in the PSD protein
interaction network, and proteins associated with NDD are Syngap1 protein interactors (J, B et
al. 2016, Coba, Ramaker et al. 2018). We have found expression of multiple components of the
core signaling machinery of the PSD in our proteomic analysis and shown that some of these
proteins are interactors of SYNGAP1 in cortical progenitors. It is tempting to speculate that the
complex controlling structural integrity at the PSD of excitatory neurons is also important in
regulating the scaffolding properties of hRGCs. In support of this hypothesis, dysregulation of
DLGAP4, another synapse-related scaffold protein, has been recently shown to regulate cell
adhesion and actin cytoskeleton remodeling at the apical domain of radial glial cells during
38

cortical neurogenesis in embryonic mice (Romero, Poirier et al. 2022). It will be crucial to
characterize whether the disruption of proteins classically considered important for maintenance
of the PSD scaffold in neurons may represent a point of convergence for NDDs.

39

Figures

Figure 0-2. SynGAP1 is expressed in human radial glial progenitors and colocalizes with
the tight junction protein TJP1.

(A)SynGO analysis results from D.I.V. 7 corrected organoids proteomic data set. 21 organoids
from 3 independent experiments were analyzed. (B) Two-month-old control organoid stained for
the neural progenitor marker SOX2, the tight junction protein TJP1 and SYNGAP1. SYNGAP1
is highly expressed at the ventricular wall. White box indicates the region of interest selected for
the merged images showing colocalization of the nuclear marker DAPI, TJP1, and SYNGAP1.
(C) Schematic for the protein interaction network of SYNGAP1. Analysis performed on 21
40

organoids from 3 independent experiments at D.I.V. 7. The tight junction protein TJP1 is
highlighted in pink. (D) Two-month-old Patient
Corrected
organoid stained for the radial glial
marker NESTIN, the neuronal marker MAP2, and SYNGAP1. SYNGAP1 is highly expressed
within mature MAP2 positive neuronal populations outside of the VZ, as well as in NESTIN
positive cells at the ventricle wall. White box indicates the region of interest selected for the
merged images showing colocalization of DAPI, SYNGAP1, and NESTIN positive cells.
(E)Schematic of key functional domains within the SYNGAP1 alpha 1 isoform and TJP1
proteins including representative spectra of the two identified peptides for the alpha1 isoform.
(F) Immunohistochemical staining of the human brain at gestational week 17. Tissue section is
from the prefrontal cortex at the level of the lateral ventricle and medial ganglionic eminence.
White box indicates the region of interest selected for the merged images showing colocalization
of DAPI, TJP1, and SYNGAP1.

41

Figure 0-3. SYNGAP1 plays a role in the cytoskeletal organization of human radial glia.
42

(A) Selected GO terms for biological processes for bulk RNA sequencing data collected
from D.I.V. 7 control organoids. A total of 100 organoids from 2 independent
experiments were analyzed. (B) Still frames taken from live imaging of Patient
Corrected

rosette formation from day 5 to day 7 after initial seeding. (C) Array of single rosettes
generated from the Patient
Corrected
line control labeled with TJP1 staining. (D) A single
rosette generated from Patient
Corrected
iPSCs. The rosette is composed of cells positive for
the neural stem cell marker SOX2 and radial glial progenitors positive for PAX6.
Acetylated tubulin labels the microtubules of radial glial progenitors and highlights their
radial organization around the luminal space. (E) Quantification of the number of rosettes
successfully formed in the Patient
Corrected
and Patient
p.Q503X
lines. Successful rosette
formation was defined as containing a densely packed central area positive for TJP1 and
radial organization of surrounding progenitor cells. Chi-square test was performed on
n=281 control single rosettes and n= 223 Patient
p.Q503X
single rosettes from 3 independent
experiments. P value <0.0001. (F) Array of single rosettes generated from the
Patient
p.Q503X
line labeled with TJP1 staining. (G) A single rosette generated from
Patient
p.Q503X
iPSCs. Similar to the Patient
Corrected
rosette, it is composed of cells positive
for SOX2 and PAX6. Acetylated tubulin labels the microtubules of radial glial
progenitors and shows diminished radial organization around the luminal space as
compared to the Patient
Corrected
rosette. (H) Quantification of the rosette lumen perimeter,
as marked by TJP1 labeling in the Patient
Corrected
and Patient
p.Q503X
lines. Unpaired t-test
was performed on n=94 corrected single rosettes and n= 198 Patient
p.Q503X
single rosettes
from 3 independent experiments. P value <0.0001. (I) Quantification of the circularity of
the rosette lumen as marked by TJP1 labeling in the Patient
Corrected
and Patient
p.Q503X
lines.
Unpaired t-test was performed on n=99 corrected single rosettes and n= 69 Patient
p.Q503X

single rosettes from 3 independent experiments. P value <0.0001. (J) Array of single
rosettes generated from the 03231
Control
line labeled with TJP1 staining. (K) A single
rosette generated from 03231
Control
iPSCs. It is composed of cells positive for SOX2 and
PAX6. Acetylated tubulin labels the microtubules of radial glial progenitors and shows
radial organization and central luminal space. (L) Quantification of the number of
rosettes successfully formed in the 03231
Control
and 03231
p.Q503X
lines. Successful rosette
43

formation was defined as containing a densely packed central area positive for TJP1 and
radial organization of surrounding progenitor cells. Chi-square test was performed on
n=210 03231
Control
single rosettes and n= 200 03231
p.Q503X
single rosettes. P value
<0.0001. Analysis was performed from 3 independent experiments.(M) Array of single
rosettes generated from the 03231
p.Q503X
line labeled with TJP1 staining. (N) A single
rosette generated from 03231
p.Q503X
iPSCs. Similar to the 03231
Control
rosette, it is
composed of cells positive for SOX2 and PAX6. Acetylated tubulin labels the
microtubules of radial glial progenitors and shows little to no radial organization around
the luminal space as compared to the 03231
Control
rosette. (O) Quantification of the
perimeter of the rosette lumen as marked by TJP1 labeling in the 03231
Control
and
03231
p.Q503X
lines. Unpaired t-test was performed on n=45 03231
Control
single rosettes and
n= 88 03231
p.Q503X
single rosettes from 3 independent experiments. P value <0.0001. (P)
Quantification of the circularity of the rosette lumen as marked by TJP1 labeling in the
03231
control
and 03231
p.Q503X
lines. Unpaired t-test was performed on n=45 03231
Control

single rosettes and n= 88 03231
p.Q503X
single rosettes from 3 independent experiments. P
value <0.0001 (Q) Array of single rosettes generated from the 03231
RGD
line labeled with
TJP1 staining. (R) A single rosette generated from 03231
RGD
iPSCs. Similar to the
03231
Control
rosette, it is composed of cells positive for SOX2 and PAX6. Acetylated
tubulin labels the microtubules of radial glial progenitors and shows little to no radial
organization or central luminal space. (S) Quantification of the number of rosettes
successfully formed in the 03231
Control
and 03231
RGD
lines. Successful rosette formation
was defined as containing a densely packed central area positive for TJP1 and radial
organization of surrounding progenitor cells. Chi-square test was performed on n=213
03231
Control
single rosettes and n= 251 03231
RGD
single rosettes. P value <0.0001.
Analysis was performed from 3 independent experiments.

44

Figure 0-4. SYNGAP1 haploinsufficiency disrupts the organization of the developing
cortical plate.
45

(A) Two-month-old organoids show expression of SOX2, a neural stem cell marker, and
nuclei marker DAPI. Patient
Corrected
organoids display SOX2 expression exclusively within
the ventricular zone (VZ), while Patient
p.Q503X
organoids lack a defined VZ. (B) VZ analysis
shows VZ thickness (µm) in Patient
p.Q503X
and Patient
corrected
organoids. Patient
p.Q503X

organoids present less proliferative VZ compared to Patient
corrected
. Student’s t-test was
performed on 4 independent experiments where 20-30 VZs from 3 organoids were analyzed
in each experiment. Single dots represent individual VZs. P value (<0.0001). Data is shown
as mean ± SD. (C) VZ analysis shows VZ area (µm
2
) in Patient
p.Q503X
and Patient
Corrected

organoids. SYNGAP1
p.Q503X
organoids present less extended VZ compared to Patient
Corrected
.
Student’s t-test was performed on 4 independent experiments where 20-30 VZs from 3
organoids were analyzed in each experiment. Single dots represent individual VZs. P value
(<0.0001). Data is shown as mean ± SD. (D) VZ analysis shows VZ number per Region of
Interest (ROI) in Patient
p.Q503X
and Patient
Corrected
organoids. Patient
p.Q503X
organoids present
fewer VZs compared to corrected. Student’s t-test was performed on 4 independent
experiments where 3-6 ROI from 3 organoids were analyzed in each experiment. Single dots
represent the mean number of VZs per ROI in individual organoids. P value (<0.0001). Data
is shown as mean ± SD. (E) Two-month-old organoids show expression of SOX2, a neural
stem cell marker, and nuclei marker DAPI. 03231
Control
organoids display SOX2 expression
exclusively within the ventricular zone (VZ), while 03231
p.Q503X
organoids lack a defined
VZ. (F) VZ analysis shows VZ thickness (µm) in 03231
p.Q503X
and 03231
Control
organoids.
03231
p.Q503X
organoids present less proliferative VZ compared to 03231
Control
Student’s t-test
was performed on 4 independent experiments where 20-30 VZs from 3 organoids were
analyzed in each experiment. Single dots represent individual VZs. P value <0.0099. Data is
shown as mean ± SD. (G) VZ analysis shows VZ area (µm
2
) in 03231
p.Q503X
and 03231
Control

organoids. 03231
p.Q503X
organoids present less extended VZ compared to 03231
Control

Student’s t-test was performed on 4 independent experiments where 20-30 VZs from 3
organoids were analyzed in each experiment. Single dots represent individual VZs. P value
(<0.0046). Data is shown as mean ± SD. (H) VZ analysis shows VZ number per Region of
Interest (ROI) in 03231
p.Q503X
and Patient
Corrected
organoids. 03231
p.Q503X
organoids present
46

fewer VZs compared to corrected. Student’s t-test was performed on 4 independent
experiments where 3-6 ROI from 3 organoids were analyzed in each experiment. Single dots
represent the mean number of VZs per ROI in individual organoids. P value (<0.0134). Data
is shown as mean ± SD. (I) Two-month-old organoids show expression of SOX2 and
microtubule associated protein-2 (MAP2), a pan-neuronal marker. Patient
Corrected
organoids
display SOX2 expression in the VZ, while MAP2 labels neurons that have migrated away
from the VZ and now populate the cortical plate. Dashed yellow circles identify VZ regions.
(J) Patient
p.Q503X
organoids display SOX2 expression in the VZ and MAP positive neurons
inside and outside of the VZ, indicating impaired migration of neurons away from the VZ.
Dashed yellow circles identify VZ regions. (K) Quantification of the occurrence of organized
versus disorganized VZ structures in Patient
Corrected
and Patient
p.Q503X
organoids based on
SOX2 and MAP2 staining patterns. Chi-square test was performed on mean values of VZs
from 3-9 ROI of 3 organoids, analyzed in 4 independent experiments. P value <0.0001. Data
is shown as mean ± SD. (L) Two-month-old organoids show expression of SOX2 and
microtubule associated protein-2 (MAP2), a pan-neuronal marker. 03231
Control
organoids
display SOX2 expression in the VZ, while MAP2 labels neurons that have migrated away
from the VZ and now populate the cortical plate. Dashed yellow circles identify VZ regions.
(M) 03231
p.Q503X
organoids display SOX2 expression in the VZ and MAP positive neurons
inside and outside of the VZ, indicating impaired migration of neurons away from the VZ.
Dashed yellow circles identify VZ regions. (N) Quantification of the occurrence of organized
versus disorganized VZ structures in 03231
Control
and 03231
p.Q503X
organoids based on SOX2
and MAP2 staining patterns. Chi-square test was performed on mean values of VZs from 3-9
ROI of 3 organoids, analyzed in 4 independent experiments. P value <0.0001. Data is shown
as mean ± SD.(O) Patient
Corrected
and Patient
p.Q503X
organoids stained for the progenitor
marker SOX2, the neuronal marker NeuN and the proliferative marker BrdU. (P) Binning
analysis for the number of double positive BrdU and SOX2 cells normalized to the total
number of BrdU positive cells. The higher number of double positive cells in earlier bins in
the Patient
Corrected
organoids indicates a propensity for progenitors to remain in a proliferative
state when compared to Patient
p.Q503X
. A two-way ANOVA was performed on 15 Patient
p.Q503X
ventricles and 12 Patient
Corrected
from 3 independent experiments. P Value Bin 1 = 0.4,
P Value Bin 3 = 0.2. Data is shown as mean ± SD. (Q) Binning analysis for the number of
47

double positive BrdU and NeuN cells normalized to the total number of BrdU positive cells.
The higher number of double positive cells in the Patient
p.Q503X
organoids indicates a
propensity for progenitors to transition to a more differentiated state when compared to
Patient
Corrected
. A two-way ANOVA was performed on 15 Patient
p.Q503X
ventricles and 12
Patient
Corrected
from 3 independent experiments. P Value Bin 4 = 0.0094. Data is shown as
mean ± SD. (R) 03231
Control
and 03231t
p.Q503X
organoids stained for the progenitor marker
SOX2, the neuronal marker NeuN and the proliferative marker BrdU. (S) Binning analysis
for the number of double positive BrdU and SOX2 cells normalized to the total number of
BrdU positive cells. The higher number of double positive cells in earlier bins in the
03231
Control
organoids indicates a propensity for progenitors to remain in a proliferative state
when compared to 03231
p.Q503X
. A two-way ANOVA was performed on 18 03231
p.Q503X
ventricles and 18 03231
Control
ventricles from 3 independent experiments. P Value Bin 1 =
0.0001>, P Value Bin 2 = 0.0110, P Value Bin 3 = 0.0076. Data is shown as mean ± SD. (T)
Binning analysis for the number of double positive BrdU and NeuN cells normalized to the
total number of BrdU positive cells. The higher number of double positive cells in the
03231
p.Q503X
organoids indicates a propensity for progenitors to transition to a more
differentiated state when compared to 03231
Control
. A two-way ANOVA was performed on 18
03231
p.Q503X
ventricles and 18 03231
Control
ventricles from 3 independent experiments. P
Value Bin 1 = 0.0448, P Value Bin 3 = 0.0400, P Value Bin 7 = 0.0094. Data is shown as
mean ± SD.

48

Figure 0-5. SYNGAP1 affects the division mode of human radial glial progenitors.
49

(A) Patient
Corrected
and Patient
p.Q503X
organoids display SOX2 expression in the VZ, dividing
neural progenitors marked by phospho-vimentin (pVIM), and the centrosome labeling
marker Pericentrin. (B) Schematic representation of cell divisions at the VZ wall. Schematic
illustrates self-renewing divisions (vertical, with angle between 60 to 90 degrees from the
apical wall to the mitotic spindle) and differentiative divisions (oblique, 30 to 60 degrees;
horizontal, 0 to 30 degrees). (C) Cleavage angle analysis showing increased proliferative
divisions in cells from Patient
Corrected
organoids and increased differentiative divisions from
Paitent
p.Q503X
organoids. Mann-Whitney test was performed on a total of 195 cells for each
line, from 3 independent experiments. P value < 0.0001. (D) 03231
Control
and 03231
p.Q503X

organoids display SOX2 expression in the VZ, dividing neural progenitors marked by
phospho-vimentin (pVIM), and the centrosome labeling marker Pericentrin. (E) Cleavage
angle analysis showing increased proliferative divisions in cells from 03231
Control
organoids
and increased differentiative divisions from 03231
p.Q503X
organoids. Mann-Whitney test was
performed on a total of 78 cells for 03231
Control
and 188 cells 03231
p.Q503X
cells for condition,
from 3 independent experiments. P value < 0.0001. (F) Combined t-distributed stochastic
neighbor embedding (t-SNE) from single cell RNA sequencing analysis of all organoids at 2
months. (G) Individual t-SNE plots for three individual Patient
corrected
organoids at 2 months.
Organoid #1 (n= 8676 cells), Organoid #2 (n= 8377), Organoid #3 (n= 7687). (H) Individual
t-SNE plots for three individual Patient
p.Q503X
organoids at 2 months. Organoid #1 (n= 7511
cells), Organoid #2 (n= 9203), Organoid #3 (n= 9138). (I) Graphical representation of
downregulated GO-Terms in Patient
p.Q503X
apical radial glia (aRG). Main biological process
and cellular component GO-Terms are related to cell cycle and division. (J) Graphical
representation of upregulated GO-Terms in Patient
p.Q503X
apical radial glia (aRG). Main
biological process, cellular component and molecular function GO-Terms are related to
neuronal differentiation and synapse formation. (K) Violin plot of gene expression for
CCPG1 (Cell Cycle Progression Gene 1) in each organoid for Patient
corrected
and
Patient
p.Q503X
.CCPG1 expression levels are higher in the aRG of Patient
p.Q503X
organoids. (L)
Violin plot of gene expression for MAP2 (Microtubule Associated Protein 2) in each
organoid for Patient
corrected
and Patient
p.Q503X
. MAP2 expression levels are higher in the aRG
of Patient
p.Q503X
organoids.
50

Figure 0-6. Decrease in SYNGAP1 levels lead to asynchronous corticogenesis.
(A) Representative images of SOX2 expression in 2-month-old Patient
Corrected
and Patient
p.Q503X
organoids. (B) Representative images of NeuN expression in 2-month-old Patient
Corrected
and
Patient
p.Q503X
organoids. (C) Quantification of the total number of SOX2 positive cells
normalized to DAP1. Patient
p.Q503X
organoids show a reduced density of SOX2 positive
progenitors indicating and earlier depletion of the progenitor pool. Each dot represents an
average value for all organoids from 1 differentiation. A Student’s t-test was performed on
51

average values for 6-10 organoids from 4 differentiations. P Value =0.0032. Data is shown as
mean ± SD. (D) Quantification of the total number of NeuN positive cells normalized to DAP1.
The higher density of NeuN positive cells in Patient
p.Q503X
organoids indicates an accelerated
differentiation of radial glial progenitors. Each dot represents an average value for all organoids
from 1 differentiation. A Student’s t-test was performed on average values for 6-10 organoids
from 4 differentiations. P Value =0.0184. Data is shown as mean ± SD. (E) Representative
images of SOX2 expression in SYNGAP1 Wild Type (WT), Heterozygous (Het) and KnockOut
(KO) E18.5 mice. (F) Quantification of SOX2 thickness lining the ventricular zone of the lateral
ventricle in sections of E18.5 mouse brains. A decrease in the thickness of the SOX2+ area
surrounding the ventricle in HET and KO as compared to WT mice indicates an earlier depletion
of the proliferative niche. A One Way ANOVA was performed on 8-12 ventricle from four
animals for each genotype. P<0.0001. (G) Quantification of the number of SOX2
+
cells in 100
um
2
of the VZ area. The same density of SOX2+ cells was observed across genotypes. A One
Way ANOVA was performed on 8-12 ventricles from four animals for each genotype. P=ns. (H)
Representative images of NEUN expression in SYNGAP1 Wild Type (WT), Heterozygous (Het)
and Knock Out (KO) E18.5 mice. (I) Quantification of NeuN thickness in the cortical plate in
sections of E18.5 mouse brains. An increase in the NeuN thickness in KO and Het mice indicates
an accelerated differentiation of radial glial cells. A One Way ANOVA was performed on 8
ventricles from four animals for each genotype. WT vs Het P=0.0311, WT vs KO P<0.0001, Het
vs KO P<0.0001. (J) Quantification of the number of NeuN
+
cells in 100 um
2
of the VZ area. A
One Way ANOVA was performed on 8-12 ventricles from four animals for each genotype. P=ns.

52

Figure 0-7. SYNGAP1organoids exhibit accelerated maturation of cortical projection
neurons.

53

(A) Representative image of RFP positive bipolar neuron from a 4-month-old Patient
Corrected
organoid used for dendritic arborization analysis. (B) Representative image of RFP positive
multipolar neuron from a 4-month-old Patient
p.Q503X
organoid used for dendritic arborization
analysis. (C) Representative image of RFP positive bipolar neuron from a 4-month-old
03231
Control
organoid used for dendritic arborization analysis. (D) Representative image of RFP
positive multipolar neuron from a 4-month-old 03231
p.Q503X
organoid used for dendritic
arborization analysis. (E) Dendritic arborization analysis on 4-month-old Patient
Corrected
and
Patient
p.Q503X
organoids. Unpaired t-test performed on a total of 28 cells for Patient
Corrected

organoids and 49 cells for Patient
p.Q503X
organoids, from 3 independent experiments. P = 0.0009.
(F) Dendritic arborization analysis on 4-month-old 03231
Control
and 03231
p.Q503X
organoids.
Unpaired t-test performed on a total of 35 cells for 03231
Control
organoids and 36 cells for
03231
p.Q503X
organoids, from 3 independent experiments. P = <0.0001. (G) GO-Terms from
single cell RNA sequencing preformed in 4 month old Patient
p.Q503X
and Patient
Corrected

organoids. Graphical representation of upregulated terms for Patient
p.Q503X
Corticofugal
Projection Neurons (CFuPN). Main biological process and cellular component GO-Terms are
related to neuronal differentiation and synapse formation. (H) Violin plot for selected genes
showing expression levels between Patient
Corrected
and Patient
p.Q503X
organoids. DCX (Adj. P
value = 0.04153089), CNTN1 (Adj. P value = 4.39E-07), SYT4 (Adj. P value = 6.77E-06) (I)
GO-Terms from single cell RNA sequencing preformed in 4 month old Patient
p.Q503X
and
Patient
Corrected
organoids. Graphical representation of upregulated GO-Terms in Patient
p.Q503X

Callosal Projection Neurons (CPN). Main biological process and cellular component GO-Terms
are related to neuronal differentiation and synapse formation. (J) Violin plot for selected genes
showing expression levels between corrected and Patient
p.Q503X
organoids. DCX (Adj. P value =
0.00040542), GRIN2B (P value =0.00031511), SLYTRK5 (P value = 3E-06). (K) ΔF/F(t) from
GCaMP6f2 recordings of Patient
Corrected
and Patient
p.Q503X
organoids visualized as a heatmap. (L)
Calcium average activation per frame analysis on 4-month-old Patient
Corrected
and Patient
p.Q503X

organoids, showing an increase in firing activity in Patient
p.Q503X
organoids. Unpaired t-test
performed on a total of 40 recordings in 12 Patient
Corrected
and Patient
pQ503X
organoids from 3
independent differentiations. P=0.0006. (M) ΔF/F(t) from GCaMP6f2 recordings of 03231
Control

and 03231
p.Q503X
organoids visualized as a heatmap. (N) Calcium average activation per frame
54

analysis on 4-month-old 03231
Control
and 03231
p.Q503X
organoids, showing an increase in firing
activity in 03231
p.Q503X
organoids. Unpaired t-test performed on a total of 20 recordings in 6
03231
Control
organoids and 24 recordings in 8 Patient
pQ503X
organoids from 3 independent
differentiations. P=0.0012.

55

56

Figure S0-8
(A) Expression of early forebrain marker genes of PAX6, HES5, EOMES (TBR2) and
SYNGAP1 from post-conception day (PCD) 26 to 54 from single cell RNA-seq data.
(B) UMAP visualization of age-dependent clustering of fetal single cells. (C)
SYNGAP1 expression at PCD 56 grouped by cell types; intermediate progenitor cells
(IPC), neuroepithelial cells (NE), radial glial cells (RGCs) and neurons. (D) D.I.V. 7
cortical organoids are composed of cells positive for the neural stem cell marker SOX2,
the radial glial progenitor marker PAX6, the nuclear marker DAPI and SYNGAP1. (E)
A coronal section from E13.5 mouse brain showing expression of the neural stem cell
marker SOX2, the tight junction protein TJP1, and SYNGAP1. SYNGAP1 is highly
expressed at the ventricular wall. White box indicates the Region of Interest selected for
the merged images showing colocalization of DAPI, TJP1, and SYNGAP1. (F) Peptide
competition assay shows the specificity of the SYNGAP1 antibody used. 5X and 10X
concentrations of the commercial antigenic peptide were evaluated, showing a strong
reduction in specific signal in the apical wall of the ventricular zone. (G) SynGAP1
expression in E18.5 wild type and SynGAP1 KO mouse showing the overall decrease in
SynGAP1 levels. Decreased levels of SynGAP are most evident at the VZ.

57

58

Figure S0-9
(A) Annotated spectra of the SYNGAP1 isoform alpha 1 specific peptide
“GSFPPWQQTR” identified from MS analysis of immune-isolated SYNGAP1 protein
from D.I.V. 7 organoids. (B) Annotated spectra of the SYNGAP1 isoform alpha 1
specific peptide “LLDAQR” identified from MS analysis of immune-isolated SYNGAP1
protein from D.I.V. 7 organoids.

59

Figure S0-10
(A)Selected GO terms for biological processes for SYNGAP1 immunoprecipitation data
collected from D.I.V. 7 cortical organoids. (B) Schematic of line generation details for isogenic
control of Patient
p.Q503X
. (C) Chromatogram of the generated corrected line (Patient
Corrected
). The
truncating “T” was substituted with the wild type “C” base pair. (D) Representative Western blot
60

for SYNGAP1 in the Patient
p.Q503X
(P), Patient
Corrected
(C) and KO (K) iPSCs showing a
reduction of SYNGAP1 levels in P and complete loss in K iPSCs (E) Quantification of the
western blot shows significant reduction in SYNGAP1 levels in Patient
p.Q503X
iPSCs compared
to the Patient
Corrected
iPSCs in four biological replicates. P<0.01. Individual dots represent
independent replicates. Bar: mean values. Unpaired T-test. (F) Quantification of the SYNGAP1
peptide. Graphical representation of SYNGAP1 protein levels quantified by timed parallel
reaction monitoring (tRPM). Plot shows a decrease of SYNGAP1 total protein levels in
Patient
p.Q503X
:64.83 (51.6%) as compared to its corresponding isogenic control (Patient
Corrected
):
125.6 expressed as fg peptide/ug digested protein. N=9 across three independent differentiations.
Unpaired t test P<0.0001 (G) Karyotypic analysis of Patient
Corrected
iPSCs revealed a normal
karyotype. (H) Chromatogram of the Patient
p.Q503X
iPSCs carrying the truncating mutation. (I)
PCR of RGD, Patient
p.Q503X
, 03231 cell line. (J) Chromatogram of the 03231
Control
iPSCs carrying
the wild type sequence (K) Chromatogram of the 03231
RGD
iPSCs carrying the homozygous
mutation in the RGD domain. (L) Karyotypic analysis of 03231
RGD
iPSCs revealed a normal
karyotype. (M) Chromatogram of the 03231
p.Q503X
iPSCs carrying the truncating mutation. (N)
PCR of 03231
Control
cell line and 03231
p.Q503X
cell line

showing haploinsuffiency in the
03231
p.Q503X
line. (O) Karyotypic analysis of 03231
p.Q503X
iPSCs revealed a normal karyotype.

61

Figure S0-11

(A) Single rosette from the Patient
Corrected
cell line expressing SOX2 and PAX6 markers. (B)
Single rosette from the Patient
p.Q503X
cell line expressing SOX2 and PAX6 markers. (C) Single
rosette from the 03231
Control
cell line expressing SOX2 and PAX6 markers. (D) A single rosette
was generated from Patient
Corrected
line. The rosette is composed of cells positive for the neural
progenitor marker SOX2 and SYNGAP1. SYNGAP1 is also highly expressed at the apical wall
of the lumen. The tight junction protein TJP1 labels the central luminal space of the rosette.
62

Merged images show colocalization of DAPI, SYNGAP1, and TJP1. (E) A single rosette was
generated from Patient
p.Q503X
line. The rosette is composed of cells positive for the neural
progenitor marker SOX2 and SYNGAP1. Merged images show colocalization of DAPI,
SYNGAP1, and TJP1. The Patient
p.Q503X
single rosettes display a larger and more irregularly
shaped central luminal space. (F) A single rosette was generated from 03231
Control
line. The
rosette is composed of cells positive for the neural progenitor marker SOX2 and SYNGAP1.
SYNGAP1 is also highly expressed at the apical wall of the lumen. Merged images show
colocalization of DAPI, SYNGAP1, and TJP1. (G) Single rosette from the 03231
p.Q503X
cell line
expressing SOX2 and PAX6 markers. (H) Single rosette from the 03231
RGD
cell line expressing
SOX2 and PAX6 markers. (I) A single rosette was generated from 03231
p.Q503X
line. The rosette
is composed of cells positive for the neural progenitor marker SOX2 and SYNGAP1. Merged
images show colocalization of DAPI, SYNGAP1, and TJP1. The tight junction protein TJP1 is
weakly expressed with little to no central luminal organization. (J) A single rosette was
generated from 03231
RGD
line. The rosette is composed of cells positive for the neural progenitor
marker SOX2 and SYNGAP1. Merged images show colocalization of DAPI, SYNGAP1, and
TJP1. The tight junction protein TJP1 is weakly expressed with no central luminal organization.
(K) A Survival curve for organoids generated from the 03231
RGD
line. Data was collected from
10 independent differentiations, each representing an average of 6 organoids for each time point.
Single dots represent total averages for that time point. Student’s t-test was performed (Day 30
P=0.0134, Day 60 P<0.0001). Data is shown as mean ± SEM.

63

Figure S0-12
(A) Representative single channel images from BrdU pulse-chase experiments in 2-month-old
Patient
Corrected
organoids. Images show the expression of the progenitor marker SOX2, the
neuronal marker NeuN and the proliferative marker BrdU. (B) Representative single channel
images from BrdU pulse-chase experiments in 2-month-old Patient
p.Q503X
organoids. Images
show the expression of the progenitor marker SOX2, the neuronal marker NeuN and the
proliferative marker BrdU. (C) Representative single channel images from BrdU pulse-chase
experiments in 2-month-old 03231
Control
organoids. Images show the expression of the progenitor
marker SOX2, the neuronal marker NeuN and the proliferative marker BrdU. (D) Representative
single channel images from BrdU pulse-chase experiments in 2-month-old 03231
p.Q503X

64

organoids. Images show the expression of the progenitor marker SOX2, the neuronal marker
NeuN and the proliferative marker BrdU.

65

Figure S0-13
(A) Representative images of SOX2 and NeuN expression in 2-month-old 03231
Control
and
03231
p.Q503X
organoids. (B) Quantification of the total number of SOX2 positive cells normalized
to DAP1. 03231
p.Q503X
organoids show a reduced density of SOX2 positive progenitors
66

indicating and earlier depletion of the progenitor pool. A Student’s t-test was performed on. Each
dot represents an average value for all organoids from 1 differentiation. A Student’s t-test was
performed on average values for 6-10 organoids from 4 differentiations. P Value =0.0112. Data
is shown as mean ± SD. (C) Quantification of the total number of NeuN positive cells
normalized to DAP1. The higher density of NeuN positive cells in 03231
p.Q503X
organoids
indicates an accelerated differentiation of radial glial progenitors. A Student’s t-test was
performed on average values for 6-10 organoids from 4 differentiations. P Value =0.0217. Data
is shown as mean ± SD. (D) Representative images of TBR2 expression in 2-month-old
Patient
Corrected
and Patient
p.Q503X
organoids. (E) Quantification of the total number of TBR2
positive intermediate progenitor cells normalized to DAP1 in 2-month-old Patient
Corrected
and
Patient
p.Q503X
organoids showing no difference in TBR2 density between the lines. A Student’s t-
test was performed on average values for 6-10 organoids from 4 differentiations. P= ns. Data is
shown as mean ± SD. (F) Quantification of the SOX2 positive area in the dorsal cortex of E18.5
mouse brains. Data was collected from 26-29 ventricles from 4 brains for each genotype. A One
Way ANOVA was preformed between the genotypes, showing a decrease in the SOX2 positive
progenitor regions in Het and KO as compared to WT mice. P<0.0001. Data is shown as mean ±
SD. (G) Quantification of the SOX2 positive area in the lateral cortex of E18.5 mouse brains.
Data was collected from 26-29 ventricles from 4 brains for each genotype. A One Way ANOVA
was preformed between the genotypes, showing no change in the SOX2 positive progenitor
regions in Het and KO as compared to WT mice. P=ns. Data is shown as mean ± SD. (H)
Representative images of TBR2 expression in WT, Het and KO E18.5 mouse brains. (I)
Quantification of TBR2 thickness in the cortical plate in sections of E18.5 mouse brains. No
change in the TBR2 thickness was observed between genotypes. A One Way ANOVA was
performed on 8 ventricles from four animals for each genotype. P=ns. (J) Quantification of the
number of TBR2
+
cells in 100 um
2
of the VZ area. A One Way ANOVA was performed on 8-12
ventricles from four animals for each genotype. P=ns. (K) Analysis of organoid area over time
assessed by brightfield images for organoids generated from the Patient
Corrected
and Patient
p.Q503X

lines showing similar organoid size throughout long term culture. Data was collected from 10
independent differentiations, each representing an average of 6 organoids for each time point.
Data is shown as mean ± SEM. (L) Analysis of organoid perimeter over time assessed by
brightfield images for organoids generated from the Patient
Corrected
and Patient
p.Q503X
lines
67

showing similar organoid size throughout long term culture. Data was collected from 10
independent differentiations, each representing an average of 6 organoids for each time point.
Data is shown as mean ± SEM. (M) Head circumference measurements over time represented as
dots from the Patient
p.Q503X
donor plotted against the WHO child growth standards showing a
consistent placing between the 3
rd
and 15
th
percentile.

68

Figure S0-14

69

(A) GO-Terms from single cell RNA sequencing preformed in 2-month-old Patient
p.Q503X
and
Patient
Corrected
organoids. Graphical representation of upregulated terms for Patient
p.Q503X

Corticofugal Projection Neurons (CFuPN). Main biological process, cellular component, and
molecular function GO-Terms are related to neuronal differentiation and synapse formation. (B)
GO-Terms from single cell RNA sequencing preformed in 4-month-old Patient
p.Q503X
and
Patient
Corrected
organoids. Graphical representation of upregulated GO-Terms in Patient
p.Q503X

Callosal Projection Neurons (CPN). Main biological process and cellular component GO-Terms
are related to neuronal differentiation and synapse formation. (C) Combined t-distributed
stochastic neighbor embedding (t-SNE) from single cell RNA sequencing analysis of pooled
Patientp.
Q503X
and Patient
Corrected
organoids at 4 months. (D) Individual t-SNE plot for pooled
Patient
corrected
organoids at 4 months (n=7540 cells). (E) Individual t-SNE plot for pooled
Patient
p.Q503X
organoids at 4 months (n=3123 cells). (F) ΔF/F(t) from GCaMP6f2 recordings of
Patient
Corrected
and Patient
p.Q503X
organoids. (G) Calcium spike frequency analysis on 2-month-old
Patient
p.Q503X
organoids before and during bath application of glutamate (Glu). Unpaired t-test
performed on a total of 16 cells from Patient
p.Q503X
organoids, from 3 independent experiments. P
value = 0.0005. Data is shown as mean ± SD. (H) ΔF/F(t) from GCaMP6f2 recordings of
03231
Control
and 03231
p.Q503X
organoids. (I) Calcium spike frequency analysis on 2-month-old
Patient
p.Q503X
organoids before and during bath application of tetrodotoxin (TTX). Unpaired t-test
performed on a total of 9 cells from Patient
p.Q503X
organoids, from 3 independent experiments. P
value =0.0001. Data is shown as mean ± SD

70

Chapter 3. Future Directions
The role of SYNGAP1 in the developing human cerebellum

Graphical Abstract

Figure 0-1
To further address the role of SYNGAP1 across diverse brain regions and cell types we have
begun a project focused in understanding the role of SYNGAP1 in the cerebellum. The human
cerebellum, which contains four-fifths of the brain’s neurons (S 2009), is endowed with an
unmatched computational power to regulate motor and non-motor behavior including language,
spatial processing, working memory, executive functions, and emotional processing. The
development of this complex structure differs significantly in humans compared to any other
species, which challenges the current approaches used to study the pathogenesis of cerebellar
disorders (S 2009, Amore G 2021). The cerebellum has been gaining substantial attention, given
71

emerging evidence of its role in cognitive functions, including language, spatial processing,
working memory, executive functions, and emotional processing (2022), in addition to its well-
described role in motor behaviors. Several lines of evidence have also shown
72

Figure 0-2. In-vitro development and characterization of human iPSC derived cerebellar
organoids.
(A) Graphical description of the protocol used to generate and maintain cerebellar organoids. (B) A UMAP from
single cell RNA sequencing of a two-month-old Corrected p.Q503X organoid with all discernable clusters
appropriately labeled. (C) A chart generated from the single cell data set depicting the expression of key identity
genes for each cluster identified.
cellular and gross morphological abnormalities within the cerebellum of murine models of major
autism risk genes including FMR1 (Domanski, Booker et al. 2019) and MECP2 (NP, LJ et al.
2021). To date, there has only been one study that has investigated the role of SYNGAP1 in the
cerebellum. This study was completed in primary murine granule cells and reported that
SYNGAP1 participates within a granule cell axon signaling complex to govern axon formation
and outgrowth (Tomoda, Kim et al. 2004). When SYNGAP1 is disrupted, there is resulting
inappropriate axon growth which can negatively impact neuronal circuitry. To interrogate the
human specific consequences of SYNGAP1 mutations during early stages of cerebellar
development, a fellow graduate student within my laboratory, Alexander Atamian, developed a
protocol to generate human iPSC derived cerebellar organoids (Figure 8-2a) which are amenable
to long term culture and capable of producing several major cerebellar cell types including
Bergman Glia, Granule Cells, and Purkinje Cells (Figure 8-2b-c). The presence of these cell
types and the ability to track development over time allowed for the interrogation of the role for
SYNGAP1 in these critical cerebellar cell types using the patient iPSC derived Patient
p.Q503X
line
and its isogenic corrected control. To ensure reproducibility across organoids in both their ability
to generate cerebellum and in any potentially observed disease phenotype, three individual
organoids from the Patient
p.Q503X
and the Corrected
p.Q503X
lines were sequenced (Figure 8-3a).
Indeed, it was observed that this protocol is capable of reproducibly generating a rich diversity of
cell types appropriate for the human cerebellum across organoids. Interestingly, SYNGAP1
expression was seen in across all defined clusters, spanning both progenitor and neuronal
73

populations (Figure 8-3b). A comparison of the cell populations generated between the patient
and corrected lines did not reveal any significant difference in the relative size of any cellular
population.

Figure 0-3. Deciphering the developmental trajectory of distinct cell types of the
cerebellum.
(A) UMAPS for individually sequenced Patient
p.Q503X
and the Corrected
p.Q503X
organoids at 2 months old (B) A
series of UMAPS each highlighting an individual gene to show its lineage trajectory (C) Pseudotime analysis of the
excitatory and inhibitory clusters. (D) Pseudotime analysis of all clusters comparing the Patient
p.Q503X
and the
Corrected
p.Q503X
cell populations.
74

However, pseudotime analysis pointed to a trend in Patient
p.Q503X
organoids containing a larger
proportion of cell types that were consistent with a more differentiated state (Figure 8-3c-d). To
validate this finding of accelerated differentiation and to investigate if this phenotype is coupled
to accelerated maturation an analysis of neuronal structure and function was performed. To
visualize the entirety of individual neurons organoids were sparsely labeled with a red
fluorescent protein (RFP) harboring lentivirus (Figure 8-4a). It was observed that labeled
Patient
p.Q503X
neurons had a more complex structure and were more often multipolar when
compared to Corrected
p.Q503X
neurons (Figure 8-4b). Additionally, it was observed that the soma
of Patient
p.Q503X
neurons was larger (Figure 8-4c) and that they produced longer and more
numerous dendrites (Figure 8-4d-f). This preliminary data is in line with what we have
previously reported in SYNGAP1 haploinsufficient radial glia and neurons of the dorsal
forebrain. These initial findings again highlight the importance of investigating the role of
SYNGAP1 across brain regions, cell types, and developmental time points. Further work will
need to be done to assess the protein interaction networks for SYNGAP1 and the potential
dysregulation of key pathways in individual cell types affected by SYNGAP1 haploinsufficiency
within the context of the cerebellum.

75

Figure 0-4. SYNGAP1 haploinsufficient cerebellar neurons display a more mature state.
a b
c
d
e
f
76

(A) RFP labeled neurons from Patient
p.Q503X
and the Corrected
p.Q503X
organoids. (B) Pie charts displaying the relative
percentages of neurons that are either multipolar, bipolar or unipolar between Patient
p.Q503X
and the Corrected
p.Q503X
.
(C) Graph displaying the differences in soma perimeter between Patient
p.Q503X
and the Corrected
p.Q503X
neurons. (D)
Graph displaying the differences in dendrite length between Patient
p.Q503X
and the Corrected
p.Q503X
neurons. (E)
Graphical representation of the number of dendrites observed at 60um from the soma of the neuron. (F) Graphical
representation of the number of dendrites observed at 30um from the soma of the neuron

77

Tools for tracing the lineage of distinct progenitor cell types through
development.

Graphical Abstract

Figure 0-5
While single cell RNA sequencing alone provides an in-depth snapshot of cellular
identity and dynamics, it lacks the ability to accurately trace the lineage of distinct cell types
over time. Induced pluripotent stem cell (iPSC)-derived brain organoids provide the potential to
address foundational questions in early human cortical development, such as which cell types
arise from which progenitors at what times, and how those dynamics change in response to
mutations or other perturbations associated with neurodevelopmental disorders such as
SYNGAP1 mutations. There is therefore a need to advance technology to match the potential
78

that organoids as a model system provide. To begin to address this, a fellow graduate student in
the laboratory, Jean Paul Urenda, in collaboration with the Elowitz laboratory at CalTech has
begun to develop and validate several technologies that allow for longitudinal analysis of
individual cells and their descendants over developmental timescales of days to months.
The Hypercascade system is similar to other currently available lineage tracing technologies that
utilize a barcode system; however, this system utilizes barcode targets that consist of 74-unit
arrays split into four layers. The layers are activated sequentially over time allowing for deep
sequencing of large populations of edited cells. This type of read out provides a comprehensive
picture of which progenitor subtypes are present in the developing cortex and what their
individual contributions to the generation of specific subtypes of postmitotic cells are.
The Zombie system which leverages RNA polymerases from bacteriophages to transcribe
genomically integrated barcodes in fixed cells, producing an amplified RNA product that can
then be detected using single-molecule FISH. This allows for meaningful analysis of the
spatiotemporal development of distinct types of cortical cells. The organization of both
individual cells and cell populations within tissue is a critical component of their biological
function. Preserving this information while also having the ability to determine lineage
trajectories can provide a clearer picture of how cells interact with each other and their
environment during critical periods of brain development.
The Synthetic RNA export system can package and secrete specific RNA molecules from
living cells in nanoparticles. Critically, by packaging engineered barcodes that are stochastically
edited over time in individual cells, the system potentially allows reconstruction of cell
population dynamics and lineage relationships. Thus, they are ideally suited to non-destructively
reveal the dynamics of organoid development. Integration of the RNA export system into
79

organoids has the capability to establish a generalizable platform for dynamic real time analysis
of developmental processes and reveal lineage and population size dynamics of human cortical
neurogenesis. The combination of single-cell sequencing with this system allows for the
reconstruction of cell population dynamics and lineage relationships, revealing the interplay
between proliferation and cell death during key stages of cortical development. More broadly,
this platform has the potential to dissect lineage trajectories in normal conditions or following
genetic and pharmacological perturbations.
Each of these technologies have their respective pros and cons in regard to the type and the
amount of data they are able to provide. The synthetic RNA export package is particularly
appealing in disease modeling studies because it allows for the collection of exported RNA from
the same individual control and mutation harboring organoids over time as well as before and
after an attempted rescue of a phenotype. Alternatively, because of the general lack of
knowledge in neuronal progenitor biology and the sizeable contribution of these progenitor
populations to neurodevelopmental disorders, the Zombie system would provide valuable
information on progenitor dynamics and organization under both normal developmental
conditions and in various disease states.
This future use of this technology to further interrogate the role of SYNGAP1 in early
human corticogenesis will be integral in understanding how progenitor biology is altered when
SYNGAP1 levels are decreased and how this affects their progeny and the totality of brain
development.

80

Conclusions
Neurodevelopmental diseases can have debilitating effects on afflicted individuals. The
currently available therapeutics are limited in their efficacy and often include adverse side
effects, highlighting the need for more effective disease-modifying therapies. To address these
challenges, human iPSC derived organoid models of neurodevelopment are valuable tools to
help bridge the translational gap between traditional in vitro systems and animal models.
Although current organoid models have limitations, including a lack of key cells such as
microglia and vasculature they are capable of generating cellular diversity and epigenetic states
that follow the developmental trajectory of the corresponding endogenous cell types (Camp,
Badsha et al. 2015, Quadrato, Nguyen et al. 2017, Velasco, Kedaigle et al. 2019, Trevino,
Sinnott-Armstrong et al. 2020, Gordon, Yoon et al. 2021, Paulsen, Velasco et al. 2022), allowing
for the functional characterization of ASD-risk genes in a longitudinal modeling and human
cellular context. Here, we employed an organoid model of SYNGAP1 pathology using patient
derived iPSCs and their isogenic CRISPR corrected controls.
In a cortical model of SYNGAP1 we show for the first time the expression of the synaptic
Ras GTP-ase activating protein 1 (SYNGAP1), one of the top ASD risk genes (Satterstrom,
Kosmicki et al. 2020), in human cortical progenitors (hCPs). Interestingly, we found that
multiple components of the postsynaptic density (PSD) of excitatory synapses, of which
SYNGAP1 is one of the most abundant components (Chen, Rojas-Soto et al. 1998), are enriched
in the proteome of hCPs. Specifically, we discover that SYNGAP1 is expressed within the apical
domain of human radial glia cells (hRGCs) where it lines the wall of the developing cortical
ventricular zone colocalizing with the tight junction-associated protein and MAGUK family
member TJP1. In a cortical organoid model of SYNGAP1 haploinsufficiency, we show
dysregulated cytoskeletal dynamics that impair the scaffolding and division plane of hRGCs,
81

resulting in disrupted lamination of the cortical plate and accelerated maturation of cortical
projection neurons. Additionally, within our cerebellar organoid model of SYNGAP1 we again
see expression of SYNGAP1 in progenitor population and the accelerated differentiation and
maturation of SYNGAP1 haploinsufficient neuronal populations. Future goals to address the
potential alteration in the developmental lineage of progenitor populations across diverse brain
regions will be pursued through advanced lineage tracing techniques such as the Hypercascade,
Zombie or RNA Exporter systems previously described.
Additionally, because SYNGAP1 is seen across progenitor populations in diverse brain
regions it would be intriguing to investigate its role in support cells such as astrocytes and
oligodendrocytes as well as in immune cells such as microglia. The ability to perform these
experiments in a human specific brain organoid model system requires more complex patterning
strategies involving either modulation of morphogens to allow for the genesis and maturation of
these cell types or the later integration of these separately generated cell types once organoid
identity has been established. Again, lineage tracing and single cell RNA sequencing will be
instrumental in determining the potential of SYNGAP1 haploinsufficiency in diverse progenitor
populations within the brain to contribute to dysregulation in mature cell types including but not
limited to neurons.
The idea of a point of convergence in the pathophysiology of neurodevelopmental disorder
has garnered attention in recent years. There have been several highly impactful studies
describing asynchronous neurogenesis and in the involvement of classically defined neuronal
proteins in neurogenic processes within progenitor populations (Willsey, Exner et al. 2021,
Paulsen, Velasco et al. 2022, Romero, Poirier et al. 2022) Because of the complex and
heterogenous nature of neurodevelopmental diseases, there has been little progress in the
82

development of effective treatments. The identification of a point of convergence across
neurodevelopmental diseases would provide a promising direction for the development of future
therapeutics. The evidence presented within this thesis and in recently published studies suggests
that this point of convergence may lie in very early stages of neurodevelopment and
predominantly effect radial glial populations, altering their division mode and ability to
accurately migrate away from their proliferative niches. While this is an exciting discovery it
suggests that treatment to correct this dysregulation would also need to occur during early stages
of neurogenesis. This would require in-utero diagnostic and therapeutic technologies, two fields
that are still in early stages of development and largely inaccessible to patients. With time we
hope that the ability to accurately diagnose and treat neurodevelopmental diseases in-utero will
progress while in the meantime we continue our work to better understand these disorders on a
cellular and molecular level.

83

References
(2022). "Cerebellar Structure and Function in Autism Spectrum Disorder." Journal of Psychiatry
and Brain Science.

Aaku-Saraste E, H. A., Huttner WB. (1996). "Loss of occludin and functional tight junctions, but
not ZO-1, during neural tube closure--remodeling of the neuroepithelium prior to neurogenesis."
Dev Biol.

Aceti, M., et al. (2015). "Syngap1 Haploinsufficiency Damages a Postnatal Critical Period of
Pyramidal Cell Structural Maturation Linked to Cortical Circuit Assembly." Biological Psychiatry
77(9): 805-815.

Alemany, A., et al. (2018). "Whole-organism clone tracing using single-cell sequencing." Nature
556(7699): 108-112.

Amore G, S. G., Ieni A, et al. (2021). "A Focus on the Cerebellum: From Embryogenesis to an
Age-Related Clinical Perspective." Fronteirs in Systems Neuroscience.

Araki Y, H. I., Gamache TR, Ju S, Collado-Torres L, Shin JH, Huganir RL. (2020). "SynGAP
isoforms differentially regulate synaptic plasticity and dendritic development." eLife.

Araki, Y., et al. (2015). "Rapid Dispersion of SynGAP from Synaptic Spines Triggers AMPA
Receptor Insertion and Spine Enlargement during LTP." Neuron 85(1): 173-189.

Atamian, A., et al. (2021). "Taming human brain organoids one cell at a time." Seminars in Cell
& Developmental Biology 111: 23-31.

Baio, J., et al. (2018). "Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years
— Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014."
MMWR. Surveillance Summaries 67(6): 1-23.

Berryer, M. H., et al. (2013). "Mutations inSYNGAP1Cause Intellectual Disability, Autism, and a
Specific Form of Epilepsy by Inducing Haploinsufficiency." Human Mutation 34(2): 385-394.

Bershteyn, M., et al. (2017). "Human iPSC-Derived Cerebral Organoids Model Cellular Features
of Lissencephaly and Reveal Prolonged Mitosis of Outer Radial Glia." Cell Stem Cell 20(4): 435-
449.e434.

Bhaduri, A., et al. (2021). "An atlas of cortical arealization identifies dynamic molecular
signatures." Nature 598(7879): 200-204.

Birey, F., et al. (2017). "Assembly of functionally integrated human forebrain spheroids." Nature
545(7652): 54-59.

Bourne, H. R., et al. (1990). "The GTPase superfamily: a conserved switch for diverse cell
functions." Nature 348(6297): 125-132.

C, O., et al. (2012). "Role of the MAGUK protein family in synapse formation and function."
Developmental neurobiology 72(1).

84

Cadwell, C. R., et al. (2016). "Electrophysiological, transcriptomic and morphologic profiling of
single neurons using Patch-seq." Nature Biotechnology 34(2): 199-203.

Cakir, B., et al. (2019). "Engineering of human brain organoids with a functional vascular-like
system." Nature Methods 16(11): 1169-1175.

Camp, J. G., et al. (2015). "Human cerebral organoids recapitulate gene expression programs
of fetal neocortex development." Proceedings of the National Academy of Sciences 112(51):
15672-15677.

Cappello, S., et al. (2012). "A Radial Glia-Specific Role of RhoA in Double Cortex Formation."
Neuron 73(5): 911-924.

Carlisle, H. J., et al. (2008). "SynGAP Regulates Steady-State and Activity-Dependent
Phosphorylation of Cofilin." J Neurosci 28(50): 13673-13683.

Chambers, S. M., et al. (2009). "Highly efficient neural conversion of human ES and iPS cells by
dual inhibition of SMAD signaling." Nature Biotechnology 27(3): 275-280.

Chatterjee, S., et al. (2018). "Nontoxic, double-deletion-mutant rabies viral vectors for retrograde
targeting of projection neurons." Nature Neuroscience 21(4): 638-646.

Chen, B.-C., et al. (2014). "Lattice light-sheet microscopy: Imaging molecules to embryos at
high spatiotemporal resolution." Science 346(6208): 1257998.

Chen, H.-J., et al. (1998). "A Synaptic Ras-GTPase Activating Protein (p135 SynGAP) Inhibited
by CaM Kinase II." Neuron 20(5): 895-904.

Chen, W.-T., et al. (2020). "Spatial Transcriptomics and In Situ Sequencing to Study
Alzheimer’s Disease." Cell 182(4): 976-991.e919.

Chen, X., et al. (2015). "PSD-95 family MAGUKs are essential for anchoring AMPA and NMDA
receptor complexes at the postsynaptic density." Proceedings of the National Academy of
Sciences 112(50): E6983-E6992.

Chenn, A. and S. K. Mcconnell (1995). "Cleavage orientation and the asymmetric inheritance of
notchl immunoreactivity in mammalian neurogenesis." Cell 82(4): 631-641.

Cherfils, J. and M. Zeghouf (2013). "Regulation of Small GTPases by GEFs, GAPs, and GDIs."
https://doi.org/10.1152/physrev.00003.2012.

Clement, J. P., et al. (2012). "Pathogenic SYNGAP1 mutations impair cognitive development by
disrupting maturation of dendritic spine synapses." Cell 151(4): 709-723.

Clement, J. P., et al. (2013). "SYNGAP1 Links the Maturation Rate of Excitatory Synapses to
the Duration of Critical-Period Synaptic Plasticity." J Neurosci 33(25): 10447-10452.

Coba, M. P., et al. (2018). "Dlgap1 knockout mice exhibit alterations of the postsynaptic density
and selective reductions in sociability." Scientific Reports 8(1).

85

Codeluppi, S., et al. (2018). "Spatial organization of the somatosensory cortex revealed by
osmFISH." Nature Methods 15(11): 932-935.

Concordet, J. P. and M. Haeussler (2018). "CRISPOR: Intuitive guide selection for
CRISPR/Cas9 genome editing experiments and screens." Nucleic Acids Research 46(W1).

Creson, T. K., et al. (2019). "Re-expression of SynGAP protein in adulthood improves
translatable measures of brain function and behavior." eLife 8.

De Jong, J. O., et al. (2021). "Cortical overgrowth in a preclinical forebrain organoid model of
CNTNAP2-associated autism spectrum disorder." Nature Communications 12(1).

De Rubeis, S., et al. (2014). "Synaptic, transcriptional and chromatin genes disrupted in autism."
Nature 515(7526): 209-215.

Domanski, A. P. F., et al. (2019). "Cellular and synaptic phenotypes lead to disrupted
information processing in Fmr1-KO mouse layer 4 barrel cortex." Nature Communications 10(1).

Edmondson, J. and M. Hatten (1987). "Glial-guided granule neuron migration in vitro: a high-
resolution time- lapse video microscopic study." The Journal of Neuroscience 7(6): 1928-1934.

Eng, C.-H. L., et al. (2019). "Transcriptome-scale super-resolved imaging in tissues by RNA
seqFISH+." Nature 568(7751): 235-239.

Esk, C., et al. (2020). "A human tissue screen identifies a regulator of ER secretion as a brain-
size determinant." Science 370(6519): 935-941.

Espuny-Camacho, I., et al. (2013). "Pyramidal Neurons Derived from Human Pluripotent Stem
Cells Integrate Efficiently into Mouse Brain Circuits In Vivo." Neuron 77(3): 440-456.

Eze, U. C., et al. (2021). "Single-cell atlas of early human brain development highlights
heterogeneity of human neuroepithelial cells and early radial glia." Nature Neuroscience 24(4):
584-594.

Frieda, K. L., et al. (2017). "Synthetic recording and in situ readout of lineage information in
single cells." Nature 541(7635): 107-111.

Fromer, M., et al. (2014). "De novo mutations in schizophrenia implicate synaptic networks."
Nature 506(7487): 179-184.

Gamache, T. R., et al. (2020). "Twenty Years of SynGAP Research: From Synapses to
Cognition." The Journal of Neuroscience 40(8): 1596-1605.

Genovese, G., et al. (2016). "Increased burden of ultra-rare protein-altering variants among
4,877 individuals with schizophrenia." Nature Neuroscience 19(11): 1433-1441.

Giandomenico, S. L., et al. (2019). "Cerebral organoids at the air–liquid interface generate
diverse nerve tracts with functional output." Nature Neuroscience 22(4): 669-679.

86

Gil-Sanz, C., et al. (2014). "Proliferative Defects and Formation of a Double Cortex in Mice
Lacking Mltt4 and Cdh2 in the Dorsal Telencephalon." Journal of Neuroscience 34(32): 10475-
10487.

Giovannucci, A., et al. (2019). "CaImAn an open source tool for scalable calcium imaging data
analysis."

Gomes, A. R., et al. (2020). "Modeling Rett Syndrome With Human Patient-Specific Forebrain
Organoids." Frontiers in Cell and Developmental Biology 8: 610427.

Gonzalez, W. G., et al. (2019). "Persistence of neuronal representations through time and
damage in the hippocampus." Science 365(6455): 821-825.

González, F., et al. (2014). "An iCRISPR Platform for Rapid, Multiplexable, and Inducible
Genome Editing in Human Pluripotent Stem Cells." Cell Stem Cell 15(2): 215-226.

Gordon, A., et al. (2021). "Long-term maturation of human cortical organoids matches key early
postnatal transitions." Nature Neuroscience 24(3): 331-342.

GT, K., et al. (2018). "Engineering induction of singular neural rosette emergence within hPSC-
derived tissues." eLife 7.

Götz, M. and W. B. Huttner (2005). "The cell biology of neurogenesis." Nature Reviews
Molecular Cell Biology 6(10): 777-788.

Hamdan, F. F., et al. (2009). "Mutations inSYNGAP1in Autosomal Nonsyndromic Mental
Retardation." New England Journal of Medicine 360(6): 599-605.

Hansen, D. V., et al. (2010). "Neurogenic radial glia in the outer subventricular zone of human
neocortex." Nature 464(7288): 554-561.

He, S., et al. (2015). "Inside-Out Radial Migration Facilitates Lineage-Dependent Neocortical
Microcircuit Assembly." Neuron 86(5): 1159-1166.

He, Z., et al. (2022). "Lineage recording in human cerebral organoids." Nature Methods 19(1):
90-99.

Hughes, C. S., et al. (2018). "Single-pot, solid-phase-enhanced sample preparation for
proteomics experiments." Nature Protocols 14(1): 68-85.

Ivics, Z., et al. (1997). "Molecular Reconstruction of Sleeping Beauty, a Tc1-like Transposon
from Fish, and Its Transposition in Human Cells." Cell 91(4): 501-510.

J, L., et al. (2016). "Long-term potentiation modulates synaptic phosphorylation networks and
reshapes the structure of the postsynaptic interactome." Science signaling 9(440).

Jimenez-Gomez, A., et al. (2019). "Phenotypic characterization of individuals with SYNGAP1
pathogenic variants reveals a potential correlation between posterior dominant rhythm and
developmental progression." Journal of Neurodevelopmental Disorders 11(1).

87

Jo, J., et al. (2016). "Midbrain-like Organoids from Human Pluripotent Stem Cells Contain
Functional Dopaminergic and Neuromelanin-Producing Neurons." Cell Stem Cell 19(2): 248-
257.

Jourdon, A., et al. (2022). ASD modelling in organoids reveals imbalance of excitatory cortical
neuron subtypes during early neurogenesis, Neuroscience.

Kadowaki M, N. S., Machon O, Krauss S, Radice GL, Takeichi M. (2007). "N-cadherin mediates
cortical organization in the mouse brain." Dev Biol 304(1): 22-33.

Kang, Y., et al. (2021). "A human forebrain organoid model of fragile X syndrome exhibits
altered neurogenesis and highlights new treatment strategies." Nature Neuroscience.

Kanton, S., et al. (2019). "Organoid single-cell genomic atlas uncovers human-specific features
of brain development." Nature 574(7778): 418-422.

Kawaguchi, A. (2021). "Frontiers | Neuronal Delamination and Outer Radial Glia Generation in
Neocortical Development." Frontiers in Cell and Developmental Biology.

Khachadourian, V., et al. (2023). "Comorbidities in autism spectrum disorder and their
etiologies." Translational Psychiatry 13(1).

Khan, T. A., et al. (2020). "Neuronal defects in a human cellular model of 22q11.2 deletion
syndrome." Nature Medicine 26(12): 1888-1898.

Kilinc M, A. V., Creson TK, Rojas C, Le AA, Lauterborn J, Wilkinson B, Hartel N, Graham N,
Reich A, Gou G, Araki Y, Bayés À, Coba M, Lynch G, Miller CA, Rumbaugh G. (2022).
"Endogenous Syngap1 alpha splice forms promote cognitive function and seizure protection."
eLife.

Kilinc, M., et al. (2018). "Species-conserved SYNGAP1 phenotypes associated with
neurodevelopmental disorders." Molecular and Cellular Neuroscience 91: 140-150.

Kim, J. H., et al. (2003). "The Role of Synaptic GTPase-Activating Protein in Neuronal
Development and Synaptic Plasticity." The Journal of Neuroscience 23(4): 1119-1124.

Kim, J. H., et al. (1998). "SynGAP: a Synaptic RasGAP that Associates with the PSD-95/SAP90
Protein Family." Neuron 20(4): 683-691.

Kim, J. H., et al. (1998). "SynGAP: a synaptic RasGAP that associates with the PSD-95/SAP90
protein family." Neuron 20(4): 683-691.

Kirov, G., et al. (2012). "De novo CNV analysis implicates specific abnormalities of postsynaptic
signalling complexes in the pathogenesis of schizophrenia." Molecular Psychiatry 17(2): 142-
153.

Klaus, J., et al. (2019). "Altered neuronal migratory trajectories in human cerebral organoids
derived from individuals with neuronal heterotopia." Nature Medicine 25(4): 561-568.

Knuesel, I., et al. (2005). "A role for synGAP in regulating neuronal apoptosis." 21(3): 611-621.

88

Komiyama, N. H., et al. (2002). "SynGAP Regulates ERK/MAPK Signaling, Synaptic Plasticity,
and Learning in the Complex with Postsynaptic Density 95 and NMDA Receptor." The Journal
of Neuroscience 22(22): 9721-9732.

Lancaster, M. A., et al. (2017). "Guided self-organization and cortical plate formation in human
brain organoids." Nature Biotechnology 35(7): 659-666.

Lancaster, M. A., et al. (2013). "Cerebral organoids model human brain development and
microcephaly." Nature 501(7467): 373-379.

Lavagnino, Z., et al. (2016). "4D (x-y-z-t) imaging of thick biological samples by means of Two-
Photon inverted Selective Plane Illumination Microscopy (2PE-iSPIM)." Scientific Reports 6(1):
23923.

Li, J., et al. (2017). "Spatiotemporal profile of postsynaptic interactomes integrates components
of complex brain disorders." Nature Neuroscience 20(8): 1150-1161.

Li, W., et al. (2001). "Characterization of a Novel synGAP Isoform, synGAP-β." Journal of
Biological Chemistry 276(24): 21417-21424.

Lippmann, E. S., et al. (2014). "Defined Human Pluripotent Stem Cell Culture Enables Highly
Efficient Neuroepithelium Derivation Without Small Molecule Inhibitors." Stem Cells 32(4): 1032-
1042.

Llamosas, N., et al. (2020). "SYNGAP1Controls the Maturation of Dendrites, Synaptic
Function, and Network Activity in Developing Human Neurons." The Journal of Neuroscience
40(41): 7980-7994.

Madhavan, M., et al. (2018). "Induction of myelinating oligodendrocytes in human cortical
spheroids." Nature Methods 15(9): 700-706.

Mariani, J., et al. (2015). "FOXG1-Dependent Dysregulation of GABA/Glutamate Neuron
Differentiation in Autism Spectrum Disorders." Cell 162(2): 375-390.

Marton, R. M., et al. (2019). "Differentiation and maturation of oligodendrocytes in human three-
dimensional neural cultures." Nature Neuroscience 22(3): 484-491.

Mckenna, A. and J. A. Gagnon (2019). "Recording development with single cell dynamic lineage
tracing." Development 146(12): dev169730.

McMahon, A., et al. "SynGAP isoforms exert opposing effects on synaptic strength." Nat
Commun 3: 900-.

Mellios, N., et al. (2018). "MeCP2-regulated miRNAs control early human neurogenesis through
differential effects on ERK and AKT signaling." Molecular Psychiatry 23(4): 1051-1065.

Michaelson, S. D., et al. (2018). "SYNGAP1 heterozygosity disrupts sensory processing by
reducing touch-related activity within somatosensory cortex circuits." Nature Neuroscience
21(12): 1-13.

89

Muguruma, K., et al. (2015). "Self-Organization of Polarized Cerebellar Tissue in 3D Culture of
Human Pluripotent Stem Cells." Cell Reports 10(4): 537-550.

Nicoll, R. A. (2017). "A Brief History of Long-Term Potentiation." Neuron 93(2): 281-290.

Noctor, S. C., et al. (2004). "Cortical neurons arise in symmetric and asymmetric division zones
and migrate through specific phases." Nature Neuroscience 7(2): 136-144.

Nowakowski, T. J., et al. (2017). "Spatiotemporal gene expression trajectories reveal
developmental hierarchies of the human cortex." Science 358(6368): 1318-1323.

Nowakowski, Tomasz J., et al. (2016). "Transformation of the Radial Glia Scaffold Demarcates
Two Stages of Human Cerebral Cortex Development." Neuron 91(6): 1219-1227.

NP, A., et al. (2021). "Deleting Mecp2 from the cerebellum rather than its neuronal subtypes
causes a delay in motor learning in mice." eLife 10.
Rett syndrome is a devastating childhood neurological disorder caused by mutations in
MECP2. Of the many symptoms, motor deterioration is a significant problem for patients.
In mice, deleting Mecp2 from the cortex or basal ganglia causes motor dysfunction,
hypoactivity, and tremor, whi …

O'Roak, B. J., et al. (2011). "Exome sequencing in sporadic autism spectrum disorders identifies
severe de novo mutations." Nature Genetics 43(6): 585-589.

Okita, K., et al. (2013). "An Efficient Nonviral Method to Generate Integration-Free Human-
Induced Pluripotent Stem Cells from Cord Blood and Peripheral Blood Cells." Stem Cells 31(3):
458-466.

Oliva, C. and J. Sierralta (2018). MAGUK. Encyclopedia of Signaling Molecules, Springer
International Publishing: 2918-2924.

Ozkan, E. D., et al. (2014). "Reduced cognition in Syngap1 mutants is caused by isolated
damage within developing forebrain excitatory neurons." Neuron 82(6): 1317-1333.

O’Roak, B. J., et al. (2012). "Sporadic autism exomes reveal a highly interconnected protein
network of de novo mutations." Nature 485(7397): 246-250.

P, R. (1971). "Guidance of neurons migrating to the fetal monkey neocortex." Brain research
33(2).

P, R. (1972). "Mode of cell migration to the superficial layers of fetal monkey neocortex." The
Journal of comparative neurology 145(1).

P, R. (1978). "Neuronal migration and contact guidance in the primate telencephalon."
Postgraduate medical journal 54 Suppl 1.

Park, J., et al. (2018). "A 3D human triculture system modeling neurodegeneration and
neuroinflammation in Alzheimer’s disease." Nature Neuroscience 21(7): 941-951.

Paulsen, B., et al. (2022). "Autism genes converge on asynchronous development of shared
neuron classes." Nature 602(7896): 268-273.
90

Paşca, A. M., et al. (2015). "Functional cortical neurons and astrocytes from human pluripotent
stem cells in 3D culture." Nature Methods 12(7): 671-678.

Peça, J. and G. Feng (2012). "Cellular and synaptic network defects in autism." Current Opinion
in Neurobiology 22(5): 866-872.

Pollen, A. A., et al. (2019). "Establishing Cerebral Organoids as Models of Human-Specific
Brain Evolution." Cell 176(4): 743-756.e717.

Qian, X., et al. (2016). "Brain-Region-Specific Organoids Using Mini-bioreactors for Modeling
ZIKV Exposure." Cell 165(5): 1238-1254.

Qian, X., et al. (2020). "Sliced Human Cortical Organoids for Modeling Distinct Cortical Layer
Formation." Cell Stem Cell 26(5): 766-781.e769.

Quadrato, G., et al. (2017). "Cell diversity and network dynamics in photosensitive human brain
organoids." Nature 545(7652): 48-53.

Raaijmakers, J. H. and J. L. Bos (2009). "Specificity in Ras and Rap Signaling." Journal of
Biological Chemistry 284(17): 10995-10999.

Raj, B., et al. (2018). "Simultaneous single-cell profiling of lineages and cell types in the
vertebrate brain." Nature Biotechnology 36(5): 442-450.

Romero, D. M., et al. (2022). "Novel role of the synaptic scaffold protein Dlgap4 in ventricular
surface integrity and neuronal migration during cortical development." Nature Communications
13(1).

Rumbaugh, G., et al. (2006). "SynGAP regulates synaptic strength and mitogen-activated
protein kinases in cultured neurons." Proc Natl Acad Sci U S A 103(12): 4344-4351.

S, H.-H. (2009). "The human brain in numbers: a linearly scaled-up primate brain." Frontiers in
human neuroscience 3.

Saelens, W., et al. (2019). "A comparison of single-cell trajectory inference methods." Nature
Biotechnology 37(5): 547-554.

Sakaguchi, H., et al. (2015). "Generation of functional hippocampal neurons from self-organizing
human embryonic stem cell-derived dorsomedial telencephalic tissue." Nature Communications
6(1): 8896.

Salmén, F., et al. (2018). "Barcoded solid-phase RNA capture for Spatial Transcriptomics
profiling in mammalian tissue sections." Nature Protocols 13(11): 2501-2534.

Samarasinghe, R. A., et al. (2021). "Identification of neural oscillations and epileptiform changes
in human brain organoids." Nature Neuroscience 24(10): 1488-1500.

Satterstrom, F. K., et al. (2020). "Large-Scale Exome Sequencing Study Implicates Both
Developmental and Functional Changes in the Neurobiology of Autism." Cell 180(3): 568-
584.e523.
91

Sawada, T., et al. (2020). "Developmental excitation-inhibition imbalance underlying psychoses
revealed by single-cell analyses of discordant twins-derived cerebral organoids." Molecular
Psychiatry 25(11): 2695-2711.

Schafer, S. T., et al. (2019). "Pathological priming causes developmental gene network
heterochronicity in autistic subject-derived neurons." Nature Neuroscience 22(2): 243-255.

Schmunk, G., et al. (2020). Human microglia upregulate cytokine signatures and accelerate
maturation of neural networks, Cold Spring Harbor Laboratory.

Schöneberg, J., et al. (2018). "Engineering biofunctional in vitro vessel models using a
multilayer bioprinting technique." Scientific Reports 8(1).

Shitamukai, A., et al. (2011). "Oblique Radial Glial Divisions in the Developing Mouse Neocortex
Induce Self-Renewing Progenitors outside the Germinal Zone That Resemble Primate Outer
Subventricular Zone Progenitors." The Journal of Neuroscience 31(10): 3683-3695.

Smits, L. M., et al. (2019). "Modeling Parkinson’s disease in midbrain-like organoids." npj
Parkinson's Disease 5(1).

Song, L., et al. (2019). "Functionalization of Brain Region-specific Spheroids with Isogenic
Microglia-like Cells." Scientific Reports 9(1).

Spanjaard, B., et al. (2018). "Simultaneous lineage tracing and cell-type identification using
CRISPR–Cas9-induced genetic scars." Nature Biotechnology 36(5): 469-473.

Su, P., et al. (2019). "Disruption of SynGAP–dopamine D1 receptor complexes alters actin and
microtubule dynamics and impairs GABAergic interneuron migration." Science Signaling
12(593): eaau9122.

Tanaka, Y. H., et al. (2018). "Thalamocortical Axonal Activity in Motor Cortex Exhibits Layer-
Specific Dynamics during Motor Learning." Neuron 100(1): 244-258.e212.

ten Berge, D., et al. (2008). "Wnt Signaling Mediates Self-Organization and Axis Formation in
Embryoid Bodies." Cell Stem Cell 3(5): 508-518.

Tidball, A. M., et al. (2022). Self-organizing Single-Rosette Brain Organoids from Human
Pluripotent Stem Cells, Cold Spring Harbor Laboratory.

Tomoda, T., et al. (2004). "Role of Unc51.1 and its binding partners in CNS axon outgrowth."
Genes & Development 18(5): 541-558.

Trevino, A. E., et al. (2020). "Chromatin accessibility dynamics in a model of human forebrain
development." Science 367(6476): eaay1645.

Urresti, J., et al. (2021). "Cortical organoids model early brain development disrupted by
16p11.2 copy number variants in autism." Molecular Psychiatry 26(12): 7560-7580.

92

Uzquiano, A., et al. (2022). "Single-cell multiomics atlas of organoid development uncovers
longitudinal molecular programs of cellular diversification of the human cerebral cortex."
BioRxiv: 123.

van den Hurk M, E. J., Yeo GW, Gage FH, Bardy C (2018). "Patch-Seq Protocol to Analyze the
Electrophysiology, Morphology and Transcriptome of Whole Single Neurons Derived From
Human Pluripotent Stem Cells." Fronteirs in Molecular Neuroscience 11(261).

Velasco, S., et al. (2019). "Individual brain organoids reproducibly form cell diversity of the
human cerebral cortex." Nature 570(7762): 523-527.

Villa, C. E., et al. (2022). "CHD8 haploinsufficiency links autism to transient alterations in
excitatory and inhibitory trajectories." Cell Reports 39(1): 110615.

Wagner, D. E. and A. M. Klein (2020). "Lineage tracing meets single-cell omics: opportunities
and challenges." Nature Reviews Genetics 21(7): 410-427.

Walkup Ward G. , S. M. J., Graham Robert L., Hess Sonja, Kennedy Mary B. (2018).
"Phosphorylation of synaptic GTPase-activating protein (synGAP) by polo-like kinase (Plk2)
alters the ratio of its GAP activity toward HRas, Rap1 and Rap2 GTPases." Biochemical and
Biophysical Research Communications 503(3): 1599-1604.

Walkup, W. G., et al. (2016). "A model for regulation by SynGAP-α1 of binding of synaptic
proteins to PDZ-domain 'Slots' in the postsynaptic density." eLife 5.

Wang, C. C., et al. (2013). "SynGAP Regulates Protein Synthesis and Homeostatic Synaptic
Plasticity in Developing Cortical Networks." PLoS One 8(12).

Wang, G., et al. (2018). "Multiplexed imaging of high-density libraries of RNAs with MERFISH
and expansion microscopy." Scientific Reports 8(1).

Wang, M., et al. (2020). "Modeling neuropsychiatric disorders using human induced pluripotent
stem cells." Protein & Cell 11(1): 45-59.

Wilkinson, B., et al. (2019). "Endogenous Cell Type–Specific Disrupted in Schizophrenia 1
Interactomes Reveal Protein Networks Associated With Neurodevelopmental Disorders."
Biological Psychiatry 85(4): 305-316.

Wilkinson, B., et al. (2017). "Synaptic GAP and GEF Complexes Cluster Proteins Essential for
GTP Signaling." Sci Rep 7.

Willsey, H. R., et al. (2021). "Parallel in vivo analysis of large-effect autism genes implicates
cortical neurogenesis and estrogen in risk and resilience." Neuron 109(5): 788-804.e788.

Xiang, Y., et al. (2019). "hESC-Derived Thalamic Organoids Form Reciprocal Projections When
Fused with Cortical Organoids." Cell Stem Cell 24(3): 487-497.e487.

Xiang, Y., et al. (2020). "Dysregulation of BRD4 Function Underlies the Functional Abnormalities
of MeCP2 Mutant Neurons." Molecular Cell 79(1): 84-98.e89.

93

Xiang, Y., et al. (2017). "Fusion of Regionally Specified hPSC-Derived Organoids Models
Human Brain Development and Interneuron Migration." Cell Stem Cell 21(3): 383-398.e387.

Yoon, K.-J., et al. (2014). "Modeling a Genetic Risk for Schizophrenia in iPSCs and Mice
Reveals Neural Stem Cell Deficits Associated with Adherens Junctions and Polarity." Cell Stem
Cell 15(1): 79-91.

Zeng, M., et al. (2017). "Anchoring high concentrations of SynGAP at postsynaptic densities via
liquid-liquid phase separation." Small GTPases: 1-9.

Zeng, M., et al. (2016). "Phase Transition in Postsynaptic Densities Underlies Formation of
Synaptic Complexes and Synaptic Plasticity." Cell 166(5): 1163-1175.e1112.

Zhang H, Y. L., Duan J, Zeng Q, Chen L, Fang Y, Hu J, Cao D and Liao J (2021). "Phenotypes
in Children with SYNGAP1 Ecephalopathy in China." Fronteirs in Neuroscience.

Zhu, J. J., et al. (2002). "Ras and Rap Control AMPA Receptor Trafficking during Synaptic
Plasticity." Cell 110(4): 443-455.

Ziffra, R. S., et al. (2021). "Single-cell epigenomics reveals mechanisms of human cortical
development." Nature 598(7879): 205-213.

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Appendices
Methods and Materials
hiPSC Line Generation
Patient
p.Q503X
Cell Line: An iPSCs line from a patient carrying a SYNGAP1 – c.1507C>T;
p.Q503X nonsense mutation was generated. iPSCs were generated using the episomal expression
of Yamanaka factors in patient-derived PBMCs (Okita, Yamakawa et al. 2013).
Patient
Corrected
Cell Line: A sgRNA targeting the patient-specific mutation in SYNGAP1 was cloned
into pSpCas9(BB)-2A-Puro (PX459) V2.0 (Addgene plasmid #62988). This, along with an HDR
template containing the WT SYNGAP1 sequence, were nucleofected into the patient-derived
iPSC line. Individual iPSC colonies were transferred to 24 well plates and subsequently
underwent restriction enzyme-based genotyping. Positive colonies were then confirmed via
Sanger sequencing and expanded in culture.
HDRTemplate:CCGCGAGAACACGCTTGCCACTAAAGCCATAGAAGAGTATATGAGAC
TGATTGGTCAGAAATATCTCAAGGATGCCATTGGTATGGCCCACACTCAGGCCCTCT
TCTTCCCAAACCTGCCA.
The underlined CAG sequence corresponds to the insertion of the wildtype "T" base pair and the
underlined T base corresponds to a silent mutation to disrupt the PAM sequence of the sgRNA.
The substitution of the truncating “T” with the wildtype “C” base pair was screened for via
restriction enzyme digestion and then confirmed via Sanger sequencing.

Mutation – c.1507C>T; p.Q503X nonsense mutation
Genotyping info – Introduction of correction destroys DrdI restriction enzyme site which was
used for initial screening of cell lines. Work on the patient-derived line patient p.Q503X is
approved by the USC IRB: HS-18-00745.

RASGAP Dead Line
A sgRNA targeting the arginine finger region of SYNGAP1 was cloned into pSpCas9(BB)-2A-
Puro (PX459) V2.0 (Addgene plasmid #62988). This, along with an HDR template to introduce
the R485P RasGAP-dead mutation
80
, were nucleofected in the 03231 control iPSC line derived
from a healthy 56-year-old male
45
. Individual iPSC colonies were transferred to 24 well plates
95

and subsequently underwent restriction enzyme-based genotyping. Positive colonies were
subsequently confirmed via Sanger sequencing. Guide Sequence used:
CGTGTTCTCGCGGAATATGHDR Template used:
ACTTCCTTTCAGACATGGCCATGTCTGAGGTAGACCGGTTCATGGAACGGGAGCACt
TaATATTCCcCGAGAACACGCTTGCCACTAAAGCCATAGAAGAGTATATGAGACTGA
TTGGTCAGA. The introduction of silent PAM mutation creates a new MseI restriction enzyme
site which was used for initial screening of cell lines.

03231
p.Q503X

The 03231
p.Q503X
cell line was generated in the 03231 control iPSC line derived from a healthy 56-
year-old male(Wilkinson, Evgrafov et al. 2019). Via substitution of c.1507C>T; p.Q503X. A
sgRNA targeting the SYNGAP1 c.1507C site was cloned into pSpCas9(BB)-2A-Puro (PX459)
V2.0 (Addgene plasmid #62988). The sgRNA together with the HDR template to introduce the
1507C>T mutation. were nucleofected in the 03231 control iPSC line derived from a healthy 56-
year-old male (Wilkinson, Evgrafov et al. 2019). Individual iPSC colonies were transferred to 24
well plates and subsequently underwent restriction enzyme-based genotyping. Positive colonies
were subsequently confirmed via Sanger sequencing. Guide Sequence used:
CCATACCAATGGCATCCTTG.
HDR template used: CCGCGAGAACACGCTTGCCACTAAAGCCATAGAAGAGTATATG
AGACTGATTGGTTAGAAATATCTCAAGGATGCCATTGGTATGGCCCACACTCAGGCC
CTCTTCTTCCCAAACCTGCCA
The Underlined TAG region shows the 1507C>T inserted mutation and the underlined T base
shows the introduced silent PAM site.
Genotyping info – Introduction of correction modifies the DrdI restriction enzyme site which
was used for the initial screening of cell lines.

Off-target predictions were carried out using CRISPOR (Concordet and Haeussler 2018) he top
ten off predicted off-target sites for the Patient 1- Corrected and RASGAP dead iPSC lines
amenable to PCR were amplified using Q5 High-Fidelity DNA Polymerase (New England
Biolabs; M0491S) and the resulting PCR products underwent Sanger Sequencing. All primers
96

used for PCR amplification of predicted off-target sites were ordered from Integrated DNA
Technologies and are listed in Supplemental Table 4.

Cell Culture and Dorsal Forebrain Organoid Generation
hiPSC lines were maintained with daily media change in mTeSR (STEMCELL Technologies,
#85850) on 1:100 geltrex (GIBCO, #A1413301) coated tissue culture plates (CELLTREAT,
#229106) and passaged using ReLeSR (STEMCELL Technologies, #100-0484). Cells were
maintained below passage 50 and periodically karyotyped via the G-banding Karyotype Service
at Children’s Hospital Los Angeles. Organoid generation was performed as previously described
in

(Velasco, Kedaigle et al. 2019).

Procurement of Human Tissue
The de-identified human specimen was collected from autopsy, with previous patient consent to
institutional ethical regulations of the University of California San Francisco Committee on
Human Research. Collection was at a postmortem interval (PMI) of less than 24 hours. Tissue
was collected at the following institution with previous patient consent to institutional ethical
regulations: (1) The University of California, San Francisco (UCSF) Committee on Human
Research. Protocols were approved by the Human Gamete, Embryo and Stem Cell Research
Committee (Institutional Review Board GESCR# 10- 02693) at UCSF. Specimens were
evaluated by a neuropathologist as control samples. Tissues were cut coronally, and 1 mm tissue
blocks were fixed with 4% paraformaldehyde for two days, and cryoprotected in a 30% sucrose
gradient. The tissue was then frozen in OCT and blocks were cut at 30 μm with a cryostat and
mounted onto glass slides.

Procurement of Mouse Tissue
All animal procedures were conducted in accordance with the Guide for the Care and Use of
Laboratory Animals of the National Institutes of Health, and all procedures were approved by the
Institutional Animal Care and Use Committee (IACUC) of the Herbert Wertheim UF Scripps
Institute for Biomedical Innovation and. Males and females were used in all experiments and
final male/female ratio in datasets reflect uncontrollable variables, such as the ratio of
male/female (M/F) offspring achieved from the multigenerational breeding schemes and
97

experimental attrition. Mice were housed four or five per cage on a 12-h normal light–dark cycle.
We used inbred Syngap1 constitutive Syngap1
+/−
(heterozygous) mice
13
. Each line is maintained
by colony inbreeding on a mixed background of C57-BL6/129s. Every seventh
generation, Syngap1
+/−
mice are refreshed by crossing colony breeders into C57-BL6/129 F1
(Taconic B6129F1) animals for one generation. Offspring from these crosses, like those used for
this study, are then inbred for up to seven generations. For staging of embryos, the day of vaginal
plug was considered E0.5. Embryo collection was carried out at E18.5. The dams were
anesthetized using an isoflurane induction chamber (5% isoflurane) and placed in a nose cone
with flowing isoflurane for maintenance (2.5% isoflurane). After fixation on a prewarmed
surgery platform and sterilization of the skin with Betadine, the abdominal cavity was opened
through 2 incisions along the midline to expose the uterine horns. The uterine wall was incised to
expose embryos within their fetal membranes. The pups were extracted from the yolk sac and
then placed on a petri dish with ice cold PBS. All pups were decapitated, the brains quickly
extracted from the skull, and each submerged in vials with 4% PFA. Following the pup
dissections, dams were euthanized by cervical dislocation while under isoflurane anesthesia.
Genotyping of all transgenic mouse lines was outsourced to Transnetyx automated genotyping
services.

Singular Neural Rosette Tissues
All pluripotent lines were maintained in Essential Eight medium (E8) (Thermo Fisher,
#A1517001) on geltrex (GIBCO, #A1413301) coated tissue culture plates and routinely passaged
with ReLeSR (STEMCELL Technologies, #05872). RGCs derivation from hPSCs was
performed using Essential Six Medium (E6) (Thermo Fisher, #A1516501)(Lippmann, Estevez-
Silva et al. 2014). To generate RGCs-derived micropatterned, cells were first rinsed with PBS,
dissociated with Accutase (STEMCELL Technologies, #07922) for 5 min at 37°C, and collected
via centrifugation at 1000 rpm for 5 min. Singularized RGCs were re-suspended in E6 media
with 10 μM ROCK inhibitor (Y27632; STEMCELL Technologies, #72302) and seeded onto
micropatterned substrates at 75,000 cells/cm2 in 2 mL of media per well. The following day, the
media was replaced with 2 mL of E6 media, and 50% media changes were performed daily
thereafter. 96-well plates were custom made with micropatterning of poly(ethylene glycol methyl
98

ether)-grafted substrates, presenting arrays of 250μm diameter circular regions and coated with
Matrigel over-night
44
.

Immunohistochemistry
Organoids
Organoids were fixed in 4% PFA for 30 min at room temperature before an overnight incubation
at 4℃ in 30% sucrose solution. Organoids were then embedded in Tissue-Tek O.C.T. compound
(Sakura, #62550) and sectioned at 20 µm with a cryostat onto glass slides (Globe Scientific,
#1354W). Slides were washed 3x with a 0.1% Tween20 (Sigma, #P9416) solution before a 1-
hour incubation in 0.3%TritonX-100 (Sigma, #T9284) and 6% bovine serum albumin (Sigma,
#AA0281) solution. An overnight incubation at 4℃ in a primary antibody solution was followed
by a 2-hour room temperature incubation in a secondary antibody solution, both consisting of
0.1%TritonX-100 and 2.5%BSA with 3 washes before and after secondary antibody incubation.
Slides were cover slipped using Fluoromount G (EMS, #50-259-73). BrdU staining was
performed by initially treating the slides with 2M HCL (Sigma, H1758-100ml) for 30 minutes at
room temperature followed by a neutralization step with 0.1 M sodium borate (Millipore, #
SX0355-1) buffer at pH 8.5 for 10 minutes at room temperature before continuing with the above
described IHC protocol.

Mouse Tissue
Mouse tissue underwent a similar IHC protocol aside from the addition of antigen retrieval prior
to beginning the IHC protocol. Antigen retrieval was performed by incubating slides in citrate
buffer at 95℃ for 30 minutes. Slides were then returned to room temperature and allowed to sit
in the citrate buffer for 1 hour before continuing with the IHC protocol.

Antibody Species Catalog Number Company
DAPI -- 80051-386 Sigma/Millipore
SATB2 Mouse AB51502 Abcam
99

MAP2 Chicken AB5392 Abcam
NESTIN Mouse AB22035 Abcam
CTIP2 (BLC11B) Rat AB18465 Abcam
SOX2 Goat AF2018 RD Systems
TBR2 (EOMES) Rabbit AB2283 Millipore
TBR2 (EOMES) Chicken
AB15894
Millipore
PAX6 Rabbit 901301 Biolegend
Pericentrin Rabbit AB4448 Abcam
Anti-RFP Rabbit 600-401-379 Rockland
p-Vimentin Mouse D076-3 MBL
ZO-1 (TJP1) Mouse 610966 BD Transduction Laboratories
SYNGAP1 Rabbit 5539 Cell Signaling Technology
SYNGAP1 Rabbit 5540 Cell Signaling Technology
SYNGAP1 Rabbit AB77235 Abcam
Acetylated Tubulin Mouse T6793-100UL Sigma Aldrich
Bromodeoxyuridine (BrdU) Rat AB6326 Abcam
NeuN Rabbit AB177487 Abcam

Peptide competition assay
Three consecutive organoids slices were used for analysis. Rabbit anti-SYNGAP1 (5539, Cell
Signaling Technology) was diluted at a concentration of 1:200 in 0.3%TritonX-100 (Sigma,
#T9284) and 6% bovine serum albumin (Sigma, #AA0281) blocking solution. The solution was
100

divided in three tubes where no blocking antigenic peptide, 5x and 10x peptide (32835S, Cell
Signaling Technology) were added. Tubes were incubated with agitation overnight at 4℃. The
immunofluorescence procedure was performed as described in the manuscript.

BrdU Labeling in Cortical Organoids
2-month-old organoids were incubated with 10 µm of the thymidine analogue
Bromodeoxyuridine (BrdU) (Sigma, #B5002) for 2 hours before being rinsed with PBS and then
allowed to remain in culture for 24hrs. After the 24hr chase organoids were removed from
culture and fixed for 30 minutes in 4% PFA at room temperature.

Whole proteome analysis of organoids
Deep proteome profiling was performed on 21 human cortical organoids at D.I.V. 7 from the
03231 control line. After lysis in RIPA buffer (Pierce), extracted proteins were reduced with 5
mM DTT, followed by incubation with 20 mM iodoacetamide in the dark. Sample cleanup was
performed using the SP3 method and on-bead digestion was performed overnight using
Trypsin/Lys-C (Promega). Eluted tryptic peptides from SP3 beads were pre-fractionated by high
pH reverse phase chromatography into 96 individual fractions using a 64-minute gradient from
1% to 50% solvent B (A: 10mM NH4OH, B: acetonitrile) on a Cadenza C18 column (Imtakt) The
collected 96 fractions were recombined (Hughes, Moggridge et al. 2018) into final 24 fractions
by pooling every 24
th
fraction for LC-MS/MS analysis. 500 ng peptide from each fraction was
analyzed by a 60-minute LC/MS/MS method on an Orbitrap Fusion Lumos mass spectrometer
(ThermoFisher Scientific) interfaced with a Ultimate 3000 UHPLC system (ThermoFisher
Scientific). Full scans were acquired in the Orbitrap at a resolution of 120K and a scan range of
400-1600 m/z. Most abundant precursor ions from the full scan were selected using an isolation
window of 1.6 Da and subjected to HCD fragmentation with an NCE of 30% and detection in the
iontrap. Raw data files were searched using Byonic (v2.16.11) in Proteome Discoverer (v2.4)
against the Swissprot human protein database (downloaded November, 2020). The following
search parameters were used: fully tryptic peptides with a maximum of 2 missed cleavages, 10
ppm precursor mass tolerance, 0.5 Da fragment mass tolerance, fixed modification of cysteine
carbamidomethylation, oxidation of methionine, deamidation of glutamine and asparagine were
selected as dynamic modifications. The protein and peptide-level confidence thresholds were set
101

at 99% (FDR <0.01). Using this pipeline, we identified a total of 8686 proteins, including 24
unique peptides for SYNGAP1. The protein/gene list obtained from MS analysis was imported
into SynGO portal and cellular component annotation where obtained.

Generation and Analysis of the SYNGAP1 Interactome
SYNGAP1 protein immunoisolation was performed using 50 human cortical organoids at D.I.V.
7, generated from both the 0323
control
and the Patient
Corrected
iPSC lines, in duplicate assays. SYNGAP1
was immunoprecipitated using 2ug/ml of SYNGAP1 antibody (Cell Signaling 5540) and 3mg/ml
of total protein lysate. The SYNGAP1 KO cell line was used in duplicate assays a IP control.
Peptide identification was performed as described for whole proteome analysis. Protein
interactors were defined as proteins present in duplicate samples and absent in KO controls.

Quantitation of SYNGAP1 total protein and identification of the SYNGAP1 alpha 1
isoform
Peptides were synthesized commercially (ThermoFisher Scientific) TVSVPVEGR; DAIGEFIR,
and GSFPPWVQQTR. SYNGAP1 id: A0A2R8Y6T2. Both unlabeled light and isotope labeled
heavy forms were synthesized. Commercially synthesized labeled peptides used
13
C and
15
N
labeled lysine or arginine. An internal standard was prepared from the isotope-labeled standards
in 3% acetonitrile with 0.1% formic acid with 5 fmol/µL of Peptide Retention Time Calibration
(PRTC) mixture (ThermoFisher Scientific) and 10 µg/mL E. coli lysate digest (Waters) as a
carrier. Isotope-labeled peptides were dissolved at 2000 pg/mL. Standard Concentration:
1000pg/mL. A calibration curve was prepared from the light standards in 3% acetonitrile with
0.1% formic acid and 10 µg/mL E. coli lysate digest, but without the PRTC mixture. The
highest concentration stock was prepared at 250000 pg/mL The final calibration standards were
made by mixing the stocks 1:1 with internal standard mixture. Dried protein digests were
dissolved in 20µL of a 1:1 mixture of internal standard mixture and 10 µg/mL E. coli lysate
digest and 5 µL was injected on-column for PRM data acquisition.
Samples were analyzed on an Ultimate 3000 nanoflow UHPLC system coupled to an Orbitrap
Fusion Lumos mass spectrometer (ThermoFisher Scientific). Digested peptides were separated
using a 25 cm C18 EasySpray column (75 µM ID, 2 µm particle size) using 0.1% formic acid in
water as mobile phase A and 0.1% formic acid in acetonitrile as mobile phase B. Peptides were
102

analyzed using a timed parallel reaction monitoring (tPRM) method. Expected retention times
were measured before each batch by analyzing the internal standard. Each peptide was given a
retention time window of ±2 minutes. Precursor m/z for each peptide. Data was analyzed in
Skyline. For each assay, top three fragment ions without any interference were selected for
quantitation. The calibration curve used the ratio of light to heavy peptide using a bilinear curve
fitting and 1/x
2
weighting. The limit of quantitation was estimated as the lowest calibration point
with a coefficient of variability below 15% and an average error below 15%. Limit of detection
was calculated using the standard of deviation of the blank and the standard of deviation of the
sample at the limit of quantitation; the higher value was used as the limit of detection. Peptides
were considered detected if all three product ions were detected, the dot product ratio was at least
0.7, and the measured quantity was above the limit of detection.

Bulk-RNA Sequencing
Organoids derived from haploinsufficient and corrected control lines were collected at DIV 7
from 2 independent differentiations (50 corrected and 100 patient organoids per genotype, per
differentiation). Total RNA was isolated using Qiagen columns. Library preparation and RNA
sequencing were performed as a service by QuickBiology.

Data preprocessing was performed with trimmomatic to filter out adapter sequences and low-
quality reads. The processed reads were mapped to the human reference genome from Ensembl
(GRCh38.p13) using HISAT2 v2.1.0. We summed the read counts and TPM of all alternative
splicing transcripts of a gene to obtain gene expression levels and restricted our analysis to
20000 expressed genes with an average TPM >1 in each sample. Differential expression analysis
was performed with the DESeq2 package (v1.20.0). The following cutoffs values were used for
assigning differentially expressed genes (DEGs): P-adjusted value < 0.05, false discovery rate
(FDR) < 0.05 and |log2FC| ≥ 0.6. We obtained a list of both upregulated and downregulated
DEGs between SYNGAP1+/- and control organoids. ClusterProfiler software (v.4.2.2) was used
to perform functional annotations of the DEGs, according to Gene Ontology (GO) categories
(biological process, molecular function and cellular components). Using these gene lists, we
searched the Panther GO-Slim Biological Processes ontology database using a statistical
overrepresentation test (FDR, P < 0.05).
103

Single Cell Dissociation
7-day-old organoids were rinsed with 1X PBS (Corning, #21-040-CV) and incubated at 37℃ for
15 min with 1x TripLE Express Enzyme (Thermo Fisher Scientific, #12-605-010). Organoids
were dissociated by pipetting up and down with a 1000 µl pipette followed by 200 µl pipette
until a single cell resuspension was obtained. Cells were plated onto 1:100 geltrex coated round
plastic coverslips (Thermo Fisher Scientific, #NC0706236) at a density of 15800 cells/cm
2
.

Single Cell Dissociation for scRNA-Sequencing
Organoids were dissociated as previously described
30,51
. Briefly, 3-4 pooled organoids at 3-4
months of age or three single organoids at 2-month age from both haploinsufficient and corrected
lines were transferred to a 60 mm dish containing a papain and DNase solution from the Papain
Dissociation Kit (Worthington, #LK003150). Organoids were minced into small bits with razors
and incubated for 30 min at 37
o
C on an orbital shaker, then mixed with a 1ml tip several times
and returned for another 5-10 min at 37
o
C. Next, the pieces were triturated 5-10 times with a 10
ml pipet and transferred to a 15 ml conical tube containing 8 ml final Inhibitor solution and
DNase. The tube was inverted a few times and left upright for a few minutes for larger debris (if
any) to settle, then the single cell suspension was transferred to a new conical tube, and
centrifuge for 7 min at 300 g. The cell pellet was resuspended in 500 ul to 1 ml of 0.04%
BSA/PBS and passed through a 0.4 μm filter basket and counted. The solution was then adjusted
to a target concentration of 1000 cells/µl.

Sequencing Analysis, Quality Control (QC), and Clustering
10X Genomic scRNA sequencing was performed by the USC Molecular Genomics Core
Facility. Samples were processed on the 10x Single Cell Gene Expression 3’ v3.1 kit. Raw
sequencing reads were aligned with the human reference genome (GRCh38-2020-A) via the
CellRanger (v6.0.2) pipeline to generate a cell-by-gene count matrix. Next, we used Seurat
(v4.0.1 using R v4.0.) to perform initial QC with standard cutoffs of min.cells = 3, min.features =
200, mitochondrial percentage (<15%), and removal of low complexity cells (nCount < 1250).
For the 2-month age organoids, we recovered, after quality control, a total of 25832 patient and
24740 corrected cells (total: 50572), while for the 4-month, pooled organoids, 3123 patient and
104

7540 corrected cells (total: 10663) were recovered. The regression of the cycling cell genes,
normalization, variable features, and scaling were done using the SCTransform function.
Principal component analysis (PCA) was performed. No batch correction was required for the
merging of the six individual organoids from patient and correct lines. However, comparison of
our organoids with other human fetal and organoids data at 2-month and 4-month (Uzquiano,
Kedaigle et al. 2022)

required merging using the Seurat pipeline based on Canonical Correlation
Analysis (CCA) integration. Next, using the FindNeighbors and FindClusters functions
(resolution = 0.2, 0.8 and 1.2), clusters of cell types were generated. Clusters were classified
according to known markers, previously identified molecular profiles from organoids (Quadrato,
Nguyen et al. 2017, Velasco, Kedaigle et al. 2019), a human fetal data set (Nowakowski,
Bhaduri et al. 2017) and coclustering (CCA) with other 2-month and 4-month old organoids
(Uzquiano, Kedaigle et al. 2022). To calculate the DEGs between control and mutant organoids
for each cluster, we used the FindMarker function with the test.use attribute set to the default
Wilcoxon rank sum test. Using the ToppFun application on the Toppgene site
(toppgene.cchmc.org), we entered the significant DEGs from each cell type along with their
respective background genes to detect and generate GO-terms with functional enrichment. Next,
we selected representative genes from relevant and significant GO terms and visualized them as
violin plots with an equal sample size between conditions.

RFP Labeling
Organoids were transduced with EF1A-RFP lentivirus (Cellomics Technology, # PLV-10072-
50). 1 µl of stock virus (1x10^8 TU/ml) was diluted into 500 µl Cortical Differentiation Medium
IV (CDMIV, without Matrigel) in a 24-well ultra-low attachment plate (Corning, # 3473)
containing a single organoid. After 24 hours of incubation, full media change was performed. 48
hours later, organoids were transferred to a 6-well ultra-low attachment plate (Corning, #3471). 1
week after transduction, organoids were randomly selected for imaging analysis and individually
transferred to a u-Slide 8-well Glass-bottom plate (Ibidi, #80827).

Calcium Imaging
Organoids were transduced with pAAV-CAG-SomaGCaMP6f2 (Addgene, #158757) as
described in
2
. Four-month-old cortical organoids were randomly selected and transferred to a
105

recording chamber kept at 37 °C using a heating platform and a controller (TC-324C, Warner
Instruments) in 5% methyl-cellulose in BrainPhys Imaging Optimized Medium (STEMCELL
Technologies, #05796). Imaging was performed using a SP-8X microscope with a multiphoton
laser. Time-lapse images were acquired at 1 frame for 860 ms, using a 25x 0.95 NA water
objective (2.5 mm WD) and resulting in a view of 200 x 200 µm
2
. Basal activity was recorded for
10 mins in each of the 3 randomly selected areas of the imaged organoid. Pharmacological
treatment was performed with a bath application of Tetrodotoxin, TTX (Tocris, #1078/1) at a
final concentration of 2 µM, and glutamate (Hello Bio, #HB0383) at 100 µM.

Singular Neural Rosette Tissues Analysis
The presence of 0 polarization foci were ‘0 Rosette’; 1 rosette foci were ‘1 Rosette’; ≥1 rosette
with ≥1 additional polarization foci were ‘+1 Rosette’.
The presence of 0 or more than 1 rosette was assessed and classified as 0 rosettes.

Singular Neural Rosette Live Imaging Analysis
Singular rosettes have been imaged with a 20x objective of Leica Thunder Microscope for 14
hours under brightfield light. Co2 and temperature were maintained at 5% and 37C throughout
the recording using a recording chamber.

Morphological Dendrite Analysis
RFP positive organoids were imaged using a 20x objective with the Leica Thunder Microscope.
Maximum projection of each organoid was applied, and the number of dendrites per cell was
calculated using the Sholl Analysis plugin in Image-J software.

Ventricular Zone Analysis of 2-month-old Organoids
Two-month-old organoids were sectioned and immunostained for SOX2 and DAPI. Only
cryosections near the middle of each organoid were used for analysis. The ventricular zone (VZ)
was defined by exclusive SOX2 immunoreactivity and neural tube-like morphology. Image-J
software was used to analyze the thickness, area, and total number of VZs. The line tool was
used to measure the thickness of each VZ (µm); an average of 3 measurements per VZ were
considered. The freehand tool was used to trace the entire VZ and measure the total area (µm
2
).
106

For each organoid, 3-6 regions of interest (ROI) were defined, and the number of VZs in each
Region of Interest (ROI) were counted. For all VZ analyses, 4 independent differentiations and 3
organoids from each differentiation were measured.

The organized versus disorganized analysis of the VZ was based on MAP2 staining. The
ventricles with clusters of MAP2 positive cells in the germinal zone were defined as
disorganized; the ventricles showing clear boundaries between the cortical and germinal zones
were defined as organized. For each line, 3 organoids from 3 independent differentiations were
quantified.

The cleavage angle was defined as the angle between the ventricular apical surface and the
cleavage plane of dividing cells. Pericentrin and pVimentin were used to stain the centrosome
and the dividing RG, respectively, to clearly visualize the cleavage plane. The angle was
measured manually with the angle tool in Image-J.

Binning analysis was performed on relatively isolated ventricles to ensure the binning area has
no other interfering ventricles. Seven 25x50 µm rectangular bins were stacked vertically starting
from the edge of the ventricle and extending to the nearest edge of the organoid. This provided a
uniform grid or binning area that was then used as a visual for the layering of specific cell
markers including: CTIP2, SATB2, and TBR2. Positive cells for each stain in each of the bins
were manually counted and normalized to the total number of DAPI positive cells per bin.

NeuN, TBR2 and SOX2 Density Analysis of 2-month-old Organoids
2-month-old organoids stained by anti-NeuN, TBR2, and SOX2 were imaged and used for
quantification. Images were opened in ImageJ software and the background noise was reduced.
To count all the cells, DAPI-positive cells were initially counted. The lowest and maximum
Threshold values were set at 30 and 250, respectively. The proportion of NeuN, TBR2 or
SOX2-positive cells was calculated by normalization to the number of DAPI-positive cells.

NeuN, TBR2 and SOX2 Thickness and Density Analysis of E18.5 Mouse Tissue
107

For each genotype (WT, HET, KO), the thickness of labeled cells within the lateral cortex was
quantified in ImageJ software from 4-5 20μm sections sampled at ∼100μm intervals along the
rostro caudal axis within the presumptive somatosensory region of the cortex.
Density was calculated by the number of NeuN, TBR2, or SOX2 positive cells in 100 um
2
.

SOX2 Area and Density Analysis of E18.5 Mouse Tissue
For each genotype (WT, HET, KO), the SOX2 positive area around the VZ was selected by free-
hang image tool in ImageJ software and quantified from 4-5 20μm sections sampled at ∼100μm
intervals along the rostro caudal axis within the presumptive somatosensory region of the cortex.

BrdU Pulse-Chase Data Analysis
Binning analysis was performed on relatively isolated ventricles to ensure the binning area has
no other interfering ventricles. Seven 25x50 µm rectangular bins were stacked vertically starting
from the edge of the ventricle and extending to the nearest edge of the organoid. This provided a
uniform grid or binning area that was then used as a visual for the layering of specific cell
markers including: SOX2, NeuN, and BrdU. Positive cells for each stain in each of the bins were
manually counted and normalized to the total number of DAPI positive cells.

Organoid size:
Every three days, bright-field microscopy was utilized to capture images of all organoids from
day 3 to 60. ImageJ software was then used to measure the area and the perimeter of each single
organoid. The Prism software was then used to plot the size average of the organoids of each
differentiation.

Organoid yields:
To check the organoids’ survivability, bright-field microscopy was used to image the organoids
during the culture period. All organoids were then counted. Measurement of survival in
percentile was made considering the number of starting organoids.

Calcium Imaging Data Analysis
108

Raw tiff calcium imaging files were analyzed using the CNMF and CalmAN package as
previously described (CaImAn an open-source tool for scalable calcium imaging data analysis
(Giovannucci, Friedrich et al. 2019), to identify fluorescent transients and spike estimation in
MATLAB (MathWorks). Calcium traces were plotted as relative scaled height in function of
time.

Statistical Analysis
Data is shown as mean ± SD/SEM. Statistical analysis was performed using the Graph Pad Prism
6.0. Shapiro-Wilk test was performed to determine the normality of the data (alpha=0.05).
Comparisons of means in 2 or more groups were made using an unpaired Student’s t-test,
analysis of variance (ANOVA) or Chi-square test. Significant main effects were analyzed further
by post hoc comparisons of means using Bonferroni’s multiple comparisons test.

Ethical approval
Work on the patient-derived line patient p.Q503X is approved by the USC IRB: HS-18-00745

Abstract (if available)

Abstract Autism spectrum disorder (ASD) is a genetically heterogeneous disorder linked with rare, inherited and de novo mutations occurring in two main functional gene categories: gene expression regulation and synaptic function. Accumulating evidence points to dysregulation in cortical neurogenesis as a convergent mechanism in ASD pathophysiology. While asynchronous development has been identified as a shared feature among ASD-risk genes in the category of gene expression regulation, it remains unknown whether this phenotype is also associated with ASD-risk genes in the synaptic function category. The recent advent of human derived brain organoids has allowed for the longitudinal modeling of neurodevelopmental diseases while preserving the patient’s unique genetic architecture. In this thesis, I present our efforts to show the expression and function of the synaptic Ras GTP-ase activating protein 1 (SYNGAP1), one of the top ASD risk genes, in human cortical progenitors (hCPs) using a human brain organoid model system. Using this model, we were able to demonstrate key neurodevelopmental phenotypes associated with SYNGAP1 haploinsufficiency. Overall, the discovery of the expression and function of SYNGAP1 in cortical progenitor cells reframes our understanding of the pathophysiology of SYNGAP1-related disorders and, more broadly, underscores the importance of dissecting the role of synaptic genes associated with neurodevelopmental disorders in distinct cell types across developmental stages.

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Asset Metadata

Creator Del Dosso, Ashley N. (author)

Core Title The autism-associated gene SYNGAP1 regulates human cortical neurogenesis

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Development, Stem Cells and Regenerative Medicine

Degree Conferral Date 2023-12

Publication Date 09/01/2023

Defense Date 08/09/2023

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag autism spectrum disorder,brain development,disease modeling,neurogenesis,OAI-PMH Harvest,organoids,stem cells,SynGAP1

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Ichida, Justin (committee chair), Chen, Jianfu (committee member), Coba, Marcelo (committee member), Quadrato, Giorgia (committee member)

Creator Email deldosso@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113302893

Unique identifier UC113302893

Identifier etd-DelDossoAs-12296.pdf (filename)

Legacy Identifier etd-DelDossoAs-12296

Document Type Dissertation

Format theses (aat)

Rights Del Dosso, Ashley N.

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Source 20230901-usctheses-batch-1089 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

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