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Elucidating neurodevelopmental consequences of syngap1 mutations and inactivated functional regions in human iPSC-derived neurons

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Elucidating neurodevelopmental consequences of syngap1 mutations and inactivated functional regions in human iPSC-derived neurons

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Content Copyright 2024 Ilse Flores
ELUCIDATING NEURODEVELOPMENTAL CONSEQUENCES OF SYNGAP1
MUTATIONS AND INACTIVATED FUNCTIONAL REGIONS IN HUMAN IPSC-DERIVED
NEURONS
By
Ilse Flores
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
(NEUROSCIENCE)
May 2024

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Dedication
To my family, muchísimas gracias por todo lo que me han dado. Gracias por siempre creer en mi
y por todo su apoyo todos estos años. Todo lo que soy es gracias a ustedes. Los quiero mucho.
To my friends, thank you for all your support and encouragement during this PhD. Thanks for all
the fun distractions and all your love.
To my amazing partner, Shai, te amo. Thank you for being my rock and for supplying me with
daily laughs.
And last but not least, to the love of my life, Poopy. The cutest little black void that has brought
me so much joy. And I guess Spooky, too.

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Acknowledgements
I could not have done this without my wonderful mentors Marcelo Coba, PhD and Veronica
Clementel. They provided the lab environment I needed to truly grow and thrive as a scientist.
Their kindness and encouragement allowed me to fall back in love with research, and I am
eternally grateful to them both for giving that back to me.
I am also grateful to my dissertation committee members: Giorgia Quadrato, PhD, Marcelo
Coba, PhD and Judith Hirsch, PhD, who provided great feedback on my proposed projects. A
special thanks to Judith Hirsch for her guidance, kindness, and support throughout my entire
PhD.
I would also like to thank key members of the lab that have helped me progress through my
projects: Brent Wilkinson, PhD, Jianzhi Jiang, PhD, Amir Arya, and Skylar Bailey.
I would also like to acknowledge researchers whose mentorship inspired me to pursue a PhD,
including: Thereasa Cronan, PhD, Robert K. Heaton, PhD, Maria J. Marquine, PhD, Changiz
Geula PhD, Lokesh Kukreja, PhD, Jerel Adam Fields, PhD, Cristian L. Achim, MD, PhD, and
Jared Young, PhD. I would like to give a special thanks to the NIH-funded Advancing Diversity
in Aging Research Program (ADAR) that allowed me to obtain extensive undergraduate research
experience from such great mentors. Without ADAR, I cannot imagine having been able to
pursue a PhD.

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Table of Contents
Dedication....................................................................................................................................... ii
Acknowledgements........................................................................................................................iii
List of Tables .................................................................................................................................. v
List of Figures................................................................................................................................ vi
Abstract......................................................................................................................................... vii
CHAPTER 1: GENERAL INTRODUCTION ............................................................................... 1
CHAPTER 2: PATHOGENIC VARIANTS OF SYNGAP1: A COMPARATIVE STUDY OF
NEURONAL MATURATION AND NETWORK ACTIVITY PHENOTYPES OF HUMAN
IPSC-DERIVED NEURONS ....................................................................................................... 10
Introduction .............................................................................................................................................10
Results.....................................................................................................................................................12
Discussion ...............................................................................................................................................32
Methods...................................................................................................................................................35
CHAPTER 3: SYNGAP1 FUNCTIONAL REGIONS: IMPLICATIONS IN NEURONAL
MATURATION............................................................................................................................ 45
Introduction .............................................................................................................................................45
Results.....................................................................................................................................................48
Discussion ...............................................................................................................................................57
Methods...................................................................................................................................................63
CHAPTER 4: CONCLUSION ..................................................................................................... 67
References..................................................................................................................................... 74

v
List of Tables
Table 1.1 Functional Regions of SYNGAP1………………………………………. 1
Table 2.1 Primary and Secondary Antibodies……………………………………… 48

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List of Figures
Figure 1.1 SYNGAP1 Structure and Isoforms……………………………………… 9
Figure 2.1 Generation of Cell Lines………………………………………………… 18
Figure 2.2 Generation of Differentiated Cells………………………………………. 19
Figure 2.3 CRISPR/Cas9-Mediated SYNGAP1 Mutation Correction Results in
Neurons Similar to Healthy Control…………………………………….. 21
Figure 2.4 Patient-Derived P.Q503X SYNGAP1 Mutation Alters Dendritic Spine
Morphology of Excitatory Neurons……………………………………... 23
Figure 2.5 Patient-Derived P.Q503X SYNGAP1 Mutation Alters Synaptic Activity 24
Figure 2.6 Genetic Background Has No Influence on Patient-Derived P.Q503X
SYNGAP1 Mutation Effect on Dendritic Spine Morphology of
Excitatory Neurons………………………………………………………. 25
Figure 2.7 Genetic Background Has No Influence on Patient-Derived p.Q503X
SYNGAP1 Mutation Effect on Neuronal Activity Excitatory Neurons…. 26
Figure 2.8 Patient-Derived p.Q503X SYNGAP1 Mutation Alters Dendritic Spine
Morphology of Inhibitory Neurons………………………………………. 27
Figure 2.9 Genetic Background Has No Influence on Patient-Derived p.Q503X
SYNGAP1 Mutation Effect on Dendritic Spine Morphology of
Inhibitory Neurons……………………………………………………….. 28
Figure 2.10 Patient-Derived c.3583-9G>A SYNGAP1 Mutation Alters Dendritic
Spine Morphology………………………………………………………... 30
Figure 2.11 Patient-Derived c.3583-9G>A SYNGAP1 Mutation Alters Synaptic
Activity…………………………………………………………………… 31
Figure 2.12 Patient-Derived c.3583-9G>A SYNGAP1 Mutation Alters Dendritic
Spine Morphology of Inhibitory Neurons. ………………………………. 32
Figure 2.13 Patient Genetic Background Does Not Influence SYNGAP1 Mutation
Effects on Dendritic Spine Morphology of Excitatory Neurons…………. 33
Figure 2.14 Patient Genetic Background Does Not Influence SYNGAP1 Mutation
Effects on Neuronal Activity of Excitatory Neurons…………………….. 34
Figure 2.15 Patient Genetic Background Does Not Influence SYNGAP1 Mutation
Effects on Dendritic Spine Morphology of Inhibitory Neurons…………. 36
Figure 2.16 SYNGAP1 Patient-Derived Mutations Differentially Decrease Total
Protein Levels……………………………………………………………. 37
Figure 3.1 Generation of Cell Lines…………………………………………………. 55
Figure 3.2 Impact Of RGD And ΔPDZ Mutation on Dendritic Spine Morphology of
Excitatory Neurons………………………………………………………. 57
Figure 3.3 Impact Of RGD And ΔPDZ Mutation on Dendritic Spine Morphology of
Inhibitory Neurons. ……………………………………………………… 59
Figure 3.4 RGD SYNGAP1 Inactivation Alters Neuronal Firing of Excitatory
Neurons…………………………………………………………………… 60
Figure 3.5 ΔPDZ SYNGAP1 Inactivation Alters Neuronal Firing and Bursting
Activity…………………………………………………………………… 62

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Abstract
SYNGAP1 is a critical gene implicated in the development of intellectual disability and plays a
pivotal role in synaptic function and activity. In Chapter 1, we review the current state of the
literature regarding SYNGAP1 mutations and their effects on neuronal subtypes. In Chapters 2-
3, data is presented from two studies involving the use of human iPSCs to study the impact of
SYNGAP1 mutations and SYNGAP1 critical motifs on the function of glutamatergic and
GABAergic neurons. In Chapter 4, we discuss the implications and future directions of the data
collected in this dissertation. Altogether, the work in this dissertation fills a significant gap in the
literature regarding how SYNGAP1 mutations lead to the observed experimental phenotypes in
patient-derived cells. Overall, the data suggest that SYNGAP1 mutations can differentially alter
the maturation rate and SYNGAP1 total protein expression of both glutamatergic and
GABAergic neurons, consequently impacting their network activity. Additionally, the data show
that while the RasGAP domain of the SYNGAP1 protein is not involved in spinogenesis, it is
needed for regulation of spine maturation and dendritic growth, subsequently enhancing neuronal
activity. Lastly, we show the PDZ-binding motif of SYNGAP1 is necessary for the regulation of
dendritic growth, spinogenesis and spine maturation, consequently enhancing neuronal activity.
This dissertation provides valuable insights into how SYNGAP1 patient mutations affect
neuronal development and activity, while also highlighting the differential roles of the RasGAP
domain and PDZ-binding motif in phenotypic differences.

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CHAPTER 1: GENERAL INTRODUCTION
Intellectual disability (ID) is a common and debilitating neurodevelopmental disorder
(NDD) with a prevalence of 1% to 2% of the general population (Li et al., 2023). According to
the DSM-V, ID is characterized by the presence of significant limitations in cognitive and
adaptive behaviors with onset during the developmental period (Diagnostic and statistical
manual of mental disorders: DSM-4TM, 5th ed, 2013). The underlying mechanisms of
monogenic ID are being revealed as the associated genes and their mutations are being
discovered and researched. One mechanism frequently underlying monogenic ID is that of
altered synaptic function; subsequently, a variety of genes encoding for proteins that regulate
synaptic function and structure have been identified (Zoghbi & Bear, 2012). Here, we highlight
SYNGAP1, located on chromosome 6p21.23, which encodes for the protein Synaptic GTPase
Activating Protein 1 and accounts for 2-8% of sporadic ID cases (Berryer et al., 2013; Hamdan et
al., 2011).
Terminus Functional Region Function
N-Terminus Pleckstrin homology (PH)
domain
Signal-dependent membrane
localization of proteins,
protein-protein interaction
Core domains C2 domain Ca2+ binding
GAP Activates GTPases for
Ras/Rap proteins
C-terminus QTRV (PDZ ligand) PDZ (PSD-95, DLG, ZO-1)
binding motif
Table 1. Functional Regions of SYNGAP1 (adapted from Agarwal et al., 2019). Abbreviations: Ca2+, calcium ion; GAP,
GTPase activating protein; T/SXV, C-terminal binding motif.

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SYNGAP1: Expression, Functional Domains and Isoforms
SYNGAP1 is a 140kD protein that contains several functional modules that are thought
to be responsible for its various functions (Table 1)(Chen et al., 1998; Kim et al., 1998; Walkup
et al., 2015). SYNGAP1 is primarily localized to dendritic spines in glutamatergic synapses and
as the third most abundant protein in the post-synaptic density (PSD), it is well positioned to
regulate activity-dependent synaptic modifications. The PSD is a complex of approximately
1000 highly conserved proteins (Bayés et al., 2012; Bayés et al., 2011; Bayés et al., 2017;
Collins et al., 2006; Collins et al., 2005; Husi et al., 2000), including scaffolding proteins (PSD95), Ca2+/calmodulin dependent protein kinase (CaMKII), and synaptic GTPases like proteins of
the Ras family and their regulators, that link glutamate receptors to downstream signaling
pathways Additionally, SYNGAP1 regulates NMDA receptor (NMDAR) mediated AMPA
receptor (AMPAR) trafficking, as such Syngap1 heterozygous mice exhibit increased numbers of
AMPARs as well as an increased number of mature spines earlier in development(Aceti et al.,
2015; Clement et al., 2012). Syngap1 plays an important role in the regulation of spine formation
and maturation in rodent and human neurons, such that reduced expression of SYNGAP1 causes
enhanced excitatory neuronal activity during early development (Clement et al., 2012;
Rumbaugh et al., 2006; Vazquez et al., 2004). This perturbation in neuronal activity greatly
impacts dendritic morphogenesis in a pleiotropic manner where some neurons display increased
dendritic arborization, while others undergo stunted dendritic morphogenesis(Aceti et al., 2015;
Llamosas et al., 2020; Michaelson et al., 2018).

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One potential mechanism through which SYNGAP1 performs such diverse cellular
functions is through alternative splicing (Araki et al., 2020; Gou et al., 2020). There are four
distinct C-terminal (α1, α2, β, and γ; Figure 1) isoforms that are expressed in rodents and humans
and there are indications that these isoforms are differentially expressed across mammalian brain
development, however, these results are derived from antibody-based studies that may not
accurately reflect the localization of the isoforms (Araki et al., 2020; Gou et al., 2020). The most
studied and characterized isoform SYNGAP-α1 contains the PDZ-binding motif (PBM) that
enables it to interact with major scaffolding proteins (such as PSD-95) that bind to NMDA
receptors within glutamatergic neurons. Conversely, the remaining C-terminal isoforms lack the
PBM(Li et al., 2001). It has been suggested that distinct isoforms are differentially expressed in a
brain region- and cell type- specific manner, as indicated by mRNA studies (McMahon et al.,
2012; Moon et al., 2008). A few studies found that Syngap1 is primarily expressed in forebrain
structures, with C-terminus isoforms localizing to hippocampus and cortex, and mRNA levels
peaking at postnatal day 14 in rodents and steadily decrease to levels seen in adulthood by 2
months of age (Clement et al., 2012; McMahon et al., 2012).
Figure 1. SYNGAP1 Structure and Isoforms (adapted from Agarwal et al, 2019; created on Biorender). SYNGAP1
has 3 core domains (C2, GAP,). There are 3 N-terminal isoforms (A, B, C) and 4 C-terminal isoforms (α1, α2, β, and γ).
Isoforms A and B have a PH domain, but it is absent in the C isoform. In the C-terminal isoforms, only α1 has a PDZ-binding
motif.

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SYNGAP1 and GABAergic Neurons
While glutamatergic neurons are particularly relevant to ID, with several of associated
mutated genes being expressed in pre- and/or post-synaptic components of such synapses,
previous studies have found that GABAergic inhibition system dysfunction is associated with
neurodevelopmental disorders (Berryer et al., 2016; Michetti et al., 2022; Moretto et al., 2018).
The neurotransmitter y-aminobutyric acid (GABA) is considered the more prominent inhibitory
neurotransmitter of the mammalian central nervous system, which exerts depolarizing actions
during neurodevelopment in cooperation with NMDARs to drive spontaneous synchronous
activity that is crucial for the development of neural networks (Cserép et al., 2012). Conversely,
mature GABAergic neurons are inhibitory and exert hyperpolarizing actions on postsynaptic
neurons providing a brake to neural firing that is important for preventing those neurons from
reaching threshold (Ben-Ari et al., 2007; Cserép et al., 2012). Thus, GABAergic neurons are
particularly important in excitatory regulation and maintaining E/I (excitatory/inhibitory) balance
throughout neurodevelopment.
The GABAergic System
The GABAergic system comprises GABA, GABA transporters, GABAergic receptors,
and GABAergic neurons. GABA and GABAergic markers are expressed long before synapses
are formed, with GABA acting as a trophic factor in early development where it modulates
several developmental processes such as neuronal migration, synapse formation, neuronal
growth and network stabilization (Barker et al., 1998; Kriegstein, 2005; Owens & Kriegstein,
2002). Different subtypes of GABAergic interneurons express various proteins including
calcium-binding protein parvalbumin (PV), neuropeptide somatostatin (SST), as well as the
ionotropic serotonin receptor 5HT3aR (Bi et al., 2020; Fee et al., 2017)). Ultrastructural studies

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have shown that GABAergic neurons contain synaptic vesicles in the presynaptic active zones
that release neurotransmitters into the synaptic cleft (Peters & Palay, 1996). There are various
proteins expressed at the presynaptic terminals that are involved in the loading and release of
these neurotransmitter-filled vesicles, including Bassoon and Synapsin I (Chiappalone et al.,
2009). Bassoon is a large scaffolding protein localized at the active zone of neurotransmitter
release, playing a critical role in the organization and function of the presynaptic release
structures (Montenegro-Venegas et al., 2022) . Similarly, Synapsins are highly enriched in
presynaptic terminals and are involved in the predocking and postdocking stages of
neurotransmitter release (Forte et al., 2020). Studies are continuing to identify scaffolding
proteins (e.g. Gephyrin), cell adhesion molecules (e.g. Neurexins-Neuroligins), and signal
transduction proteins (e.g. Neuregulin 1) with advancements in biochemical assays, indicating
that the organization of synaptic proteins in GABAergic neurons follows a similar pattern to that
of glutamatergic neurons, albeit with different molecular players. (Chubykin et al., 2007;
Fritschy et al., 2008; Kim & Sheng, 2004; Mei & Xiong, 2008).
GABAergic Dysfunction in Neurodevelopmental Disorders
A considerable portion of NDD risk genes encode proteins that comprise the GABAergic
system, which ultimately result in perturbations in the generation, migration, connectivity and
function of GABAergic neurons (Satterstrom et al., 2020; Tang et al., 2021). Of the various
identified NDD risk genes, those associated with ID encode proteins such as GABAARs; the
presynaptic cell-adhesion molecules Neurexin-1, -2, and –3; the synaptic scaffold proteins
gephyrin and collybistin; and the voltage-gated GABA transporter 1(Chen et al., 2014; Gauthier
et al., 2011; Johannesen et al., 2018; Vaags et al., 2012). These pathogenic variants disrupt
excitatory/inhibitory (E/I) balance such that an elevated E/I ratio has been observed in rodent

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NDD models as a compensatory mechanism in an attempt to maintain “homeostatic” neural
firing(Antoine et al., 2019). However, despite this attempt, abnormalities in GABAergic neurons
are frequently observed in GABAergic neuron-specific NDD models.
One Syngap1 study sought to investigate whether the protein plays a role in the
innervation of Parvalbumin positive ( PV+) basket cells through the induction of single-cell
Syngap1 deletion in cortical organotypic cultures (Berryer et al., 2016). They found that Syngap1
strongly modulated GABAergic synaptic connectivity, decreasing inhibition on excitatory
synapses. Heterozygous SYNGAP1 deletions have been shown to increase apoptosis of
calbindin-positive GABAergic neurons (Muhia et al., 2010). Clearly, SYNGAP1 is involved in
the function of glutamatergic and GABAergic neurons, likely leading to the disruption of E/I
balance. This balance is intricately involved in the onset and efficacy of critical periods of
synaptic plasticity; thus, neural circuit organization and function becomes impaired and
neurodevelopmental disorders arise (Aceti et al., 2015; Hensch, 2005).
Clinical Features
There are more than 1000 confirmed SYNGAP1 cases worldwide, many of the de novo
mutations are predicted to cause protein truncations that might result in haploinsufficiency of
SYNGAP1 (Graglia, 2020). Patients with predicted SYNGAP1 haploinsufficiency experience
moderate to severe forms of ID, while most are also co-diagnosed with epilepsy (Hamdan et al.,
2011). As well, SYNGAP1 patients have severely impacted expressive and receptive speech
development, with one third of patients remaining non-verbal, while language in verbal patients
ranges from single words to brief sentences (Mignot et al., 2016; Vlaskamp et al., 2019).
Additionally, a large portion of SYNGAP1 patients exhibit severe behavioral problems including

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hyperexcitability, aggression, tantrums, self-injury, and sleep difficulties (Berryer et al., 2013;
Mignot et al., 2016; Vlaskamp et al., 2019).
Most of the reported pathogenic SYNGAP1 variants result from loss-of-function
mutations such as nonsense and splice variants, frameshift insertions/deletions, and exon
deletions; additionally, pathogenic missense variants have also been reported (Holder et al.,
1993; Mignot et al., 2016). Recent evidence suggests that milder clinical phenotypes often
coincide with mutations localized to exons 1-4, while more severe phenotypes occur more often
in mutations involving exons 8-15 (Agarwal et al., 2019; Vlaskamp et al., 2019). Altogether,
these findings seem to indicate that the complexity of the gene and the many resulting isoforms
could help explain the variation in phenotypic severity.
Outline of the Dissertation
Research over the last two decades has highlighted the critical importance of SYNGAP1
for the structural and functional maturation of neurons. It has been proposed that SYNGAP1
physically interacts as a molecular “off switch” with small GTPases such as Ras and Rap that are
upstream of numerous NMDA receptor-mediated cellular functions including actin cytoskeletal
arrangement and AMPA receptor insertion and removal. However, a recent study using mouse
models of SYNGAP1 with an inactivated GAP domain reports that there is no effect on the
mature synapses nor in the cognition of the mice (Araki et al., 2024). Conversely, we have
previously shown that a RasGAP dead iPSC line has a robust effect on the cytoskeletal
architecture of radial glial cells, indicating a role of SYNGAP1 catalytic activity in
neurodevelopment (Birtele et al., 2023). This discrepancy in results clearly shows the need to
delve into the complex role that SYNGAP1 and its functional regions play in neurodevelopment
and throughout the lifespan. Moreover, there exists several lines of evidence showing that the

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PDZ-binding motif of SYNGAP1 is heavily implicated in a vast array of functions at the synapse
such as the regulation of spine development, PSD composition, LTP, and synaptic strength
(Araki et al., 2020; Kilinc et al., 2022; McMahon et al., 2012; Walkup et al., 2016), The
importance of SYNGAP1 at the synapse is also exemplified by deleterious mutations linked to
neurodevelopmental disorders such as intellectual disability (Agarwal et al., 2019; Berryer et al.,
2013; Clement et al., 2012). While SYNGAP1 function has mainly been studied in excitatory
neurons, GABAergic cells have also been implicated. As well, disruption of the
excitatory/inhibitory balance is emerging as a key player in such brain disorders in that
glutamatergic synaptic strength is dramatically increased, disrupting cognition and behavior.
However, there remains a critical challenge in understanding the molecular mechanisms
underlying the differential roles of SYNGAP1 across various cell types, particularly in the
context of its mutations and their impact on cellular maturity and function. This challenge is
paramount, as understanding these intricate mechanisms is essential for developing targeted
therapies for neurodevelopmental disorders associated with SYNGAP1 mutations.
To begin addressing this challenge, we investigated the relationship between cellular
phenotype and patient-derived SYNGAP1 mutations. Our repertoire of human induced
pluripotent stem cells (iPSCs) come from SYNGAP1 patients that exhibit various mutation types
as well as different clinical phenotypes. While iPSC models alone are not enough to directly
correlate the patients’ clinical profiles to observed cellular differences, they have allowed us to
begin parsing out possible explanations for why SYNGAP1 patients can present with such
variation in their severity. We certainly appreciate the fact that dissecting exactly how
SYNGAP1 exerts its effects and leads to variations in clinical severity among patients is further
complicated by several factors. These include the genetic background of each patient, which may

9
influence how mutations manifest; absolute protein expression levels, which can vary widely and
affect cellular function; mosaicisms, and the presence of different functional domains and
isoforms of SYNGAP1, each potentially contributing to distinct aspects of its role in
neurodevelopment and synaptic function. Understanding these variables is crucial for drawing
accurate correlations between SYNGAP1 mutations and their clinical impact, highlighting the
complexity of translating genetic alterations into predictable phenotypic outcomes. In Chapter
2, I will discuss the cellular phenotypes observed in our SYNGAP1 patient iPSC-derived
glutamatergic and GABAergic models and their relationship to patient genetic
background. Given SYNGAP1’s critical role at the synapse, our hypothesis is that heterozygous
SYNGAP1 mutations will impact neuronal maturation and network activity, and we will assess
the roles that total protein levels and genetic background have in these resulting phenotypes. In
Chapter 3, I will discuss the functional region correlates of the RasGAP domain and PDZbinding motif underlying the phenotypes in glutamatergic and GABAergic neurons using
SYNGAP1 patient iPSC-derived models. Our hypothesis is that the PDZ-binding motif will
play a significant role in the observed cellular phenotypes reported in Chapter 2, given its well
established functional role in rodent excitatory synapses. As well, we hypothesize that the
RasGAP domain of SYNGAP1 will play an important role in cytoskeletal architecture and
neuronal maturation, given previous findings in human organoids indicating GAP activity’s role
in the development of radial glial cells.

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CHAPTER 2: PATHOGENIC VARIANTS OF SYNGAP1: A COMPARATIVE STUDY
OF NEURONAL MATURATION AND NETWORK ACTIVITY PHENOTYPES OF
HUMAN IPSC-DERIVED NEURONS
Introduction
Synaptic GTPase Activating Protein 1 (SYNGAP1) is a GTPase-activating protein
(RasGAP) that is predominantly localized to dendritic spines within glutamatergic synapses and
helps regulate synaptic plasticity and dendritic spine development (Araki et al., 2015; Clement et
al., 2012). Recent advances in stem cell biology and gene editing have allowed us to start
investigating the role of SYNGAP1 mutations found in patients, and their role in synaptic
dysfunction in human neurons. However, the genotype-phenotype relationship, and the role of
the patient's genetic background in this model is yet to be fully understood. Pathogenic variants
of the SYNGAP1 gene arise from predominately truncating mutations (Vlaskamp et al., 2019).
Clinical features of SYNGAP1 mutations typically involve seizures, developmental delay,
intellectual disability, and severe behavioral problems.
Here, we used human induced pluripotent cells (iPSCs) from SYNGAP1 patients with
different clinical phenotypes and mutations to assess whether these differences translate into
divergent cellular phenotypes. Our lab has a repertoire of numerous SYNGAP1 patients, most of
which have different mutations and clinical profiles. In this study, we utilized iPSCs from four
patient lines that express two mutations. Patient 1 presents with a truncating mutation, p.Q503X,
in the RasGAP domain in Exon 9. Patients 3, 10 and 14 exhibit a single-nucleotide mutation,
c.3583-9G>A, in an intron that creates a cryptic splice acceptor site and a premature stop
codon(Araki et al., 2023a). While others have found that truncating and splice-site mutations
result in similar clinical phenotypes, the c.3583-9G>A patients exhibit phenotypic variability

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compared to the p.Q503X patient (Mignot et al., 2016; Vlaskamp et al., 2019). However, in vitro
and mouse models, suggests that both mutations can produce a truncation in the SYNGAP1
protein with a possible nonsense mediating decay that might generate haploinsufficient models
of disease (Berryer et al., 2013).
We show that the presented SYNGAP1 mutations differentially alter the firing patterns
and dendritic spine development of patient-derived neurons when compared to their isogenic
control as well as a healthy control line. To discard the role of genetic background on the
observed cellular phenotypes in glutamatergic and GABAergic neurons, we inserted the
p.Q503X mutation into a healthy control line, WT03231. The results indicate that there was not
an effect of genetic background on the modulation of synaptic maturation, given that we
observed similar phenotypes in this insertion line to that of the Patient 1 cells. To examine the
extent to which patient genetic background was modulating the phenotypic expression of
SYNGAP1 mutations, we introduced the Patient 1 p.Q503X mutation into the corrected
background of Patient 3 and found that genetic background was not influencing the cellular
phenotype. Altogether, these data suggest that different SYNGAP1 mutations identified in
patients can lead to distinct in vitro neuronal phenotypes, underscoring the complexity of the
genotype-phenotype relationship in the context of synaptic dysfunction. The observed
phenotypic divergences are unlikely attributed solely to the genetic background of the
individuals, pointing towards other underlying mechanisms such as variations in total SYNGAP1
protein levels or differential expression of SYNGAP1 isoforms. Indeed, we determined that
while both mutations led to a decrease in total protein levels, the p.Q503X mutation lead to a
more significant decrease in protein expression compared to the c.3583-9G>A mutation. These
findings highlight the need for a deeper understanding of the molecular consequences of specific

12
SYNGAP1 mutations to inform potential therapeutic strategies for addressing the varied clinical
manifestations associated with this gene.
Results
Generation of CRISPR/Cas9-edited Lines
To begin addressing the role of SYNGAP1 mutations in neuronal function, we used the
CRISPR/Cas9 genome engineering system to generate new lines. Firstly, we successfully
corrected the p.Q503X mutation of the Patient 1 line to create an isogenic control (Patient 1C;
Figure 1A-B). Next, we corrected the splicing site mutation, c. 3583-9G>A, of the Patient 3 line
to create an isogenic control (Patient 3C; Fig. 1A). Additionally, two patient lines (Patient 10 and
14) containing the same splicing site mutation as Patient 3 were included to assess the impact of
Figure 1. Generation of Cell Lines. (A) A diagram of SYNGAP1 structure and its domain architecture: PH, C2,
RASGAP and domain of unidentified function (DUF) 3498. The QTRV region describes the 4 amino acids at the Cterminal of the alpha1 SYNGAP1 isoform. Diagram shows each of the mutations studied: the truncations of
haploinsufficient Patient 1 p.Q503X and Patient 3 c.3583-9G>A. (B) Gene targeting scheme illustrating the correction of
Patient 1 p.Q503X mutation in SYNGAP1 in induced pluripotent stem cells using the CRISPR/Cas9 genome engineering
System. The site of double strand break induction is annotated by the red triangles. Restriction digest-based genotyping
and Sanger sequencing were conducted. (C) Characterization of generate iPSCs from Patient 1 and corrected lines which
stained for OCT4/SSEA4 and had normal karyotype. Similar workflow was conducted for all generated lines. Scale bar =
100um.

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genetic background. Finally, to discard differences in phenotype due to genetic background
effects, we generated a p.Q503X truncation mutation in the Patient 3C background (Patient 1 in
Patient 3C; Fig. 1A) and in a healthy control line (Patient 1 in WT3231; Fig. 1A). All lines were
karyotyped, Sanger sequenced and assayed for off-target effects (Fig 1B-C). The iPSC lines
maintained expression of pluripotency markers OCT4 and SSEA4 (Fig. 1 C).
To study the impact of SYNGAP1 mutations on human glutamatergic neurons, we used
forced expression of Neurogenin 2 (Ngn2) and reverse tetracycline-controlled transcriptional
activator (rtTA) to convert iPSCs into induced glutamatergic neurons (GLUT-iNs). The iPSCderived GLUT-iNs were differentiated for 21 days and characterized by immunofluorescence for
neural marker MAP2 (Figure 2A). Similarly, we used forced expression of ASCL1/DLX2 to
differentiate iPSCs into Somatostatin (SST)-expressing induced GABAergic neurons (GABAiNs) over a period of 9 days (Fig. 2B).
Figure 2. Generation of Differentiated Cells. (A) Representative confocal images of iPSC-derived glutamatergic induced
neurons (GLUT- iNs) express the neural marker MAP2. (B) Representative confocal images of iPSC-derived GABAergic
neurons (GABA-iNs) express somatostatin (SST) and the neuronal marker MAP2. Images are max intensity z-projections.
Scale bars = 100 μm.

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CRISPR/Cas9-corrected Lines Result in Neurons that Do Not Differ from Healthy
Controls
We used CRISPR/Cas9 to correct patient mutations and assessed the morphology and
electrophysiology of Patient 1C, Patient 3C and WT03231 lines. For GLUT-iNs, dendritic
morphology was measured at 21 DIV by tracing dendrites of sparsely labeled GFP+ cells (Figure
3A). Dendritic spine analysis of 40-80um segments revealed that Patient 1C, Patient 3C, and
WT03231 GLUT-iNs did not have significantly different spine density and did not differ in their
spine head width/neck width ratio of mature spines (HN-Index), indicating that the spines of all
three lines were of a similar size proportion (Fig.3B,C). Similarly, dendritic morphology of
GABA-iNs was measured at 9 DIV by tracing sparsely labeled GFP+ cells and we found that the
GABA-iNs did not differ significantly in dendritic spine density or HN-Index (Fig. 3I,J). Next,
we measured the electrical recordings of Patient 1C, Patient 3C, and WT03231 GLUT-iNs on
multielectrode arrays (MEAs) at 56 DIV and observed that they did not have substantially
different firing rates or bursting activity (Fig. 3D-G). These data indicate that the CRISPR/Cas9-
corrected GLUT-iNs behaved similarly to healthy control GLUT-iNs and would serve as proper
isogenic controls in subsequent experiments.

15
Figure 3. CRISPR/Cas9-mediated SYNGAP1 mutation correction results in neurons similar to healthy control. (A)
Representative confocal max intensity projection images of cultured GLUT-iNs at 21 DIV after GFP-transfection at 18DIV
from the healthy control (WT03231) and two patient corrected lines. B-C, Quantification of spine density and spine
head/spine neck ratio (HN-Index). (B)The number of spines per 10um of 40-80um dendritic segments did not differ
(p=0.6906) between WT03231 (0.2088(0.3999)), Patient 1C (0.1160(0.5932)), and Patient 3C (0.2376(0.6482)). Median
(IQR) (C) The HN-Index of non-filopodial spines did not differ (p=0.4444) between WT03231 (0.6667(1.069))), Patient 1C
(0.8070(0.8027)), and Patient 3C (0.8214(0.8625)). Median with interquartile range. D-G, Graphs represent mean firing
frequency, bursting rate, mean burst duration, and percent of spikes in bursts from multielectrode array recordings of
WT03231, Patient 1C and Patient 3C cultured neurons at 56 DIV. (D) Mean firing frequency of WT03231 (10.32(13.67)),
Patient 1C(9.931(12.80)), and Patient 3C (11.30(7.522) did not differ significantly, Kruskal-Wallis H test H=3.435,p=0.1795.
(E) Bursts per minute of WT03231 (3.204(5.265)), Patient 1C (2.643(3.238) and Patient 3C (2.657(4.635)) did not differ
significantly, Kruskal-Wallis H test H=5.873, p=0.0531. (F) Mean burst duration of WT03231 (25.89(4.809)) Patient
1C(26.40(6.017)), and Patient 3C (25.14(6.678)) did not differ significantly, Kruskal-Wallis H test H=5.096, p=0.0782. (G)
Percent of spikes in bursts from WT03231 (2.807±0.2420), Patient 1C (2.656±0.3105) and Patient 3C (2.133±0.1989) did not
differ significantly, F(2.0,45.7)=2.740, p=0.752. mean ± sem. For each cell line, 30 replicates were plated from at least three
differentiations. Violin plots show all data points, with median and interquartile range. (H) Representative confocal max
intensity projection images of cultured GABA-iNs at 9 DIV after GFP-transfection at 6 DIV from the healthy control
(WT03231) and two patient corrected lines. Scale bar, 50um. I-K, Quantification of spine density and spine head/spine neck
ratio (HN-Index). (I) The number of spines per 10um of dendritic segments of at least 10um in length did not differ
(p=0.0750) between WT03231 (0.2082(3.275)), Patient 1C (0.5839(3.513)), and Patient 3C (0.7361(2.825)). Median (IQR).
(J) The HN-Index of non-filopodial spines did not differ (p=0.5066) between WT03231 (0.8461(0.994)), Patient 1C
(0.9337(0.805)), and Patient 3C (0.9487(1.021)). Median (IQR). (K) Average dendritic length did not differ (p=0.5128)
between WT03231 (13.21(51.75)), Patient 1C (11.64(46.39)), and Patient 3C(9.482(64.07)). Median (IQR).

16
SYNGAP1 p.Q503X Patient Mutation Alters Maturation of Glutamatergic Neurons
SYNGAP1 haploinsufficiency disrupts the maturation rate of dendrites and synapses;
therefore, we examined the dendritic morphogenesis of GLUT-iNs from the Patient 1 line and its
isogenic control (Patient 1C). We found that the Patient 1 p.Q503X mutation resulted in GLUTiNs that had significantly more spines (0.6896±0.0844, p<0.0001) than those of control neurons
(0.1962± 0.0639; Figure 4B). The HN-Index (spine head width/neck width) serves as a critical
indicator of dendritic spine maturity and functionality. Wider spine heads combined with thinner
spine necks suggest a transition towards more mature mushroom-like spines (Arellano et al.,
2007; Ebrahimi & Okabe, 2014). Mature spines contain larger post-synaptic densities which are
essential for neurotransmitter release and receptor anchoring (Borczyk et al., 2019; Harris et al.,
1992; Noguchi et al., 2005). Thus, the greater the dendritic spine volume the larger PSD area and
stronger the synapse (Holtmaat & Svoboda, 2009; Patterson & Yasuda, 2011). Plotting the HNIndex by spine length provides allowed us to categorize the type of spine morphologies and
effectively visualize a spectrum of spine types from immature thin, filamentous and stubby
spines to mature mushroom-like spines, providing a clear representation of spine maturity and
type distribution within our cultured neurons. The morphological evolution towards wider heads
and thinner necks is indicative of an enhanced capacity for synaptic transmission and plasticity;
therefore, the observed increase in HN-Index in the context of this p.Q503X mutation highlights
a significant shift in spine morphology (1.130(1.935),p=0.0014) compared to controls (0.1962±
0.0639) that could underpin alterations in neuronal activity, emphasizing the profound impact of
SYNGAP1 mutations on functional maturation (Fig. 4C,D). These data indicate that SYNGAP1
p.Q503X haploinsufficiency results in the increase of dendritic spines and a widening of the
spine heads, indicative of a shift towards more mature spines.

17
Figure 4. Patient-Derived p.Q503X SYNGAP1 Mutation Alters Dendritic Spine Morphology of Excitatory Neurons.
(A) Representative confocal max intensity projection images of cultured GLUT-iNs at 21 DIV after GFP-transfection at
18DIV from Patient 1 and Patient 1C. Scale bar, 50um. B-D, Quantification of spine density and HN-Index in Patient 1,
Patient 1C, and insertion lines. (B) The number of spines per 10um of 40-80um dendritic segments was significantly higher
in Patient 1 (0.6896±0.0844,p<0.0001) relevant to Patient 1C (0.1962± 0.0639). (C) The HN-Index of non-filamentous
spines was significantly higher in Patient 1 (1.130(1.935),p=0.0014) relevant to Patient 1C (0.8070(0.8027)).Median
(IQR). (D) Individual non-filopodial spines were plotted according to their length (um) and HN-Index for each line. For
each cell line, 6 replicates were plated from at least three differentiations. mean + s.e.m.

18
To correlate changes in spinogenesis and dendritic spine morphology with neuronal
network activity, we measured the electrical recordings of GLUT-iNs on MEAs. At 56 DIV, we
found that the Patient 1 p.Q503X mutation resulted in GLUT-iNs that had substantially higher
firing rates (13.42(14.29), p=0.0032)than Patient 1C control GLUT-iNs (9.931(12.80); Figure
5A). Then we measured bursting activity and observed that the Patient 1 GLUT-iNs
(7.000(30.47), p<0.0001) were bursting faster than the control line (2.643(3.236); Fig. 5 B), and
the bursts themselves were significantly longer (27.62(47.58), p=0.0296) than that of controls
(26.40(6.017); Fig.5C). Lastly, we found that the mutation significantly increased the percent of
spikes present in bursts (4.119(34.95), p=0.0075) relevant to controls (2.346(2.601); Fig. 5D).
These data suggest that the maturation effects SYNGAP1 p.Q503X haploinsufficiency had on
spine morphology were also correlated with enhanced neuronal activity, with GLUT-iNs
carrying the mutation exhibiting more enhanced firing patterns than control lines.
Figure 5. Patient-Derived p.Q503X
SYNGAP1 Mutation Alters Synaptic
Activity. A-D, Graphs represent mean
firing frequency, bursting rate, mean burst
duration, and percent of spikes in bursts
from multielectrode array recordings of
Patient 1 and Patient 1C cultured GLUTiNs at 56 DIV. (A) Mean firing frequency
of Patient 1 (13.42(14.29), p=0.0032) was
significantly higher relevant to Patient 1C
(9.931(12.80)) (B) Bursting rate of Patient
1 (7.000(30.47), p<0.0001) was
significantly higher relevant to Patient 1C
(2.643(3.236)). (C) Mean burst duration
of Patient 1 (27.62(47.58), p=0.0296) was
significantly higher relevant to Patient 1C
(26.40(6.017)). (D) Percent of spikes in
bursts of Patient 1 (4.119(34.95),
p=0.0075) was significantly higher
relevant to Patient 1C (2.346(2.601)). For
each cell line, at least 15 replicates were
plated from at least three differentiations.
Violin plots show all data points, with
median and interquartile range.

19
To discard an influence of the genetic background in the observed phenotypes, we
examined the dendritic morphogenesis of p.Q503X mutation insertion line, Patient 1 in
WT03231 (Figure 6). We found that the p.Q503X in this WT03231 background resulted in
similar morphological changes as Patient 1. Namely, the mutation resulted in GLUT-iNs that had
increased spine density (Patient 1 0.6112±0.0844, p<0.0001; Patient 1 in WT03231
0.4671±0.072, p<0.0001) and enlarged spines (Patient 1 (1.130(1.935),p<0.0001; Patient 1 in
WT03231 0.9972(1.934),p<0.0001) compared to WT03231 control cells (0.2088±0.0364 and
0.6667(1.069), respectively; Fig. 6B-D). These results suggest that there are no general genetic
background effects on the observed differences.
Figure 6. Genetic Background Has
No Influence on Patient-Derived
p.Q503X SYNGAP1 Mutation
Effect on Dendritic Spine
Morphology of Excitatory
Neurons. (A) Representative
confocal max intensity projection
images of cultured GLUT-iNs at 21
DIV after GFP-transfection at 18DIV
from Patient 1 , WT03231, and
Patient 1 in WT03231. Scale bar,
50um. B-D, Quantification of spine
density and HN-Index in Patient 1,
Patient 1C, and insertion lines. (B)
Individual non-filopodial spines were
plotted according to their length (um)
and HN-Index for each line. (C) The
number of spines per 10um of 40-
80um dendritic segments was
significantly higher in Patient 1
(0.6112±0.0844, p<0.0001) and
Patient 1 in WT03231
(0.4671±0.072, p<0.0001) relevant to
WT03231 (0.2088±0.0364). Mean +
s.e.m. (D) The HN-Index of spines
was significantly higher in Patient 1
(1.130(1.935),p<0.0001) and Patient
1 in WT03231
(0.9972(1.934),p<0.0001) relevant to
WT03231 (0.6667(1.069)). Median
(IQR). For each cell line, 6 replicates
were plated from at least three
differentiations.

20
We then assessed general background effects on neuronal activity by examining the
Patient 1, Patient 1 in WT03231 and WT03231 GLUT-iNs. We found that Patient 1 and Patient 1
in WT03231 GLUT-iNs showed a significant increase in firing (13.42(14.29), p=0.0013 and
13.89(40.66), p=0.0264, respectively) and bursting rates (7.000(30.47), p=0.0016 and
5.943(55.77), p=0.0120, respectively) relative to WT03231 GLUT-iNs (10.32(13.67)) and
3.204(5.265), respectively; Fig. 7A,B). As well, we observed a significant increase in mean burst
duration in Patient 1 (27.62(47.58), p=0.0052) and Patient 1 in WT03231 GLUT-iNs
(27.29(29.70), p=0.0046) relevant to controls (25.89(4.809); Fig. 7C). Lastly, we observed a
significant increase in percent spikes in bursts in Patient 1 (4.119(34.95), =0.0060) and Patient 1
in WT03231 GLUT-iNs (5.468(44.13), p<0.0001) relevant to controls (2.479(4.922);Fig. 7D).
These results further support that there are no genetic background effects on neuronal firing
patterns.
SYNGAP1 p.Q503X Patient Mutation
Impairs GABAergic Neurons
Figure 7. Genetic Background Has No
Influence on Patient-Derived p.Q503X
SYNGAP1 Mutation Effect on Neuronal
Activity Excitatory Neurons. A-D, Graphs
represent mean firing frequency, bursting
rate, mean burst duration, and percent of
spikes in bursts from multielectrode array
recordings of Patient 1, WT03231, and
Patient 1 in WT03231 cultured GLUT-iNs at
56 DIV. (A) Mean firing frequency of
Patient 1 (13.42(14.29), p=0.0013) and
Patient 1 in WT03231 (13.89(40.66),
p=0.0264) were significantly higher relevant
to WT03231 (10.32(13.67)). (B) Bursting
rate of Patient 1 (7.000(30.47), p=0.0016)
and Patient 1 in WT03231 (5.943(55.77),
p=0.0120) were significantly higher relevant
to WT03231 (3.204(5.265)). (C) Mean burst
duration of Patient 1 (27.62(47.58),
p=0.0052) and Patient 1 in WT03231
(27.29(29.70), p=0.0046) were significantly
higher relevant to WT03231 (25.89(4.809)).
(C) Percent of spikes in bursts of Patient 1
(4.119(34.95), =0.0060) and Patient 1 in
WT03231 (5.468(44.13), p<0.0001) were
significantly higher relevant to WT03231
(2.479(4.922)). For each cell line, at least 15
replicates were plated from at least three
differentiations. Violin plots show all data
points, with median and interquartile range.

21
Given that SYNGAP1 is expressed in both excitatory and inhibitory neurons, we explored
whether p.Q503X haploinsufficiency would also disrupt the maturation rate of dendrites and
synapses as we observed in GLUT-iNs. We found that differences in dendritic morphology were
apparent at 9 DIV, such that the Patient 1 p.Q503X mutation resulted in GABA-iNs that had
significantly more spines (1.178±0.1191, p=0.0027) than those of control neurons (0.5807±
0.1193); Figure 8B). There was a shift in the morphologies of the spines in Patient 1 neurons
toward that of mature spines with wider heads (1.315(2.109), p<0.0001) compared to controls
Figure 8. Patient-Derived p.Q503X SYNGAP1 Mutation Alters Dendritic Spine Morphology of Inhibitory Neurons.
(A) Representative confocal max intensity projection images of cultured GABA-iNs at 9 DIV after GFP-transfection at
6DIV from Patient 1 and its isogenic control (Patient 1C).B-C Quantification of spine density, HN-Index, and dendritic
length in GABA-iNs of Patient 1 and Patient 1C (B) The number of spines per 10um of 40-80um dendritic segments was
significantly higher in Patient 1 (1.178±0.1191, p=0.0027) relevant to Patient 1C (0.5807± 0.1193). (C) The HN-Index of
spines was significantly higher in Patient 1 (1.315(2.109), p<0.0001) relevant to Patient 1C (0.9029(0.9454)).Median(IQR).
(D) The average dendritic length was significantly increased in Patient 1 (39.42±4.451, p=0.0004) relevant to Patient 1C
(17.08±1.927). (E) Individual non-filopodial spines were plotted according to their length (um) and HN-Index for each line.
For each cell line, 6 replicates were plated from at least three differentiations.

22
(0.9029(0.9454); Figure 8C,E). Total dendritic fields were significantly larger in Patient 1 GABAiNs (39.42±4.451, p=0.0004) relative to the control line (17.08±1.927); Fig. 8D).
When we examined the p.Q503X mutation in the WT03231 background, we observed
similar effects such that the mutation resulted in GABA-iNs with a higher spine density (Patient
1 (1.178±0.1191, p<0.0001) ; Patient 1 in WT03231 1.574±0.3519, p=0.0004) and enlarged
spines (Patient 1 1.315(2.109), p<0.0001; Patient 1 in WT03231 1.362(2.045), p<0.0001) , as
well as lengthened dendrites (Patient 1(39.42±4.451, p=0.0022); Patient 1 in WT03231
30.38±4.665, p=0.0230) relative to WT03231 GABA-iNs (Fig. 9A-E). These data indicate that
SYNGAP1 p.Q503X haploinsufficiency produces a similar effect on dendritic morphology of
GABAergic neurons as that of glutamatergic neurons, with no influence of the genetic
background, suggesting that SYNGAP1 is also involved in the maturation of inhibitory neurons.
Figure 9. Genetic Background Has No Influence on Patient-Derived p.Q503X SYNGAP1 Mutation Effect on
Dendritic Spine Morphology of Inhibitory Neurons. (A) Representative confocal max intensity projection images of
cultured GABA-iNs at 9 DIV after GFP-transfection at 6DIV from Patient 1, its isogenic control (Patient 1C), WT03231, and
patient insertion lines (Patient 1 in WT03231). B-E, Quantification of spine density, HN-Index, and dendritic length in
GABA-iNs of Patient 1, WT03231 and insertion line. (B) The number of spines per 10um of segments of at least 10um in
length was significantly higher in Patient 1 (1.178±0.1191, p<0.0001) and Patient 1 in WT03231 (1.574±0.3519, p=0.0004)
relevant to WT03231 (0.4247±0.0999). (C) The HN-Index of mature spines was significantly higher in Patient 1
(1.315(2.109), p<0.0001) and Patient 1 in WT03231 (1.362(2.045), p<0.0001) relevant to WT03231 (0.8522(0.9941)). (D)
The dendritic length was significantly increased in Patient 1 (39.42±4.451, p=0.0022) and Patient 1 in WT03231
(30.38±4.665, p=0.0230) lines relevant to WT03231 (18.40±1.539). (E) Individual non-filopodial spines were plotted
according to their length (um) and HN-Index for each line. For each cell line, 6 replicates were plated from at least three
differentiations.

23
SYNGAP1 c.3583-9G>A Patient Mutation Alters Spinogenesis of Glutamatergic Neurons,
but Not Spine Maturation or Neuronal Activity
We examined the dendritic morphogenesis of GLUT-iNs from the Patient 3 line and its
isogenic control, as well as the Patient 14 line that shares the c.3583-9G>A mutation (Figure 10).
Unfortunately, we were not able to obtain GFP+ dendritic tracings of Patient 10 GLUT-iNs.
Dendritic spine analysis revealed that the Patient 3 and Patient 14 c.3583-9G>A GLUT-iNs had
similar morphologies in that they did not differ significantly from one another in their spine
density and HN-Index (Fig. 10 B-D). When comparing Patient 3 cells (0.8661±0.1275,
p=0.0001) to the Patient 3C control line (0.2360±0.0379) we observed a significant increase in
spine density (Fig. 10B). When individual spines were plotted according to their HN-Index and
length, we did not observe a significant change in the parameters of spines in Patient 3 GLUTiNs relevant to controls (Fig. 10C,D). Similarly, the Patient 14 GLUT-iNs showed increased
dendritic protrusions (0.8145±0.1360, p<0.0001) while the HN-Index remained unchanged (Fig.
10B-D). These data show that while both mutations show similar effects on spine density, these
c.3583-9G>A lines did not produce an effect on spine size, which contrasts the findings from the
p.Q503X mutation that showed enlarged spines.

24
To assess any changes in network activity, we measured the neuronal activity of Patient 3
and Patient 3C GLUT-iNs on multielectrode arrays (Figure 11). At 56 DIV, we observed Patient
3 GLUT-iNs had similar firing rates to its respective isogenic control (Fig. 11A). Then we
measured bursting activity and observed that the c.3583-9G>A mutation did not significantly
increase the bursting rate, the duration of the bursts and the percent of spikes in bursts relevant to
the control line (Fig. 11 B-D). Similar phenotypes were observed in Patients 10 and 14 relevant
to Patient 3C cells, such that they did not differ from the control cells on any other parameters
(Fig. 11A-D). This data demonstrates that the c.3583-9G>A mutation had a consistent effect on
spine morphology and neuronal activity across GLUT-iNs derived from different patients,
Figure 10. Patient-Derived c.3583-
9G>A SYNGAP1 Mutation Alters
Dendritic Spine Morphology of
Excitatory Neurons. (A) Representative
confocal max projection images of
cultured GLUT-iNs at 21 DIV after
GFP-transfection at 18DIV from Patient
3, its isogenic control (Patient 3C), and
Patient 14. Scale bar, 50um. B-C,
Quantification of spine density, HNIndex, and proportion of spine subtypes.
(B)The number of spines per 10um of
40-80um dendritic segments was
significantly higher in Patient 3
(0.8661±0.1275, p=0.0001) and Patient
14 (0.8145±0.1360, p<0.0001) relevant
to Patient 3C (0.2360±0.0379). (C) The
HN-Index of mushroom spines was not
significantly different in Patient 3
(1.004(1.606)), p=0.2398) and Patient
14(0.9845(1.095), p=0.0512) relevant to
Patient 3C (0.8214(0.9634)).
Median(IQR). (D) Individual nonfilopodial spines were plotted according
to their length (um) and HN-Index for
each line. Each dot represents an
individual spine. For each cell line, 6
replicates were plated from at least three
differentiations. mean + s.e.m.

25
indicating a specific cellular phenotype induced by this mutation irrespective of patients’ diverse
genetic backgrounds.
SYNGAP1 c.3583-9G>A Patient Mutation Impairs GABAergic Neurons
We examined the dendritic morphogenesis of GABA-iNs from the Patient 3 line and its
isogenic control and observed similar effects to that of the c. 3583-9G>A GLUT-iNs. Specifically,
when comparing Patient 3 cells to their isogenic control, we observed an increase in spine density
(2.014±0.1624, p<0.0001) relevant to Patient 3C GABA-iNs (0.6363±0.086, p<0.0001) similar
to what was observed in GLUT-iNs; however, like the GLUT-iNs, the Patient 3 GABA-iNs also
did not differ in the HN-Index of the mushroom spines (Figure 12A-E). Dendritic fields of Patient
3 GABA-iNs (29.83±3.354, p=0.0215) were significantly larger than that of Patient 3C
(21.08±2.130; Fig. 12C). Altogether, these data indicate that SYNGAP1 c.3583-9G>A mutation
results in cultures comprising GABAergic neurons with longer dendrites that grow more spines
with no significant difference in spine maturation.
Figure 11. Patient-Derived c.3583-9G>A SYNGAP1 Mutation Alters Synaptic Activity. A-D, Graphs represent mean
firing frequency, bursting rate, mean burst duration, and percent of spikes in bursts from multielectrode array recordings of
Patient 3, Patient 3C, Patient 10, and Patient 14 cultured neurons at 56 DIV. (A) Mean firing frequency of Patient 3
(12.94(21.57), p=0.1495), Patient 10(10.97(11.80),p=0.8590) and Patient 14 (14.20(15.42), p=0.0688) did not differ
significantly relevant to Patient 3C(11.31(7.522)). (B) Bursts per minute of Patient 3 (2.810(8.114) p=0.3844), Patient
10(3.159(8.508),p=0.1561) and Patient 14 (4.849(13.66),p=0.0560) did not differ significantly relevant to Patient
3C(2.657(4.635)). (C) Mean burst duration of Patient 3 (26.27(13.21, p=0.2680), Patient 10(27.40(6.031), p=0.1500) and
Patient 14 (25.79(5.619), p=0.2494) did not differ significantly relevant to Patient 3C(25.20(6.78)). (D) Percent of spikes in
bursts from of Patient 3 (2.433(16.26), p=0.0956), Patient 10(2.639(6.506), p=0.1112) and Patient 14 (3.295(13.11),
p=0.1190) did not differ significantly relevant to Patient 3C(1.979(3.604). For each cell line, 30 replicates were plated from at
least three differentiations. Violin plots show all data points, with median and interquartile range.

26
SYNGAP1 Patient- c.3583-9G>A Genetic Background Does Not Influence Cellular
Phenotype
Given that both SYNGAP1 p.Q503X and c.3583-9G>A mutations are reported to produce
truncation mutations, this line of investigation was meant to examine why we observed different
cellular phenotypes between mutations. We had observed a milder cellular phenotype in the
c.3583-9G>A that were consistent among the three c.3583-9G>A lines, indicating that genetic
background does not significantly influence the cellular phenotype. However, in order to get a
better understanding of the role of patient genetic background and investigate potential
“protective” effects it might provide against the SYNGAP1 mutation, we expanded our analysis
to include Patient 1 p.Q503X mutation in Patient 3C background (Figure 13). We found that, like
Patient 3 GLUT-iNs, Patient 1 (0.6896±0.0844, p<0.0001) and Patient 1 in Patient 3C
(0.8567±0.1892, p=0.0009) cells had a higher spine density relative to the Patient 3C
Figure 12. Patient-Derived c.3583-9G>A SYNGAP1 Mutation Alters Dendritic Spine Morphology of Inhibitory
Neurons. (A) Representative confocal max intensity projection images of cultured GABA-iNs at 9 DIV after GFPtransfection at 6DIV from Patient 3 and its isogenic control (Patient 3C). Scale bar, 50um B-E Quantification of spine
density, HN-Index, and dendritic length in GABA-iNs of Patient 3 and Patient 3C. (B) The number of spines per 10um of 40-
80um dendritic segments was significantly higher in Patient 3 (2.014±0.1624, p<0.0001) relevant to Patient 3C
(0.6363±0.086, p<0.0001). (C) The average dendritic length was significantly increased in Patient 3 (29.83±3.354) relevant
to Patient 3C (21.08±2.130, p=0.0215). (D) Individual non-filopodial spines were plotted according to their length (um) and
HN-Index for each line. (E) The HN-Index of spines was not significantly different (p=0.9112) in Patient 3 (0.9713(3.030))
relevant to Patient 3C (0.9725(1.339)). Median (IQR). For each cell line, 6 replicates were plated from at least three
differentiations.

27
(0.2360±0.0379; Fig. 13C). Additionally, Patient 1 (1.130(1.935), p=0.0034) and Patient 1 in
Patient 3C cells (1.113(3.210), p=0.0298) had a higher HN-Index relative to the Patient 3C
(0.8214(0.9634); Fig. 13B,D).These data indicate that the Patient 1 p.Q503X mutation has a
more pronounced effect on spine maturation than SYNGAP1 c.3583-9G>A mutation, resulting
in cultures comprising neurons with more dendritic protrusions and enlarged spines. As well,
these results further suggest that SYNGAP1 plays a pleiotropic role in the development of spine
heads and the morphological transformation from filamentous to mushroom spines, independent
of the patient genetic background.
Figure 13. Patient Genetic
Background Does Not
Influence SYNGAP1
Mutation Effects on
Dendritic Spine Morphology
of Excitatory Neurons. (A)
Representative confocal max
projection images of cultured
GLUT-iNs at 21 DIV after
GFP-transfection at 18DIV
from Patient 3, its isogenic
control (Patient 3C), and
insertion line (Patient 1 in
Patient 3C). Scale bar, 50um.
B-D, Quantification of spine
density, HN-Index, and
proportion of spine subtypes.
(B) Individual non-filopodial
spines were plotted according
to their length (um) and HNIndex for each line. Each dot
represents an individual spine.
(C) Spine density was
significantly higher in Patient
1 (0.6896±0.0844, p<0.0001)
and Patient 1 in Patient 3C
(0.8567±0.1892, p=0.0009)
relevant to Patient
3C(0.2360±0.0379). (D) HNIndex was significantly higher
in Patient 1 (1.130(1.935),
p=0.0034) and Patient 1 in
Patient 3C (1.113(3.210),
p=0.0298) relevant to Patient
3C(0.8214(0.9634)). For each
cell line, 6 replicates were
plated from at least three
differentiations. mean + s.e.m.

28
We then compared mutation effects on
neuronal activity and found that, like our findings
in morphology, the Patient 1 p.Q503X mutation
led to a more robust effect relative to the Patient 3
and corrected line (Figure 14B-D). Specifically,
the Patient 3 (2.810(8.114)) and Patient 3C
(2.657(4.635)) GLUT-iNs had a lower bursting
rate compared to the Patient 1 (7.00(30.47),
p=0.0052 and p=0.0007, respectively) and Patient
1 in Patient 3C GLUT-iNs (5.118(12.70),
p=0.0081 and p<0.0001,respectively; Fig. 14B).
Patient 3 (26.27(13.21)) and Patient 3C
(25.20(6.78)) GLUT-iNs had shorter bursts
relative to the Patient 1 (27.62(23.99), p=0.0351
and p<0.0001) and Patient 1 in Patient 3C GLUTiNs (28.14(29.78), p=0.0088 and p<0.0001; Fig.
14C). As well, Patient 3 (2.433(16.26)) and
Patient 3C (1.979(3.604)) had less spikes in bursts
relative to the Patient 1 (4.119(34.95), p=0.0063
and p<0.0001) and Patient 1 in Patient 3C cells
(Fig. 14D). The Patient 1 GLUT-iNs showed a
higher firing rate than Patient 3C, while the
Patient 1 in Patient 3C GLUT-iNs did not have
Figure 14. Patient Genetic Background Does Not
Influence SYNGAP1 Mutation Effects on Neuronal
Activity of Excitatory Neurons. A-D, Graphs
represent mean firing frequency, bursting rate, mean
burst duration, and percent of spikes in bursts from
multielectrode array recordings of Patient 3, Patient
3C, Patient 1 and Patient 1 in Patient 3C cultured
neurons at 56 DIV. (A) Mean firing frequency of
Patient 3C was significantly lower than Patient 1
(13.42(14.29), p=0.0134). Patient 3 firing rate was
significantly higher than Patient 1 C (9.931(12.80),
p=0.0056). (B) Bursts per minute of Patient 3C were
significantly lower than Patient 1 (7.00(30.47),
p=0.0007) and Patient 1 in Patient 3C (5.118(12.70),
p<0.0001). Patient 3 were significantly lower than
Patient 1 (p=0.0052**) and Patient 1 in Patient 3C
(p=0.0081). (C) Mean burst duration of Patient 1
(27.62(23.99), p<0.0001) and Patient 1 in Patient 3C
(28.14(29.78) p<0.0001) was significantly higher
relevant to Patient 3C. Patient 3 had significantly
shorter bursts than Patient 1 (p=0.0351) and Patient 1
in Patient 3C (p=0.0088). (D) Percent of spikes in
bursts of Patient 3C were significantly lower relevant
to Patient 1 (4.119(34.95), p<0.0001) and Patient 1 in
Patient 3C (6.983(31.76), p<0.0001). Patient 3 had
significantly less spikes in bursts relevant to Patient 1
(p=0.0063) Patient 1 in Patient 3C (p=0.0010). For
each cell line, 30 replicates were plated from at least
three differentiations. Violin plots show all data points,
with median and interquartile range.

29
significantly higher firing rates than the corrected line (6.983(31.76), p=0.0010 and p<0.0001;
Fig.14A). Altogether, these data suggest that there is no evidence for a protective effect of the
genetic background on a truncation mutation of SYNGAP1.
Similarly, GABA-iNs demonstrated that Patient 1 p.Q503X mutation in Patient 3C
background resulted in morphological patterns that were more in line with Patient 1 than Patient
3 (Figure 15A-E)). Specifically, when comparing the lines on spine density we found that
Patient 3 (2.014±0.1624) had significantly more spines than Patient 1 (0.7621±0.1191,
p<0.0001) and Patient 1 in Patient 3C (1.592±0.1922, p=0.0018; Fig. 15C). Conversely, when
comparing the lines on HN-Index, we found that Patient 1 (1.312(2.109)) and Patient 1 in Patient
3C (1.161(1.725) had more enlarged than Patient 3 (p<0.0001 and p=0.0008, respectively) and
Patient 3C (p<0.0001 and p=0.0004, respectively; Fig. 15B,D). As well, when comparing the
lines on dendritic length, we found that Patient 1(48.32±5.641) and Patient 1 in Patient 3C
(56.70±8.204) had longer dendrites than Patient 3 (p=0.0045 and p<0.0001,respectively) and
Patient 3C (p<0.0001 and p<0.0001, respectively; Fig. 15E). These observations indicate that
while the Patient 3 c.3583-9G>A mutation primarily influences spine density, suggesting an
increase in the number of potential synaptic connections, the p.Q503X mutation more
significantly impacts the HN-Index, indicating a shift towards more mature spine morphology.
This delineation in mutation effects highlights a nuanced role of SYNGAP1 in GABA-iN
synaptic development, where different mutations may selectively affect spine number versus
spine maturation. Interestingly, the mutation-specific effects on GABA-iN spine density differed
from what was observed in GLUT-iNs for which we observed comparably similar mutation
effects (Fig.13C). However, consistent with observations in GLUT-iNs (Fig. 13D), the p.Q503X
mutation directly impacted the HN-Index of GABA-iN spines while the Patient 3 c.3583-9G>A

30
mutation did not show such an effect. This divergence in mutation effects between neuronal
subtypes may suggest that SYNGAP1’s role in dendritic spine development and maturation is
modulated by cell-type-specific factors or the intrinsic properties of different neuronal
Figure 15. Patient Genetic Background Does Not Influence SYNGAP1 Mutation Effects on Dendritic Spine
Morphology of Inhibitory Neurons. (A) Representative confocal max intensity projection images of cultured GABA-iNs at
9 DIV after GFP-transfection at 6DIV from Patient 1, Patient 1 in Patient 3C, Patient 3 and Patient 3C. Scale bar, 50um B-E,
Quantification of spine density, HN-Index, and dendritic length in GABA-iNs of Patient 3, Patient 3C, Patient 1, Patient 1C,
and Patient 1 in Patient 3C. (B) Individual non-filopodial spines were plotted according to their length (um) and HN-Index
for each line. (C) The number of spines per 10um was significantly higher in Patient 1 (0.7621±0.1191) relevant to Patient
3C (p=0.0016) but less than Patient 3 (p<0.0001). Patient 1 in Patient 3C (1.592±0.1922) had significantly more spines than
Patient 3C (p=0.0018) but less spines than Patient 3 (p=0.0038) (D) The HN-Index of spines was significantly higher in
Patient 1 (1.312(2.109)) relevant to Patient 3C (p<0.0001) and Patient 3 (p<0.0001). Patient 1 in Patient 3C HN-Index
(1.161(1.725) was significantly higher than Patient 3C (p=0.0004) and Patient 3 (p=0.0008). Median (IQR). (E) The average
dendritic length was significantly increased in Patient 1 (48.32±5.641) relevant to Patient 3C (p<0.0001) and Patient 3
(p=0.0045). Patient 1 in Patent 3C dendritic length (56.70±8.204) was significantly increased relevant to Patient 3C
(p<0.0001) and Patient 3 (p<0.0001).

31
populations: however, more work needs to be done to fully understand the role of SYNGAP1 in
different neuronal populations.
SYNGAP1 Patient-derived Mutations Increase Total Protein Levels in Glutamatergic
Neurons
Given the lack of influence of genetic background on the phenotypic variations observed
in our study, we extended our investigation to assess protein expression levels associated with
each patient mutation. We analyzed GLUT-iN samples from Patient 1, Patient 3 and their
respective isogenic controls. Preliminary analysis (not pictured) suggested that both mutations
resulted in protein truncation and a subsequent reduction in the overall SYNGAP1 protein levels.
Interestingly, the preliminary data hinted at a higher protein
expression in Patient 3 compared to Patient 1. To obtain a
more precise quantitation of these protein differences, we
employed mass spectrometry analysis which confirmed that
Patient 1 (56.33+4.099, p<0.0001) and Patient 3
(71.29+4.522, p<0.0001) mutations indeed led to a
significant reduction in SYNGAP1 protein levels compared
to their isogenic controls (111.9+4.912 and 101.8+3.936,
respectively; Figure 16) Moreover, a comparative analysis
between Patient 1 and Patient 3 GLUT-iNs revealed a
significant difference in protein quantities, with Patient 3
exhibiting higher protein levels than Patient 1 (p=0.0270).
This variance in protein expression may offer insight into
the phenotypic differences observed in GLUT-iNs,
Figure 16. SYNGAP1 Patient-Derived
Mutations Differentially Decrease
Total Protein Levels. HPLC/LC-MS
quantification of total SYNGAP1 protein
at 21DIV in GLUT-iNs from Patient 1,
Patient 3, and respective isogenic
controls. Patient 1 GLUT-iNs
(56.33±4.099, p<0.0001) expressed
significantly less protein than Patient 1C
(111.9±4.912). Patient 3 GLUT-iNs
(71.29±4.522, p<0.0001) expressed
significantly less protein than Patient 3C
GLUT-iNs (101.8±3.936), but more
protein than Patient 1 (p=0.0270). Patient
1C GLUT-iNs did not differ from Patient
3C (p=0.1171). Mean±sem.

32
suggesting that the extent of protein truncation and the resulting functional protein levels might
underlie the differential impacts of SYNGAP1 patient mutations on neuronal development and
maturation.
Discussion
We produced glutamatergic and GABAergic neurons from human iPSCs to investigate
how SYNGAP1 patient-derived mutations impacted neuronal maturation. This is an important
research question given that pathogenic SYNGAP1 variants result in intellectual disability and
clinical profiles of varying degrees of severity (Vlaskamp et al., 2019). We found that
SYNGAP1 is involved in the maturation of dendrites and synapses from human iPSC-derived
neurons. Moreover, by utilizing two SYNGAP1 mutations with various genetic backgrounds, we
uncovered unexpected differences in cellular phenotypes that are mutation-specific. As well, we
found that while pathogenic SYNGAP1 variants lead to a decrease in protein levels, they don’t
result in the same amount of protein expression.
SYNGAP 1 p.Q503X haploinsufficiency enhanced dendritic morphogenesis and
increased network activity in glutamatergic neuronal cultures. Our data indicate that the decrease
in functional SYNGAP1 protein resulting from the p.Q503X haploinsufficiency was responsible
for the observed dendrite and synapse maturation phenotypes. We observed longer dendrites in
GFP-positive GABAergic neurons derived from lines that contained the p.Q503X truncation
mutation, as well as increased spine density in glutamatergic and GABAergic neurons. The
truncation mutation also influenced the morphological parameters of the individual spines for
both neuronal subtypes, such that it enlarged the spine heads. The HN-Index (head-to-neck
ratio) of dendritic spines serves as a critical morphological indicator of neuronal maturity and
synaptic strength. The size of the spine head is correlated with increased PSD area and receptor

33
number, which are associated with higher synaptic strength thus suggesting a mature connection
(Arellano et al., 2007). Furthermore, the diffusion through spine necks and their dimensions
greatly impact synaptic compartmentalization, influencing receptor localization and signaling
pathways essential for synaptic plasticity (Adrian et al., 2017; Adrian et al., 2014). Distributed
neuronal activity measured by multielectrode arrays confirmed that the structural maturation of
dendrites translated into increased network activity in glutamatergic p.Q503X cultures, given
that network bursting is largely driven by increased functional synaptic connectivity in
neurons(Suresh et al., 2016). These data support the conclusion that SYNGAP1 protein regulates
the maturation rate of dendritic and synaptic structures and has pronounced effects on network
activity. Additionally, these data provide a possible neurobiological mechanism for why
individuals with SYNGAP1 truncation mutations have a high incidence of epilepsy (Vlaskamp et
al., 2019).
Interestingly, SYNGAP1 c.3583-9G>A mutation presents a different cellular phenotype
to that of p.Q503X haploinsufficiency, given how it increases the spine density of glutamatergic
and GABAergic neurons, as well as the dendritic length of GABAergic neurons but does not
alter spine maturation of either neuronal subtype. Interestingly, the increased spinogenesis did
not impact connectivity of cultured glutamatergic c.3583-9G>A neurons, as depicted by the
network activity measured in multielectrode arrays, suggesting that spine size is a better indicator
for neuronal function. The lack of effect on neuronal activity is unexpected given our findings in
p.Q503X cells in which we observed enhanced spine maturation and neuronal activity.
Additionally, several prior reports describe substantially increased excitability and synaptic
function in glutamatergic neurons from Syngap1 heterozygous animal models(Araki et al., 2015;
Clement et al., 2012). When compared against the p.Q503X insertion line, spine maturation and

34
network activity phenotypes are milder. It is possible that the discrepancy observed in
GABAergic spine density, in which the c.3583-9G>A mutation had a more marked effect on
spine density, is indicative of there being different SYNGAP1 isoforms expressed from each
mutated gene and in neuronal subtypes, although we would need to confirm that idea with
targeted mass spectrometry. This particular line of inquiry was driven by our desire to ascertain
if the pronounced effects previously noted in Patient 1, as well as in Patient 1 in WT03231,
would be conserved within the context of Patient 3 genetic background. This approach allowed
us to directly assess the impact of the p.Q503X mutation, further confirming that variations in
genetic background did not significantly alter the mutation’s effects on dendritic spine
morphology. Our data indicate that the decrease in functional SYNGAP1 protein resulting from
the c.3583-9G>A mutation was responsible for the observed dendrite phenotypes and provide
evidence for the complex role that other components might play in SYNGAP1 functions.
Data implicating the diverse regulation SYNGAP1 exerts on excitatory synapse
transmission is consistent with findings from studies using Syngap1 heterozygous mutant
animals. The overexpression of Syngap1 decreases excitatory synaptic activity through the
internalization of AMPA receptors(Rumbaugh et al., 2006). One study reports that Syngap1
isoforms each regulate synaptic transmission in opposing directions (McMahon et al., 2012). The
complete ablation of SYNGAP1 results in increased excitatory synapse strength and an earlier
appearance of synaptic activity in human glutamatergic neurons (Clement et al., 2012; Llamosas
et al., 2020). However, the ablation of all Syngap1 splice forms in rodents stunts the maturation
and synaptic transmission of neurons specifically in the somatosensory cortex(Michaelson et al.,
2018). While our studies in human induced glutamatergic and GABAergic neurons support a role
for SYNGAP1 protein levels to exert a diverse regulation of dendritic maturation, it is still

35
unclear what is driving those results. Despite not creating a CRISPR/Cas9-inserted swap line
with the Patient 1 Corrected background, we were able to include two additional patient-derived
lines that shared the SYNGAP1 c.3583-9G>A mutation and support the conclusion that in vitro
phenotypes are dominated by mutation-specific modulation rather than individual genetic
background. However, we did not assess the expression of different isoforms that results from
each of the SYNGAP1 mutations included in this study. It will be of considerable interest to
assess the expression levels of C-terminal isoforms in each of the genotypes in future studies
using targeted quantitation of SYNGAP1 isoforms by mass spectrometry to assess their role in
the observed phenotypes. In the following chapter, we address the possible role that SYNGAP1
functional domains might play in the observed phenotypes. Specifically, we determine how the
RasGAP domain of SYNGAP1 and the PDZ-binding motif of the α1 isoform influence dendritic
maturation and synaptic transmission.
Methods
Cell Lines, Cell Culture and Neural Differentiation
The iPSC lines were generated using Yamanaka factors in patient-derived PBMCs, as
previously described (17). iPSC lines were maintained with mTeSR plus (STEMCELL
Technologies #100-0275) media changes every other day on 1:200 geltrex (GIBCO, #A1413301)
coated tissue culture 6-well plates (Genesee Scientific #25-105) and passaged using ReLeSR
(STEMCELL Technologies #05872). Cells were maintained below passage 50 and periodically
karyotyped via the G-banding Karyotype Service at Children’s Hospital Los Angeles.

36
CRISPR/Cas9-edited iPSC Line Generation
SYNGAP1 patients provided venous blood samples for genomic DNA analysis and iPSC
generation. Patient 1 was found to have a nonsense (c.1507C>T; p.Q503) mutation. Patients 3,
10, and 14 were all found to have a splicing site mutation (c.3583-9G>A).
SYNGAP1 Patient 1 Corrected Line. A sgRNA targeting the patient-specific mutation
(p.Q503X) in SYNGAP1 was cloned into pSpCas9(BB)-2A-Puro (PX459) V2.0 (Addgene
plasmid #62988). The sgRNA construct and the HDR template containing the WT SYNGAP1
sequence, were electroporated into the Patient 1 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.
HDR Template:
CCGCGAGAACACGCTTGCCACTAAAGCCATAGAAGAGTATATGAGACTGATTGGTC
AGAAATATCTCAAGGATGCCATTGGTATGGCCCACACTCAGGCCCTCTTCTTCCCAA
ACCTGCCA
The underlined CAG sequence corresponds to the insertion of the WT "T" base pair and
the underlined T base corresponds to a silent PAM mutation. The substitution of the truncating
"T" with the WT "C" base pair was screened for via restriction enzyme digestion (DrdI) and then
confirmed via sanger sequencing.
SYNGAP Patient 3 Corrected Line. A sgRNA targeting the patient-specific mutation
(c.3583-9G>A) in SYNGAP1 was cloned into pSpCas9(BB)-2A-Puro (PX459) V2.0. The sgRNA
construct and the HDR template containing the WT SYNGAP1 sequence, were nucleofected into
the Patient 3 iPSC line. Individual iPSC colonies were transferred to 24 well plates and

37
subsequently underwent restriction enzyme-based genotyping. Positive colonies were then
confirmed via Sanger sequencing and expanded in culture.
HDR Template:
GGCTGGGTGGTGGGCTTGGGGTGGGGCGCCCCTCATAGTGCGGGGTCGTGTGCCCGGCGGG
CAGGTGAAGGAGTACGAGGAGGAGATTCACTCACTGAAAGAGCGGCTGCA
The underlined CCG sequence corresponds to the insertion of the WT "G" base pair and
the silent PAM mutation. The substitution of the truncating "A" with the WT "G" base pair was
screened for via restriction enzyme digestion HpaII and then confirmed via sanger sequencing.
To account for the contribution of the patient’s genetic background to the neuronal
phenotypes, Patient 1 mutation was inserted into 03231 control (WT03231) iPSC line derived
from a healthy 56-year-old male (Patient 1 in WT03231) and into the CRISPR/Cas9-corrected
Patient 3C line.
SYNGAP1 Patient 1 Mutation Insertions. The SYNGAP1 Patient 1 in WT03231 and
Patient 1 in Patient 3C cell lines were generated 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. The sgRNA and the HDR template were nucleofected in the 03231 control and Patient 3C
iPSC lines. Individual iPSC colonies were transferred to 24 well plates and subsequently
underwent restriction enzyme-based genotyping. Positive colonies were then confirmed via
sanger sequencing.
HDR template:
CCGCGAGAACACGCTTGCCACTAAAGCCATAGAAGAGTATATG
AGACTGATTGGTTAGAAATATCTCAAGGATGCCATTGGTATGGCCCACACTCAGGCC
CTCTTCTTCCCAAACCTGCCA

38
The underlined TAG region shows the 1507C>T inserted mutation and the underlined T
base shows the introduced silent PAM mutation. The substitution of the WT "C" with the
truncating "T" base pair was screened for via restriction enzyme digestion (DrdI) and then
confirmed via sanger sequencing.
Neural Differentiation
Glutamatergic Induced Neurons. iPSC cells were seeded at a density of 1.5x105
cells/well on geltrex-coated 6-well plates with mTesR Plus media and 10 μM Rock inhibitor Y27632 (Selleck Chemicals, Houston, TX; #S1049). The following day, cells were infected with
lentivirus plasmids that inducibly express Ngn2 and constitutively express the Puromycin
resistance gene (packaged using pLV-TetO-hNGN2-Puro plasmid from Addgene, Plasmid
#79049 (Addgene, Cambridge, MA)) and a reverse tetracycline transactivator (FUdeltaGW-rtTA
from Addgene, Plasmid #19780), 1 μg/ml of doxycycline(Enzo, #09191425) and 2 μg/ml
of polybrene (Sigma Aldrich, #107689-10G). After overnight incubation, the media was
replaced with fresh mTeSR Plus media with 2 μg/ml of Doxycycline. The next day, 0.7 μg/ml of
puromycin (Sigma Aldrich#P8833-10MG) was added to the culture. After a 48hr selection, the
media was changed with fresh mTeSR Plus media and cells were fed every other day until they
reached approximately 80% confluency. To start neuron induction, confluent cells were
dissociated with Accutase (Innovative Cell Technologies, #AT104-500) and plated onto geltrexcoated 6-well plates in N2 media (DMEMF12 (Corning, #24922006), 1X N2 Supplement
(Gibco, #17502048), 1X NEAA (Gibco, #2301967), 10ng/ml BDNF (Shenandoah, #01221-100-
01), 10ng/ml NT3 (Fujifilm, #2208120002)) supplemented with 10uM of ROCK inhibitor and
1ug/ml doxycycline at a cell density of 2x10^5 cells per well (Day 0). On Day 1, media was
replaced with N2 media supplemented with 1ug/ml doxycycline and 0.7ug/ml puromycin. On

39
Day 3, media was replaced with B27 media (Neurobasal (Gibco, #2523113), 1X B27 supplement
(Gibco, #17504044), 1X GlutaMAX (gibco, #2523105), 10ng/ml BDNF (Shenandoah #01221-
100-01), 10ng/ml NT3(Fujifilm #2208120002)) supplemented with 1ug/ml Doxycycline and
2uM Ara-C (1-β-D-Arabino-furanosylcytosine, Calbiochem, #251010). Half media changes with
B27 media supplemented with doxycycline were done every other day for 21 days, after which
doxycycline was removed from the media to stop the overexpression of NGN2. If co-cultured
with murine astrocytes (ScienCell #M1800-57) for electrophysiology, B27 media was
supplemented with FBS (Genessee Scientific #25-514) after 10 days in culture.
GABAergic Induced Neurons. iPSC cells were seeded at a density of 1.5x105 cells/well
on geltrex-coated 6-well plates with mTesR Plus media and 10 μM Rock inhibitor Y-27632. The
following day, cells were infected with lentivirus plasmid that inducibly expresses ASC11 and
constitutively expresses the Puromycin resistance gene (packaged using pTet-O-FUW-Asc11-
puromycin plasmid from Addgene, Plasmid #97329 (Addgene, Cambridge, MA)), lentivirus
plasmid that inducibly expresses DLX2 and constitutively expresses the Hygromycin resistance
gene (packaged using pTet-O-FUW-Dlx2-hygromycin plasmid from Addgene, Plasmid #97330
(Addgene, Cambridge, MA)), and a reverse tetracycline transactivator, 1 μg/ml of doxycycline
and 2 μg/ml of polybrene. After overnight incubation, the media was replaced with fresh mTeSR
Plus media with 2 μg/ml of Doxycycline. The next day, 0.7 μg/ml of puromycin was added to the
culture. After a 48hr selection, the media was changed with fresh mTeSR Plus media and cells
were fed every other day until they reached approximately 80% confluency. To start neuron
induction, confluent cells were dissociated with Accutase and plated onto geltrex-coated 6-well
plates in GABA-N2 media (DMEMF12, 1X N2 Supplement, 1X NEAA, supplemented with
10uM of ROCK inhibitor and 1ug/ml doxycycline at a cell density of 2x10^5 cells per well (Day

40
0). On Day 1, media was replaced with GABA-N2 media supplemented with 1ug/ml
doxycycline, 0.7ug/ml puromycin, and 100ug/ml hygromycin (Corning #30-240-CR). On Day 3,
media was replaced with GABA-B27 media (Neurobasal, 1X B27 supplement, 1X GlutaMAX)
supplemented with 1ug/ml doxycycline and 2uM Ara-C. Media was replaced every other day
until cells reached their endpoint.
Biochemistry
Immuniprecipitation
iPSC-derived neurons cultured in geltrex coated 10 cm2 tissue culture dishes were harvested via
accutase treatment and lysed in cell lysis buffer (50 mM Tris pH 7.4, 2 mM EDTA, 10 mM
NaVO4, 30 mM NaF, 20 mM β-glycerolphosphate, 1% n-Dodecyl-βMaltopyranoside,
supplemented with complete Protease Inhibitor Cocktail Tablets using mechanical
homogenization followed by incubation at 4 degrees Celsius while rotating for 40 minutes. The
cell lysate was then centrifuged at 35,000 RPM for 30 min at 4 degrees Celsius and the protein
concentration of the supernatant was subsequently determined using the BCA assay kit ( Thermo
Cat# 23227). 2 mg of total protein were incubated with anti-SYNGAP1 antibody (Tabl 1) at 4
degrees Celsius overnight with gentle rotation. The following day, samples were mixed with 50
ul of Dynabeads protein G (ThermoFisher Cat# 10004D) and incubated at 4 degrees Celsius for
2 hours with gentle rotation. Beads were washed 3 times in IP wash buffer (25 mM Tris pH 7.4,
150 mM NaCl, 1 mM EDTA, 1% n-Dodecyl-β-Maltopyranoside) and then incubated with 50 ul
2X LDS sample buffer (Invitrogen Nupage NP0008) on a thermomixer (Eppendorf Cat #) for 15
min at 95 degrees Celsius with rotation (500 rpm). If the samples were for Mass Spectrometry,
they were incubated with 10mM DTT (Invitrogen. Cat#15508-0) at 56 degrees Celsius for 1 hour

41
followed by 20mM Iodoacetamide (Sigma I1149-25G) at room temperature for 45 min in the
dark.
Western Blot
Following immunoprecipitation using cell lysates, samples were combined with LDS
sample buffer 10 mM DTT and then incubated at 95 degrees Celsius for 15 minutes. Samples
were then loaded on 4 – 12% Bis-Tris gels (NuPAGE Novex, Thermo Fisher Scientific,
Waltham, MA) and separated at 135V for 1.5 hours. Proteins were then transferred to a PVDF
membrane using a Bio-Rad Trans-Blot Turbo Transfer System (Bio-Rad, Hercules, CA).
Membranes were blocked for 1 hour at room temperature with 5% bovine serum albumin (BSA)
in 0.05% TBS-Tween (TBST) and then incubated with primary antibody overnight at 4 degrees
Celsius. Membranes were washed with 0.05% TBST four times, ten minutes each, and then
incubated with secondary antibodies for 1 hour at room temperature. Membranes were washed
with 0.05% TBST 4 times, 5 minutes each, and imaged using a 4000MM Pro Image Station
(Carestream, Rochester, NY). All primary and secondary antibody antibodies used along with
their dilutions can be found in Table 1.
Mass spectrometry Sample Preparation
Samples were separated on 4–12% Bis-Tris gels (NuPAGE Novex) followed by staining
with InstantBlue (Expedeon) for protein visualization. Following destaining, lanes were cut and
placed in 96-well perforated plates for destaining and peptide digestion via trypsin at 37 degrees
Celsius overnight. Peptides were then extracted with acetonitrile, dried down using a Savant SPD
1010 SpeedVac Concentrator (Thermo Scientific), and then suspended in 3% ACN/0.1% FA. A
Nano/Capillary LC System Ultimate 3000 (Thermo/Dionex) was used for desalting and reversephase separation of peptides. The LC system was coupled to a hybrid linear ion-Fourier

42
transform ion cyclotron resonance LTQ-FT (FTICR) 7 Tesla mass spectrometer (LC/MS) for
data acquisition.
Immunofluorescence
Cells were fixed with 4% PFA and permeabilized with 0.1% PBS (Corning #21-040-
CV)+ TritonX100 (Sigma #T8532-100ML; PBST) for 15 minutes at room temperature, and
subsequently blocked in 1% bovine serum albumin (Genesee Scientific #25-529; BSA) in
0.025% PBST for 2 hours at room temperature and then incubated overnight with primary
antibodies (Table 1) in blocking solution at 4C. The following day, cells were washed three
times with 0.025%PBST and then incubated with secondary antibodies (Table 1) in blocking
solution for 1 hour at room temperature. Cells were triple washed with 0.025% PBST and nuclei
were stained with DAPI (1:2000; Cell Signaling #4083) diluted in 1xPBS for 5 minutes. Cells
were
washed
three
times for
5 min
with
1xPBS
before
mounting
coverslips
on slides
Antigen Dilution Company
Catalog
Number Assay
Primary Antibodies
Rabbit anti-OCT4 1:450 Cell Signaling 2840S
ICC
Mouse anti-SSEA4 1:450 Cell Signaling 4755S
Chicken anti-GFP 1:10000 Aves Lab GFP-1010
Rabbit anti-Map2 1:300 Cell Signaling 8707S
Mouse anti-Somatostatin 1:200 Invitrogen MA5-17182
Mouse anti-Synaptophysin 1:200 Cell Signaling 9020S
Mouse anti-PSD95 1:500
UC Davis/NIH NeuroMab
Facility 75-028
Rabbit anti-Syngap1 1:1000 Thermo Fisher PA1-046 WB
Rabbit anti-Syngap1 2ug/mg Cell signaling D78B11 IP
Secondary Antibodies
Alexa Fluor 488 goat anti-rabbit 1:500 Invitrogen A11034
ICC
Alexa Fluor 488 goat anti-chicken 1:500 Invitrogen A11039
Alexa Fluor 594 goat anti-mouse 1:500 Invitrogen A11020
Alexa Fluor 647 goat anti-rabbit 1:500 Invitrogen A21244
anti - Rabbit IgG (H+L) Peroxidase
conjugated 1:20000 Jackson Immuno Research 111-035-144
WB
anti - Mouse IgG (H+L) Peroxidase
conjugated 1:20000 Jackson Immuno Research 115-035-146
Table 1. Primary and secondary antibodies.

43
(VWR #48311-703) with ProLong Diamond Antifade mountant (Invitrogen #P36965).
Functional Assays
Dendritic Spine Analysis
Excitatory and inhibitory neurons were cultured as monocultures on poly-L-ornithine
(Sigma #P3655-10MG) and laminin (Gibco #23017-015) coated glass coverslips (neuVitro #GG12-1.5-PRE) in 24 well plates (Falcon #353047) and assayed at 21 and 9 DIV, respectively. For
morphological analysis neurons were transfected with GFP (pSin-Ef1a-EGFP Addgene #21320)
and spines co-visualized with anti-MAP2 and anti-GFP antibodies. For each assay,
morphological analyses of dendritic spines were performed by 3D reconstruction using Imaris
Filament Tracer (Bitplane) on images acquired on a Nikon A1R HD microscope with a Nikon
Plan Apo � 60x oil objective. Dendritic length was obtained by manually tracing cells in FIJI on
brightfield images acquired on a Nikon DS-Fi3 camera with a Nikon Plan Apo � 4x objective to
capture the entire dendritic field of each cell. All assays were performed in three independent
differentiations using 3 replicate assays per differentiation. Data was gathered by an individual
blinded to the experimental conditions.
Multielectrode array recordings
iPSC-derived glutamatergic neurons were co-cultured with primary murine astrocytes
and plated onto six-well multielectrode chips (nine electrodes and one ground per well) coated
with poly-L-ornithine and laminin. To study the inhibitory effect of GABAergic neurons derived
from the different iPSC lines, WT03231 GLUT-iNs were co cultured with GABA-iNs on MEAs.
Spontaneous network activity was recorded from day 56 in culture using a MultiChannel
Systems MEA-2100 multielectrode array (MEA) amplifier (ALA Scientific) with built-in heating
elements set to 37 °C. Cells were allowed to acclimate for 5 min after chips were placed into the

44
MEA amplifier before beginning 7min recordings. Active electrodes were defined as those that
averaged more than 10 spikes per minute. Bursting electrodes were defined as those that had at
least 1 burst per minute. Bursting wells were defined as well that had more than 30% bursting
electrodes. All wells that did not meet these criteria were discarded. Spikes were detected by
crossing of a threshold set to a level of 3 standard deviations from the baseline noise level. Mean
spike frequency (Hz), bursts per minute, mean burst duration, and percent spikes in bursts were
determined using the accompanying MC Rack software.
Data Analysis
Analysis was performed with the statistical software package Prism Origin (GraphPad
Software). Differences between two groups were analyzed using a two-tailed Student's t test,
unless the data was non-normally distributed for which two-sided Mann-Whitney testing was
used. Differences between more than two groups were analyzed by one way-ANOVA with
Tukey correction for multiple testing, unless the data was non-normally distributed for which a
Kruskall-Wallis H test was used. Significance was assumed at P < 0.05. Error bars represent the
s.e.m. unless otherwise stated.

45
CHAPTER 3: SYNGAP1 FUNCTIONAL REGIONS: IMPLICATIONS IN NEURONAL
MATURATION
Introduction
Synaptic transmission is regulated by a complex biochemical machinery known as the
post-synaptic density (PSD) that comprises several proteins involved in synaptic plasticity,
including CaMKIIa, PSD-95, NMDA receptors, and SYNGAP1. SYNGAP1 has been shown to
play a role in the regulation of synaptic function and interacts with scaffolding proteins at the
PSD of excitatory neurons through the PDZ-binding motif (PBM) of the α1 isoform (Kim et al.,
1998; Walkup et al., 2016; Walkup et al., 2015). SYNGAP1’s GTPase activating domain shares
a significant homology with other RasGAPs, indicating that the critical amino acids for the
interaction with Ras and the consequent stimulation of Ras activity are conserved (Kim et al.,
1998; Scheffzek et al., 1997). However, it remains to be established whether SYNGAP1’s GAP
activity is directly involved in synaptic modifications in human cells. Heterozygous loss-offunction mutations in SYNGAP1 lead to intellectual disability (ID), often with comorbidities
such as epilepsy (Berryer et al., 2013; Mignot et al., 2016). Given its high expression within the
PSD of glutamatergic neurons, comprehending the molecular characteristics of SYNGAP1 is
essential for a deeper grasp of its role at the synapse and in neurodevelopmental disease
pathology. However, the underlying mechanisms and the SYNGAP1 critical motifs involved in
neuronal maturation in humans are yet to be fully understood.
One potential mechanism through which SYNGAP1 might impact neuronal maturation is
through activation of its RasGAP domain. Ras proteins are key molecular switches that are
thought to control various cellular processes, including cell growth, differentiation, and synaptic
plasticity (Agarwal et al., 2019). It has been suggested that the RasGAP domain in SYNGAP1

46
functions as a catalyst to accelerate the hydrolysis of GTP (guanosine triphosphate) to GDP
(guanosine diphosphate) in Ras proteins, leading to their inactivation (Kim et al., 1998; Walkup
et al., 2015). When Ras proteins are active (bound to GTP), they transmit signals that promote
cell growth and other signaling cascades. However, to maintain proper cellular balance, Ras
proteins need to be inactivated after their signaling tasks are completed. By enhancing the
conversion of GTP to GDP, the RasGAP domains efficiently turns off Ras protein signaling,
preventing prolonged and unchecked cell growth and signaling activities (Scheffzek et al., 1997)
. In the context of neuronal function and synaptic transmission, the RasGAP domain's activity in
SYNGAP1 would appear to be particularly important given how Ras signaling is known to be
involved in processes like synaptic development and maturation (Araki et al., 2015; Clement et
al., 2012; Zhu et al., 2002). However, recent evidence suggests that the RasGAP domain of
SYNGAP1 is not playing a significant role in synaptic plasticity and cognition in mice (Araki et
al., 2024). Conversely, recent evidence from our in vitro models implicating SYNGAP1 GAP
activity in cytoskeletal arrangement in radial glial cells, suggesting a role for SYNGAP1 during
early neurodevelopment (Birtele et al., 2023). Thus, we have set out to determine whether
SYNGAP1’s catalytic activity is involved in maturation of cultured human neurons.
Concurrently, the PBM within SYNGAP1 plays a vital role in shaping synaptic plasticity
by orchestrating intricate protein-protein interactions at the PSD. Of the four distinct C-terminal
(α1, α2, β, and γ) isoforms that are expressed, the most studied and characterized isoform
SYNGAP-α1 uniquely includes the PBM-containing C-terminus (Gou et al., 2020; Walkup et al.,
2016). By binding to PDZ domains of scaffolding proteins in the PSD, the PBM influences the
assembly of protein complexes critical for synaptic organization and function. These complexes,
in turn, determine the precise positioning of receptors, ion channels, and signaling molecules

47
essential for proper synaptic transmission and plasticity. Prior studies using mouse models with
point mutations in the PBM have revealed that its major function is to limit mobility of the α1
isoform in response to NMDAR activity, such that disrupting PBM function decreased the
threshold for NMDAR-signaling involved in synaptic plasticity (Kilinc et al., 2020; Zeng et al.,
2016). This deficit led to increased excitability of glutamatergic neurons, impaired cognitive
function, and lowered seizure threshold in the mice. Notably, while these findings have
significantly contributed to our understanding, there remains a critical gap in fully
comprehending SYNGAP1's effects in human cells. In this context, the novelty of our study lies
in our focus on investigating how SYNGAP1 exerts these impacts by dissecting its various
functional motifs in human-derived neurons. This research is particularly pivotal given that much
of the existing knowledge has stemmed from rodent models, underscoring the importance of
utilizing human induced pluripotent cells (iPSC) models to bridge this gap and attain a more
comprehensive understanding.
Here, we used iPSCs to address the role of SYNGAP1 RasGAP domain and PDZ-binding
motif in human glutamatergic and GABAergic neuronal maturation and functioning. We show
that the RasGAP domain is involved in the regulation of dendritic lengthening and spine
enlargement of human iPSC-derived glutamatergic and GABAergic neurons. Additionally, we
found that the PBM of the SYNGAP1 α1 isoform is involved in the dendritic and synaptic
maturation, albeit with a more pronounced effect on the bursting activity of glutamatergic
neurons.

48
Results
Generation of CRISPR/Cas9-edited Lines
To begin addressing the role of SYNGAP1 and its domain functions in neuronal
maturation, we used CRISPR/Cas9 genome engineering system to generate new lines. Firstly, we
targeted the RasGAP domain of a healthy control line (WT03231) to insert a homozygous R485P
mutation to generate a non-functional RasGAP domain (RasGAP Dead; Figure 1A). A novel
homozygous PDZ-ligand mutant line (ΔPDZ) was generated by Synthego in the WT03231 line
in which we replaced the PDZ-ligand sequence QRTV with QIRE (Fig.1B). Finally, to avoid
differences in phenotype due to genetic background effects, we generated a p.Q503X truncation
mutation in the WT03231 background (Patient 1 in WT03231; Fig. 1A, as described in Chapter
2). All lines created in house were karyotyped, Sanger sequenced and assayed for off-target
effects. The iPSC lines maintained expression of pluripotency markers OCT4 and SSEA4. To
study the impact of SYNGAP1 mutations on human glutamatergic neurons, we used forced
expression of Ngn2 and rtTA to convert iPSCs into induced glutamatergic neurons (GLUT-iNs)
and forced expression of ASC11/DLX2 to differentiate iPSCs into SST+ induced GABAergic
neurons (GABA-iNs) over a period of 9 days (as described in Chapter 2).

49
Lack of SYNGAP1 RasGAP Function Results in Enhanced Spine Enlargement in
Glutamatergic Neurons and Enhanced Spinogenesis in GABAergic Neurons
Given that our findings from Chapter 2 demonstrated that patient-derived SYNGAP1
mutations disrupted the maturation rate of dendrites and synapses of glutamatergic and
GABAergic neurons, we sought to investigate whether the RasGAP domain of SYNGAP1 plays
a role in the observed phenotypes. The RasGAP domain of SYNGAP1 was mutated at a residue
essential for its enzymatic function that eliminates its GAP catalytic rate and affinity for Ras.
Figure 1. Generation of Cell Lines. (A) A diagram of SYNGAP1 structure and the gene targeting scheme illustrating the
inactivation of the GAP region to generate the RasGAP dead (RGD) line. The underlined sequence indicates the guide used.
(B) Restriction-digest based genotyping of WT03231, RGD het, and RGD homo. (C) Sanger sequencing traces confirming
genotype, Arginine replaced with Proline. (D) A diagram of SYNGAP1 structure and the gene targeting scheme illustrating
the inactivation of PDZ-binding motif done by Synthego. The QTRV region was replaced with QIRE. (E) Synthego
sequencing traces. The site of double strand break induction is annotated by the vertical dashed line. The black arrow
indicates the base pair change, T>A.

50
Our tracing studies of the RasGAP Dead (RGD) GLUT-iNs revealed that the domain is not
involved in the development of new dendritic spines; however, a nonfunctional RasGAP domain
increases the dendritic length (463.1±94.83 , p=0.0039) and spine head width/neck width ratio
(HN-Index; 1.166(1.068), p=0.0005) when compared to control WT03231 GLUT-iNs
(115.1±19.25 and 0.6667(1.069), respectively; Fig. 2B, C). The RGD GLUT-iNs did not differ
significantly from the Patient 1 in WT03231 cells in these measures; however, the Patient 1 in
WT03231 cells did have significantly longer dendrites (720.1±147.3, p=0.0398), more spines
(0.5561±0.0718, p<0.0001), and a higher HN-Index (0.9960(0.8674), p=0.0.0043) than the
WT03231 (Fig. 2C). These results indicate that a nonfunctional RasGAP domain of SYNGAP1
is not a critical player in the formation of dendritic spines but is involved in the maturation of
spines in glutamatergic neurons.

51
Figure 2. Impact of RGD and ΔPDZ Mutation on Dendritic Spine Morphology of Excitatory Neurons. (A)
Representative confocal max intensity projection images of cultured GLUT-iNs at 21 DIV after GFP-transfection at 18DIV
from WT03231, Patient 1 in WT03231, RGD, and ΔPDZ lines. Scale bar, 50um. B-C, Quantification of spine density,
dendrite length and HN-Index in WT03231, Patient 1 in WT03231, RGD and ΔPDZ lines. (B) Individual non-filopodial
spines were plotted according to their length (um) and HN-Index for each line. (C) Left, The number of spines per 10um of
40-80um dendritic segments was significantly higher in Patient 1 in WT03231 (0.5561±0.0718, p<0.0001) but not in RGD
(0.3889±0.0753, p=0.2839) relevant to WT03231 (0.1959±0.0364). Middle, Dendrite length of Patient 1 in WT03231
(720.1±147.3, p=0.0398) and RGD (463.1±94.83 , p=0.0039) was significantly longer relevant to WT03231 (115.1±19.25).
Right, The HN-Index of non-filopodial spines was significantly higher in Patient 1 in WT03231 (0.9960(0.8674),
p=0.0.0043) and RGD (1.166(1.068), p=0.0005) relevant to WT03231 (0.6667(1.069)). Median (IQR). (D) Left, The
number of spines per 10um of 40-80um dendritic segments was significantly higher in ΔPDZ (2.461±0.4431) relevant to
WT03231 (p<0.0001) and Patient 1 in WT03231 (p=0.0005). Middle, Dendrite length of PDZ (407.5±61.07, p<0.0001) was
significantly longer than WT03231. Right, The HN-Index of mature spines was significantly higher in ΔPDZ (1.140(2.758),
p<0.0001) relevant to WT03231. For each cell line, 6 replicates were plated from at least three differentiations. mean + s.e.m.

52
We examined the dendritic morphology of GABA-iNs of the RGD, Patient 1 in
WT03231 and WT03231 GABA-iNs at 9 DIV by tracing dendrites of sparsely labeled GFP+
cells (Figure 3). Patient 1 in WT03231 (1.574±0.3519, p=0.0004) had more spines than
WT03231 (0.4247±0.0999) GABA-iNs while RGD (0.8816±0.1203) GABA-iNs did not show a
significant increase in spine density; however, Patient 1 in WT03231 cells (1.362(2.045)) had
significantly higher HN-Index than RGD (0.9468(1.502), p<0.0001) and control
(0.8522(0.9941), p<0.0001) GABA-iNs (Fig. 3C). There was a significant difference in total
dendritic fields between the cell lines such that dendritic fields were significantly larger in RGD
(33.55±4.549, p=0.0295) and Patient 1 in WT03231 (30.38±4.665, p=0.0061) GABA-iNs
relative to the WT03231 (17.03±1.531) GABA-iNs but were not significantly different from
each other (Fig. 3C). These data indicate that a nonfunctional RasGAP domain of SYNGAP1
results in cultures comprising larger GABAergic neurons with more spines, suggesting that the
RasGAP domain is involved in dendrite and spine growth, but does not play a significant role in
dendritic spine maturation of GABAergic neurons.

53
Figure 3. Impact of RGD and ΔPDZ Mutation on Dendritic Spine Morphology of Inhibitory Neurons.
(A)Representative confocal max intensity projection images of cultured GABA-iNs at 9 DIV after GFP-transfection at 6DIV
from WT03231, Patient 1 in WT03231, RGD, and ΔPDZ lines. Scale bar, 50um. B-C, Quantification of spine density and
HN-Index in Patient 1, Patient 1C, and insertion lines. (B) Individual non-filopodial spines were plotted according to their
length (um) and HN-Index for each line. (C) Left, The number of spines per 10um of 40-80um dendritic segments was
significantly higher in Patient 1 in WT03231 (1.574±0.3519, p=0.0004) but not in RGD (0.8816±0.1203) relevant to
WT03231 (0.4247±0.0999). Middle, Average dendritic length was significantly longer in Patient 1 in WT03231
(30.38±4.665, p=0.0061) and in RGD (33.55±4.549, p=0.0295) relevant to WT03231 (17.03±1.531). Right, The HN-Index
of non-filopodial spines was significantly higher in Patient 1 in WT03231 (1.362(2.045)) relevant to RGD (0.9468(1.502),
p<0.0001) and to WT03231 (0.8522(0.9941), p<0.0001). Median (IQR). (D) Left, The number of spines per 10um of 40-
80um dendritic segments was significantly higher in ΔPDZ (0.8325±0.1224, p=0.0042) relevant to WT03231. Middle,
Average dendritic length was significantly higher in ΔPDZ (39.12±4.738, p<0.0001) relevant to WT03231. Right, The HNIndex of mature spines was significantly higher in ΔPDZ (1.288(1.175),p<0.0001) relevant to WT03231. For each cell line, 6
replicates were plated from at least three differentiations. mean + s.e.m.

54
We then determined that the lack of function of the SYNGAP1 RasGAP domain
produced an effect on neuronal activity which indicated that the resulting dendritic spines were
abnormal and ultimately affected the electrical phenotype of glutamatergic neurons, suggesting
that the extant SYNGAP1 at the synapse is not
functional. We measured the electrical recordings
of RGD, WT03231 and Patient 1 in WT03231
GLUT-iNs on multielectrode arrays (MEAs). At 56
DIV, we observed a significant difference in firing
rates such that RGD (16.18±0.8219, p<0.0001)
and Patient 1 in WT03231 (18.66±2.918,p=0.0264)
GLUT-iNs had faster firing rates relative to
WT03231 GLUT-iNs (10.32±0.6106), but did not
differ from each other (Figure 4A). Then we
measured bursting activity and observed a
significant difference in bursts between the
genotypes where Patient 1 in WT03231 GLUT-iNs
(14.98±4.383) had more bursts per minute relevant
to RGD GLUT-iNs (4.097±0.8661, p=0.0267) and
WT03231 GLUT-iNs (3.622±0.2635, p=0.0120),
while RGD cells did not differ from controls (Fig.
4B). When comparing mean burst duration both
RGD (68.13±12.86, p=0.0061) and Patient 1 in
WT03231 (31.76±2.234, p=0.0046) cells had
Figure 4. RGD SYNGAP1 Mutation Alters
Neuronal Firing. A-D, Graphs represent mean firing
frequency, bursting rate, mean burst duration, and
percent of spikes in bursts from multielectrode array
recordings of WT03231, Patient 1 in WT03231, and
RGD GLUT-iNs at 56 DIV. (A) Mean firing
frequency of RGD (16.18±0.8219, p<0.0001) and
Patient 1 in WT03231 (18.66±2.918,p=0.0264) were
significantly higher relevant to
WT03231(10.32±0.6106) (B) Bursting rate of Patient
1 in WT03231 (14.98±4.383) were significantly
higher relevant to WT03231 (3.622±0.2635,
p=0.0120) and RGD (4.097±0.8661, p=0.0267). RGD
did not differ from WT03231 (p=0.6865). (C) Mean
burst duration of RGD (68.13±12.86, p=0.0061) and
Patient 1 in WT03231 (31.76±2.234, p=0.0046) were
significantly higher relevant to WT03231
(26.06±0.2399) (D) Percent of spikes in bursts of
RGD GLUT-iNs (7.478±1.773, p=0.0211) and Patient
1 in WT03231 (9.350±2.067, p<0.0001) were
significantly higher relevant to
WT03231(2.807±0.2420). For each cell line, at least
18 replicates were plated from at least three
differentiations. Violin plots show all data points, with
median and interquartile range.

55
significantly longer bursts than the control cells (26.06±0.2399) but did not differ significantly
from one another (Fig. 4C). Lastly, RGD (7.478±1.773, p=0.0211) and Patient 1 in WT03231
(9.350±2.067, p<0.0001) GABA-iNs had higher spikes in burst percentage than the control
GABA-iNs (2.807±0.2420; Fig. 4D). These data suggest that although GAP activity was not
playing a role in the development of new spines, it is influencing the maturation of spines and the
neuronal activity of cultured glutamatergic neurons.
SYNGAP1 PDZ-Ligand is Crucial for Spine Formation and Morphogenesis
Given the evidence for the essential role of SYNGAP1 PDZ-binding motif (PBM) for
Syngap1 function, we examined the dendritic morphogenesis of GLUT-iNs from the ΔPDZ
mutant line, the Patient 1 in WT03231 line and their isogenic control. Dendritic fields of ΔPDZ
(407.5±61.07, p<0.0001) GLUT-iNs were significantly larger than that of WT03231
(115.1±19.25) but did not differ significantly from Patient 1 in WT03231 GLUT-iNs (Figure
3D). Dendritic spine analysis revealed that ΔPDZ (2.461±0.4431, p<0.0001) GLUT-iNs had
significantly more spines relevant to Patient 1 in WT03231 (0.5561±0.0718, p<0.0001) and
WT03231 GLUT-iNs (0.1959±0.0364; Fig. 3D). The HN-Index of ΔPDZ (1.140(2.758),
p<0.0001) was significantly higher relevant to WT03231 GLUT-iNs (Fig. 3B,D). These data
indicate that an intact PBM of SYNGAP1 is necessary to slow down the widening of spine heads
as well as the formation of spines and the lengthening of dendrites.
We examined the dendritic morphogenesis of GABA-iNs of the ΔPDZ and WT03231
GABA-iNs. There was a significant difference in total dendritic fields between the cell lines such
that dendritic fields were significantly larger in ΔPDZ GABA-iNs (39.12±4.738, p<0.0001)
relative to the WT03231 GABA-iNs (17.03±1.531), but were not significantly different from that
of Patient 1 in WT03231 GABA-iNs (Fig. 4D). In line with the ΔPDZ GLUT-iNs findings, the

56
HN-Index of the spines increased in the ΔPDZ GABA-iNs (1.288(1.175),p<0.0001) relative to
the WT03231 GABA-iNs (0.8522(0.9941); Fig. 4 B,D). These data indicate that a nonfunctional
PBM of SYNGAP1 results in cultures comprising larger neurons with longer dendrites that have
more spines, as well as a shift towards wider spines in
GABAergic neurons.
To test whether changes in spinogenesis and
spine morphology translated into changes in neuronal
activity, we measured the electrical activity of ΔPDZ,
WT03231 and Patient 1 in WT03231 GLUT-iNs on
MEAs. At 56 DIV, we observed significant
differences in firing rates such that ΔPDZ
(14.96±0.6454, p<0.0001) GLUT-iNs had
substantially higher firing rates than WT03231
(10.32±0.6106) GLUT-iNs, but did not differ
significantly Patient 1 in WT03231 (Figure 5A).
Remarkably, the Patient 1 in WT03231 cells
(14.98±4.383) showed a substantial increase in burst
rate relevant to ΔPDZ (3.858±0.6357, p=0.0261) and
WT03231 (3.622±0.2635, p=0.0120; Fig. 5B). The
ΔPDZ (79.68±10.22, p<0.0001) GLUT-iNs showed a
significant increase in burst duration relevant to the
WT03231 (26.06±0.2399), however, ΔPDZ GLUTiNs had significantly longer (p<0.0001) bursts than
Figure 5. ΔPDZ SYNGAP1 Mutation Alters
Neuronal Firing And Bursting Activity. A-D,
Graphs represent mean firing frequency, bursting
rate, mean burst duration, and percent of spikes in
bursts from multielectrode array recordings of
WT03231, Patient 1 in WT03231, and ΔPDZ
GLUT-iNs at 56 DIV. (A) Mean firing frequency
of ΔPDZ (14.96±0.6454, p<0.0001) and Patient 1
in WT03231 (18.66±2.918,p=0.0264) were
significantly higher relevant to WT03231
(10.32+0.6106) (B) Bursting rate of Patient 1 in
WT03231 (14.98±4.383) was significantly higher
relevant to WT03231 (3.622±0.2635, p=0.0120)
and ΔPDZ (3.858±0.6357, p=0.0261). (C) Mean
burst duration of ΔPDZ (79.68±10.22, p<0.0001)
and Patient 1 in WT03231 (31.76±2.234,
p=0.0046) were significantly higher relevant to
WT03231 (26.06±0.2399). ΔPDZ had longer
bursts than Patient 1 in WT03231 (p<0.0001). (D)
Percent of spikes in bursts of ΔPDZ
(5.478±0.5298, p<0.0001) and Patient 1 in
WT03231 (9.350±2.067, p<0.0001) were
significantly higher relevant to WT03231
(2.807±0.2420). For each cell line, at least 18
replicates were plated from at least three
differentiations. Violin plots show all data points,
with median and interquartile range.

57
Patient 1 in WT03231 GLUT-iNs (31.76±2.234, p=0.0046; Fig. 5C). Percent of spikes in bursts
of ΔPDZ (5.478±0.5298, p<0.0001) GLUT-iNs was significantly higher than the WT03231 cells
(2.807±0.2420; Fig. 6D). We then determined that the lack of function of the SYNGAP1 PBM
produced a similar effect on neuronal activity observed for the Patient 1 in WT03231
haploinsufficient model, showing that PBM function is involved in neuronal activity but the
mechanisms by which it acts are likely to be at least partially distinct to that of the patientderived mutation given the differences observed in bursting rate and duration.
Discussion
We induced glutamatergic and GABAergic neurons from human iPSCs to investigate
whether certain SYNGAP1 functional regions play a role in neuronal maturation. This is an
important research question given that pathogenic SYNGAP1 variants result in a complex
neurodevelopmental disorder with varying degrees of severity and symptoms (Hamdan et al.,
2011; Vlaskamp et al., 2019). Using CRISPR/Cas9 technology, we generated human iPSC lines
from a healthy control that had either a disrupted endogenous RasGAP domain, PDZ-binding
motif of SYNGAP1 alpha1 isoform, or a patient-derived p.Q503X mutation. Supporting a lossof-function mechanism of disease, all models showed altered maturation of glutamatergic and
GABAergic neurons to some degree.
In the previous chapter, we had established that the p.Q503X truncation mutation resulted
in precocious spine formation and maturation, regardless of genetic background. In the current
study, we found that the RasGAP domain was not involved in the formation of new spines but
did, however, result in a more pronounced increase in the size of spine heads as well as increased
dendritic length. In comparison, the Patient 1 in WT03231 glutamatergic neurons displayed more
robust changes relevant to WT03231 cells, particularly in spine density and neuronal activity.

58
Indeed, electrical activity measurements further differentiated the effects of the RGD mutation
from the patient-derived haploinsufficiency. Although excitatory neurons from both mutation
lines were firing more and had more synchronized bursting, as exemplified by the increase in
spikes within bursts, Patient 1 in WT03231 cells exhibited more bursting activity. This suggests
that while the RasGAP domain’s enzymatic function might not be critical for spine
development, it does influence the maturation of spines and overall neuronal activity, albeit to a
lesser extent than a haploinsufficient model of SYNGAP1 function. Based on our observations,
we hypothesize that the HN-Index, indicative of spine size and maturity, is the primary driver
behind the enhanced neuronal activity observed in RGD glutamatergic neurons. This conclusion
is drawn in part from the findings discussed in Chapter 2, where c.3583-9G>A glutamatergic
neurons exhibited increased spine density without changes in HN-Index, and notably, these
alterations did not correlate with changes in neuronal activity. This contrast suggests that while
having more spines might affect certain aspects of synaptic networking, it is the maturity and
size of these spines that more significantly influence neuronal functional capabilities. The
relationships between dendritic spine density and neuronal activity is complex; however,
literature suggests that while increased spine density can enhance synaptic connectivity, it does
not necessarily correlate with higher functional neuronal activity unless accompanied by
sufficient synaptic maturation (Holtmaat & Svoboda, 2009). Moreover, the size and maturity of
spines, often associated with larger postsynaptic densities and more stable synaptic connections,
are crucial for the enhancement of synaptic efficacy and neuronal firing (Bourne & Harris,
2008). Therefore, the pronounced effects on neuronal activity in RGD neurons likely result from
changes in spine maturation, rather than merely an increase in spine number.

59
Similarly, a disrupted RasGAP domain and p.Q503X mutation in GABA-iNs showed
enhanced dendritic length, with the p.Q503X cells showing a significantly higher HN-Index than
RGD and control GABAergic neurons. Additionally, the RGD GABA-iNs did not show altered
spine density. It is possible that we had conducted dendritic spine analysis too early into their
development to detect differences in HN-Index, given how GABAergic neurons were only
cultured for 9 DIV whereas glutamatergic neurons were cultured for 21 DIV. The timing of spine
analysis could also explain why we did not observe differences in spine density of glutamatergic
neurons; thus, it will be of considerable interest to run a time-course analysis on spine
development and maturation in both neuronal populations. It is important to note, however, that
our iPSC-derived models represent neurons that have been directed into their neuronal identity
using transcription factors, bypassing the neural progenitor phase. Notably, the glutamatergic
neurons develop more slowly than the GABAergic neurons such that GABA-iNs typically
develop their processes and spines within 7 DIV, whereas GLUT-iNs require at least 21DIV to
form synapses. This discrepancy in developmental timelines informed our decision to choose
specific timepoints for our analyses. However, we recognize that this difference in maturation
rates introduces a significant variable when interpreting the impact of SYNGAP1 mutations on
neuronal maturation. The observed changes might not solely reflect the direct role of RasGAP
activity but could also be indicative of SYNGAP1 exerting an influence earlier in the neuronal
development process, which provides a possible explanation for why our findings contrast with
the RGD mouse models used in the Araki et al (2024) study.
On the other hand, a nonfunctional PBM of SYNGAP1 resulted in a much more robust
cellular phenotype. By examining excitatory and GABAergic neurons from ΔPDZ and Patient 1
in WT03231 lines, we found significant alterations in dendritic architecture and spine

60
morphology. Specifically, ΔPDZ glutamatergic neurons exhibited enlarged dendritic fields, an
increased number of dendritic spines, and an elevated HN-Index relative to controls, indicating
that a functional PBM is essential for moderating dendrite and spine development. Similar
patterns were observed in cultured GABAergic neurons, underscoring the role of the PBM across
neuronal types. Moreover, we observed that these morphological changes in glutamatergic
neurons were accompanied by pronounced alterations in neuronal activity such that they were
firing more often, and their firing was becoming more synchronized. Notably, the bursts in
ΔPDZ glutamatergic neurons were much longer than the control and p.Q503X truncation
mutation cells, while the bursting rate of p.Q503X cells showed an increase relative to ΔPDZ and
control cells. This suggests that the SYNGAP1 PBM not only contributes to the structural
development of neurons but also to their functional activity, with distinct mechanisms possibly
underlying the observed differences in neuronal behavior between ΔPDZ mutation and patientderived mutation.
Our findings contribute uniquely to the existing literature on SYNGAP1, particularly
regarding the role of its functional regions in neuronal maturation and development. Prior
research has primarily emphasized the significance of the RasGAP domain in the developmental
effects of SYNGAP1 mutations, and our work suggests that, at least in human neurons, the
RasGAP domain’s is playing a role in neuronal development and maturation (Kim et al., 1998;
Vazquez et al., 2004). This aligns with recent evidence from a collaborative study in which we
demonstrated that SYNGAP1 is expressed within the apical domain of human radial glial cells
(hRGCs) in a cortical organoid model (Birtele et al., 2023). The findings from that study suggest
that the RasGAP domain might regulate cytoskeletal organization of hRGCs. This is in contrast
with a recent study that reported mouse models with a heterozygous GAP mutation did not

61
exhibit abnormal behavior and did not show altered LTP in CA1 of the hippocampus (Araki et
al., 2024). Their homozygous GAP mutant mice were viable and had normal LTP and behavior
as well. Additionally, their data showed that the GAP-dependent signaling functions of Syngap1
are involved in spine size changes during LTP, but does not affect AMPA receptor content in
synapses in vivo. Our multielectrode array (MEA) findings in the RGD lines offer further insight
into this complex narrative by demonstrating that SYNGAP1s RasGAP domain, while not
crucial for spine formation in glutamatergic neurons, does play a role in spine enlargement and
the modulation of network activity. Given that our in vitro models are more reflective of
neurodevelopment, our findings highlight that SYNGAP1’s catalytic activity may have a more
pronounced role during the early stages of neurodevelopment.
In contrast, our ΔPDZ findings corroborate current literature emphasizing the
significance of the PDZ-binding motif in synaptic function and neuron maturation, underlining
the multifunctional nature of SYNGAP1 (Kilinc et al., 2020; Vazquez et al., 2004). The
pronounced cellular phenotypes resulting from a disrupted PBM in both excitatory and inhibitory
neurons underscore the motif’s essential role in regulating dendritic and spine development.
Prior rodent studies have demonstrated that the a1 isoform is a negative regulator of excitatory
synapse structure and function through its association with PDZ domains of PSD-95 and the
docking of AMPARs within the PSD independently from its RasGAP function (Araki et al.,
2020; Araki et al., 2015; Rumbaugh et al., 2006; Vazquez et al., 2004; Walkup et al., 2015;
Wang et al., 2013). Thus, it helps regulate the size and strength of synapses. Evidence has
indicated that phosphorylation of Syngap1 results in ‘dispersion’ of Syngap1 away from the PSD
and consequently activates Ras, induces LTP, and increases spine size (Araki et al., 2015). Spine
size and synaptic strength are significantly correlated and as such, it is not surprising that

62
Syngap-PDZ interactions have been found to be necessary for synaptic transmission in cultured
primary neurons (Rumbaugh et al., 2006). Similarly, our MEA results in ΔPDZ cells provide
human-based evidence for the critical role of SYNGAP1 in modulating neuronal activity,
illustrating that disruptions in the PBM lead to significant alterations in neuronal firing patterns
and synchronization. These findings reinforce the importance of SYNGAP1-PDZ interactions in
maintaining balanced neuronal communication, contributing to extant literature supporting the
theory that SYNGAP1’s interactions within synaptic complexes are crucial for the regulation of
synaptic and neuronal activity.
Altogether, these data further support the notion that SYNGAP1 is a dominant driver of
neuronal maturation, which is in line with the broader SYNGAP1 literature. This work has
contributed to our understanding of how specific functional motifs of SYNGAP1 influence
maturation in both human glutamatergic and GABAergic neurons. By utilizing CRISPR/Cas9
technology to model SYNGAP1 mutations in human iPSC-derived neurons, this research
highlights the complex role of SYNGAP1 in neuronal development and the pathophysiology of
related neurodevelopmental disorders. We have demonstrated that while RasGAP activity may
not be essential for the development of new spines, it influences spine size changes and dendritic
length, while we observed more pronounced effects in the presence of a disrupted PDZ-binding
motif. These findings suggest that the functional diversity of SYNGAP1’s critical motifs plays a
complex role in neuronal development and maturation. Our results underscore the complexity of
SYNGAP1’s functions across different models and developmental stages, pointing to the
importance of context in evaluating the impacts of genetic mutations on neuronal development.
Looking ahead, addressing the limitations identified in our study, such as the need for a more
extended time-course analysis and a more thorough examination of synaptic structures, will be

63
crucial. The timing of our dendritic spine analysis, particularly for GABAergic neurons, may
have precluded the detection of significant differences in spine density and morphology. Future
work in our lab will aim to incorporate a broader range of analytical techniques, including patchclamp recordings to assess synaptic activity more comprehensively. As well, we plan to explore
GABAergic neuron functionality further through calcium imaging and MEA co-cultures with
glutamatergic neurons. These approaches will not only enhance our understanding of
SYNGAP1’s role in neurodevelopment but also contribute to a more nuanced comprehension of
the molecular mechanisms underlying neurodevelopmental disorders.
Methods
Cell Lines, Cell Culture and Neural Differentiation
The iPSC lines were generated using Yamanaka factors in patient-derived PBMCs, as
previously described (17). hiPSC lines were maintained with mTeSR plus (STEMCELL
Technologies #100-0275) media changes every other day on 1:200 geltrex (GIBCO, #A1413301)
coated tissue culture 6-well plates (Genesee Scientific #25-105) and passaged using ReLeSR
(STEMCELL Technologies #05872). Cells were maintained below passage 50 and periodically
karyotyped via the G-banding Karyotype Service at Children’s Hospital Los Angeles.
CRISPR/Cas9-edited iPSC Line Generation
A SYNGAP1 patient provided venous blood samples for genomic DNA analysis and iPSC
generation. Patient 1 was found to have a nonsense (c.1507C>T;p.Q503) mutation, which was
corrected through the CRISPR/Cas9 gene engineering as described in Chapter 2. To account for
the contribution of the patient’s genetic background to the neuronal phenotypes, Patient 1
mutation was inserted into 03231 control (WT03231) iPSC line derived from a healthy 56-yearold male (Patient 1 in WT03231; as described in Chapter 2).

64
To investigate the role of RASGAP activity and PDZ-ligand protein interaction on
SYNGAP1 pathology, two lines were generated in the 03231 control iPSC background,
RASGAP dead (RGD) and ΔPDZ-ligand mutant.
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). The sgRNA and
an HDR template to introduce the R485P RasGAP-dead mutation, were nucleofected in the
03231 control iPSC line derived from a healthy 56-year-old male. Individual iPSC colonies were
transferred to 24 well plates and subsequently underwent restriction enzyme-based genotyping.
Positive colonies were subsequently confirmed via Sanger sequencing.
HDR 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.
PDZ-ligand Mutant Line. iPSC from 03231 control line were sent to Synthego for
CRISPR editing services. There, a chemically modified synthetic sgRNA targeting the PDZbinding motif of SYNGAP1 was complexed with the spCas9 to form a ribonucleoprotein. This,
and an HDR template to replace the PDZ-ligand QRTV sequence with QIRE, were nucleofected
in the 03231 control iPSC line. Individual iPSC colonies confirmed via Sanger sequencing and
shipped by Synthego.
HDR used:
CCTTTTTGGTGTCTTGCAGGAGAGGCAGCTTCCCCCCTTGGGTCCAACAAATCCGCG
AGTGACGCTGGCCCCACCGTGGAATGGCCTGGCCCCCCCAGCCCCACCACCC

65
Neural Differentiation
Glutamatergic and GABAergic induced neurons were generated from each of the iPSC
lines as described in Chapter 2. Briefly, iPSCs were infected with lentivirus plasmids that
express NGN2 and rtTA to create inducible glutamatergic neurons (GLUT-iNs). To generate
inducible GABAergic neurons (GABA-iNs), iPSCs were infected with lentivirus plasmids that
express ASCL1/DLX2.
Biochemistry
Immunoprecipitation, Western Blot and immunofluorescence protocols were carried out
as described in Chapter 2.
Dendritic Spine Analysis
Excitatory and inhibitory neurons will be cultured in monocultures and assayed at 21
DIV. For morphological analysis neurons will be transfected with GFP (pSinEGFP##) and
spines co-visualized with anti-Synaptophysin (Cell Signaling #9020S), anti-GFP (Aves Labs
#GFP-1010), and anti-PSD95 (NeuroMab #75-028) antibodies. For each assay, morphological
analyses of dendritic arborization and dendritic spines were performed by manual 3D
reconstruction using Nikon NIS Element software. Dendritic length were obtained by tracing
dendrites of a neuron starting about 50 µm away from the soma, a distance where spines are
abundant, until the dendrite is cut off or at 15 µm from the terminus, an area where spine density
tapers off. Spine counts were obtained by manually counting dendritic spines along the traced
dendrites. Spine density were assayed as the spine count divided by the length of the traced
dendrite. To measure volumetric parameters, the head width was defined as the average length of
the head that is perpendicular to the neck of the spine. Images were acquired on a Nikon A1R
HD microscope. All assays were performed in three independent differentiations using 3

66
replicate assays per differentiation. Data was gathered by an individual blinded to the
experimental conditions.
Multielectrode array recordings
iPSC-derived glutamatergic neurons were co-cultured with primary murine astrocytes
and plated onto six-well multielectrode array (MEA) chips (nine electrodes and one ground per
well) coated with poly-L-ornithine and laminin as described in Chapter 2. To study the inhibitory
effect of GABAergic neurons derived from the different iPSC lines, WT03231 GLUT-iNs were
co cultured with GABA-iNs on MEAs. Spontaneous network activity was recorded over the
course of 8 weeks. Cells were allowed to acclimate for 5 min after chips were placed into the
MEA amplifier before beginning 7min recordings. Active electrodes were defined as those that
averaged more than 5 spikes per minute. Active wells were defined as well that had more than
30% active electrodes. All wells that did not meet these criteria were discarded. The threshold
for spike detection was determined as -20uV. Mean spike frequency (Hz) and bursts per second
were determined using the accompanying MC Rack software.
Data Analysis
Analysis was performed with the statistical software package Prism Origin (GraphPad
Software). Differences between two groups were analyzed using a two-tailed Student's t test,
unless the data was non-normally distributed for which two-sided Mann-Whitney testing was
used. Differences between more than two groups were analyzed by one way-ANOVA with
Tukey correction for multiple testing. Significance was assumed at P < 0.05. Error bars represent
the s.e.m. unless otherwise stated.

67
CHAPTER 4: CONCLUSION
General Discussion
Mutations in genes that encode synaptic proteins have long been implicated in the
phenotypic manifestation of intellectual disability (ID) and other comorbid neurodevelopmental
disorders such as epilepsy, global developmental delay, and autism(Mignot et al., 2016;
Vlaskamp et al., 2019). Recent advances in genomic and transcriptomic techniques continue to
reveal more de novo dominant mutations that lead to functional loss of one copy of the gene, one
of which is SYNGAP1. The resulting haploinsufficiency of SYNGAP1 mutations has been
reported to be one of the most common causes for nonsyndromic ID, with a prevalence of up to
2-4%(Mignot et al., 2016). Understanding the genetic and molecular basis of ID remains a major
challenge with direct relevance to the development of therapeutic strategies aimed at patient
symptomology.
Previous research has established SYNGAP1’s role in regulating neuronal development
and plasticity, with more recent publications highlighting the importance of SYNGAP1 in
cortical inhibitory interneurons(Berryer et al., 2016; Clement et al., 2012; Kim et al., 2003; Su et
al., 2019). Most of this work, presented in detail in the introduction, includes studies that have
greatly contributed to our understanding of the molecular signaling cascades regulated by
SYNGAP1. These studies have also shown that Syngap1 expression rises during postnatal
development in rodent neurons and regulates the maturation rate of excitatory synapse strength,
independently from its role in plasticity(Clement et al., 2012; Gou et al., 2020). Furthermore, a
growing body of this work has begun to investigate the neurophysiological properties in human
models of SYNGAP1 haploinsufficiency(Llamosas et al., 2020). This is of great importance
given the fundamental differences in how human and rodent brains develop. Namely, the rate at

68
which neurons develop in human brains is much slower than that of rodent brains(Charrier et al.,
2012). Recent studies using human induced pluripotent stem cell (iPSC) models have found that
SYNGAP1 also regulates the postmitotic maturation of human neurons, influencing the
development of neural networks(Llamosas et al., 2020). However, there remains a gap in the
literature addressing how specific SYNGAP1 mutations found in humans lead to disease, given
how most of the studies utilize heterozygous KO rodents and iPSC-derived neurons.
While knockout Syngap1 models have surely begun to disentangle the very complex role
that SYNGAP1 protein plays in the postsynaptic density of glutamatergic neurons, we have yet
to fully understand how patient-specific mutations alter neurodevelopment. In the preparation of
this dissertation, an article was published on the investigation of knock-in mouse models with
pathogenic Syngap1 variants found in people with ID(Araki et al., 2023b). In that study, they
were able to recapitulate phenotypic features of previous KO rodent models, including the
haploinsufficiency and behavioral abnormalities, with the added relevance of human disease
pathogenesis.
Examining the Role of Patient-Specific Mutation on Cellular Phenotypes
In this work, we have studied whether and to what extent patient-derived SYNGAP1
haploinsufficiency in glutamatergic and GABAergic neurons contributes to cellular
abnormalities. We used iPSCs from two patients (Patient 1 and Patient 3) that had different
SYNGAP1 mutations. Patient 1 has a truncation mutation in the RasGAP domain, p.Q503X,
while Patient 3 had a splicing site mutation, c. 3583-9G>A, which also happens to be one of the
patient-derived mutations studied in the Araki article. To directly investigate the relationship
between patient-derived mutations and neuronal phenotypes, we utilized CRISPR/Cas9
technology to create isogenic corrected control iPSCs for two patient lines. For our studies, we

69
have decided to use the forced expression of neurogenin-2 (NGN2) resulting in glutamatergic
induced neurons (GLUT-iNs). Likewise, we use the forced expression of ASC11/DLx2 that
results in GABAergic neurons. Neurons made using these methods have previously served as
particularly useful models in analyzing neuronal function and connectivity(Zhang et al., 2013).
In our hands, both patient lines resulted in GABAergic and glutamatergic neurons that
had enhanced dendritic spine density compared to their isogenic controls; however, when
comparing the two patient lines to each other it was clear that the truncation mutation of Patient
1 had a more robust effect. However, the two patient mutations had different effects on the
morphological parameters of individual spines in which the Patient 1 p.Q503X mutation resulted
in the enlargement of spine heads, indicative of increased spine maturity, while the Patient 3 c.
3583-9G>A mutation had no effect on this measure. This effect on spine size proved to be
consistent with increased distributed network spiking activity in the p.Q503X line. Network
bursting is largely driven by increased functional synaptic connectivity; thus, our results indicate
that the rate at which Patient 1 excitatory neurons are maturing is greater than that of Patient 3
neurons(Nehme et al., 2018). Increased functional connectivity in p.Q503X networks driven by
dendrites with more spines that are also more enlarged may contribute to the precocious onset of
synchronized network bursting observed in our MEA experiments. These data further strengthen
the conclusion that SYNGAP1 haploinsufficiency drives effects on neuronal activity, and that
the observed changes in neuronal activity are largely driven by spine maturity. Additionally,
given how patients with SYNGAP1 mutations display seizures and hyperactivity, the idea of
network hyperexcitability can provide a possible explanation for such symptomology. Even so,
while these findings are intriguing, we had to account for possible genetic background effects.

70
To do so, we utilized CRISPR/Cas9 technology to insert the Patient 1 p.Q503X mutation
into the background of a healthy control line, WT03231, and found there were no general genetic
background effects on morphological and electrical phenotypes. To further discard the possibility
that Patient 3 background was involved in the phenotype or provided some level of “protection”
against SYNGAP1 mutations, we inserted the Patient 1 p.Q503X mutation into the corrected
background of Patient 3. While we were unable to successfully generate a line with the Patient 3
c.3583-9G>A mutation inserted into the corrected background of Patient 1, we did have a
repertoire of iPSC lines from patients that also exhibited the same c.3583-9G>A splicing site
mutation, Patient 10 and 14. Nevertheless, our findings indicate that genetic background was not
playing a significant role in the cellular phenotypes we had observed. The findings from the
Patient 1 in Patient 3C excitatory neurons in particular support the idea that the milder phenotype
presented by the Patient 3 neurons is not a result of genetic background factors. If that had been
the case, we would likely have observed a decrease in neuronal activity of the swap line in
comparison to the Patient 1 line. Conversely, we were able to show that the Patient 1 p.Q503X
mutation was penetrative enough to overcome any potential genetic background effects of the
Patient 3 line. As well, the Patient 10 and 14 lines further support that sentiment given how their
cellular phenotypes were similar to that of Patient 3 in both excitatory and inhibitory neurons.
Dissecting the Role of SYNGAP1 Functional Domains in Cellular Phenotypes
The second part of this dissertation utilized CRISPR/Cas9 technology to genetically alter
two important functional domains of the SYNGAP1 protein: the RasGAP catalytic domain and
the SYNGAP1 a1-specific PDZ-binding motif. Firstly, we were interested in examining the
pathophysiology associated with a homozygous inactivation of the RasGAP domain. The role of
Ras/Rap signaling in long-term potentiation (LTP) has long been evidenced in heterozygous

71
rodent and cell culture studies; however, the relationship between SYNGAP1 and Ras in the
context of neuronal maturation and network signaling remains unclear(Berryer et al., 2013;
Komiyama et al., 2002; Krapivinsky et al., 2004; Rumbaugh et al., 2006). Therefore, we sought
to test if an inactivated RasGAP domain would recapitulate the cellular phenotypes observed in
our haploinsufficient models.
In our hands, this RasGAP dead (RGD) model led to an enlargement of spine heads and
lengthened dendritic processes in both neuronal subtypes; however, we did not observe any
changes in spine density for either neuronal type. These results were in line with data from
previous work where we show that human brain organoids derived from our RGD cell line
showed disrupted apico-basal polarity and a reduced central tight junction protein-positive
luminal space of radial glial cells, indicating a marked impairment in the cytoskeletal
architecture of apical endfeet (Birtele et al., 2023). They also found that they were unable to
thoroughly characterize RGD organoids at later stages of development because the mutation led
to a loss of 90% of the organoids at around the 2-month mark. However, our present work
contrasts with results from a recent publication using hippocampal slices from Syngap1 GAP
mutant mice showing that GAP-dependent signaling is not required for synaptic plasticity and
several cognitive behaviors(Araki et al., 2024). Our work provides further evidence for the
conclusion that the GAP-dependent signaling functions of SYNGAP1 are important for spine
size changes, and consequently influence the maturation of dendritic spines. Furthermore, these
alterations in spine maturation that lead to changes in network firing activity suggest that GAPdependent signaling has an impact on the excitability and firing patterns of glutamatergic
neurons but might not directly influence the mechanisms underlying synchronized bursting
activity. Specifically, calcium channels are known to contribute to the generation of burst firing

72
in neurons given how they can support low-threshold calcium spikes that, in turn, trigger bursts
of action potentials(Beurrier et al., 2000). Conversely, voltage-gated sodium and potassium
channels are critical for the initiation and propagation of action potentials, and the repolarization
of membrane potential following a spike, respectively(Armstrong & Hille, 1998; Harnett et al.,
2013). As such, it is possible that SYNGAP1 protein without a functional RasGAP domain
would
Lastly, we utilized an iPSC line generated in the WT03231 line that has an inactivated
PDZ-binding motif (ΔPDZ) of the SYNGAP1 α1 isoform. SYNGAP1 is expressed in multiple
isoforms, as discussed in Chapter 1, which have different functions and affect neuronal
physiology in different ways. The best characterized of these is the α1 isoform, which has been
found to uniquely express a PDZ-binding motif (PBM) that allows SYNGAP1 to interact with
scaffolding proteins at the postsynaptic density, regulating postsynaptic structure organization
and function(Araki et al., 2015; Kim et al., 1998; Vazquez et al., 2004). We found that the PBM
of SYNGAP1 is necessary for the regulation of dendritic growth, spinogenesis, and spine
maturation of glutamatergic and GABAergic neurons. Moreover, we observed that the
morphological changes in dendritic spines of glutamatergic neurons translated into enhanced
neuronal activity. Additionally, the cellular phenotypes resulting from the ΔPDZ neurons were
more robust than those observed in the RGD and Patient 1 p.Q503X insertion neurons, given that
all dendritic spine measures were impacted by an inactivated PBM whereas RGD neurons
showed lengthened dendritic processes and enlarged spines. Altogether, our findings highlight
the importance of an intact PBM and RasGAP domain in early stages of neurodevelopment.

73
Limitations and Future Directions
We would like to note that although we were not able to generate the Patient 3 in Patient
1C line in time for these experiments, we have recently altered our CRISPR/Cas9 design and
successfully created the new swap line, which will be included in the submission of a publication
resulting from these findings. We would also like to recognize that the comparisons of Patient 10
and 14 were done against control lines that did not share their genetic background, however we
have recently generated CRISPR/Cas9- corrected isogenic controls and plan on conducting
similar experiments to provide further evidence for this argument. Additionally, while we
provided dendritic morphology data from investigations on GABAergic neurons, we have yet to
assess mutation effects on the function of these neurons. At present, we are exploring a coculture system on MEAs in which we plate excitatory and inhibitory neurons to study how
mutation-carrying GABAergic cells impact the network activity of excitatory neurons. As well,
we are exploring the use of calcium imaging of GABAergic neurons as an additional method to
study the functionality of the cells, given the central role that calcium signaling plays in nearly
every cellular task(Islam, 2020). These additional assays will address the limitations of the
current study and will be crucial in strengthening our conclusions.
Absolute abundances of SYNGAP1 isoforms are unclear, and their expression might
provide another possible explanation for the differences we observed in our in vitro models. As
such, we have prepared a targeted mass spectrometry method that utilizes XX peptides which
will allow us to quantify the absolute expression of total SYNGAP1 and its isoforms in different
cell types. At present, we are finalizing the parameters of this method with our collaborators and
plan on processing lysates from all cell lines utilized in this dissertation. The resulting proteomic
data will also be included in the submitted publications that will result from this body of work.

74
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Abstract (if available)

Abstract SYNGAP1 is a critical gene implicated in the development of intellectual disability and plays a pivotal role in synaptic function and activity. In Chapter 1, we review the current state of the literature regarding SYNGAP1 mutations and their effects on neuronal subtypes. In Chapters 2-3, data is presented from two studies involving the use of human iPSCs to study the impact of SYNGAP1 mutations and SYNGAP1 critical motifs on the function of glutamatergic and GABAergic neurons. In Chapter 4, we discuss the implications and future directions of the data collected in this dissertation. Altogether, the work in this dissertation fills a significant gap in the literature regarding how SYNGAP1 mutations lead to the observed experimental phenotypes in patient-derived cells. Overall, the data suggest that SYNGAP1 mutations can differentially alter the maturation rate and SYNGAP1 total protein expression of both glutamatergic and GABAergic neurons, consequently impacting their network activity. Additionally, the data show that while the RasGAP domain of the SYNGAP1 protein is not involved in spinogenesis, it is needed for regulation of spine maturation and dendritic growth, subsequently enhancing neuronal activity. Lastly, we show the PDZ-binding motif of SYNGAP1 is necessary for the regulation of dendritic growth, spinogenesis and spine maturation, consequently enhancing neuronal activity. This dissertation provides valuable insights into how SYNGAP1 patient mutations affect neuronal development and activity, while also highlighting the differential roles of the RasGAP domain and PDZ-binding motif in phenotypic differences.

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Asset Metadata

Creator Flores, Ilse (author)

Core Title Elucidating neurodevelopmental consequences of syngap1 mutations and inactivated functional regions in human iPSC-derived neurons

School College of Letters, Arts and Sciences

Degree Doctor of Philosophy

Degree Program Neuroscience

Degree Conferral Date 2024-05

Publication Date 04/30/2024

Defense Date 04/17/2024

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

Tag dendritic spine morphology,intellectual disability,iPSC,neurodevelopment,neurons,OAI-PMH Harvest,rasgap,SynGAP1

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Quadrato, Giorgia (committee chair), Coba, Marcelo (committee member), Hirsch, Judith (committee member)

Creator Email ilse.flores3@gmail.com,ilseflor@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113911989

Unique identifier UC113911989

Identifier etd-FloresIlse-12866.pdf (filename)

Legacy Identifier etd-FloresIlse-12866

Document Type Dissertation

Format theses (aat)

Rights Flores, Ilse

Internet Media Type application/pdf

Type texts

Source 20240503-usctheses-batch-1146 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright.

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA

Repository Email cisadmin@lib.usc.edu