Scalable and Systematic Neurobiology of Psychiatric and Neurodevelopmental Disorder Risk Genes

Team:

Daniel Geschwind, U.C. Los Angeles
Bennett Novitch, U.C. Los Angeles
Daniel Aharoni, U.C. Los Angeles
Aparna Bhaduri, U.C. Los Angeles
Robert Damoiseaux, U.C. Los Angeles
Peyman Golshani, U.C. Los Angeles
Kitai Kim, U.C. Los Angeles
Chongyuan Luo, U.C. Los Angeles
Michael Wells, U.C. Los Angeles

Abstract:

Human genetic studies have identified hundreds of genes contributing to Neuropsychiatric and Neurodevelopmental Disease (NPD) risk. But for most genes, their normal function or the consequences of their absence or reduction on neurodevelopment and neural function are not known. Here, we propose to address the substantial challenges of discerning potential functions of hundreds of NPD genes through the development of a High Throughput Neuropsychiatric Disease Phenotyping Center (UCLA HT-NPC), driven by the activity of 9 highly collaborative investigators (Aharoni, Bhaduri, Damoiseaux, Geschwind, Golshani, Kitai, Luo, Novich, and Wells) and two substantial core facilities (UCLA Molecular Screening Shared Resource and the Human Stem Cell and Genome Engineering Center). Through a tiered approach, we combine high throughput and high value, quantitative phenotyping with stem cell engineering to characterize the functional consequences of NPD gene knockouts (null alleles), a key initial step that will inform our understanding of disease pathways. In the first step, we will rapidly generate null alleles for 250 genes chosen by the Consortium using a rapid, high throughput lentiviral based system in hESCs. Viability and neural induction potential will be assessed, and quantitative phenotyping conducted using RNA-seq on all lines. Those genes passing viability and neural induction tests will be used in the production of clonal null hiPSC lines (male and female) for downstream phenotyping and wider distribution to the community. Subsequently, we will perform high throughput, quantitative, multi-scale phenotyping at the molecular, morphological, and physiological levels in both 2D and 3D hiPSC-based models of human cortical development. We leverage the relative strengths and scalability of each model to enable us to perform both snRNA and bulk RNA-seq, measure the maturation, morphology, and synaptic density of neural cells using automated imaging, including the multiplexed, protein-based CODEX (Phenocycler) platform, and characterize neuronal activity and synchronization through optical recordings using custom-built mini-scope arrays (STIMscope). By using multiple systems (e.g., hESC/hiPSC; gene editing, 2D and 3D cultures), we test biological reproducibility across systems and technical reproducibility through replication. The use of experimentally validated, quantitative phenotypes across multiple scales of analysis facilitates data sharing and comparisons with other SSPsyGene investigators and

Team:

Zhiping Pang, Rutgers U
Jubao Duan, NorthShore U. HealthSystem
Jennifer Mulle, Rutgers U
Ronald Hart, Rutgers U
Xin He, U. Chicago
Wei Vivian Li, Rutgers U
Carlos Pato, Rutgers U.
Alan Sanders, NorthShore U. HealthSystem
Andreas Tolias, Baylor Coll Medicine
Siwei Zhang, NorthShore U. HealthSystem

Abstract:

In the past decade, the scientific community has witnessed accelerated genetic discoveries for neurodevelopmental and psychiatric disorders (NPD) such as schizophrenia (SZ), autism spectrum disorder (ASD), bipolar disorder, and major depression. Genome-wide association studies (GWAS) and whole-exome sequencing (WES) have identified a mounting number of NPD risk genes. However, translating these exciting genetic discoveries into clinically actionable biology has been impeded by our limited knowledge of gene function and related disease mechanisms. A bottleneck in the field is that most biological characterization has focused on very few NPD genes, which have not necessarily been selected for study based on pathophysiological importance. Furthermore, genes are often studied one at a time, hindering the pace of our understanding of disease mechanisms. We propose an alternative strategy: large-scale, unbiased, parallel study of NPD genes in disease-relevant model systems, in response to the RFA-MH-22-111 (Scalable and Systematic Neurobiology of Psychiatric and Neurodevelopmental Disorder Risk Genes-SSPsyGene). We propose to establish the Assay and Data Generation Center (ADGC) for the Model of induced pluripotent stem cell (iPSC)-derived Neurons for NPD (MiNND), where we will implement and optimize novel scalable and systematic assays for interrogating the molecular and neurobiological functions of up to 200 NPD risk genes. Teaming up with the SSPsyGene Consortium and leveraging our team’s respective expertise in stem cell biology, functional genomics, neuroscience, and functional analysis, our MiNND-ADGC will generate loss-of-function (LoF) iPSC human neural models and perform high-content morphometric and single-cell transcriptomic (scRNA-seq) analyses of NPD LoF alleles. We will also assay synaptic functions using optical sensors in a high-throughput fashion and carry out multimodal PatchSeq analyses and modeling to predict neuronal properties from scRNA-seq data. Finally, working with the SSPsyGene Consortium, we will conduct data integration, curation, and dissemination to the research community and public for further analysis. Our MiNND-ADGC will build a valuable resource and integrated knowledge base that will provide a fertile foundation for future studies of disease mechanisms. The data from studying the selected NPD risk genes on multiple genetic backgrounds, including the understudied African American iPSC lines, will enable robust inferences of potential cross-disorder and cross-population biological convergence and divergence relevant to NPD.

Team:

Ellen Hoffman, Yale U.
Kristen Brennand, Yale U
Rong Fan, Yale U
Laura Huckins, Yale U
Zuoheng Anita Wang, Yale U

Abstract:

There is a critical need to develop high-throughput scalable assays to identify biological mechanisms underlying risk genes in neurodevelopmental and neuropsychiatric disorders (NPD). In this proposal, we aim to leverage the unique advantages of two scalable systems – human induced pluripotent stem cells (hiPSCs) and zebrafish – to perform parallel functional assays of NPD genes in vitro and in vivo, and to pilot the development of innovative spatial multi-omics technologies applicable across systems. We propose to establish an Assay and Data Generation Center (ADGC) as part of the SSPsyGene Consortium that capitalizes on the unique and complementary expertise of our labs in large-scale hiPSC CRISPR screens (Brennand), high-throughput zebrafish screens (Hoffman), and cutting-edge multi-omics tool development (Fan). Our goal is to gain novel insights into the convergent and divergent mechanisms by which diverse NPD gene loss of function affects neurodevelopment at the molecular, cellular, structural, circuit, and behavioral levels. We propose to screen 250 NPD genes using a tiered strategy in hiPSCs and zebrafish by conducting pooled and arrayed transcriptomic and phenotypic screens in hiPSCs-derived neurons and glia (Aim 1), CRISPR screens in zebrafish to assess the effects of gene loss of function on whole-brain structure, activity, and basic behaviors (Aim 2), and spatial transcriptomic and multi-omic CRISPR screens to investigate the transcriptional effects of NPD gene disruption in both systems (Aim 3). We will advance the field by identifying biologically relevant phenotypes resulting from NPD gene loss of function across multiple scales, informing gene prioritization schema, and establishing new spatial multi-omics platforms for the functional analysis of NPD genes. These studies will generate an unprecedented resource of matched molecular, cellular, structural, circuit, and behavioral data in hiPSCs and zebrafish, which will be provided for open distribution to the broader community to yield new insights into NPD.

Team:

Samouil Farhi, Broad Institute
Ralda Nehme, Broad Institute
Ernest Fraenkel, Mass. Inst Technology

Abstract:

Autism spectrum disorders (ASD) are genetically diverse, characterized by both rare variants of large effect size and common variants of small effect size. Identifying the molecular mechanisms resulting from these variants presents a key challenge for the development of clinical interventions. Human pluripotent stem-cell derived neurons (hPSC-Ns) allow studies against a human genetic background and show altered morphology and electrophysiology in ASD conditions. However, identifying mechanisms remains difficult with small numbers of lines, especially for common genetic variants. To overcome this challenge, we will leverage multi-omic characterization of hPSC-Ns perturbed with CRISPRi knockdown of both large effect size ASD risk genes and genes related to neuronal morphology (Aim 1) and electrophysiology (Aim 2). We will complement these screens with a characterization (Aim 3) of a larger, diverse cohort of 46 ASD lines and 46 matched controls which do not harbor coding variants in the genes perturbed in the previous Aims. An integrative analysis of this data (Aim 4) will generate interpretable genetic signatures related to each of these phenotypes and will show how these signatures interact with ASD risk genes. This approach is made possible by new techniques for pooled stem cell culture developed in Dr. Ralda Nehme’s lab, high content optical profiling methods developed by Dr. Samouil Farhi’s team, and data integration tools developed by Dr. Ernest Fraenkel’s group. The overall project will provide a basic neurobiological understanding of hPSC-Ns; provide valuable insight into how both common and rare variants induce observed cell-intrinsic phenotypes; and define an analytic framework and genetic signatures which can be used to understand mechanistic recruitment of new genetic risk loci and other psychiatric diseases.

Although numerous genes and loci associated with autism spectrum disorder and neurodevelopmental delay
(ASD/NDD) have been identified through genome sequencing efforts, the precise mechanisms by which most of
these genetic variants lead to the condition remain largely unknown. We propose to combine high-content in vivo
genetic screening with whole brain cytoarchitecture spatial information from neurons with loss-of-function
mutations in ASD/NDD risk genes to bridge the gap between genetic insights and mechanistic understanding.
This approach, which can be scaled to interrogate large panels of genetic variants in parallel, has the power to
reveal how these diverse gene variants converge to produce ASD/NDD, including identifying the specific brain
regions, cell types, neural circuits, developmental time windows, and molecular networks involved in the
pathogenesis of these disorders.
To achieve this, we propose to use high-resolution and multimodal phenotypic characterizations to
comprehensively map the functions in the neocortex and striatum of a set of 72 high-confidence ASD/NDD risk
genes, many of which encode transcriptional regulators. We will adapt in vivo Perturb-seq to allow high efficiency
screening across multiple developmental time points with both single-nucleus transcriptome and chromatin
accessibility readouts. These rich datasets will enable us to build gene regulatory networks (GRNs) that will
reveal shared and divergent molecular signatures associated with this set of ASD/NDD risk genes. In parallel,
we will explore how perturbation of 5 high-confidence ASD/NDD risk genes impacts cellular migration,
morphology, and long-range connectivity. Here, we will use Perturb-CAST (cytoarchitecture see-through) to
combine sparse genetic perturbations in vivo with whole mount brain clearing and light-sheet imaging to examine
brain-wide changes in cytoarchitecture across developmental time points.
This work will expand two major technologies, in vivo Perturb-seq and Perturb-CAST, which will be broadly
impactful tools for understanding the genetic basis of ASD/NDD and other complex brain disorders. By focusing
on corticostriatal pathways and integrating spatial information, the proposal seeks to uncover commonalities and
shared mechanisms among ASD/NDD risk genes, ultimately contributing to a more comprehensive
understanding of the disorder and potentially guiding future therapeutic approaches.