Scalable and Systematic Neurobiology of Psychiatric and Neurodevelopmental Disorder Risk Genes
SSPsyGene is an NIMH-initiated consortium. We will functionally characterize the contribution of 250 genes to neurodevelopmental and psychiatric disorders (NPD). Our collaboration will result in a comprehensive phenotypic catalog across biological scales.
SSPsyGene Centers
Data Resource and Administrative Coordination Center (U24)
Team:
David Haussler, U.C. Santa Cruz
Tomasz Nowakowski, U.C. San Francisco
Maximilian Haeussler, U.C. Santa Cruz
Mohammed Mostajo-Radji, U.C. Santa Cruz
Benedict Paten, U.C. Santa Cruz
Katie Pollard, Gladstone Institute
Olena Vaske, U.C. Santa Cruz
Catharina Lindley, U.C. Santa Cruz
Abstract:
Our team proposes to lead the SSPsyGene consortium into the Data Biosphere. We will do this by adapting data biosphere technology and management techniques we have already deployed for other NIH institutes, NIH Common Fund, the NIH Office of the Director, the Chan Zuckerberg Initiative (CZI), and the California Institute for Regenerative Medicine (CIRM), making SSPsyGene interoperable across multiple disease areas. We also bring our expertise with neurological data through our involvement with BICCN, Psychiatric Cell Map Initiative, CZI’s Pediatric Brain Map, NHGRI’s Center for Live Cell Genomics/Biotechnology, and our close relationship with PsychENCODE and the Allen Brain Institute. For SSPsyGene, we have 4 major tasks: (1) We will assemble all the information necessary to empower the consortium to choose between 100 and 250 genes to experimentally characterize (Aim 2). We have identified more than 20 different types of information to be integrated for this purpose, many of which are already in the UCSC Genome Browser. We will apply multiple ranking algorithms to this integrated information source to guide the SSPsyGene Consortium’s decision process. (2) We will work to establish an ontology structure that is sufficiently expressive yet fully maintainable, supporting FAIR data use by both researchers and machines (Aim 3). Our previous work with the UCSC Genome Browser and our close relationships with ontology organizations will help us to bridge the gaps between molecular, cellular, tissue/organoid, and model organism measurements, and to extend these resources when needed. Inspired by our experience with the clinical ontologies in OMOP and FHIR, we propose a novel service to allow researchers to query phenotype-phenotype associations in large clinical cohorts, such as All of Us and HEDIS, the database of records from Medicare and Medicaid. (3) We will create a state-of-the-art SSPsyGene Data Biosphere fully compatible with those we created for other NIH institutes (Aim 4). Our emphasis will be on standardization of the data submission process with extensive quality monitoring to ensure timely and effective data release. We will leverage our deep involvement with the Global Alliance for Genomics and Health to ensure all data and metadata will meet FAIR standards. We have experience with the complex data types that will be generated by the SSPsyGene consortium, including -omics, imaging, electrophysiology and other data types. (4) We have served as trusted third-party organizers to many NIH consortia, developing a reputation for fairness and impartiality in data sharing and publication, and expertise in coordinating, generating consensus, publishing results, and creating a resource with maximal impact (Aim 5). Based on our strengths in biomedical data, metadata and ontologies, FAIR platforms, and consortium leadership, we are confident that we will achieve all the goals of the SSPsyGene Consortium.
Assay and Data Generation Center (RM1) – Group 1
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
Assay and Data Generation Center (RM1) – Group 2
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.
Assay and Data Generation Center (RM1) – Group 3
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.
Assay and Data Generation Center (R01) – Group 4
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.