Jackson Laboratory

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY Aging is a terminal process that affects all biological systems. Biological aging—in contrast to chronological aging—occurs at different rates for different individuals. In humans, growing old comes with increased health issues and mortality rates, yet some individuals live long and healthy lives, and others succumb earlier to diseases and disorders. The concept of frailty is used to quantify this heterogeneity and is defined as the state of increased vulnerability to adverse health outcomes. The frailty index (FI) is an invaluable and widely used tool which outperforms other methods to quantify frailty. FIs have been adapted for use in mice using a variety of both behavioral and physiological measures as index items. However, because conducting mouse FI requires trained individuals for manual scoring, it often limits the scalability of the tool. Thus, although the FI is an extremely useful tool for aging research, an increase in its scalability, reliability, and reproducibility through automation would enhance its utility. We used machine learning applied to video data to create an automated visual FI (vFI). The is easy to implement, unbiased, and scalable. Here we propose to improve our tool and carry out an interventional study. We will adopt the vFI to function with genetically diverse mice (R61: Aim 1). We will also create features from long-term monitoring to increase accuracy and breadth of systems measured in the vFI (R61: Aim 2). Finally, we will apply the vFI to a diet intervention study to show its utility for large scale studies (R33: Aim 3). We will test a high fat high sugar diet (increased frailty) and caloric restriction group (decreased frailty) with normal chow (control) in a Diversity Outbred population of mice. The result of this project will be a fully validated and automated vFI that can be used for high-throughput interventional studies, enabling therapeutics for healthy aging.

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY/ABSTRACT OVERALL The Jackson Laboratory (JAX) Cellular Senescence Network Mouse Tissue Mapping Center (JAX-Sen) represents a multi-modal interdisciplinary effort that draws upon existing, longstanding aging research programs at JAX, our role as a consortium site of KAPP-Sen, a funded SenNet human Tissue Mapping Center, and JAX’s close collaboration with UConn Health. JAX-Sen is organized around three cores nested in the well-resourced environment for aging research and multi-omics profiling at JAX. JAX-Sen will profile senescent cells in kidney, adipose tissue, placenta, pancreas, heart, and hypothalamus, selected for their clinical relevance to chronic diseases of aging, the domain expertise of the JAX-Sen leadership team in the biology of these tissues, and the overlap of four of the tissues with KAPP-Sen. We will leverage cutting-edge mouse resources including the Diversity Outbred, which offers unparalleled genetic diversity for modelling a range of molecular senescence phenotypes, and new inbred (C57BL/6J) transgenic mice that express p16 and p21 driven fluorescent tags to allow visualization enrichment for specific senescent cell subsets. The Biological Analysis Core will apply a multitude of analytical modalities to selected tissues (bulk and single cell and single nucleus RNAseq, Visium spatial transcriptomics, multiplexed antibody-based imaging, multiplexFISH, imaging mass spectrometry including lipidomics, metabolomics, proteomics, 3D tissue reconstruction from serial sections), and will re- evaluate these technologies throughout the project period to ensure our approaches align with those of other centers and that we maximally benefit from the technology development efforts in SenNet. These profiling activities will yield subcellular resolution of biomolecular content in senescent cells not possible with human samples, along with an expanded set of senescent cell biomarkers. The Data Analysis Core will combine robust computational capability with scalable and reproducible scientific workflows to develop and implement Network- wide open data and metadata standards. The Data Analysis Core will benefit from JAX’s unique mouse research resources to establish the diversity of senescence by integrating with expression quantitative trait locus and protein quantitative trait locus data in DO mice and JAX bioinformatics resources, e.g., Mouse Genome Informatics, Mouse Phenome Database, Monarch Initiative. The integrative mining of JAX-Sen data will lead to novel methods for multi-modal 3D map reconstruction from imaging data and will yield an important resource for SenNet interpretation and enrichment of human senescent cell data. Finally, the Administrative Core will provide strong oversight of project progress and nurture a culture of collaborative, dynamic scientific exchange within JAX-Sen. It will also maximize JAX-Sen’s engagement in the consortium through collaborative activities that will help optimize data generation activities and create new research synergies. In so doing, JAX-Sen will help achieve the goal of SenNet to generate a unprecedented atlas of mouse senescent cells and new biomarkers of senescence for human analysis and therapeutic application.

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY This proposal will establish a Molecular Phenotypes of Null Alleles in Cells (MorPhiC) Phase 1: Data Production Research and Development Center based entirely at The Jackson Laboratory for Genomic Medicine – the JAX MorPhiC Center. JAX MorPhiC will comprise, under one roof, a team of highly collaborative scientists with complementary skill sets and decades of cumulative experience in mammalian gene knockouts (KO), stem cell and developmental biology, molecular phenotyping, single cell analysis, and advanced metabolomics and lipidomics capabilities. We will KO 250 protein-coding genes over the Phase 1 period of this initiative and will engineer these KOs in human induced pluripotent stem cells (iPSCs) that will subsequently be differentiated into two cell lineages, the extra-embryonic and the neuroectodermal, where cells will then be comprehensively phenotyped. Our rationale for selecting these lineages is that they are two of the most evolutionary divergent between species, and primate-specificity is one of our criteria for gene prioritization. In addition, the extra- embryonic lineage rapidly develops into a cellular functional endpoint responsible for many biological processes, thus permitting interpretation of function of diverse genes, whereas the early neuroectodermal lineage is relevant to neurodevelopmental disorders. In Aim 1, we will prioritize genes for knockout; selection criteria include expression in extra-embryonic or neuroectodermal lineages, primate-specific features, broad classes of functions while enriching for transcription factors, and genes implicated in human disease. In Aim 2, we will generate iPSC KO clones in high-throughput using high-efficiency protocols and workflows established in JAX's Cellular Engineering core. We will engineer KO clones for 250 genes in the well-characterized, stable human iPSC line, KOLF2.1, while considering the effects of sex, genetic background, possible adaptive/compensatory responses, and different KO strategies including incorporation of conditional/reversible and scalable approaches. In Aim 3, will carry out comprehensive phenotyping of derivatives differentiated from KO iPSCs. We have selected a combination of assays to maximally integrate consistency, scalability, and functional informativeness to help achieve the overall objectives of the MorPhiC Consortium. These include imaging, single cell transcriptomics, single nucleus epigenomics, and metabolomics/lipidomics. Our research Aims will be coordinated in administrative Aim 4, which will ensure efficient project management and oversight, internal and external communications, and data dissemination to the MorPhiC Data Resource and Administrative Coordination Center (DRACC). Successful completion of the proposed work will address several main barriers hampering the ultimate goal of the MorPhiC Consortium to functionally characterize all human genes: identifying the most effective KO strategies and optimal phenotyping technologies, as well as scaling efficiencies to expand this program towards future MorPhiC Phases. In the process, we will generate a valuable resource of 250 human iPSC KO lines that will be distributed to the scientific community via existing operational infrastructure at JAX.

NIH Research Projects · FY 2025 · 2022-07

PROJECT SUMMARY/ABSTRACT The long-term goal of this project is to increase the ability of researchers to create faithful mouse and stem-cell models of human cancers and other diseases. Currently available genetic-engineering approaches, including the CRISPR-Cas9 system, which has revolutionized genome editing, lack the capacity for efficient integration of large DNA constructs (> 10 kilobases; kb) in mouse zygotes and mouse and human stem cells. This limitation significantly hinders the modeling of human diseases, including cancer. For example, tandem duplications (TDs), super-enhancers (SEs; large clusters of transcriptional enhancers), and large non-coding structural variants have been linked to human diseases, including cancers, but available technologies do not permit modeling such large variants in whole animals or cell lines. To fill this gap, we will develop a gene-editing toolbox that couples the precision of the CRISPR-Cas9 system with the fidelity and efficiency of the serine integrase Bxb1 to enable rapid, efficient insertion of large DNA constructs in mice, mouse embryonic stem cells, and human induced pluripotent stem cells (hiPSCs). Bxb1 integrase uses DNA attachment sites (attP in the genome, attB in the donor DNA) as substrates for catalyzing efficient transgenesis. We show that our innovative Cas9-Bxb1 toolbox can precisely integrate DNA constructs up to ~43 kb in length in mice. Here, in three aims we will further develop and validate the toolbox to enable precise transgenesis of large DNA constructs (~100 kb) and to facilitate generation of DNA rearrangements. Aim 1: Optimize the Cas9-Bxb1 toolbox for insertion of large DNA (10 to 100 kb) constructs into mouse zygotes. We will use reporter constructs with differing lengths to determine the maximum length of DNA construct that can be inserted efficiently, and will validate a one-step protocol for rapid generation of transgenic mice without the need to first generate and characterize mice with attachment sites. Aim 2: Generate mouse and hiPSC models of human diseases, including cancer, using the Cas9-Bxb1 toolbox. Using our toolbox to insert large genomic variants, we will generate a mouse model of breast cancer (insertion of a 23.7-kb TD), hiPSC model of triple negative breast cancer (27.2-kb SE), and mouse model of Hirschsprung disease (~80-kb human risk allele). Aim 3: Enable use of the Cas9-Bxb1 toolbox for generation of DNA rearrangements. In cre-lox recombination systems, cre catalyzes recombination between two loxP sites flanking a target locus, enabling diverse DNA rearrangements. Studies suggest that cre-recombination efficacy is limited by the inter-loxP-site distance and the particular genomic site targeted. We will determine whether the Cas9- Bxb1 toolbox is more efficient than cre-lox for generation of DNA rearrangements, by determining Bxb1-mediated recombination efficacy at different inter-attP/attB distances. Successful completion of this project will provide the community with three new models for future studies, and a versatile tool for development of novel and improved mouse and hiPSC models of cancer and other diseases.

NIH Research Projects · FY 2026 · 2022-06

Project Summary The Hedgehog (Hh) signaling pathway is essential for normal embryonic development and when perturbed, frequently results in human disease, including those that impact development of the craniofacial complex. The Gli transcription factors are the downstream effectors of the pathway and have been the subject of much research as they are associated with a number of craniofacial syndromes (e.g., Grieg cephalopolysyndactyly) and can function as both transcriptional activators and repressors of the Hh pathway. Gli3 is most stable and abundant as a repressor. Despite this, our recent work identified a specific and necessary role for Gli3 activator (Gli3A) function during normal development of the mandible that requires additional regulatory inputs to convey a robust Gli3A response. Little is known regarding what is required for Gli3, as a bimodal transcription factor, to function as a potent activator during development. To address existing knowledge gaps in how full-length Gli3 is converted into an activator, we engineered a set of endogenously epitope tagged alleles for Gli3. With these novel tools we propose to: (Aim1) determine if/how chromatin accessibility modulates Gli3A function; (Aim2) investigate the role of co-factors and regulatory grammar in regulating enhancer output; and (Aim3) unbiasedly identify protein interactors of Gli3A within the nucleus. We will focus on craniofacial development, specifically development of the mandible, as a relevant model for testing these principles given the requirement for Gli activity during glossogenesis and mandibular skeletogenesis. This developmental system will allow us to determine the requirement for chromatin accessibility, exhaustively interrogate the regulatory grammar, and identify the constituents of the Gli3 activator complex. Recent technological advances will enable hypothesis testing through single-cell analysis of chromatin accessibility and transcription profiles from mutants predicted to have pioneering activity. To validate our findings, we will perform in vivo experiments to test enhancer activity and apply CRISPR/Cas9 mutagenesis to functionally assess native binding site requirements. Collectively, our studies will shed light on the regulatory principles governing Gli-directed cellular programs that when disrupted can result in range of human disorders ranging from structural birth defects to cancer. Understanding how these programs are deployed and interpreted during normal development has the potential to improve human health through the expansion of therapeutic interventions that can help mitigate pathway dysregulation.

NIH Research Projects · FY 2025 · 2022-04

PROJECT SUMMARY Elucidating the mechanism and function of neural encodings and circuit dynamics has been a major challenge in neuroscience and behavioral analyses. However, quantitative behavior analysis has dramatically accelerated and improved with the implementation and application of new machine learning methods, including new deep learning-based methods to track animals at high temporal and spatial resolution. This technology has broad current and potential application that will impact a breadth of fields that have direct relevance and impact on studies of human health and disease, including the fields of neuroscience, behavior, genetics, psychiatry, and biomedicine. However, several roadblocks limit the widespread adoption of these tools and analyses. First, many tracking and behavior analysis packages require a high level of computational expertise and are thus limited in application to expert labs. Second, with high-resolution data streams, quantitating behavior requires new statistical tools and proper modeling of data. Since the application of machine learning to behavioral analyses is an emerging and key methodology, we recognize an unmet need for investigators in a variety of relevant fields to learn the fundamentals of its rigorous use. Thus, to train a new generation of interdisciplinary researchers at the interface of neuroscience, machine learning, and behavior, we propose to establish an annual 4-day workshop that brings together experts in quantitative behavior, computer vision, and experimental design to provide a practical introduction to the field of quantitative neuroethology and behavior: we propose the unique and timely interdisciplinary course The Short Course on the Application of Machine Learning for Automated Quantification of Behavior at the Jackson Laboratory (JAX). This Short Course will provide attendees (in-person and virtually) with; information on the state-of-the-art of machine learning based behavior quantitation, the fundamentals of behavior quantitation, hands-on workshops and data analysis, a forum for student-teacher interaction for networking, and training at the leading edge of computational ethology. Students will emerge from the course with the ability to: 1) design a high quality, adequately powered behavior experiment; 2) select and install a suitable platform for high-resolution analysis of animal behavior; 3) deploy a behavior data analysis strategy, including collecting new training datasets, training analysis software, and validating performance on held-out data; and 4) run workflows/pipelines that are necessary to analyze their data following extraction. To achieve this, we propose: Aim 1. To develop and deliver a 4-day workshop to train scientists on application of machine learning to animal behavior quantitation. Aim 2. To create an environment that will expand the field of quantitative behavior analysis by fostering idea generation, discussion, and collaboration to yield new discoveries, broader applications, and advance technology development. Aim 3. Foster the recruitment and development of junior investigators in neuroscience, behavioral genetics, and quantitative analysis of animal behavior.

NIH Research Projects · FY 2026 · 2022-03

PROJECT SUMMARY/ABSTRACT Heritable retinal disorders, for which effective treatments are generally unavailable, contributes to the 1.02 million adults who are blind in the US. Among children, the heritable disease - Leber Congenital Amaurosis, accounts for 20% of blindness, and 10-15%of those are caused by mutations in the CRB1 gene. In addition to LCA, CRB1 mutations can also cause congenital or early-onset retinitis pigmentosa (RP), a more slowly progressive disease. CRB1 RP variants are sometimes associated with unique disease features, such as retinal telangiectasia with or without exudative retinal detachment (Coat's disease), a loss of RPE pigmentation except near arterioles (preservation of para-arteriolar RPE or PPRPE), pigment paravenous chorioretinal atrophy, cone-rod dystrophy, nanophthalmos with optic disc drusen, retinoschisis, cystoid macular edema, and macular dystrophic disease. The cause of the wide range of disease phenotypes associated with CRB1 mutations is not fully understood. Genotype-phenotype correlations that could explain the disease spectrum have not been detected among patients bearing CRB1 mutations, suggesting that environmental factors or genetic background modifiers contribute to the variability in the disease phenotypes observed. Another potential contributor to the phenotypic variability in disease presentation are Crb1 isoforms which have recently been shown to have spatially and temporally distinct expression patterns. Clearly, understanding the reasons for the variability and the mechanisms underlying the observed pathologies is extremely important for developing effective therapies. In this proposal, we will test the hypothesis that pathological changes due to Crb1 mutations depend upon the isoform affected and the genetic background on which it occurs, and their potential interactions. We will identify the molecular basis of genetic modifiers that enhance or suppress Crb1rd8 associated disease phenotypes or are epistatic upon Crb1rd8. Through the use of mouse models with isoform specific knockout alleles and controlled genetic backgrounds, we will determine their contribution to disease variability and the mechanisms through which they function. These studies address a critical unmet need for acquiring the basic biological knowledge necessary to develop effective therapies that can target the pre-symptomatic stage to prevent, delay onset or decrease severity of the disease. Animal models serve an important and unique role to further our understanding of the genetic underpinnings of disease and as a resource to examine tissue pathology, and to perform pre-clinical therapeutic tests that cannot be readily conducted in humans.

NIH Research Projects · FY 2025 · 2022-02

PROJECT SUMMARY The overall objective of this proposal is to develop and validate a deep learning analytical framework to integrate histological traits into systems genetics analysis of complex diseases. Mapping the risk genes for poor health outcomes is a major focus of biomedical research, and new approaches to improve genetic mapping power can have a transformative impact on public health. Genetic disease risk manifests through complex interactions between gene regulation and tissue structure, ultimately influencing organ function. However, quantifying tissue structure for quantitative genetic mapping has not been widely adopted. This is partly because histological scoring has traditionally been labor intensive and error prone, and limited to coarse measures (e.g., discrete categories) that are suboptimal for association testing. In contrast, deep neural networks (DNNs) now routinely automate laborious image quantification tasks for histopathology, making them an ideal platform for integrating histology into genetic analysis. Furthermore, unlike human-defined histological scores, DNN readouts enable objective histological trait discovery as a function of genetic, molecular, and physiological variation. In this project, histological features will be rigorously and robustly quantified using DNNs and these data will be integrated into novel multiscale statistical models that will connect genetic, molecular, and histological variation to physiological outcomes. In particular, novel methods will be developed to integrate histology into three major classes of systems genetic analysis, i.e., heritable trait inference, causal mediation analysis, and molecular quantitative trait locus (mQTL) mapping. These methods will be developed and validated using a data set of genetic, histological, transcriptomic, proteomic, and physiological data from a cohort of Diversity Outbred mice used for the study of age-related kidney disease. By using a model system, complex genetic effects and causal mediation hypotheses can be directly tested to validate and refine the analytical framework. The specific aims of this proposal include: Aim 1: Identify maximally heritable histological traits through deep learning on paired genotypes and histological images. Aim 2: Genetically map histological mediators of complex physiological traits using deep learning on histological images. Aim 3: Identify causal paths connecting molecular QTLs (mQTLs) to outcomes through histological mediators. The outcome of this study will be a validated methodological framework for histological systems genetics that is modular, enabling a wide range of users to incorporate appropriate computer vision tools into state-of-the-art systems genetics workflows for any complex disease.

NIH Research Projects · FY 2025 · 2022-01

PROJECT SUMMARY/ABSTRACT Alport syndrome is a human hereditary glomerulonephritis, which in most cases, results in end-stage renal disease. It is the most common inherited glomerular disease leading to renal failure and is caused by mutations in any one of the genes encoding a3, a4, or a5 chains of type IV collagen (COL4A3, COL4A4, and COL4A5, respectively). There is large variation in the age of onset and severity of the disease, even between patients with similar mutations. Studies in mice have shown that the renal phenotype is highly dependent on the genetic background. It is widely accepted that modifier genes contribute to this variation, which could represent a source of novel therapeutic targets in Alport syndrome and other renal diseases. We identified human-relevant modifier genes in a small cohort of genetically diverse mice with a Col4a5 mutation (leading to X-linked Alport syndrome (XLAS)) and validated that decreased expression of one of these genes, Fmn1, leads to a less severe renal phenotype. We further found that two of the candidate modifier genes (Pik3r1 and Dgke) modulate other forms of kidney disease, including diabetic nephropathy and hematolytic urea syndrome. In this application we will discover novel candidate modifier genes of XLAS by high-resolution genetic mapping in a large genetically diverse XLAS mouse cohort and confirm the translational relevance of the modifiers in humans. The functional impact and causality of the modifier genes will be assessed in preclinical mouse models of XLAS and other forms of kidney disease. We will generate a large, genetically diverse XLAS mouse population that, combined with our previous population, will allow us gene-resolution mapping of modifier loci (Aim 1). Whole exome sequencing and targeted testing for the detection of the most likely candidate modifier genes in human XLAS pedigrees will be conducted to confirm the translational relevance of the candidate modifier genes found in our mouse studies (Aim 2). We will use available knockout resources and/or CRISPR- Cas9 gene editing to test causality of as many as five candidate genes in the XLAS mouse model (Aim 3A). We will further test these modifier genes for causality in mouse models of two common forms of kidney disease: diabetic nephropathy and focal segmental glomerulosclerosis syndrome (Aim 3B). Identification of the genes responsible for the onset and severity of disease will provide meaningful insights into understanding the molecular events underlying the pathogenesis of kidney disease and provide the basis for developing novel therapeutic strategies.

NIH Research Projects · FY 2026 · 2022-01

PROJECT SUMMARY The WHO estimates that annual epidemics of influenza result in 3-5 million cases of severe illness and 300,000- 500,000 deaths. 90% of influenza-related deaths occur in older adults despite widespread vaccination programs with vaccines tailored for this high-risk group. The estimated effectiveness of the influenza vaccine in the U.S. for the 2018-2019 influenza season overall was 47%, but only 12-13% in older adults. There is therefore an urgent need to understand the mechanisms that are turned on/off in older adults that result in their limited response rate to the most commonly used influenza vaccine, Fluzone® High-Dose. There is also a need to understand whether and why next-generation influenza vaccines might be more efficacious. Immunosenescence is known to be associated with declines in optimal B cell and T cell adaptive immunity, however, our overall understanding of the mechanisms of immunosenescence is incomplete. The central goal of this proposal is to understand the mechanisms that lead to a loss of response to influenza vaccine in older adults through establishment of the 3FluAging cohort of healthy older adults who will be vaccinated with three different influenza vaccines three years in a row. We hypothesize that aging impacts specific regulatory mechanisms of humoral immunity to reduce vaccine effectiveness. In Aim 1, we will establish a cohort of 60 healthy older adults (≥65yrs) who will sequentially receive three different annual influenza vaccines, with serial blood and microbiome sample collection during three years of follow-up. Participants will undergo regular clinical assessments. In Aim 2, we will decipher the magnitude and immunodominance pattern of the humoral response to influenza virus in healthy older individuals upon vaccination. For each vaccine, we will characterize antibody titer and quality and will define responders and non-responders. In Aim 3, we will characterize the epigenome, transcriptome, cytokine production, and cell proportions of blood leukocytes in vaccinated healthy older participants. We will identify specific (epi)genomic and functional signatures, and their longevity, associated with vaccine response. We will also sequence all participants to uncover the role of genetic variation on influenza vaccine responses. In Aim 4, we will assess the function of T helper cells and antigen presenting cells, specifically dendritic cells, in influenza vaccine responders and non-responders. By identifying responders and non-responders for each vaccine and integrating these data with baseline immune status multi-omic signatures, we will determine which immune features can predict vaccine responsiveness. We expect to identify humoral immunity pathways that are altered in aging that can be used as the basis for designing novel approaches to boost efficacy of the most commonly used, as well as emerging, influenza vaccines.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY Recent advances to characterize cis-regulatory elements (CRE), including massively parallel reporter assays and CRISPR-based screens of non-coding elements, have transformed our ability to comprehensively characterize the non-coding genome at scale. Large scale efforts by us and others through the Encyclopedia of DNA Elements (ENCODE) consortium are now underway to apply these methods genome-wide across many cellular states. The results of these screens will have a transformative impact on our ability to read and write the regulatory grammar of the cell. One direct application will be in the interpretation of causal alleles for human disease risk and other phenotypic traits identified through genome-wide association studies. From these studies we now know the majority of heritability for complex traits resides in non-coding regions of the genome. Until recently it has been difficult to pinpoint individual causal alleles but progress is now being made to identify and elucidate their molecular function. Despite our burgeoning success in understanding how a variant impacts molecular phenotypes (e.g. gene transcription), we lack the ability to systematically evaluate allele(s) within model organisms to understand their impact on physiological function. This disconnect is partially due to our inability to identify the homologous non-coding region to target within model organisms. To aid in modeling human regulatory variation in the mouse, in this project we will develop improved maps of homologous CREs between human and mouse. Current comparative approaches rely on sequence homology and correlative measures of gene expression such as regions of DNase hypersensitivity and chromatin modifications. While these methods have provided valuable insight, they lack direct quantitative measurements of a CRE's impact on individual genes and the location of the cis-regulatory modules (CRMs) within the CREs responsible for activity. To overcome these shortcomings, in this study we will develop maps of CRE conservation based directly on function. To accomplish this, we will differentiate induced pluripotent stem cells (iPSCs) from human and mouse to early developmental states as the starting material for screens of CRE activity. We will use (i) a CRISPR-based screen to endogenously perturb putative CREs important for neuronal and epithelial function; and (ii) CREs with concordant and discordant activity across the two species will then undergo saturation mutagenesis using a massively parallel reporter assay (MPRA). Results from the MPRA will identify CRMs (e.g. TF binding motifs) within each CRE driving regulatory activity of the element. We will use the results from both screens to construct improved maps of CRE conservation that will inform how to copy the effects of genetic variation residing at these regions across species. Doing so will accelerate our progress in moving human disease variants into animal models, thereby allowing us to better understand the pathophysiology of complex diseases in the human population.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY/ABSTRACT To improve diagnostic yield for rare diseases, we developed the Human Phenotype Ontology (HPO) in 2008 as a comprehensive bioinformatic resource that provides a standardized terminology of phenotypic abnormalities for the analysis of human diseases. HPO reduces ambiguity in disease descriptions—thus enabling more robust differential diagnosis and clinical care—and enables phenotypic contextualization of genomic data for diagnostics and precision medicine. The performance of computational algorithms for differential diagnostics with HPO terms depends critically on the comprehensiveness and depth of HPO annotations for diseases. However, the current manual nature of our biocuration process has limited the quality, depth, and coverage of these annotations. Therefore, this proposal's objectives are to greatly expand the corpus of disease-phenotype annotations by automating portions of the curation and expanding the computational disease model. This project, HPO: Accelerating Computational Integration of Clinical Data for Genomics, will maintain and advance HPO resources to address the needs of a growing number of medical disciplines that have adopted the HPO. We will achieve this goal by 1) automating HPO development, maintenance, and release processes, 2) developing representations of rare disease treatments and interventions, and 3) extending our current computational disease models to represent time course, sex biases, and frequency of events, and to incorporate case report data. We also provide a sustainable solution to community contribution with a user-friendly, web- based portal to enable contributors to vet and suggest improvements to the ontology and the annotations and grow the HPO contributor community. In summary, our project addresses the most pressing needs for advancements of the HPO to ensure sustainable, robust, and rigorous development, to enable HPO resources to support new communities, new applications, and more medical disciplines.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY/ABSTRACT Age is one of the most clearly defined risk factors for cancer. As the incidence of cancer increases with age, rising more rapidly beginning in mid-life (ages 45-64 years), cancer can be considered an age-related disease. Recent studies have identified age-dependent somatic mutations, including alleles with a role in cancer initiation, in a spectrum of human tissues. In the hematopoietic system this is termed clonal hematopoiesis (CH) and is most commonly caused by mutations in the epigenetic regulators DNMT3A, TET2, and ASXL1 within the hematopoietic stem and progenitor cell (HSPC) compartment. How the aging process promotes clonal selection, expansion, and transformation from CH to acute myeloid leukemia (AML) is poorly understood. The long-term goal of this research is to understand the mechanisms by which aging promotes transformation causing hematologic malignancies. The overall objective of this proposal is to elucidate the mechanisms by which increased inflammation observed during aging promotes expansion of CH-mutant HSPCs, and the extent to which this fitness advantage is provided by altered epigenetic regulation occurring as a direct consequence of CH mutations. Preliminary data show that CH-mutant HSPCs have a more potent selective advantage and undergo more rapid malignant transformation in aged compared to young mice. Mechanistically, increased inflammation in aged mice is a driver of this phenotype and epigenetic alterations are found to accumulate in CH-mutant HSPCs with aging. These data support the central hypothesis that aging-associated inflammation is a selective pressure favoring CH-mutant HSPC expansion and malignant transformation, and that clonal expansion, epigenetic alterations, and risk of transformation caused by CH mutations are dependent upon sustained CH-mutant allele expression. This project will use cellular and molecular biological approaches in aged mice integrated with studies using primary human CH samples to achieve the following specific aims: AIM 1. Determine the extent to which clonal hematopoietic expansion and leukemic transformation in the aging context is due to inflammation; and AIM 2. Determine the mechanisms by which, and extent to which, reversion of a CH mutation during aging alters clonal evolution and risk of leukemia initiation. The proposed research is conceptually innovative because it is the first to determine how inflammation and epigenetic dysregulation conspire during the aging process to expand, evolve and transform CH-mutant clones. The proposed research is technically innovative as it incorporates novel co-culture systems and therapeutic studies to assess key inflammatory drivers, as well as a novel murine model with CH-mutant induction and reversion capabilities to investigate CH mutant allele dependencies in clonal expansion, epigenetic alterations, and leukemic transformation. This study is significant because understanding the mechanisms by which aging contributes to clonal expansion and transformation will provide insights into effective therapeutic strategies targeting clonal evolution, attenuate pathophysiology promoted by clonal expansion, and intercept malignant transformation.

NIH Research Projects · FY 2025 · 2021-08

PROJECT SUMMARY The overarching goal of NCI's Pediatric In Vivo Testing Program (Ped-In Vivo-TP) is to improve outcomes of pediatric cancer patients and to satisfy the requirements of the Research to Accelerate Cures and Equity (RACE) for Children Act to assess the efficacy of targeted anti-cancer agents developed for adults in pediatric contexts. To coordinate the activities of the new Ped-In Vivo-TP initiative, we have assembled a team of investigators from The Jackson Laboratory (JAX) and Seven Bridges Genomics (SB) with unique combined expertise and experience with in vivo cancer models, scalable cloud-based data management and analysis systems, informatics resource development, and multi-site project coordination. Combining the complementary strengths of JAX and SB provides the ideal foundation for a coordinating center to maximize the short- and long-term impacts of the Pediatric In Vivo Testing Program for advancing the application of precision medicine in pediatric oncology. We will manage a comprehensive and cohesive testing program to advance precision medicine in pediatric oncology through effective public-private partnerships among pharmaceutical companies, regulatory agencies, funders, and research organizations. We will achieve this goal through the following aims: Aim 1: Establish and maintain the Pediatric In Vivo Testing Coordinating Center (PIVOT CC) to provide administrative and logistical support for diverse stakeholders in the Pediatric in Vivo Testing Program consortium. We will draw on our team's combined decades of experience with multi-site program management, cancer model development, standardized testing of in vivo cancer models, data management and analysis, and informatics resource development to ensure timely decision making, conformance to standard protocols, resource tracking, and effective communications within the Ped-In Vivo-TP. Aim 2: Provide data management, statistical, and bioinformatics support to ensure data security and integrity. We will leverage existing protocols and software systems at JAX and SB to identify relevant in vivo cancer models and to collect, analyze, and securely manage data generated from testing centers within the consortium. We will perform statistical and bioinformatic analyses on consortium data to reliably inform the evaluation of the efficacy of novel therapeutic agents in a pediatric oncology setting. We will develop a public- facing data portal for sharing of data and methods with the broader scientific community. Aim 3: Provide scientific coordination to maintain an efficient and effective preclinical testing pipeline. We will draw from the extensive experience of our team with in vivo pharmacology and coordination of similar consortia to manage and coordinate the testing of agents by the Ped-In Vivo-TP centers at all stages of the process, from the identification of relevant in vivo models to the generation of final technical reports and publication of results. We will develop, record, and track performance metrics for the consortium to inform the evaluation of the program's success and impact.

NIH Research Projects · FY 2025 · 2021-08

PROJECT SUMMARY/ABSTRACT Addiction is an enormous economic, personal, and social burden, costing over $600 billion per year in the U.S. Understanding vulnerability to addiction, and developing effective therapies, requires identifying the genes and pathways that mediate the addiction process. Our long-term goal is to develop novel genetic models for addiction-relevant phenotypes, and use these models to characterize the genetic mechanisms of addiction. We propose to leverage the Jackson Laboratory Knockout Mouse Project 2 (JAX KOMP2) pipeline to prioritize addiction gene candidates, and then characterize the effects of candidate gene knockouts on addiction-related behaviors and on addiction-relevant tissues. The JAX KOMP2 Phenotyping Center performs high-throughput phenotyping of knockout mice across organ systems using an efficient, broad-based testing pipeline including behavioral assays for emotionality and sleep, both predictive of addiction phenotypes. Here we propose to exploit this rich KOMP2 dataset to select a subset of lines with emotionality and neuronal phenotypes (e.g. deviant open field, light dark, hole board, tail suspension, prepulse inhibition, rotarod, electroconvulsive seizure threshold, or sleep phenotypes) and lacking metabolism and physiology phenotypes. Our preliminary data provide compelling evidence that gene deletions leading to emotionality phenotypes in the KOMP pipeline have addiction phenotypes. We will subject these lines to deep drug abuse–relevant phenotyping, including drug self-administration, transcriptional profiling from key neuronal tissues, and whole brain imaging. The data from these will be integrated using systems analysis. The successful completion of this project will yield dozens of novel mouse models with detailed transcriptome, and neuroanatomical profile to establish mechanistic insight into this behavioral abnormality. These can serve are a resource for the research community for therapeutics development.

NIH Research Projects · FY 2025 · 2021-06

PROJECT SUMMARY/ABSTRACT The Jackson Laboratory (JAX) proposes a teacher education initiative, 'Teaching the Genome Generation' (TtGG), to provide pre-service high school teachers the content knowledge, teaching strategies, and resources needed to enhance student learning in genomics, bioethics, and bioinformatics, with an emphasis on math and data literacy. Our pre-professional development program will provide instruction in the molecular genetics of personalized medicine, use of bioinformatics tools, incorporating statistics and data analysis, and discussion of the ethical, legal, and social implications (ELSI) surrounding genetics research. In collaboration with partners in higher education, up to 32 pre-service teachers per year will participate in a hands-on short course. Pre-service teachers will also have the opportunity to engage with and practice teaching our curriculum through instructional methods coursework and student teaching/internships. Our innovative approach weaves three learning strands—molecular genetics, bioinformatics and bioethics—together within the context of the Next Generation Science Standards and Common Core Math Standards. The TtGG team will expand dissemination of our content and short course through significant enhancement of our online resources. A pilot online course will be launched in late 2020, and a full online program with additional resources accessible through a newly designed TtGG public facing website will be completed and released by the first quarter of 2022. To evaluate the impact of the short course, evaluators will administer pre and post surveys to pre-service teacher participants on genetics, genomics and bioinformatics content knowledge, teacher self-efficacy, and confidence. Evaluators will also conduct small scale efficacy studies to examine the impact of the TtGG materials on students': a) content knowledge of genetics, genomics, and applications of mathematics; b) confidence engaging in genomics concepts, lab activities, and math problems; c) interest in engaging in additional genomics-related behavior, including academic and career pursuits; and d) ability to explain how and why math skills are required for practicing life sciences. By training pre-service educators, TtGG will execute on NIH's goal of strengthening the future STEM workforce through increasing genomic and health literacy.

NIH Research Projects · FY 2026 · 2021-05

The NHGRI Genome Technology Program (GTP) encompasses a substantial diversity of scientific approaches and objectives, from instrumentation development to high-throughput application of technologies for characterizing the genomic basis for phenotypic traits. These research efforts have produced significant insight into biology and disease, and yet there are many opportunities to accelerate innovation, development, and early dissemination of genomic technologies. The goal of the Technology Development Coordinating Center (TDCC) is to maximize these opportunities by promoting interaction among grantees, supporting innovative new ideas through pilot funding, and aiding in the dissemination of research results and new technologies to the broader scientific community. The TDCC will focus on three primary areas, aligned with these goals: 1) Support information exchange across the GTP leading to cross-fertilization of ideas. We will build on established Scientific Working Groups (SWG) that provide a venue for discussion of work in progress and collaboration on areas of shared interested and by hosting the annual program meeting Advances in Genomic Technology Development (AGTD). We will also work with the Centers of Excellence in Genomic Science (CEGS) each year to host the annual CEGS program meeting, providing logistical support and programmatic continuity, while encouraging evolution of the format based on the location and host priorities. We will use the SWGs to identify gaps in the field that will provide the foundation for solicitation of Opportunity Funds. 2) Establish and manage an Opportunity Funds program to support initial development of promising new technologies and ideas or to enhance dissemination of new technologies. Peer review will be conducted by an External Review Panel of experts representing the breadth of fields of the GTP. 3) Implement outreach activities to improve awareness of GTP successes and facilitate access to GTP research by the broader scientific community. Outreach activities will be a combination of online/webinar format, focused video productions, and in-person meetings that incorporate interactive components. We will incorporate input on content and format from other NIH programs. Programming will be designed for scientists across the career spectrum and from a range of biomedical fields that use genomics approaches. The annual and SWG meetings will provide opportunities for trainee engagement and contribution. Leveraging the experience of the large number of SBIR award recipients who are TDCC participants, we will focus on issues related to commercialization of new technologies providing researchers with information and perspective on how to expand access to new methods beyond the developers’ labs. The Jackson Laboratory (JAX) is well qualified to serve as the TDCC, bringing together broad expertise in genomics, extensive experience in consortium management and conference development, and established relationships with NHGRI grantees.

NIH Research Projects · FY 2026 · 2021-05

PROJECT SUMMARY The Jackson Laboratory (JAX) will provide a unique research and training experience designed to encourage and assist faculty and trainees in the biomedical and behavioral sciences to pursue or advance research or science-related careers in addiction-related areas. The long-term goal is to educate and enable the next-generation of scientists to use cutting edge genetics and genomics techniques to study addiction. This training program consists of two components. To begin, participants will first complete a customized, virtual mentored course designed to deliver foundational skills and knowledge in mammalian and systems genetics of addiction. The virtual course will combine newly-derived content combined with material derived from several of JAX's signature courses including the McKusick Human and Mammalian Genetics Short Course, and the Short Course on the Genetics of Addiction, and from established JAX online educational modules including The Basics of Mouse Genetics, and Complex Traits. Then, a subset of course participants will be invited to return to JAX with 2 trainees (post-doctoral, graduate or undergraduate) for an extended summer research experience mentored by hosting JAX faculty. Faculty-trainee teams will be hosted at JAX by program mentors, where they will make use of JAXs advanced research resources to learn techniques needed to augment their research into addiction related phenomena through the incorporation of mammalian genetics and genomics. They will return to their home institutions with knowledge, skills, data and resources to support follow-on research, presentations, publications and grant applications. This model will foster the career development of faculty as well as both the participating young scientist-trainees and the future trainees of the faculty member. The program is designed to achieve the following Specific Aims: 1) Provide foundational education in mammalian genetics and systems genetics of addiction through virtual, mentored instruction. 2) Engage faculty and student teams in mentored research projects utilizing advanced methods and resources for addiction genetics. 3) Recruit individuals to participate in the virtual course, mentored research experiences, and career development skills training. Impact: Successful completion of these aims will result in an expanded number of addiction researchers who are actively working with model organism genetics and genomics to understand and characterize mechanisms of addiction related behavior. Educational materials will be made broadly available, and a select group of investigators will advance to develop specific genetic and genomic research programs with support in the use of emerging technologies in these fields. The effectiveness of this novel program will be evaluated and if successful, may be used as a model for expanded deployment in other research fields or institutions.

NIH Research Projects · FY 2025 · 2021-04

PROJECT SUMMARY As much as 10% of the population suffers from a rare disease (RD); 80% of these diseases are caused by gene mutations and up to 75% are present at birth or begin in childhood. Diagnosis of genetic diseases is often problematic: roughly 25% of RD patients must wait between 5 and 30 years for a diagnosis, and about half of the initial diagnoses are wrong. For many affected children, definitive diagnosis comes only after a protracted and frustrating odyssey of visits to different specialists. Emerging genetic sequencing techniques offer the possibility of shortening this long and costly path to diagnosis. Methods for determining the changes in gene sequences across all genes (exome sequencing) or all genetic material (genome sequencing), collectively referred to as Next-Generation Sequencing (NGS), and which were first used to identify the genetic cause of a disease in 2010, are now becoming routine in the clinic. The ability to make a diagnosis with NGS has more than doubled since 2010 for children with suspected genetic diseases. The diagnostic analysis of NGS data involves the assessment of tens of thousands (exome) or even millions (genome) of changes in the DNA (variants), which requires sophisticated computer algorithms that can sift through these/this data to find the cause. Our group has developed the Human Phenotype Ontology (HPO), a resource widely used around the world for the computational analysis of clinical data in human genetics and pediatrics, allowing algorithms to match the symptoms of a patient with database records of over 7,000 genetic diseases. Our Exomiser software compares the clinical phenotypes of patients with known human diseases and genetically modified animal models, and couples this with an analysis of the disease-causing potential of DNA variants, greatly reducing the search space to identify the causal variant. Exomiser efficiently processes both exome and genome data. In this proposal, we plan to extend Exomiser to utilize new genomic data types including long-read genome sequencing and NGS-based analysis of RNA data, which will improve pathogenicity prediction for structural variants (SVs) and for variants affecting gene expression or splicing. We will also predict novel disease genes through characterization of networks of clinical phenotypes and the molecular functions (pathways) of affected genes. We plan to use these algorithms to assess collections (cohorts) of unsolved cases in projects such as the 100,000 Genomes Project. Our algorithmic approach will be applied to intelligently reanalyze unsolved cases periodically as new information is added to the medical literature. And finally, we will develop tools to integrate Exomiser into a large range of settings by adding support for standards generated by the Global Alliance for Genomics and Health (GA4GH). The proposed advances will make Exomiser more efficient, more accurate, and easier for non-specialist pediatricians to use, bringing genomic diagnostics to routine pediatric clinical care.

NIH Research Projects · FY 2026 · 2021-04

PROJECT SUMMARY/ABSTRACT Metastases, accounting for over 90% of breast cancer-related deaths, preferentially occur in certain organs, with lungs being one of the major metastatic sites. Formation of the lung pre-metastatic niche has been known to be essential for metastatic colonization. Such a niche is characterized by recruitment of immunosuppressive myeloid cells, which have been thoroughly studied. In contrast, the importance of lung-resident stromal cells, particularly mesenchymal cells (MCs), has been underdetermined. Our previous work established lung MCs, particularly Ptgs2+ adventitial fibroblasts (AdvFs), as central regulators of the pre-metastatic niche through their secretion of chemokines (CXCL1/2, CCL2) and immunomodulatory factors (PGE2, IL-6) that recruit and reprogram myeloid cells to be immunosuppressive. Despite these advances, a major gap persists in metastasis research: most mechanistic investigations on metastasis utilized young models, while it remains largely unknown whether and how metastasis differs as a function of aging, the key prognostic factor for breast cancer. Our preliminary results demonstrated that aging specifically increases lung metastasis while not uniformly influencing other organs. Further, aged lung MCs exhibit upregulated expressions of IL-1R1, myeloid (CXCL1, CCL2) and B cell (CXCL13) chemokines, and elevated immunoregulatory mediators (PGE2, IL-6), coinciding with accumulation of neutrophils and CTLA4+ Breg-like cells. We then raised our hypothesis that aging reprograms lung MCs to amplify immunosuppressive niche formation, thereby increasing metastatic vulnerability. The proposed research employs multi-omics, stromal-specific genetic manipulation in aged models, human 3D coculture systems, and clinical data analyses to: 1) Characterize the cellular mechanisms by which aged lung mesenchymal cells regulate immune cell recruitment and polarization to establish a metastasis-permissive niche; 2) Define the molecular and epigenetic drivers of pro-metastatic reprogramming in aged lung mesenchymal cells; and 3) Develop stroma-targeted strategies to reverse aging-associated immunosuppression and metastatic susceptibility. Vertebrate animal models are essential for this work because they will provide the necessary physiological context to model the complex, age-dependent interactions among primary tumors, lung-resident stromal cells, and immune system during the multi-step metastatic progression. These multi-organ processes involve intricate circulatory and inflammatory dynamics, which cannot be fully recapitulated in non-animal systems. Our work will establish a foundation for the development of personalized metastasis treatments stratified by age and levels of tissue-specific stromal factors and shed light on studying the general mechanisms of aging-augmented pulmonary diseases.

NIH Research Projects · FY 2025 · 2021-03

The goal of this proposal is to determine how antigen exposure shapes subsequent Natural Killer cell responses to HIV. We propose to identify NK functional subsets in naïve and antigen-primed human NK cells using single-cell sequencing and multi-parametric flow cytometry. We propose to verify the relevance of such functional subsets to NK cell-mediated host protection from HIV disease using our established in vitro and in vivo functional assays. NK cells are innate lymphocytes that live up to their name by their ability to kill infected or tumor cells within minutes of exposure. However, the targeting of NK cell effector functions has not been a significant focus in vaccine development, which has mainly focused on their T and B cell counterparts in the adaptive immune system. Recent findings from the PI of this application indicate that NK cells deserve more attention. We recently published exciting new data that human NK cells remember prior antigen- encounters and mediate enhanced recall responses to HIV-Envelope in humanized mice. Here, we present unpublished new data that HIV-Env-primed memory NK cells suppress HIV viral titers upon experimental viral challenge. These findings have opened the opportunity to harness NK memory functions for vaccine design. However, high NK cell receptor repertoire diversity is associated with an increased risk of HIV acquisition, and NK cell receptor repertoires diversify throughout life, presumably in response to antigen exposure. These data present a challenge for vaccine design, as both protective NK memory responses and potentially risky NK repertoire diversifications are consequences of antigen exposure. The identification of specific functional subsets of HIV-responsive, host-protective NK cells and their mechanisms of host protection is therefore critically needed. Their discovery will open the door for revised vaccine designs that endure the incorporation of NK memory, rather than harmful receptor repertoire diversity, as a host protective outcome. Our data will enable the pre-screening of vaccines for the induction of protective NK functional subsets in pre- clinical models and allow for improved vaccine efficacy evaluations in humans. Thereby, our studies will provide the rationale to develop novel vaccines that exploit the antiviral activity of NK cells to protect humans from HIV infection while avoiding harmful activity.

NIH Research Projects · FY 2025 · 2021-02

SUMMARY Alternative RNA splicing is a key step in gene expression regulation and contributes to transcriptional diversity by selecting which transcript isoforms are produced in a specific cell at a specific time point. Aberrantly spliced isoforms can impact every one of the hallmarks of cancer, including increased cell proliferation, migration, or resistance to apoptosis. Regulatory splicing factors (SFs) have recently emerged as a new class of oncoproteins and tumor suppressors. In particular, the tumorigenic capacity of the oncogenic transcription factor MYC, which is dysregulated in >50% of human tumors, has been shown to be dependent on the splicing machinery and on at least 3 SFs directly regulated by MYC. However, we currently do not have a comprehensive understanding of which component(s) of the splicing machinery are regulated by MYC, or of the functions of MYC-induced spliced isoforms. The goal of this proposal is to systematically characterize the mechanisms by which MYC-regulated SFs and spliced isoforms drive tumor growth and maintenance. To begin to address this gap in knowledge, in our preliminary studies we used a mammary cell line harboring an inducible form of MYC to greatly expand the number of known SFs regulated by MYC. We uncovered that MYC activation promotes alternative splicing of >4,000 isoforms and expression of 125 SFs. These SFs are also upregulated in MYC-active breast tumors and can be grouped, based on co-expression, into groups or modules. Six SF-modules highly correlate with MYC activity in breast tumors and cell lines, and are enriched in triple negative breast cancer (TNBC). Which of these SFs play a role in MYC-driven transformation, and whether co-expression of multiple MYC-induced SFs has a stronger tumorigenic effect than individual SFs, is not known. Further, co-expression analysis in 33 TCGA tumors of different tissue origin identified an SF-module shared across all MYC-active tumors, suggesting a pan-cancer vulnerability. We hypothesize that MYC regulates a network of SFs which cooperate in tumor pathogenesis and that disrupting this network could provide a novel strategy to slow growth of MYC-driven tumors. Here, we will leverage our expertise in RNA splicing and cancer biology and apply a functional genomics approach to gain novel insights into MYC's oncogenicity. Aim 1 will characterize the function of 6 MYC-induced SF modules and their splicing targets in TNBC tumor growth in vitro and in vivo. Since it is unknown whether MYC regulates a shared set of isoforms in distinct tissues, Aim 2 will identify pan-cancer splicing signatures predictive of MYC activity and clinical outcomes, which may serve as clinical biomarkers, and will deliver putative neo-antigens generated from MYC-induced isoforms. Finally, Aim 3 will implement genomic approaches to determine which MYC-induced isoforms are essential for the growth of MYC-driven cancer cells and patient-derived organoids. This project will reveal fundamental mechanisms by which oncogenic SFs and their target spliced isoforms drive tumorigenesis downstream of MYC. These results could help inform development of therapeutic strategies for tumors driven by MYC, which remains an undruggable target.

NIH Research Projects · FY 2026 · 2020-12

PROJECT SUMMARY Type 2 diabetes (T2D) is a complex genetic disease that occurs when pancreatic islets cannot secrete sufficient insulin to overcome peripheral tissue insulin resistance. Genome-wide association studies (GWAS) have identified DNA sequence variants associated with T2D (T2D SNVs) in >600 regions of the human genome. T2D SNVs are enriched in islet cis-regulatory elements (CREs), implicating them as putative causal and functional variants that contribute to T2D by altering islet transcriptional regulation and function. Focused variant-to-function efforts are critical to understand the biological significance of these observations and identify novel therapeutic targets in T2D. In recent work, we nominated 145 T2D SNVs as high-confidence functional variants that significantly alter in vivo islet cis-regulatory element (CRE) chromatin accessibility (islet caQTL), but only a subset of these variants has been linked by us or others to their candidate target genes. Based on published and preliminary data, we hypothesize that these T2D SNVs alter cell type-specific (e.g., alpha, beta, and/or delta) CRE use, activity, and target gene expression to contribute to islet (dys)function in T2D risk and progression. In Aim 1, we will define how each of these T2D SNVs alters islet cell type-specific CRE use via chromatin accessibility quantitative trait locus (caQTL) analysis of single nucleus ATAC-seq profiles from an 80-donor islet cohort and CRE activity using massively parallel reporter assays (MPRA) in human islets. In Aim 2, we will determine the target genes of our nominated T2D-overlapping CREs with cell type-specific resolution using innovative and complementary computational (chromatin co-accessibility), genomic (CRISPR-QTL), and genetic (expression QTL) approaches in primary human islets. In Aim 3, we will assess how T2D-associated changes in islet cell type-specific target gene expression and composition affect islet (dys)function using both CRISPR/Cas9 and conventional knock-down and overexpression approaches to engineer human pseudoislets. This study will significantly advance our understanding of the islet cell type-specific determinants of T2D risk and pathophysiology. With complementary genetic, computational, and cell engineering approaches, we will identify and validate T2D target genes as high-priority therapeutic candidates for detailed mechanistic studies, preclinical models, and drug screening. Importantly, the development of ad hoc genomic tools to modulate and monitor cell type-specific gene regulation and output in primary human islets will enhance cell-type-oriented studies in primary and stem cell-derived human islets for disease modeling. Together, the novel tools and knowledge will catalyze progress in T2D risk assessment, prevention, and treatment.

NIH Research Projects · FY 2025 · 2020-12

PROJECT SUMMARY We have identified a group of genome instability configurations called the Tandem Duplicator Phenotypes (TDPs) that are found in ~50% of triple negative breast, ovarian and endometrial cancers and are characterized by the massive genome-wide distribution of somatic tandem duplications (TDs) of specific span sizes. We have identified the bona fide genetic drivers of these configurations, demonstrated that loss of Trp53 and Brca1 in the mouse mammary gland is sufficient to induce tumors with the short-span TDP configuration found in TP53- and BRCA1-deficient human cancers, and shown that upon loss of Brca1, TDs are formed through the aberrant repair of stalled replication forks. Here, we propose to deploy a combination of computational analyses, in vivo modelling and in vitro experimentation to achieve a deep mechanistic understanding of how the distinct TDP genomic configurations emerge and impact the course of breast tumorigenesis. Specifically, we will investigate the molecular mechanisms leading to de novo TD formation across the different TDP groups by exploring how local DNA features associated with DNA replication and fork stalling contribute to the generation of new TDs across a large pan-cancer dataset representing all TDP groups and all TDP genetic drivers (Aim 1A) and how loss of BRCA1 activity may modulate the spread and location of the de novo TDs formed in the context of the short-span TDP (Aim 1B). We will establish new genetically engineered mouse models (GEMMs) of breast cancer to validate that activation of the Ccne1 pathway or loss of Cdk12 activity, both in conjunction with Trp53 loss of function, induces medium- and long-span TDP configurations that mimic their human counterparts both in terms of TD span size and distribution (Aim 2A) and of the genomic features and genetic elements that are associated with and affected by TD formation (Aim 2B). We will also assess the tumor neo-antigen load of the TDP tumors emerging from the newly developed GEMMs and test whether immuno-oncology agents are effective against mammary tumors with the TDP configuration, as suggested by recently emerging clinical observations (Aim 2A). We will then use isogenic human cancer cell lines that are either proficient or deficient for BRCA1 activity, to determine the dynamics of de novo TD formation under different modes of cellular perturbation and as a function of BRCA1 status (Aim 3A). Finally, we will use the newly developed GEMMs to understand the evolutionary path to genome-wide TD distribution in the mammary gland, and to discern the dynamics of TDP emergence, both in terms of the rate of de novo TD formation and with respect to the timeline of breast tumorigenesis (Aim 3B). If successful, this proposal will uncover the root causes of a significant form of genomic instability in human cancer, the TDP, define the mutational dynamics leading to cancer formation in this condition, and generate model systems that can lead to the development of new and directed therapeutics against cancer growth.

NIH Research Projects · FY 2025 · 2020-09

PROJECT SUMMARY OVERALL The goal of the JCPG is to deploy our end-to-end pipeline to build, validate and disseminate precision models of human disease, and to accelerate the development of treatments for patients through advanced preclinical testing. Our central innovation is our ability to link world-class services efficiently and seamlessly to provide the best possible model development and preclinical testing pipeline for our partners. Our team includes leadership with a track record of building resource programs, experienced scientific, program, and project management staff, and the support of an experienced Bioinformatics Core for data analysis and dissemination. We have made outstanding progress in developing our Center and executing its goals during In the current funding phase, our expanded outreach efforts resulted in a growing number of new external project nominations for a diverse range of disease areas from investigators and patient groups from around the country. We are on track to exceed our model generation and phenotyping goals, creating alleles that include highly complex alleles with significant humanization and/or conditional potential. Our preclinical testing portfolio includes a variety of diseases, organ systems, and therapeutic approaches, with phenotyping and molecular readouts tailored to the characteristics of each project; our success is reflected in two projects started at JAX that have progressed to clinical trials. Our Bioinformatics Core developed a JCPG website, nomination portal and algorithms inform our model development strategies. Dozens of precision, validated models are now available for public distribution through JAX’s well- established and supported infrastructure. These successes reflect the JCPG’s ability to work effectively with researchers, clinicians, foundations and families to identify and delineate disease modeling needs and then create new mouse models that serve their needs. Our Specific Aims for the next phase reflect our ambition to expand our impact through the translation of human disease discoveries into precise, predictive models of disease rapidly impact therapeutic development: 1) To optimize and deploy a comprehensive, scalable, and flexible pipeline for the generation and characterization of precision mouse models of human disease and to share mouse model resources through the MMRRC. 2) To develop and execute a robust outreach, project nomination, and project management infrastructure that expands and facilitates access to our Center for clinicians, researchers, and foundations. 3) To accelerate the development of novel, precision therapeutics by linking patient data with new precision animal models, executing preclinical testing of novel therapeutics with networks of collaborative partners. 4) To integrate an analysis and dissemination infrastructure that will facilitate development of next-generation predictive models, support the integration of outcomes with human disease phenotypes, and promote data sharing. 5) To integrate our Center with other JAX programs, resources, and external-facing services to build connections to JAX’s deep expertise in mouse biology while developing a scalable, financially sustainable model for access to the JCPG.