Jackson Laboratory

NIH Research Projects · FY 2025 · 2006-09

The goal of the annual Jackson Laboratory Short Course on Experimental Models of Human Cancer is to train graduate students, postdocs, and junior investigators in the basic science and application of experimental models of human cancer. The training program will immerse participants and faculty in a unique and highly integrated scientific environment and empower the next generation of scientists tackling human cancer. The integrated program will cover advances in three critical areas: experimental cancer models, modern technology to assess mechanisms and outcomes, and the interplay of the tumor and host genetics as well as tumor microenvironment and the immune system. It will teach classical approaches to mouse and human genetics, modern molecular genetic methodologies, computational and bioinformatics concepts, ontological standards, and scientific and medical ethics. Trainees will participate in lectures, workshops, multi-disciplinary scientific debates, networking and career development sessions, and poster sessions. They will receive practical training in bioinformatics, statistical genetics, and the use and analysis of PDX models. This course will take place at The Jackson Laboratory (JAX), which hosts an NCI-designated Basic Laboratory Cancer Center and is a global resource of mouse models. The proposed 8-day intensive, immersion course focused on graduate students, postdocs, and new investigators will promote active interaction and networking between the participants as well as with the outstanding cadre of lecturers and trainers. Additionally, the Short Course will be delivered in a hybrid format, with online/virtual access to the seminars and, where practical and feasible, the workshops: this was successfully piloted in 2022. The hybrid format broadens participation for scientists who could not otherwise attend. Attendees will be actively recruited, scholarships will be provided to enable in-person attendance, and a virtual option will enable participation by those that are unable to travel. Emphasis will also be placed on best practices for cancer research to address ongoing health care disparities, the need for studies of genetically representative models, and representation of a breadth of human backgrounds within genetic databases and samples.

NIH Research Projects · FY 2026 · 2004-07

PROJECT SUMMARY The goal of the Mouse Phenome Project is to support biomedical research by delivering a widely-accessed and highly functional data repository for well-documented disease-relevant phenotypic data from heterogeneous mouse populations. Studying model organisms can provide insight, aid in prioritization, and facilitate translation of research findings into practice by improving the interpretation of modeling and understanding human disease with insights gained from mouse phenotypic analysis across diverse populations. Broader global data integration is needed such that data can come from across populations with new representations, visualizations, and imputations. Better interoperation is needed to bring the data closer to human genetics with improved user interfaces for more efficient data selection such that less “mouse insider” insight is required. Our objectives are to provide a central repository for more breadth and unification of human disease-relevant data and better representation of measurement relevance to disease states, offering a unique and important venue for investigators needing to make their data public through NIH Data Management and Sharing Plans; to continually refine and develop tools and features to best locate, present, and analyze those datasets; and to maintain, enhance, and promote this resource to further enable quantitative, standardized and predictive phenotype studies and, in turn, facilitate new scientific advances. We will achieve these objectives in three Specific Aims. Aim 1: We will expand the Mouse Phenome Database to include more extensive phenotype data by curating, annotating, organizing, and archiving those data to enhance interpretative use of MPD and improve the representation of measurement-to-trait annotations. Aim 2: We will enhance the MPD tool set to enable multivariate biostatistical and statistical genetics analysis to support use of phenotypic data to interpret and model genetic variation in human disease. Aim 3: We will enhance the implementation of MPD as a set of modern APIs to enable more versatile machine access and to expose mouse data to quantitative analysis in light of human disease and other model organism empirical studies. Impact: The proposed efforts will help maximize the value of these data and provide the traceability and scientific rigor required for extension and translation. Completion of the proposed work will result in a powerful, interoperable system for public access to and analysis of mouse phenotype data and will ultimately provide researchers a seamless experience for the extrapolation of model organism genetics data to human genetic variation.

NIH Research Projects · FY 2025 · 2003-04

PROJECT SUMMARY Identification of interventions that extend mouse lifespan provides new insights into mechanisms of longevity determination in mammals and may lay the groundwork for eventual anti-aging therapies in humans. The NIA Interventions Testing Program (ITP) evaluates drugs proposed to extend mouse lifespan by retardation of aging or postponement of late life diseases. Interventions proposed by multiple collaborating scientists from the research community are tested, in parallel, at three sites (The Jackson Laboratory, University of Michigan and University of Texas), using very similar, standardized protocols, and using enough genetically heterogeneous mice to provide 80% power for detecting changes in lifespan of 10%, for either sex, after pooling data from any two of the test sites. One hundred and two such lifespan experiments, involving various doses of 66 distinct agents, have been initiated in the first twenty years of the ITP. Thirty-six experiments have involved comparative tests of multiple doses of effective agents, variable starting ages, or alternative dosing schedules. Statistically significant effects on longevity, in one or both sexes, have been documented and then confirmed for NDGA, rapamycin, acarbose, 17-α-estradiol (17aE2), and canagliflozin. Significant effects were also noted for Protandim, glycine, meclizine, captopril, and astaxanthin. Lifespan trials are now underway for 25 new agents. ITP survival results have also documented longevity benefits from four agents started in middle-age: rapamycin, acarbose, 17aE2, and canagliflozin. A Collaborative Interactions Program (CIP) has provided tissues from ITP drug-treated mice to an open, growing, international network of scientific collaborators, meeting 26 requests from 17 distinct laboratories in the previous five-year period. Plans for the next five-year period include additional lifespan ("Stage 1") studies, detailed studies ("Stage 2") of drugs found to increase lifespan, transition from the CIP to an Interventions Biospecimens Repository, additional diagnostic specificity in pathological assessments, inclusion of RNA-Seq data in all Stage 2 studies, and comprehensive pharmacokinetic assessments of drugs found to increase lifespan, as well as continued collaborative work with a network of scientists to study drug effects on postulated aging mechanisms and links to disease. Site-specific studies at The Jackson Laboratory will add a tests for heart, kidney, and bladder function in Stage 2 studies, and image analysis of tissues using machine learning. The work proposed should allow the ITP to continue to make major contributions to mammalian aging biology.

NIH Research Projects · FY 2025 · 2001-07

PROJECT SUMMARY/ABSTRACT – Overall Component Many aspects of human health and disease are genetically complex; that is, they arise from multiple interactions between genetic, developmental, and environmental factors. Understanding this complexity is the basis of personalized medicine. Unfortunately, human genetic studies are still limited in a number of ways including inadequate, retrospective medical records, formidable sample size requirements, insufficient statistical power to study genetic interactions, and insufficient mechanistic information about many genes. These obstacles are easily addressed using non-human, mammalian models, such as mice, that are designed for fine scale dissection of genetic complexity, i.e. systems genetics. The biomedical research community has made a significant investment in the genetically diverse inbred strains and genetic reference populations of mice as tools for systems genetics research. This proposal requests ongoing support for The Special Mouse Strain Resource (SMSR) at The Jackson Laboratory. The SMSR serves as the biorepository for these unique sets of strains, ensuring permanent and open access from high health status, quality-controlled, state-of-the-art facilities. The resource currently consists of more than 300 strains, including the widely used BXD and Collaborative Cross strain panels, but importantly, the strains available in the SMSR are changed and developed as dictated by the needs of research community. The major activities of the SMSR are to: i) archive, maintain, and distribute these strains to qualified biomedical researchers, ii) provide complete, accurate and accessible information related to the mouse resources, iii) confer with an external advisory board of thought leaders from the complex trait community to define current and future resources, iv) provide leadership in best practices for research and reproducibility using SMSR resources. The SMSR also provides infrastructure, outreach and collaborative opportunities for the development of new tools for complex trait analysis, as well as access to existing strains and populations for large-scale multicenter projects; and conducts research to expand tools for genetic engineering of specialized mapping strains.

NIH Research Projects · FY 2025 · 2000-12

PROJECT SUMMARY/ABSTRACT The laboratory mouse is the preeminent animal model system for investigation into the biology and genetics of human cancer. Mouse models have provided key insights into cancer susceptibility, the molecular genetics of tumor suppressor and oncogenes, and therapy response in pre-clinical and co-clinical studies. Human tumors engrafted into immune compromised and humanized mice (aka, Patient Derived Xenografts) are playing an increasingly important role as a powerful preclinical platform for testing new cancer treatments. The Mouse Models of Human Cancer (MMHC) database is a unique on-line compendium of mouse models for human cancer. MMHCdb provides electronic access to expertly curated and harmonized information on diverse mouse models for human cancer along with tools for accessing and visualizing associated data from these models. This in turn, facilitates the selection of appropriate strains of mice for cancer genetics research. MMHCdb integrates data derived from peer-reviewed literature and from direct submissions from researchers. Data in MMHCdb are also obtained from other bioinformatics resources including PathBase, HUGO Human Gene Nomenclature database, the Gene Expression Omnibus (GEO), and ArrayExpress. In this proposal we describe our plans for the continued development of MMHCdb with an emphasis on expanded support for analysis of tumor genomic data and drug response data from Patient Derived Xenograft models. To accomplish these goals we will build on successful collaborations to develop data standards for PDX models that are now widely adopted. The major goals for the project renewal include the following: · continue to populate MMHCdb with data on strain-specific patterns of tumorigenesis in inbred, mutant, and genetically engineered mice, · leverage collaborations with Seven Bridges and PDXNet to analyze genomic data for PDX models using a common analysis pipeline, · develop a platform for the analysis of PDX genomic and drug response data, and · support the infrastructure of MMHCdb and our user community through ongoing database maintenance, development of new software components, user support services, and community outreach activities.

NIH Research Projects · FY 2026 · 1998-02

PROJECT SUMMARY/ABSTRACT Understanding how a pathogenic mutation leads to disease is extremely important for prognosis, for developing effective treatments and for assessing likely response to treatment. Genes do not act in isolation. Gene mutations typically do not cause the disease pathology themselves - rather, they activate or deactivate biological pathways, affecting a set of molecules whose function results in the manifestation and progression of disease phenotypes. Furthermore, evidence from several groups including our preliminary omics studies suggests that alterations in different sets of molecules may lead to multiple disease phenotypes, further adding to the complexities underlying genetic mutations and their effects. The goal of this application is to delve into this complexity by looking closely at three different disease aspects of the Mfrprd6 mutation, namely, photoreceptor degeneration, hyperopia and fundus spotting, and examine their association with three intermediary phenotypes, aberrant DHA levels, cytoskeletal derangements and immune cell responses. Our approach is to use clinical, functional and biochemical tests to provide a deep characterization of the disease phenotypes and to examine associated cellular changes using single-nuclear transcriptomics and proteomic analyses. These phenotypic and genomics data will be analyzed using computational methods to identify the earliest perturbations in these models, and to determine in proof-of- principle experiments, whether it is possible to manipulate the disease outcomes with nutriceutical and pharmacological interventions. Successful completion of our studies will identify the pathogenic pathways that result in observed disease phenotypes, due to the disruption of Mfrp function, revealing potential therapeutic targets that may play a role in a broad range of retinal genetic diseases with similar phenotypic manifestations. .

NIH Research Projects · FY 2025 · 1997-08

The overall mission of The Jackson Laboratory Cancer Center (JAXCC) is to bring genomic solutions to cancer medicine. We continue to develop a culture of scientific discovery, excellence, transdisciplinary research, and collaboration to yield tangible benefits to cancer patients extending beyond the generation of new knowledge. Our basic research goal is to tackle the question of “Genetics and Genomics of Aging and Cancer”, while our translational intent is to contribute new concepts, technologies, and clinical education initiatives originating from basic science to advance precision cancer medicine. The JAXCC has been supporting the basic research of its members as well as cancer researchers at large for over 40 years by focusing on genetic models of cancer. This history laid the groundwork for development of a precision genetics Program focused on therapeutic resistance and bringing novel solutions to overcome it. Building on our success, our Research Program is evolving to add the dimension of aging to further our efforts towards translating our basic cancer research discoveries for the benefit of cancer patients. The JAXCC has 37 Program members and 22 Affiliate members across our Center’s two research campuses, contributing to a single highly integrated Program. Our research is supported by three interactive and complementary Shared Resources, which provide access to cutting-edge technologies and expertise. JAXCC members are experts in varied fields converging on the cancer problem by bringing novel approaches in a concerted, transdisciplinary manner. These approaches and expertise include strengths in complex genetics, functional genomics, cross-species integration, and the development of innovative animal, cellular, and computational models for studying aging and cancer. Our organizational structure allows us to support such an integrated strategy to achieve impactful contributions that ultimately lead to advances in precision cancer medicine.

NIH Research Projects · FY 2025 · 1997-07

PROJECT SUMMARY As the cost of genome-scale sequencing continues to decrease and new technologies for genome editing become widely adopted, the laboratory mouse is more important than ever as a model system for understanding the biological significance of human genetic variation and for advancing the emergence of genomic medicine. The Mouse Genome Database (MGD) has a unique and strategic role as a community resource for facilitating the use of the laboratory mouse for understanding genomics underlying human biology and disease. MGD serves three major user communities: (i) biomedical researchers who use mouse experimentation to investigate genetic and molecular principles of biology and disease processes, (ii) translational scientists who use the laboratory mouse to model human disease, and (iii) bioinformaticians/ computational biologists who use the rich integrated data MGD provides to develop algorithms and bioinformatics tools for data analysis and interpretation. During the project period, we will continue to curate and integrate new genetic, genomic, variant, functional, phenotypic, and human disease model data essential to researchers using the laboratory mouse in biomedical research. We will make these data freely available through a variety of web-based and programmatic user interfaces. Our core aims include: (i) maintaining the canonical catalog of mouse genome features, (ii) serving as the authoritative data for mouse functional annotations, and (iii) maintaining a comprehensive catalog of mouse mutations and strains and their phenotype and disease model associations. To support our aims, we will maintain cost-effective software, database, and hardware using industry best practices. We will maintain MGD's secure infrastructure through regular maintenance, upgrades, and planned evolution. We will leverage existing software components from the Alliance of Genome Resources and other resources where possible and focus our software development activities on unique infrastructure needed to support our core aims. To ensure the greatest impact of MGD in the broader scientific community, we will provide robust user support and outreach through online user documentation, tutorials, training workshops, and one-on-one assistance using a variety of communication modalities and major social media tools. We will actively solicit community input, data submissions, and collaborations.