# Applied Research Section

> **NIH NIH U42** · JACKSON LABORATORY · 2021 · $124,334

## Abstract

PROJECT ABSTRACT
Systems genetics endeavors to explain the integration, coordination, and expression of genetic information
across phenotypes at all scales - molecular, cellular, physiological, and population; and across many contexts
– health, disease, infection, environment, etc. These systems-level approaches operate on networks and have
the potential to explain higher-order functions and emergent properties of biological systems. With the
explosion of -omics technologies, advanced computational methods for big data analysis, and the availability of
advanced genetic reference sequences for human and model organism populations, systems genetics
approaches are more powerful than ever. Our proposed pilot project will generate the methodologies,
capabilities, infrastructure, and proof-of-concept for an in vitro systems genetics service platform. This project
is responsive to the rising interest in systems genetics resources, a key growth area for the MMRRC
consortium. Moreover, while the scope of project is currently limited to the founder inbred strains of the CC/DO
genetic reference populations, it complements other funded efforts in our laboratories and across the MMRRC
consortium to develop resources from genetic reference laboratory mouse populations to support the growth of
the systems genetics community.

## Key facts

- **NIH application ID:** 10101705
- **Project number:** 5U42OD010921-12
- **Recipient organization:** JACKSON LABORATORY
- **Principal Investigator:** LAURA G REINHOLDT
- **Activity code:** U42 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $124,334
- **Award type:** 5
- **Project period:** 2010-01-01 → 2025-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10101705

## Citation

> US National Institutes of Health, RePORTER application 10101705, Applied Research Section (5U42OD010921-12). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10101705. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*