Comprehensive approaches for understanding the functional impact of genetic variation and genetic complexity

Information

  • Research Project
  • 10021020
  • ApplicationId
    10021020
  • Core Project Number
    R01GM134274
  • Full Project Number
    5R01GM134274-02
  • Serial Number
    134274
  • FOA Number
    PA-18-484
  • Sub Project Id
  • Project Start Date
    9/19/2019 - 5 years ago
  • Project End Date
    7/31/2023 - a year ago
  • Program Officer Name
    KRASNEWICH, DONNA M
  • Budget Start Date
    8/1/2020 - 4 years ago
  • Budget End Date
    7/31/2021 - 3 years ago
  • Fiscal Year
    2020
  • Support Year
    02
  • Suffix
  • Award Notice Date
    7/29/2020 - 4 years ago

Comprehensive approaches for understanding the functional impact of genetic variation and genetic complexity

Project Summary/ Abstract: Our limited ability to relate genotype to phenotype is a major obstacle for biomedical research and personalized medicine. Currently only ~2% of germline missense variants have clinical interpretations, and the remainder, variants of uncertain significance (VUS), offer no information to inform diagnosis or guide treatment. As the clinical use of whole exome and genome sequencing increases, the number of VUS will skyrocket. Large-scale functional assays in model organisms are the only methods for variant interpretation currently poised to match the pace of variant discovery, and here we propose to extend their use to interpret genetic complexity. Our approach leverages the advent of low-cost, large-scale gene synthesis and the development of high throughput in vivo assays of protein function in model organisms, such as yeast. We propose a generalizable approach for determining the functional consequences of polymorphisms in human disease genes, including individual alleles, combinations of alleles in the same gene, and combinations of alleles in multiple genes in a pathway, on a massively parallel scale. The quantitative nature of our assay and the structure of our experimental design will allow us to compare the impact of allele combinations with their individual effects, and thus detect genetic epistasis (nonlinear genetic interactions) arising from naturally occurring human genetic variation outside of the limits of outbred human populations. Through this novel approach, we will not only explore the extent to which nonlinear interactions between human genes are pervasive or rare, but by placing them in the context of protein and metabolic pathway structure, we will gain insight into their molecular underpinnings. Our study will also provide an unprecedented amount of information about the contribution of individual amino acids to the function of the three disease-relevant enzymes in our study, and we will analyze our results in the context of their published crystal structures. Finally, we will develop new methods and assays that will expand the throughput, combinatorics, and number of assays available for functional analysis of human variation. We will pilot our approach using three human genes (OTC, ASS1, and ASL) associated with a class of metabolic disorders known as urea cycle disorders (UCD). Neonatal UCD is associated with severe enzyme deficiency. These infants rapidly develop high levels of ammonia, cerebral edema, and symptoms that can include seizures, coma, and death. Less severe forms may remain undiagnosed into childhood or adulthood. Late onset UCDs generally involve an environmental trigger (e.g. surgery, pregnancy, or chemical exposure) in individuals with reduced enzyme function. Diagnosis of the adult onset form is hampered by the fact that it often presents with symptoms such as episodic psychosis, bipolar disorder and major depression, and without treatment, prognosis is poor. Thus, knowledge of the functional implications of genetic variation in these genes has the potential to reduce the morbidity and mortality associated with delayed treatment or underdiagnosis.

IC Name
NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
  • Activity
    R01
  • Administering IC
    GM
  • Application Type
    5
  • Direct Cost Amount
    297590
  • Indirect Cost Amount
    236736
  • Total Cost
    534326
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    859
  • Ed Inst. Type
  • Funding ICs
    NIGMS:534326\
  • Funding Mechanism
    Non-SBIR/STTR RPGs
  • Study Section
    GCAT
  • Study Section Name
    Genomics, Computational Biology and Technology Study Section
  • Organization Name
    PACIFIC NORTHWEST RESEARCH INSTITUTE
  • Organization Department
  • Organization DUNS
    041332172
  • Organization City
    SEATTLE
  • Organization State
    WA
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    981224302
  • Organization District
    UNITED STATES