Quantitative genetic analyses of conserved C. elegans signaling pathways
Quantitative genetic analyses of conserved C. elegans signaling pathways
批准号:
7749631
负责人:
Erik Christian Andersen
金额:
$4.72万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-01 至 2011-08-31
关键词:
AllelesAnimal ModelBehavioral AssayBiological AssayCaenorhabditis elegansCollectionCopperCoupledDevelopmentDiabetes MellitusDiseaseDisease PathwayEnglandEnhancersEnvironmentEpitheliumEtiologyExposure toGene-ModifiedGenesGeneticGenetic EpistasisGenetic PolymorphismGenetic VariationGenotypeHawaiiHawaiian populationHeat Stress DisordersHigh temperature of physical objectHumanIncidenceIndividualInsulinInsulin-Like Growth Factor ILarvaMalignant NeoplasmsMapsMeasuresMinorModificationMutationNatural SelectionsNematodaOutcomeParaquatPathway interactionsPhenotypePheromonePopulationPredispositionPseudomonas aeruginosaQuantitative GeneticsRecombinantsResearch PersonnelResearch ProposalsResistanceRiskSaltsSeveritiesSeverity of illnessSignal PathwaySignal TransductionStagingStressTechniquesTestingTimeTransforming Growth Factor betaVariantdisease-causing mutationgenetic analysisgenome wide association studyhuman diseasemutantnovelnovel therapeuticspathogenpublic health relevanceresponsetrait
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英文摘要
DESCRIPTION (provided by applicant): Mutations in many genes interacting with each other and with the environment cause most common human diseases. However, these mutations are difficult to identify because the majority cause small phenotypic effects and genetic modifiers can alter the severity of a disease. Numerous genes of large effect are known, but the genes of modest effect that predispose certain individuals to disease are less well known and vary in populations. Therefore, the same mutation that causes a severe disease in one genetic background may not cause the same severity of disease in a different genetic background. Using the genetic background differences among individuals in a population, quantitative genetic studies can identify the genes that modify disease predisposition. Caenorhabditis elegans facilitates the identification of human disease genes because most cell-signaling pathways are conserved, especially the TGF-beta and insulin pathways. In this study, I will use C. elegans quantitative genetics coupled with classical genetic epistasis to identify the genes of both major and modest effects on conserved TGF-beta and insulin pathways. First, I will score a collection of recombinant inbred lines (RILs) created from the reference strain from England and a polymorphic strain from Hawaii for pathway phenotypes. These quantitative trait analyses will rapidly identify the major effect genes that control any phenotypic differences. Next, I will determine whether subtle genetic modifiers exist in other strain backgrounds by crossing extant mutations from the reference genetic background into the Hawaiian genetic background and scoring for suppression or enhancement of TGF-beta and insulin pathway phenotypes. Last, I will create sensitized RIL collections to facilitate the identification of modest-effect genes that alter TGF-beta and insulin pathway activities.
Public Health Relevance: Common disease-causing mutations are time-consuming and costly to identify in humans. Because the TGF-beta and insulin pathways are similar in the simple nematode C. elegans as in humans, genes that modify these pathways can be rapidly and cheaply identified. These modifier genes will broaden our understanding of diseases associated with these pathways, like epithelia-derived cancers and diabetes, and suggest new therapeutics.
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