Genetic dissection of transcriptional and organismal phenotypes in C. elegans

线虫转录和有机表型的遗传解剖

• 批准号: 7652533
• 负责人: LEONID KRUGLYAK
• 金额: $ 32.94万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-16 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7652533
• 关键词: Affect; Agriculture; Alleles; Behavioral; Behavioral Assay; Bioinformatics; Biological; Biological Assay; Biomedical Research; Caenorhabditis elegans; Candidate Disease Gene; Chromosome Mapping; Collection; Complex; Data; Data Analyses; Development; Diagnosis; Disease; Disease susceptibility; Dissection; Distant; Environment; Environmental Risk Factor; Evolution; Gene Expression; Genes; Genetic; Genetic Polymorphism; Genotype; Haplotypes; Hawaii; Hawaiian population; Hot Spot; Human; Individual; Joints; Location; Maps; Measures; Medical; Molecular Profiling; Nature; Nematoda; Organism; Parents; Phenotype; Predisposition; Prevention; Public Health; RNA Interference; Recombinants; Regulation; Research; Research Personnel; Resolution; Role; Sample Size; Single Nucleotide Polymorphism; Spottings; Staging; Transcript; Transgenic Organisms; Variant; Yeasts; age related; base; design; expectation; genetic linkage analysis; human disease; improved; insight; interest; loss of function mutation; programs; research study; segregation; success; trait; young adult

DESCRIPTION (provided by applicant): The broad objective of the proposed research is high-resolution genetic dissection of a large number of complex and quantitative traits in the nematode worm C. elegans. Success in understanding the genetic basis of phenotypic variation in a metazoan will provide critical guidance for the design of genotype- phenotype studies in humans and other organisms of medical, biological, and agricultural interest, as well as supply insights into regulatory networks that connect genetic and phenotypic variation and into the evolution of phenotypic variation. Specifically, we will develop and genotype a large set of high-resolution recombinant inbred lines (RILs) from a cross between Bristol and Hawaiian isolates, and genotype a diverse collection of wild isolates. We will then use microarrays to generate expression profiles for the RILs and wild isolates, and carry out linkage and association analysis to define loci that affect gene expression. We will identify individual loci as well as pairs of interacting loci. We will determine which loci affect expression through polymorphisms in the encoding gene or its nearby control regions, and which affect expression of genes at distant locations. We will identify "hot spots"-loci that affect the expression of many genes, and use bioinformatic approaches to integrate the results with regulatory networks. We will also assay behavioral and age-related phenotypes in the RILs, map loci that affect these phenotypes, and integrate these phenotypes with transcript data. Finally, we will identify the genes and polymorphisms that underlie several transcriptional, behavioral and age-related phenotypes and confirm their roles through transgenic and RNAi experiments. We have already successfully carried out similar studies in yeast, and expect that the results will be even richer in C. elegans, given its more complex regulation in the context of multicellularity and development. Relevance to public health: Genetic factors underlie susceptibility to virtually every human disease. Much of current biomedical research is based on the expectation that identifying these factors is a crucial step in improving diagnosis, prevention, and treatment. Identification is difficult because the genetic basis of common disorders is complex, with disease susceptibility influenced by multiple genes in interaction with each other and with environmental factors. The proposed research will improve our understanding of such interactions and will provide critical guidance for studies of the genetic basis of common human diseases.

描述（由申请人提供）：拟议研究的广泛目标是对线虫C中大量复杂和数量性状进行高分辨率遗传解剖。优美的成功地理解后生动物表型变异的遗传基础将为人类和其他生物的基因型-表型研究的设计提供重要的指导，以及提供对连接遗传和表型变异的调控网络和表型变异进化的见解。具体来说，我们将开发和基因型的一个大的集合的高分辨率重组自交系（RILs）之间的布里斯托和夏威夷分离株的杂交，和基因型的野生分离株的多样化集合。然后，我们将使用微阵列生成RILs和野生分离株的表达谱，并进行连锁和关联分析，以确定影响基因表达的位点。我们将识别单个基因座以及相互作用的基因座对。我们将确定哪些基因座通过编码基因或其附近控制区的多态性影响表达，以及哪些基因座影响远处基因的表达。我们将确定“热点”-影响许多基因表达的位点，并使用生物信息学方法将结果与调控网络相结合。我们还将在RILs中检测行为和年龄相关的表型，绘制影响这些表型的基因座，并将这些表型与转录数据整合。最后，我们将通过转基因和RNAi实验来确定几种转录、行为和年龄相关表型的基因和多态性，并确认它们的作用。我们已经在酵母中成功地进行了类似的研究，并期望在C. elegans，因为它在多细胞和发育的背景下更复杂的调节。 与公共卫生的相关性：遗传因素是几乎所有人类疾病易感性的基础。目前的大部分生物医学研究都是基于这样的期望，即识别这些因素是改善诊断，预防和治疗的关键步骤。鉴定是困难的，因为常见疾病的遗传基础是复杂的，疾病易感性受多个基因相互作用和环境因素的影响。拟议的研究将提高我们对这种相互作用的理解，并将为研究常见人类疾病的遗传基础提供重要指导。