4C and Genome Editing for Causal SNP and Gene Discovery at Cancer Risk Loci

4C 和基因组编辑用于癌症风险位点的因果 SNP 和基因发现

基本信息

批准号：
8959140
负责人：
MATTHEW L FREEDMAN
金额：
$ 22.32万
依托单位：
DANA-FARBER CANCER INST
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-01 至 2017-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8959140
关键词：
17q12 19p13 8q24 Address Alleles Biological Assay Biology Breast Candidate Disease Gene Categories Chromosomes Clustered Regularly Interspaced Short Palindromic Repeats Code Colorectal Communities Complex Complex Genetic Trait DNA DNA Sequence Data Disease Emerging Technologies Enhancers Epigenetic Process Evaluation Gene Expression Gene Targeting Gene-Modified Generic Drugs Genes Genetic Genetic Code Genetic Risk Genetic Transcription Genome Genomic Segment Goals Human Human Biology Human Genetics Lead Lung Malignant Neoplasms Malignant neoplasm of ovary Malignant neoplasm of prostate Maps Mendelian disorder Methods Modification Molecular Conformation Open Reading Frames Output Ovarian Pathway interactions Predisposition Prevention Prostate Proteins Quantitative Trait Loci Regulatory Element Risk Site Susceptibility Gene Techniques Technology Tissues Validation Variant base cancer risk cancer type cell type gene discovery genetic risk factor genetic variant genome editing genome wide association study interest malignant breast neoplasm promoter public health relevance risk variant tool trait

项目摘要

DESCRIPTION (provided by applicant): In stark contrast to Mendelian disorders, the majority of complex trait-associated common variants map to non-protein coding regions. Since there is a less well-developed genetic code for the much larger non- protein coding portion of the genome, identifying the gene(s) and causal alleles underlying non- Mendelian/complex traits presents a challenge. Given the rapidity with which genome wide association studies (GWAS) are discovering regions associated with complex traits, gene and causal allele identification have become severe bottlenecks. The overall goal of this proposal is to outline a coherent strategy to discover causal genes and alleles underlying complex traits. While the proposal focuses on cancer, the strategies are generic and can be applied to any non-protein coding locus. The central hypothesis is that cancer risk loci are regulatory elements. Recent data convincingly demonstrate that GWAS loci are enriched for regulatory elements. Regulatory elements can control the level of expression of genes. Causal genes and variants are difficult to discover because the scientific community is less adept at annotating the non-protein coding portion of the genome. This proposal seeks to utilize two powerful tools, circular chromosome conformation capture (4C) and genome editing to identify causal genes and alleles. The first aim will discover the causal alleles at risk loci where a target gene has already been identified. Using the target gene promoter as a bait for 4C, we will identify the genomic regions that are physically interacting with the promoter. Each of these interacting regions are candidate regulatory elements. In parallel, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) evaluation of the candidate causal variants will be performed. Information from these assays will be integrated with genetic and epigenetic data to define the causal variant. Since we know the target gene, modifications at the causal allele site will be expected to influence transcription of this gene and will provide definitive proof of causal variant identification. Aim will focus on identifying the causal gene and variant at a risk locus where a target gene has not been identified. The locus under study is a risk locus for breast, prostate, and ovarian cancers. We specifically hypothesize that this region is acting through a common mechanism for all three cancers. Again, we will employ 4C and CRISPR technologies to define the causal variant and gene. At the completion of this project, we fully anticipate that we will have begun to unravel the genes/pathways that initiate human prostate cancer. Discovering the mechanisms underlying prostate cancer will not only inform the biology of this disease, but may also reveal opportunities to more rationally intervene in treatment and prevention.

描述（由适用提供）：与孟德尔疾病形成鲜明对比的是，大多数复杂性状相关的共同变体映射到非蛋白质编码区域。由于基因组的更大的非蛋白质编码部分的遗传密码不太发达，因此识别了非孟德尔/复杂性状的基因和因果等位基因和因果等位基因提出了挑战。鉴于基因组广泛的关联研究（GWAS）发现与复杂性状相关的区域，基因和因果等位基因鉴定已成为严重的瓶颈。该提案的总体目标是概述一项连贯的策略，以发现复杂性状的基因和等位基因。尽管该提案着重于癌症，但这些策略是通用的，可以应用于任何非蛋白质编码基因座。中心假设是癌症风险基因座是调节元素。最近的数据令人信服地表明，GWAS语言环境富含监管元素。调节元素可以控制基因表达水平。因果基因和变体很难发现，因为科学界不太擅长注释基因组的非蛋白质编码部分。该提案旨在利用两种强大的工具，即圆形染色体会议捕获（4C）和基因组编辑来识别毒素基因和等位基因。第一个目的将发现已经确定了靶基因的风险基因座的catus虫等位基因。使用靶基因启动子作为4C的诱饵，我们将确定与启动子物理相互作用的基因组区域。这些相互作用的区域中的每一个都是候选调节元素。同时，将对候选因果变异的定期间隔短的短滴定重复序列（CRISPR）评估。这些测定法的信息将与遗传和表观遗传数据集成，以定义因果变异。由于我们知道靶基因，因此预计因果等位基因位点的修饰将影响该基因的转录，并将提供因果变异鉴定的明确证明。 AIM将重点放在尚未鉴定靶基因的风险基因座上的因果基因和变体上。研究的基因座是乳房，前列腺和卵巢癌的风险基因座。我们特别假设该区域正在通过所有三种癌症的共同机制作用。同样，我们将采用4C和CRISPR技术来定义因果变体和基因。该项目完成后，我们完全预计我们将开始解开启动人类前列腺癌的基因/途径。发现前列腺癌潜在的机制不仅会为生物学提供该疾病的生物，而且还可能揭示机会更合理地干预治疗和预防。