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:9107397
- 负责人:
- 金额:$ 18.51万
- 依托单位:
- 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:
- 关键词:17q1219p138q24AddressAllelesBiological AssayBiologyBreastCandidate Disease GeneCategoriesChromosomesClustered Regularly Interspaced Short Palindromic RepeatsCodeColorectalCommunitiesComplexComplex Genetic TraitDNADNA SequenceDataDiseaseEmerging TechnologiesEnhancersEpigenetic ProcessEvaluationGene ExpressionGene TargetingGene-ModifiedGeneric DrugsGenesGeneticGenetic CodeGenetic RiskGenetic TranscriptionGenomeGenomic SegmentGoalsHealthHumanHuman BiologyHuman GeneticsLeadLungMalignant NeoplasmsMalignant neoplasm of ovaryMalignant neoplasm of prostateMapsMendelian disorderMethodsModificationOpen Reading FramesOutputOvarianPathway interactionsPredispositionPreventionProstateProteinsQuantitative Trait LociRegulatory ElementRiskSiteSusceptibility GeneTechniquesTechnologyTissuesValidationVariantbasecancer riskcancer typecell typechromosome conformation capturegene discoverygenetic risk factorgenetic variantgenome editinggenome wide association studyinterestmalignant breast neoplasmpromoterrisk varianttooltrait
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(由申请人提供):与孟德尔疾病形成鲜明对比的是,大多数复杂性状相关的常见变体映射到非蛋白质编码区。由于对于基因组的大得多的非蛋白质编码部分存在发育不太完善的遗传密码,因此鉴定非孟德尔/复杂性状的基因和致病等位基因存在挑战。鉴于全基因组关联研究(GWAS)发现与复杂性状相关的区域的快速性,基因和致病等位基因鉴定已成为严重的瓶颈。这项提案的总体目标是概述一个连贯的策略,以发现复杂性状背后的因果基因和等位基因。虽然该提案的重点是癌症,但这些策略是通用的,可以应用于任何非蛋白质编码位点。核心假设是癌症风险基因座是调节元件。最近的数据令人信服地表明,GWAS基因座富集的调控元件。调控元件可以控制基因的表达水平。致病基因和变异很难发现,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,环状染色体构象捕获(4C)和基因组编辑来识别致病基因和等位基因。第一个目标是在已经确定靶基因的风险基因座上发现致病等位基因。使用靶基因启动子作为4C的诱饵,我们将鉴定与启动子物理相互作用的基因组区域。这些相互作用区域中的每一个都是候选调控元件。与此同时,将对候选因果变异体进行重复的规则间隔短回文重复序列(CRISPR)评价。这些检测的信息将与遗传和表观遗传数据相结合,以确定因果变异。由于我们知道靶基因,因此预期致病等位基因位点的修饰将影响该基因的转录,并将提供致病变体鉴定的明确证据。目标将集中在确定致病基因和变异的风险位点,其中靶基因尚未确定。所研究的位点是乳腺癌、前列腺癌和卵巢癌的风险位点。我们特别假设该区域通过所有三种癌症的共同机制起作用。同样,我们将使用4C和CRISPR技术来定义致病变异和基因。在这个项目完成后,我们完全预计,我们将开始解开
引发人类前列腺癌的基因/途径。发现前列腺癌的潜在机制不仅可以为这种疾病的生物学提供信息,而且还可以揭示机会。
更合理地干预治疗和预防。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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MATTHEW L FREEDMAN其他文献
MATTHEW L FREEDMAN的其他文献
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{{ truncateString('MATTHEW L FREEDMAN', 18)}}的其他基金
Elucidating prostate cancer risk mechanisms through large-scale cistrome wide association studies
通过大规模顺反组广泛关联研究阐明前列腺癌风险机制
- 批准号:
10686418 - 财政年份:2022
- 资助金额:
$ 18.51万 - 项目类别:
Common biology underlying pleiotropic breast, prostate and ovarian cancer risk loci
多效性乳腺癌、前列腺癌和卵巢癌风险位点的共同生物学基础
- 批准号:
10366397 - 财政年份:2022
- 资助金额:
$ 18.51万 - 项目类别:
Common biology underlying pleiotropic breast, prostate and ovarian cancer risk loci
多效性乳腺癌、前列腺癌和卵巢癌风险位点的共同生物学基础
- 批准号:
10684639 - 财政年份:2022
- 资助金额:
$ 18.51万 - 项目类别:
Elucidation of the genetic mechanisms driving prostate tumorigenesis through integrative computational and functional approaches
通过综合计算和功能方法阐明驱动前列腺肿瘤发生的遗传机制
- 批准号:
10576263 - 财政年份:2021
- 资助金额:
$ 18.51万 - 项目类别:
Elucidation of the genetic mechanisms driving prostate tumorigenesis through integrative computational and functional approaches
通过综合计算和功能方法阐明驱动前列腺肿瘤发生的遗传机制
- 批准号:
10209764 - 财政年份:2021
- 资助金额:
$ 18.51万 - 项目类别:
Elucidation of the genetic mechanisms driving prostate tumorigenesis through integrative computational and functional approaches
通过综合计算和功能方法阐明驱动前列腺肿瘤发生的遗传机制
- 批准号:
10362714 - 财政年份:2021
- 资助金额:
$ 18.51万 - 项目类别:
Functional Effects of Ovarian Cancer Risk Variants
卵巢癌风险变异的功能影响
- 批准号:
10083194 - 财政年份:2017
- 资助金额:
$ 18.51万 - 项目类别:
Functional Effects of Ovarian Cancer Risk Variants
卵巢癌风险变异的功能影响
- 批准号:
9216819 - 财政年份:2017
- 资助金额:
$ 18.51万 - 项目类别:
Identifying causal variants and genes underlying breast cancer risk loci
识别乳腺癌风险位点的因果变异和基因
- 批准号:
9904556 - 财政年份:2016
- 资助金额:
$ 18.51万 - 项目类别:
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