Genomic and epigenomic effects of large CNV in neurons from iPSC

iPSC 神经元中大 CNV 的基因组和表观基因组效应

• 批准号: 8357036
• 负责人: Alexander Eckehart Urban
• 金额: $ 235.5万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-30 至 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8357036
• 关键词: 16p11.2; 22q11.2; 3q29; Affect; Autistic Disorder; Brain; Cell Line; Cell physiology; ChIP-seq; Complex; Copy Number Polymorphism; DNA; DNA Methylation; Development; Disease; Epilepsy; Etiology; Gene Expression Profile; Gene Expression Regulation; Genes; Genetic; Genome; Genomics; Health; Heart Diseases; Human; Immune system; Knowledge; Laboratories; Maps; Mental Retardation; Modeling; Molecular; Molecular Mechanisms of Action; Neurons; Pattern; Phenotype; Predisposing Factor; Process; Public Health; RNA; Research; Resolution; Schizophrenia; Techniques; Testing; Tissues; Variant; abstracting; autism spectrum disorder; base; combinatorial; disease phenotype; epigenomics; histone modification; human tissue; induced pluripotent stem cell; malformation; neuron development; neuropsychiatry; next generation; novel; proband; programs; public health relevance; tissue culture; transcription factor

DESCRIPTION (Provided by the applicant) Abstract: I propose to study through which molecular mechanisms of genetic control it is that large genomic Copy Number Variants (CNVs) exert their effects on gene regulation, dynamically over cellular differentiation and cellular functioning. We aim to establish a novel research program and paradigm in our laboratory that combines the use of induced Pluripotent Stem Cells (iPSC) and multi-level, comprehensive and integrated analysis of genomic and epigenomic layers of control and activity. In the process we will be testing several novel hypotheses on the molecular mechanisms through which CNVs affect gene regulation and thus cellular and eventually organismal phenotypes. This will also serve as a model for smaller CNVs and their potentially subtle and cumulative or combinatorial yet potentially substantive effects on phenotype in health and disease. Copy Number Variation (CNV) is common in the genome of healthy humans and is associated with phenotypic variation. CNV is also frequently and strongly associated with major disease phenotypes, especially in neuropsychiatric diseases that involve an aberrant development of the brain such as schizophrenia and autism. There are now several prominent examples for CNVs that are strongly associated with neuropsychiatric disorders such as schizophrenia, autism, mental retardation and epilepsy (22q11.2 deletions, 1q21.1 deletions and duplications, 15q13.3 deletions, 16p11.2 deletions and duplications, 3q29 microduplications). CNVs (and sometimes the same CNVs as mentioned above) are also strongly associated with malformation diseases of the heart as well as in phenotypes that involve the functioning of the immune system. CNVs are therefore an important phenomenon to study both in its own right as a strong predisposing factor for disease as well as an enticing point of entry for the better understanding of the molecular etiology of complex diseases with a strong and complex genetic and genomic component. A major barrier to a better understanding of how the molecular mechanisms through which CNV affect phenotype is the lack of access to relevant human tissues that carry a given disease associated CNV, for example neuronal tissue cultures with a large genomic deletion that is strongly associated with schizophrenia or autism. The use of iPSC lines from probands with a given CNV promises to overcome this barrier and will allow us to observe the effects of CNVs on a molecular level in the relevant tissue as it progresses along a developmental trajectory and then settles into the neuronal phenotype. The complete and multilevel high-resolution genomics and epigenomics analyses based on massively parallel DNA next-generation-sequencing will include comprehensive transcriptome analyses by RNA-Seq, meDNA- Seq to study DNA methylation patterns and ChIP-Seq to map regulatory histone modifications and transcription factor networks. Public Health Relevance: Neurodevelopmental, neuropsychiatric disorders such as schizophrenia and autism spectrum disorders are a major public health concern. Copy Number Variations are amongst the candidate loci with the strongest association with such diseases but they typically affect multiple genes and only very little basic knowledge about their molecular mechanisms of action exists. Our project will create a new research paradigm into the effects of CNV during neuronal development by combining iPSC techniques with comprehensive nextgeneration genomics analyses.

描述（申请人提供） 摘要：我建议研究遗传控制的分子机制，这是大基因组拷贝数变异（CNV）对基因调节的影响，动态地对细胞分化和细胞功能进行动态。我们旨在在我们的实验室中建立一个新颖的研究计划和范式，该计划结合了诱导的多能干细胞（IPSC）以及对控制和活性的基因组和表观基因组层的多层次，全面和综合分析。 在此过程中，我们将对CNV影响基因调节的分子机制进行几种新假设，从而通过这些假设，从而影响细胞和最终的生物表型。 这也将作为较小的CNV及其潜在的微妙，累积或联合性但可能对健康和疾病表型的实质性影响的模型。拷贝数变化（CNV）在健康人的基因组中很常见，并且与表型变异有关。 CNV也经常与主要疾病表型有关，尤其是在涉及精神分裂症和自闭症等大脑异常发育的神经精神疾病中。现在有几个与精神分裂症，自闭症，智力低下和癫痫症等神经精神疾病密切相关的CNV的突出例子（22q11.2删除，1q21.1删除和复制，15q13.3删除，15q13.3删除，16p11.2删除和删除量和dueletations and duletations and dupleations，3q2q29 quic29 sicrodue。 CNV（有时与上述CNV相同）也与心脏的畸形疾病以及涉及免疫系统功能的表型密切相关。因此，CNV是一个重要的现象，可以自身研究作为疾病的强大诱因，也是诱人的入境点，以更好地理解具有强大而复杂的遗传和基因组成分的复杂疾病的分子病因。 更好地理解CNV影响表型的分子机制的主要障碍是缺乏携带与给定疾病相关的CNV的相关人体组织，例如具有与精神分裂症或自闭症密切相关的大基因组缺失的神经元组织培养物。使用具有给定CNV的概率的IPSC线的使用有望克服该障碍，并使我们能够在相关组织中观察CNV对分子水平的影响，因为它沿着发育轨迹进行，然后沉降到神经元表型中。基于大规模平行DNA的下一生殖顺序的完整和多级高分辨率基因组学和表观基因组学分析将包括RNA-SEQ，MEDNA-SEQ的全面转录组分析，以研究DNA甲基化模式和CHIP-SEQ，以绘制调节性的组蛋白修饰和转录因子网络。 公共卫生相关性：神经发育，神经精神疾病（例如精神分裂症和自闭症谱系障碍）是一个主要的公共卫生问题。拷贝数的变化是与此类疾病最强关联的候选基因座之一，但它们通常会影响多个基因，并且对其分子作用机理的基本知识仅很少。我们的项目将通过将IPSC技术与全面的下一代基因组学分析相结合，从而为CNV在神经元开发过程中的影响创造一个新的研究范式。

项目成果

Identification of Human Neuronal Protein Complexes Reveals Biochemical Activities and Convergent Mechanisms of Action in Autism Spectrum Disorders.

• DOI: 10.1016/j.cels.2015.11.002
• 发表时间: 2015-11-25
• 期刊: Cell systems
• 影响因子: 9.3
• 作者: Li J;Ma Z;Shi M;Malty RH;Aoki H;Minic Z;Phanse S;Jin K;Wall DP;Zhang Z;Urban AE;Hallmayer J;Babu M;Snyder M
• 通讯作者: Snyder M

Comprehensive performance comparison of high-resolution array platforms for genome-wide Copy Number Variation (CNV) analysis in humans.

• DOI: 10.1186/s12864-017-3658-x
• 发表时间: 2017-04-24
• 期刊: BMC genomics
• 影响因子: 4.4
• 作者: Haraksingh RR;Abyzov A;Urban AE
• 通讯作者: Urban AE