Massively-parallel functional interrogation of psychiatric genetics

精神遗传学的大规模并行功能询问

• 批准号: 9310141
• 负责人: Feng Zhang
• 金额: $ 109.75万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-23 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9310141
• 关键词: Animal Model; Animals; Biological; Biological Assay; Biological Models; Biological Sciences; Breeding; CRISPR/Cas technology; Cell Count; Cell model; Cells; Code; Coupled; DNA Sequence Alteration; Data; Derivation procedure; Disease; Disease model; Engineering; Epigenetic Process; Generations; Genes; Genetic; Genetic Determinism; Genetic Variation; Genetic study; Genome; Genomic Segment; Genomics; Genotype; Guide RNA; Heterogeneity; In Vitro; Interneurons; Knock-out; Libraries; Link; Maps; Medicine; Mental disorders; Methodology; Methods; Missense Mutation; Modeling; Modification; Molecular; Mutagenesis; Mutation; Mutation Analysis; Nervous system structure; Neurons; Oxytricha; Parvalbumins; Process; RNA; Research Personnel; Schizophrenia; Series; Stem cells; System; Technology; Testing; Time; Tissues; Transcriptional Activation; Transgenic Animals; Untranslated RNA; Variant; Work; base; cell type; deletion analysis; gene correction; gene interaction; genetic variant; genome editing; genome sequencing; genome wide association study; genome-wide; high throughput screening; human genome sequencing; in vitro Model; in vivo; in vivo Model; innovation; interest; knockout gene; mammalian genome; neuropsychiatric disorder; new technology; novel; nuclease; psychogenetics; public health relevance; screening; stem cell technology; tool; working group

 DESCRIPTION (provided by applicant): The rapid advances in human genome sequencing has generated a large amount of data and consequently a large number of hypotheses. For psychiatric disease, a number of landmark studies have led to lists of genetic variations that are linked to specific diseases. However, functional testing of these hypotheses has remained challenging due to a lack of appropriate model systems and high-throughput functional assays. Here we propose to develop and apply a series of high-throughput genome perturbation methodologies to enable the rapid identification of causal genetic variants from large-scale genetics data. The technology we propose to develop will be very broadly applicable and has the potential to radically transform the scale and rate of discovery across different biomedical fields. Three complementary technologies will be developed as a part of this proposal: 1. Functional screening methods to enable rapid identification of reprogramming factors for specific cell types. By using genome-scale transcription activation or epigenetic reprogramming libraries, we will establish a systematic approach to reverse-engineer the sufficient combinations of reprogramming factors for neuron subtypes that are relevant for different neuropsychiatric diseases, such as parvalbumin positive interneurons in schizophrenia. 2. Large-scale and systematic genome perturbation tools to enable massively-parallel functional testing of genetic variants, to enable narrowing of the long lists of correlated genetic variants to a short list of causal variants. We will establish genetic perturbation technologies to enable multiplex and systematic deletion or mutational analysis of coding and non-coding genomic regions, as well as probing of their epigenetic states, to identify causal genetic variants. 3. Efficient and precise genome modification technologies to enable rapid introduction of causal variants into cellular or animal models to enable elucidation of their disease-causing mechanisms. Whereas nuclease-based genome editing systems enables efficient gene knockout, gene insertion or gene correction remains inefficient. We will characterize a novel programmed genome rearrangement mechanism and develop it into a technology for efficient and precise mammalian genome editing. This will significantly accelerate the generation of cellular and animal models Given the broad applicability of this technology, the impact of this proposed work will be far reaching and will radically transform existing experimental approaches for studying gene interactions in all fields of life science and medicine.

 描述（由申请人提供）：人类基因组测序的快速发展产生了大量的数据，从而产生了大量的假设。对于精神疾病，许多具有里程碑意义的研究已经列出了与特定疾病相关的遗传变异列表。然而，由于缺乏适当的模型系统和高通量功能测定，这些假设的功能测试仍然具有挑战性。在这里，我们建议开发和应用一系列高通量基因组扰动方法，以便能够从大规模遗传学数据中快速识别因果遗传变异。我们建议开发的技术将具有非常广泛的适用性，并有可能从根本上改变不同生物医学领域的发现规模和速度。作为该提案的一部分，将开发三种互补技术： 1. 功能筛选方法，能够快速识别特定细胞类型的重编程因子。通过使用基因组规模的转录激活或表观遗传重编程文库，我们将建立一种系统方法，对与不同神经精神疾病相关的神经元亚型（例如精神分裂症中的小白蛋白阳性中间神经元）进行逆向工程重编程因子的充分组合。 2.大规模和系统的基因组扰动工具，能够对遗传变异进行大规模并行功能测试，从而能够将相关遗传变异的长列表缩小到因果变异的短列表。我们将建立遗传扰动技术，以实现对编码和非编码基因组区域的多重和系统性删除或突变分析，以及探测其表观遗传状态，以识别因果遗传变异。 3. 高效、精确的基因组修饰技术，能够将致病变异快速引入细胞或动物模型中，从而阐明其致病机制。虽然基于核酸酶的基因组编辑系统可以实现有效的基因敲除，但基因插入或基因校正仍然效率低下。我们将描述一种新颖的程序化基因组重排机制，并将其发展成为一种高效、精确的哺乳动物基因组编辑技术。这将显着加速细胞和动物模型的生成鉴于该技术的广泛适用性，这项拟议工作的影响将是深远的，并将从根本上改变生命科学和医学所有领域中研究基因相互作用的现有实验方法。