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Massively parallel dissection of psychiatric regulatory networks

Massively parallel dissection of psychiatric regulatory networks
精神病学调节网络的大规模并行剖析
批准号:
9101722
负责人:
Nadav Ahituv
金额:
$64.34万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-05-01 至 2021-02-28
关键词:
ATAC-seqAddressAdultAffectAnimal ModelAstrocytesBiological AssayBrainCRISPR/Cas technologyCatalogingCatalogsCell LineCellsChIP-seqChromatinChromatin Interaction Analysis by Paired-End Tag SequencingChromatin StructureClinical DataCodeCollectionColony-Forming Units AssayComb animal structureComplexComputer softwareCoupledDNADNase I hypersensitive sites sequencingDataDatabasesDevelopmentDiseaseDissectionEmbryoEnhancersFutureGene ExpressionGene Expression RegulationGene TargetingGenesGenomeGenomicsGenotypeHumanHuman GenomeIn VitroKnock-outLeadLettersLinkMachine LearningMeasurementMeasuresMental HealthMental disordersModelingMolecularMusMutationNational Human Genome Research InstituteNeuronsNucleic Acid Regulatory SequencesNucleotidesOutcomePathway interactionsPhenotypeProsencephalonProtocols documentationReagentRegulator GenesRegulatory ElementRegulatory PathwayReporterResourcesRoleScanningStagingStem cellsSubfamily lentivirinaeSystemTechniquesTechnologyTestingTimeTissuesTrainingUntranslated RNAValidationVariantWorkbasebrain cellbrain tissuecell typecomputerized toolsdisease phenotypeepigenomicsfetalfollow-upfunctional genomicsgenetic associationgenome editinggenome wide association studygenome-widegenomic datahuman diseasehuman embryonic stem cellinnovationinsertion/deletion mutationnerve stem cellneurodevelopmentneurogenesisneuron developmentnovelprediction algorithmpromoterpublic health relevancerare variantrelating to nervous systemscreeningsoftware developmentsuccesstranscriptome sequencingvector

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中文摘要
翻译
 描述(由申请人提供):神经元发育异常可导致多种精神障碍。对神经发育重要的基因已经被梳理,以寻找导致精神疾病的编码突变,但成功有限,这表明基因组中的其他区域可能是致病的。各种分子和临床数据表明,与精神疾病相关的突变可以存在于基因调控序列中,如增强子。然而,迄今为止,只有少数增强子与这些疾病明确相关。这主要是因为调控突变在功能上表征并与特定基因和表型相关联具有挑战性。为了应对这一挑战,我们将使用功能基因组学数据、序列基序和进化特征来训练增强子,我们开发的软件可以高成功率预测功能增强子,现在可以特异性地识别活跃的神经发育增强子。然后将克隆超过12,000种候选神经发育增强子,并使用大规模平行报告基因测定(MPRA)在三种人胚胎干细胞(hESC)衍生的神经元系中测定其增强子活性:早期起始、在进一步分化时仅产生神经元的神经祖细胞阶段和星形胶质细胞。此外,我们还将使用一种新的基于染色质结构的预测方法(称为Targetarin)将增强子与其靶基因联系起来,从而建立一个将调控区与神经发育基因连接起来的网络。通过将可重复的精神疾病相关位点与该网络重叠,我们将识别并优先考虑 可能影响神经发育基因表达的非编码突变,这些基因在精神疾病中发挥作用。这些预测将使用基因组编辑技术敲除调控元件进行验证,然后分析发育中神经元中染色质相互作用和基因表达的变化。我们的方法的关键创新是:(i)准确,定量测量活性的数以千计的精神疾病相关的增强子候选人平行,(ii)基于染色质的基因调控网络的推理连接增强子突变的基因和途径,和(iii)一个良好的表征干细胞为基础的系统,以高通量的方式应用这些技术来开发人类神经元。我们将迅速传播软件,试剂,协议和数据集,以便在我们的心理健康合作者和许多其他人的实验室中进行后续功能研究。我们的长期目标是在许多与精神疾病相关的基因组位点中找出致病性调节变异,这些基因位点缺乏明显的编码突变。这种方法可以很容易地适用于功能特征基因调控元件参与其他复杂的人类疾病。
英文摘要
 DESCRIPTION (provided by applicant): Abnormal neuronal development can lead to a wide array of mental disorders. Genes important for neurodevelopment have been combed for coding mutations leading to psychiatric disease with limited success, suggesting that other regions in the genome could be causative. A variety of molecular and clinical data indicates that mutations associated with psychiatric disease can reside in gene regulatory sequences such as enhancers. However, only a few enhancers have been definitively linked with these disorders to date. This is primarily because regulatory mutations are challenging to functionally characterize and link to specific genes and phenotypes. To address this challenge, we will use functional genomics data, sequence motifs, and evolutionary signatures to train EnhancerFinder, software that we developed that predicts functional enhancers at high success rates, to now specifically identify active neurodevelopmental enhancers. Over 12,000 candidate neurodevelopmental enhancers will then be cloned and assayed en masse for their enhancer activity using massively parallel reporter assays (MPRAs) in three human embryonic stem cell (hESC) derived neuronal lines: early initiation, neural progenitor cell stage that produces only neurons upon further differentiation, and astrocytes. In addition, we will link enhancers to their target genes using a novel chromatin structure-based prediction approach, called TargetFinder, thereby establishing a network connecting regulatory regions to neurodevelopmental genes. By overlaying reproducible psychiatric disease associated loci with this network, we will identify and prioritize non-coding mutations that are likely to affect expression of neurodevelopmental genes with roles in psychiatric disease. These predictions will be validated using genome- editing techniques to knock out regulatory elements and then assay changes in chromatin interactions and gene expression in developing neurons. The key innovations of our approach are: (i) accurate, quantitative measurements of activity for thousands of psychiatric disease associated enhancer candidates in parallel, (ii) chromatin based inference of gene regulatory networks linking enhancer mutations to genes and pathways, and (iii) a well-characterized stem cell based system to apply these techniques in a high-throughput manner to developing human neurons. We will rapidly disseminate software, reagents, protocols, and datasets to enable follow-up functional studies in the labs of our mental health collaborators and many others. Our long-term aim is to pinpoint causative regulatory variants in the many genomic loci associated with psychiatric disease where an obvious coding mutation is lacking. This approach could easily be adapted to functionally characterize gene regulatory elements involved in other complex human diseases.
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