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Dissecting cis regulation of gene expression in schizophrenia.

Dissecting cis regulation of gene expression in schizophrenia.
剖析精神分裂症基因表达的顺式调控。
批准号:
10082418
负责人:
Panagiotis Roussos
金额:
$0.0万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-04-01 至 2022-12-31
关键词:
3-DimensionalAccountingAddressAffectAllelesAnteriorAreaAutopsyBinding SitesBiological AssayBiologyBipolar DisorderBrain DiseasesBrain regionBudgetsCell LineCell NucleusCellsCerebral cortexChromatinChromatin LoopChromatin StructureCollaborationsComplementComplexCoronary ArteriosclerosisDNADataData SetDiseaseEnhancersFluorescenceFormulationFunctional disorderFundingFutureGene ExpressionGene Expression RegulationGenerationsGenesGeneticGenetic Enhancer ElementGenetic PolymorphismGenetic RiskGenetic VariationGenomeGenotypeGoalsGrantHealth Care CostsHumanIndividualIntercistronic RegionLightLinkMapsMental HealthMolecularNeurogliaNeuronsNuclearNucleic Acid Regulatory SequencesOutcomePathway AnalysisPathway interactionsPopulationPositioning AttributeProcessQuantitative Trait LociRecording of previous eventsRegulatory ElementReportingResearchResearch PersonnelResolutionRheumatoid ArthritisRiskRoleSamplingSchizophreniaScientistSkinSorting - Cell MovementSpecimenSystemTissuesTranscription Initiation SiteTransposaseUntranslated RNAVariantVeteransWorkbasebrain tissuecausal variantcell typechromosome conformation capturecingulate cortexclinical applicationcohortcomparativedesigndisorder controldisorder riskdrug developmentepigenomeepigenomicsgene interactiongenome wide association studygenome-widehistone modificationimprovedinduced pluripotent stem cellmolecular scalenetwork modelsnovelpromoterpsychiatric genomicsrisk variantschizophrenia riskstem cell biologytranscription factortranscriptometranscriptome sequencing

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PROJECT SUMMARY  Our understanding of the genetics of schizophrenia is advancing at a rapid pace and an increasing number of  risk-­associated  polymorphisms  and  variants  have  been  discovered.  Because  the  majority  of  these  variants  reside  in  intergenic,  intronic  and  other  non-­coding  sequences,  a  precise  variant  or  target  gene  for  schizophrenia  has  not  been  identified.  Therefore,  a  major  challenge  lies  in  designing  testable  hypotheses  to  elucidate the potential function of disease-­associated non-­coding DNA. Many of the risk variants are thought to  affect  gene  expression  through  alterations  of  regulatory  elements,  including  long-­range  enhancer  sequences  physically interacting with transcription start sites separated along the linear genome of DNA. The aim of this  proposal is to map the regulatory sequences (or open chromatin) in discrete cellular populations (neurons and  glia) derived from two human cortical brain regions in a large cohort of cases with schizophrenia and controls,  followed  by  generation  of  a  high-­resolution  quantitative  trait  loci  (QTL)  map  of  regulatory  sequences.  In  addition,  high  resolution  expression  quantitative  trait  loci  (eQTLs),  mapped  in  the  same  samples  and  brain  regions,  will  be  leveraged  to  identify  schizophrenia  associated  non-­coding  regions  that  are  simultaneously  associated  with  differential  exposure  of  regulatory  regions  (open  chromatin)  and  gene  expression  of  nearby  genes (eQTLs). Long-­range enhancer-­promoter interactions of genes potentially regulated by open chromatin  sequences will be mapped in human postmortem brain tissue using chromosome conformation capture. Using  the  existing  schizophrenia-­related  large-­scale  molecular  data  and  the  high-­impact,  high-­resolution,  complementary datasets generated through the proposed studies, we will develop multiscale network models  causally  linked  to  schizophrenia.  The  action  of  individual  genes  on  molecular  and  cellular  schizophrenia-­ associated  processes  and  the  molecular  networks  identified  in  our  studies  will  be  validated  using  iPS-­cell-­ derived  cultures  of  human  neuronal  cell  systems.  The  multidimensional  approach  presented  here  provides  a  roadmap  to  place  schizophrenia  genetic  risk  variants  in  molecular  contexts  to  help  identify  the  underlying  regulatory and expression mechanisms through which they act.
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