Massively parallel characterization of psychiatric disease associated regulatory elements in defined cell types
Massively parallel characterization of psychiatric disease associated regulatory elements in defined cell types
批准号:
9901610
负责人:
Nadav Ahituv
金额:
$67.27万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-07-06 至 2023-03-31
关键词:
ATAC-seqAddressAffectAnatomyAreaBRAIN initiativeBase SequenceBase of the BrainBiological AssayBrainCRISPR/Cas technologyCell LineCellsCerebrumChromatinClinical DataCodeComputer AnalysisCoupledDataDevelopmentDiseaseElementsEngineeringEnhancersEnvironmentGene ExpressionGene Expression RegulationGene MutationGenesGeneticGenetic DiseasesGenetic VariationGenomicsGoalsHumanInterneuronsLeadLibrariesLightLinkMapsMeasuresMental disordersModelingMolecularMutateMutationNeurodevelopmental DisorderNeurologicNeuronsNucleotidesOrganoidsPathway interactionsPerinatalPhenotypePopulationProteinsRegulator GenesRegulatory ElementRegulatory PathwayReporterRepressionSamplingSpecificitySubfamily lentivirinaeSurveysTechniquesTechnologyTestingTissuesUntranslated RNAVariantbasebrain tissuecell typecombinatorialdesigndisorder riskexcitatory neurongenetic regulatory proteingenome editinghuman tissueimprovedin vivoindexinginduced pluripotent stem cellloss of function mutationnetwork modelsneurogenesisneuron developmentnovelpredictive modelingprogramssingle-cell RNA sequencingstem cellstooltranscription factortranscriptome
中文摘要
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英文摘要
Project Summary / Abstract
Abnormal neuronal development can lead to a wide array of psychiatric disorders. Mutations disrupting protein
coding genes have been found to cause some of these disorders but a large number of them still remain
unsolved. A variety of molecular and clinical data suggests that mutations in gene regulatory sequences could
be a major contributor to these disorders. However, only a few causal regulatory mutations have been found to
date. This is primarily because functional regulatory elements are difficult to identify, particularly in mixed cell
populations such as the developing brain. In addition, these elements are difficult to functionally characterize in
a high-throughput manner in these cell types. To address these challenges, we propose to use novel single-cell
genomic technologies along with massively parallel reporter assays (MPRAs) in human primary cells and
organoids to characterize thousands of brain development associated genes, regulatory elements and pathways.
First, using single cell RNA-seq (scRNA-seq) and ATAC-seq (sci-ATAC-seq) across multiple cortical areas and
subcortical regions of developing human brain at three development stages, we will generate a comprehensive
map of genes, regulatory elements and networks involved in human brain development (Aim 1). Next, we will
use similar techniques (scRNA-seq and sci-ATAC-seq) on human cerebral organoid cultures derived from
induced pluripotent stem cells (iPSCs). We will compare regulatory programs in organoid cells to cells present
during normal human brain development. To assess the contribution of key transcription factors involved in
psychiatric disorders to gene regulatory pathways in the developing brain, we will use genome editing on the
same genetic background to create heterozygous loss-of-function mutations in key transcription factors involved
in psychiatric disorders and assess their effects on gene expression (scRNA-seq) and gene regulation (sci-
ATAC-seq) (Aim 2). Finally, we will functionally characterize over 37,500 candidate enhancers and nucleotide
variants within them using a lentiviral-based MPRA (lentiMPRA) in disease-relevant cell types purified from
human primary cells and organoids. Several of these sequences will also be assayed in organoids lacking key
transcription factors deleted in Aim 2 to test the importance of these genes to regulatory activity and to identify
interactions with regulatory variants (Aim 3). Data from all aims will be used to build predictive models of gene
expression and enhancer activity as a function of regulatory sequences, which will be used to design lentiMPRA
libraries and iteratively improve models using results from initial libraries. Combined our project will use cutting-
edge techniques such as scRNA-seq, sci-ATAC-seq and MPRA coupled with advanced computational analyses
to significantly increase the number of functionally characterized human brain developmental regulatory
elements and how their activity changes in the presence of disease associated mutations to shed light on the
genetic basis for psychiatric disorders.
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海外基金