Slide-seq: high-resolution in situ expression profiling for neuropathology
Slide-seq: high-resolution in situ expression profiling for neuropathology
批准号:
9349150
负责人:
Evan Z Macosko
金额:
$267.0万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2022-08-31
关键词:
AdultAlzheimer&aposs disease modelAmyloidBiologicalBiological AssayBiologyBrainBrain DiseasesCellsClinicalDNADNA biosynthesisDevelopmentDiseaseGene ExpressionGene Expression ProfilingGenesHippocampus (Brain)HumanIn SituLaboratoriesMeasuresMethodsMicroscopeModelingMolecularMolecular ComputationsMolecular ProfilingMusNeuronsPathologicPopulationPositioning AttributeReportingResolutionSchemeSlideSpecimenSymptomsTissuesTransfer RNAValidationbasebrain tissuecell typeexperimental studygenome-wideinnovationmouse modelneuropathologyneuropsychiatric disordernew technologynovelprotein expressionsuccesstooltranscriptome
中文摘要
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英文摘要
ABSTRACT
Human brain specimens are one of few available opportunities to directly investigate the molecular
underpinnings of neuropsychiatric diseases. Assays of gene and protein expression in situ have revolutionized
our understanding of many of these diseases, but despite these advances, for many brain disorders, the tissue
changes that give rise to clinical symptoms are poorly understood. Ascertaining the full set of molecular
change(s) and the cell type(s) in which each change resides would inform the laboratory models used to study
these illnesses, and offer hypotheses for potential new treatments. This proposal outlines a novel technology,
Slide-seq, capable of performing whole-transcriptome analysis of intact brain tissue sections at single-cell (~7
μm) resolution. The method applies my recent development of a novel DNA barcoding scheme, based upon
split-and-pool DNA synthesis, to construct a microscope slide adorned with a high-diversity bead array capable
of recording fine spatial coordinates for each gene, transcriptome-wide. In this proposal, we: (1) describe the
molecular, computational, and cell biological innovations necessary to transfer RNA from tissue sections onto
this array, and successfully report their spatial positions; (2) outline three core assays for unambiguously
measuring the success of each crucial technical step; (3) critically evaluate the single-cell resolution of Slide-
seq by profiling the mouse adult hippocampus; and (4) apply Slide-seq to a mouse model of Alzheimer's
disease to uncover how surrounding cell populations respond to neuronal amyloid accumulation in the early
stages of disease. Together, these experiments will produce a well-validated tool with broad applicability to
problems in biology, most especially the analysis of pathological brain tissue.
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