Spatially Resolved CRISPR Genomics for Dissecting Testicular Gene Functions at Scale
Spatially Resolved CRISPR Genomics for Dissecting Testicular Gene Functions at Scale
批准号:
10573701
负责人:
Haiqi Chen
金额:
$24.6万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-04-15 至 2025-03-31
关键词:
AccountingAddressAdoptedAffectBar CodesCRISPR screenCRISPR/Cas technologyCell Culture TechniquesCellsClustered Regularly Interspaced Short Palindromic RepeatsCommunitiesComplexCoupledCouplesCouplingCultured CellsDataData SetDefectDiagnosisEmerging TechnologiesEquipment and supply inventoriesExclusionFertilityFoundationsGene Expression ProfilingGene TargetingGenesGeneticGenetic DiseasesGenetic TranscriptionGenomic approachGenomicsGuide RNAHumanImageImage AnalysisIn SituIn VitroInfertilityKnockout MiceLabelLentivirusMale InfertilityMediatingMessenger RNAMethodsModelingMusOrganPathologicPhenotypeProductionProtocols documentationRNA SequencesReporterReproductive BiologyResearch PersonnelResolutionResourcesSamplingSeminiferous tubule structureSolidSomatic CellSpermatogenesisTesticular TissueTestisTimeTissuesTranscriptbehavior influencecell typecomputational pipelinesdesignexperimental studyextracellularfunctional genomicsgene functiongenomic datagenomic toolsimprovedin situ sequencingin vivoinnovationinterestknock-downmalemale fertilitynext generationsertoli cellsingle-cell RNA sequencingsperm cellspermatogenic epithelium structurestem cellstranscriptometranscriptome sequencingtranscriptomic profiling
中文摘要
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英文摘要
PROJECT SUMMARY
Male infertility is a complicated pathological condition characterized by a heterogeneous spectrum of
phenotypic presentations, rendering its underlying causes obscure. In recent years, genetic disorders emerge
as one of the leading causes of male infertility, accounting for at least 15% of cases. Therefore, understanding
the genetic network that influences various aspects of male fertility such as spermatogenesis (i.e., sperm
production) would greatly benefit the diagnosis and treatment of male infertility. However, the estimate that
thousands of genes may be involved in spermatogenesis makes it difficult to ascribe specific genetic causes to
male infertility. Traditionally the functions of testis-expressing genes can be analyzed by generating knockout
mouse lines given the similarities between mouse and human spermatogenesis. However, this approach
demands significant time and resources, making it challenging to scale. Emerging technologies such as
CRISPR screens coupled with single cell RNA sequencing (scRNA-seq) can examine gene functions at scale,
but suffer from two major limitations for dissecting testicular gene functions: (i) the lack of a cell culture model
that faithfully recapitulates spermatogenesis makes it difficult to assess whether perturbation of a gene leads to
defects in sperm production in vitro; and (ii) while cell intrinsic effects of a gene perturbation may be read out
using scRNA-seq, the extracellular effects of a gene perturbation cannot be assessed due to tissue
disassociation. This excludes using CRISPR screens to identify genes controlling phenotypes that require
spatial resolution to assess such as genes encoding for secreted factors. Therefore, a CRISPR screen
approach that retains the spatial context of spermatogenesis is needed to interrogate testicular gene functions
at a high throughput. There are currently two main challenges to develop a spatially resolved CRISPR screen
approach: (i) to capture mRNA transcripts in situ at scale and at single-cell resolution; and (ii) to read out the
identity of each gene perturbation and the mRNA transcripts within a cell simultaneously. To address these two
main challenges, we will greatly improve and expand an in situ RNA sequencing protocol we have recently
established to spatially profile hundreds of mRNA species directly in testicular samples. We will also perform a
proof-of-concept experiment to demonstrate co-capture of CRISPR guide RNA and mRNA in intact testicular
tissues using the same in situ sequencing approach. Together, these efforts will enable a highly innovative
functional genomics approach to dissect gene functions in the native tissue context at an unprecedented
spatial resolution and throughput.
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