A comprehensive quality control testing strategy for engineered cells
工程细胞的全面质量控制测试策略
基本信息
- 批准号:10330008
- 负责人:
- 金额:$ 35.05万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-01-15 至 2023-06-30
- 项目状态:已结题
- 来源:
- 关键词:AddressAllelesAneuploidyBioinformaticsBiological AssayBiomedical ResearchCRISPR/Cas technologyCell TherapyCellsChromatidsChromosomesClinicalClinical EngineeringCollaborationsCollectionColorComplexContractsDNA RepairDataData SetDefectDetectionDevelopmentDiseaseDouble Strand Break RepairEngineeringExhibitsFundingG-BandingGenesGenomeGenome engineeringGenomic HybridizationsGenomicsGoalsGovernmentHealthHereditary DiseaseHumanIn Situ HybridizationIndividualInheritedKaryotypeKaryotype determination procedureKnowledgeMalignant NeoplasmsMeasurementMeasuresMedicalMethodsModelingMonitorNucleotidesOutcomePaintPatientsPediatric HospitalsPharmacologic SubstancePolyploidyPopulationProcessProviderQuality ControlResearchResolutionRiskSafetySaint Jude Children&aposs Research HospitalSamplingSister Chromatid ExchangeSiteSourceSpeedStructureSystemTechniquesTechnologyTestingTherapeuticTimeTrainingVariantWorkWritingbasecellular engineeringclinical applicationcommercial applicationcomparativedata standardsdensitydesignexperienceexperimental studyfluorophoregene therapygenome editinggenome integritygenomic datahigh resolution imagingimprovedinnovationinsertion/deletion mutationpatient safetypredictive modelingprogramsreference genomeresearch and developmentscreeningstem cellstechnological innovationtherapeutic genetherapy developmenttoolwhole genome
项目摘要
ABSTRACT
KromaTiD’s current commercial therapeutic gene editing customers have expressed the critical need for a
standard approach to screening engineered cells for quality and safety that yields a comprehensive genomic
dataset with improved resolution, localization, and speed. Directional Genomic Hybridization (dGH™) has been
developed to efficiently screen cell populations for the presence of simple, complex, and heterogenous
structural variants. In this project, A Comprehensive Quality Control Testing Strategy for Engineered Cells, by
combining five-color, whole genome dGH with the fit for purpose sequencing methods of a clinically important
genome engineering system, we propose an approach to assess, for the first time, the complete outcomes of
gene editing: successful edits, unsuccessful edits, off-target edits, sequence variants, structural variants, and
gross genome integrity. Furthermore, we propose to develop a standardized data specification integrating the
data from these methods into a regulatory ready data package.
dGH is an in-situ hybridization technique utilizes high-density chromatid paints to directly interrogate the
structure of a genome in a single cell without bioinformatic interpretation, providing a complete toolset for
hypothesis-free, single-cell measurement of SVs at edit sites, per chromosome, and across the whole genome.
For companies developing therapies based on gene editing and other cell engineering approaches,
understanding editing systems and mis-repair of DSBs are critical for patient safety and regulatory approval.
Currently, batches of edited cells are screened for edit-site errors by sequencing. Because DSBs do not all
occur at the edit site, SVs in batches of edited cells exhibit a complex, heterogenous mixture of edit-site and
random breakpoints. G-banding can be used to screen for gross genome defects but cannot detect small or
complex structural variants. dGH assays detect structural variation from a reference genome without target
information, resolve SVs of 5Kb and larger, and provide improved genomic structural assessment capable of
displacing standard karyotyping.
The potential of genome editing approaches such as CRISPR/Cas9, for the treatment of diseases is widely
recognized, and realization of the promise of such therapeutic approaches will rely on accurate confirmation of
the presence and absence of potentially risky structural variants. For these reasons, comprehensive detection
and characterization of structural variations is a necessary step toward understanding gene editing and other
cell engineering systems. dGH combined with best-fit sequencing can provide a complete analysis of the
outcomes of gene editing from SNVs and indels though large, complex SVs.
抽象的
Kromatid当前的商业理论基因编辑客户表示对
筛选工程细胞的标准方法,以获得质量和安全性,可产生全面的基因组
数据集具有改进的分辨率,本地化和速度。方向基因组杂交(DGH™)已经
开发为有效筛选细胞种群,以实现简单,复杂和异质的存在
结构变体。在这个项目中,通过
将五色的整个基因组与适合临床上重要的目的测序方法结合起来
基因组工程系统,我们提出了一种评估的方法,以首次评估
基因编辑:成功的编辑,不成功的编辑,脱离目标编辑,序列变体,结构变体和
总体基因组完整性。此外,我们建议开发一个标准化的数据规范,以集成
来自这些方法的数据转化为调节性数据包。
DGH是一种原位杂交技术,利用高密度染色单体油漆直接审问
单个细胞中基因组的结构,没有生物信息学解释,为
每个染色体和整个基因组中的SVS的假设无假设,单细胞测量。
对于基于基因编辑和其他细胞工程方法开发疗法的公司,
了解DSB的编辑系统和错过修复对于患者的安全和监管批准至关重要。
当前,通过测序筛选了批次编辑的单元格以获取编辑位点错误。因为DSB并非全部
在编辑站点发生,编辑单元批处理的SVS表现出复杂的编辑站点的异质组合和
随机断点。 G带可用于筛查总基因组缺陷,但不能检测到很小或
复杂的结构变体。 DGH测定检测没有目标的参考基因组的结构变化
信息,解决5KB及更大的SVS,并提供能够改进的基因组结构评估
取代标准的核分型。
基因组编辑方法(例如CRISPR/CAS9)的潜力,用于治疗疾病
公认的,并认识到这种治疗方法的承诺将依赖于准确的确认
存在和不存在潜在风险的结构变体。由于这些原因,全面检测
结构变化的表征是理解基因编辑和其他其他的必要步骤
细胞工程系统。 DGH结合最佳拟合测序可以提供对
SNV和Indels的基因编辑结果虽然很大,复杂的SV。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Christopher John Tompkins其他文献
Christopher John Tompkins的其他文献
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{{ truncateString('Christopher John Tompkins', 18)}}的其他基金
Automated, high-throughput identification of genetic structural variants for gene editing and undiagnosed genetic diseases screening
自动化、高通量鉴定遗传结构变异,用于基因编辑和未确诊遗传病筛查
- 批准号:
10228763 - 财政年份:2020
- 资助金额:
$ 35.05万 - 项目类别:
Automated, high-throughput identification of genetic structural variants for gene editing and undiagnosed genetic diseases screening
自动化、高通量鉴定遗传结构变异,用于基因编辑和未确诊遗传病筛查
- 批准号:
10080433 - 财政年份:2020
- 资助金额:
$ 35.05万 - 项目类别:
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