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
基本信息
- 批准号:10228763
- 负责人:
- 金额:$ 58.44万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-08-04 至 2023-07-31
- 项目状态:已结题
- 来源:
- 关键词:AlgorithmsAllelesAneuploidyArtificial IntelligenceBioinformaticsBiological AssayBiological MarkersBiomedical ResearchCRISPR screenCRISPR therapeuticsCRISPR/Cas technologyCell LineCell TherapyCellsChromatidsChromosomal RearrangementChromosome StructuresChromosomesClinicalClinical assessmentsClustered Regularly Interspaced Short Palindromic RepeatsColorComplexDNADNA Double Strand BreakDNA RepairDNA SequenceDataDetectionDevelopmentDiagnosisDiseaseDouble Strand Break RepairEventExposure toFingerprintFundingGenesGenetic DiseasesGenetic RecombinationGenetic StructuresGenome engineeringGenomic HybridizationsGenomicsGoalsGovernmentHumanImageImage AnalysisIn Situ HybridizationIndividualKnowledgeLocationMalignant NeoplasmsMapsMarketingMeasurementMeasuresMedicalMetabolismMethodsModernizationOncologyOutcomePaintPatternPattern RecognitionPharmacologic SubstancePhasePhenotypePolyploidyPopulationPrevalenceRadiationRare DiseasesReciprocal TranslocationResearchResearch PersonnelResolutionRiskSamplingSignal TransductionSister ChromatidSmall Business Innovation Research GrantSolidStructureSystemTechnologyTestingTherapeuticValidationVariantWorkautomated image analysisbasecellular engineeringclinically relevantcommercial applicationcomparative genomic hybridizationdensitydetection limitexperimental studyfluorophoregene therapygenetic variantgenome editinggenotoxicityhigh riskimprovedintelligent algorithmnew therapeutic targetpersonalized medicinereconstructionresearch and developmentscreeningstem cellsstructural genomicstechnological innovationtherapeutic genetherapeutic targettherapy developmenttoolwhole genome
项目摘要
ABSTRACT
A simple method to comprehensively discover, characterize and identify structural variants arising from normal
metabolic processes, as well as cell manipulations, would have great utility for gene editing, oncology, and rare
disease research, among other applications. De Novo Directional Genomic Hybridization (dGH™) has been
developed to efficiently screen thousands of cells for the presence of simple, complex, and heterogenous
structural variants. In this project, Automated, High-Throughput Identification of Genetic Structural Variants for
Gene Editing and Undiagnosed Genetic Diseases Screening, we propose K-Band™ dGH, an expanded dGH
method.
K-Band dGH is an in-situ hybridization method that utilizes high-density chromatid paints with bands of distinct
spectra. A normal chromosome has a definitive pattern of bands, spectra and probe density. Structural variants
are detected and identified via changes to the signal pattern. The proposed K-Band™ dGH method will provide
the means for de novo discovery of balanced allelic translocations involving breakpoints at the same loci,
inversions, and sister chromatid recombination and exchange events that are invisible to existing methods
such as sequencing and aCGH. K-Band dGH will additionally characterize deletions, duplications,
translocations, aneuploidy, polyploidy and more complex rearrangements.
Structural variations cause a wide range of disorders, from rare diseases to cancers, and can be precise and
definitive biomarkers. Also, because variations arise from the mis-repair of DNA double-strand breaks,
unintended structural damage is an inevitable and potentially high-risk byproduct of genome editing. The
potential of genome editing approaches such as CRISPR-Cas9 in the treatment of diseases is widely
recognized and the 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, diagnosing
and ultimately precisely treating genetic diseases. From a homogeneous or heterogenous population of cells,
and in a single experiment, K-Band dGH will identify cells with a structurally normal phenotype, detect all
classes of structural variants, and locate the breakpoints of all simple and complex structural variants in each
cell. With a limit of detection below 5Kb, K-Band dGH is an ideal method for determining the outcomes of gene
editing, discovering the causes of undiagnosed rare diseases, profiling genomic structural instability and
variability, and discovering and validating previously unknown structural genetic drivers of disease.
摘要
项目成果
期刊论文数量(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
A comprehensive quality control testing strategy for engineered cells
工程细胞的全面质量控制测试策略
- 批准号:
10330008 - 财政年份:2021
- 资助金额:
$ 58.44万 - 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:
$ 58.44万 - 项目类别:
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