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.
抽象的
一种全面发现、表征和识别正常结构变异的简单方法
代谢过程以及细胞操作对于基因编辑、肿瘤学和罕见疾病具有巨大的用途。
疾病研究等应用。从头定向基因组杂交 (dGH™)
开发用于有效筛选数千个细胞中是否存在简单、复杂和异质的细胞
结构变体。在这个项目中,自动化、高通量地鉴定基因结构变异
基因编辑和未确诊遗传病筛查,我们提出 K-Band™ dGH,一种扩展的 dGH
方法。
K 波段 dGH 是一种原位杂交方法,利用具有不同波段的高密度染色单体涂料
光谱。正常染色体具有明确的条带、光谱和探针密度模式。结构变体
通过信号模式的变化来检测和识别。拟议的 K-Band™ dGH 方法将提供
从头发现涉及同一基因座断点的平衡等位基因易位的方法,
现有方法无法观察到的倒位、姐妹染色单体重组和交换事件
例如测序和 aCGH。 K 波段 dGH 将另外表征删除、重复、
易位、非整倍体、多倍体和更复杂的重排。
结构变异会导致多种疾病,从罕见疾病到癌症,并且可以精确且准确地描述。
明确的生物标志物。此外,由于 DNA 双链断裂的错误修复会产生变异,
意外的结构损伤是基因组编辑不可避免且潜在高风险的副产品。这
CRISPR-Cas9等基因组编辑方法在疾病治疗中的潜力被广泛认可
认识到这种治疗方法的承诺的实现将依赖于准确的确认
是否存在潜在风险的结构变异。鉴于这些原因,综合
结构变异的检测和表征是理解、诊断的必要步骤
并最终精准治疗遗传病。来自同质或异质细胞群,
在一次实验中,K 波段 dGH 将识别具有结构正常表型的细胞,检测所有
结构变体的类别,并找到每个结构变体中所有简单和复杂结构变体的断点
细胞。 K 波段 dGH 的检测限低于 5Kb,是确定基因结果的理想方法
编辑、发现未确诊罕见疾病的原因、分析基因组结构不稳定性以及
变异性,发现和验证以前未知的疾病结构遗传驱动因素。
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
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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