A comprehensive quality control testing strategy for engineered cells

摘要 KromaTiD目前的商业治疗性基因编辑客户表示迫切需要 筛选工程细胞的质量和安全性的标准方法， 数据集，具有更高的分辨率，本地化和速度。定向基因组杂交（dGH™）已被 开发用于有效筛选细胞群体中存在的简单、复杂和异质性的细胞， 结构变体。在这个项目中，工程细胞的全面质量控制测试策略， 结合五色，全基因组dGH与临床重要目的的适合测序方法， 基因组工程系统，我们提出了一种方法来评估，第一次，完整的结果， 基因编辑：成功编辑、不成功编辑、脱靶编辑、序列变异、结构变异和 总基因组完整性此外，我们建议开发一个标准化的数据规范， 将这些方法的数据转换为监管就绪的数据包。 dGH是一种原位杂交技术，利用高密度染色单体涂料直接询问 在没有生物信息学解释的情况下，在单个细胞中的基因组结构，提供了一个完整的工具集， 在编辑位点、每条染色体和整个基因组上对SV进行无假设的单细胞测量。 对于开发基于基因编辑和其他细胞工程方法的疗法的公司， 理解编辑系统和DSB的错误修复对于患者安全和监管批准至关重要。 目前，通过测序筛选编辑的细胞批次的编辑位点错误。因为DSB并不都 当在编辑位点发生突变时，批量编辑细胞中的SV表现出编辑位点和 随机断点。G显带可用于筛查总基因组缺陷，但不能检测小的或 复杂的结构变体。dGH检测试剂盒可检测无靶标参考基因组的结构变异 信息，解析5 Kb和更大的SV，并提供能够 取代了标准的核型分析。 基因组编辑方法如CRISPR/Cas9用于治疗疾病的潜力被广泛应用。 认识到，实现这种治疗方法的承诺将依赖于准确确认， 是否存在潜在风险的结构变异。基于这些原因，全面检测 结构变异的表征是理解基因编辑和其他基因编辑的必要步骤。 细胞工程系统dGH与最佳拟合测序相结合可以提供完整的分析， 通过大的、复杂的SV从SNV和插入缺失进行基因编辑的结果。

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.