Cell-Based Assays For Deep Mutational Scans of Transcription Factors

基于细胞的转录因子深度突变扫描分析

• 批准号: 10317226
• 负责人: Barak A Cohen
• 金额: $ 43.31万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10317226
• 关键词: Address; Bar Codes; Benign; Biological; Biological Assay; Biology; Cell Culture System; Cell Culture Techniques; Cell Line; Cell model; Cells; Clinical; Code; Collection; Communities; Coupled; Data; Disease; Disease model; Engineering; Environment; Genes; Genetic; Genetic Transcription; Genetic Variation; Genomics; Goals; Homeobox; Human; Human Genome; In Vitro; Individual; Libraries; Measurement; Measures; Methodology; Modeling; Molecular; Mutation; National Human Genome Research Institute; Pathogenicity; Photoreceptors; Population; Proteins; Publications; Publishing; Reporter Genes; Reproducibility; Research Personnel; Rest; Retina; Speed; System; Technology; Testing; Time; Transfection; Variant; Vertebrate Photoreceptors; Vision; Work; base; cell type; cellular engineering; design; genetic variant; genome sequencing; high throughput screening; human disease; improved; improved functioning; in vivo; innovation; mutation screening; personalized medicine; programs; transcription factor; variant of unknown significance

PROJECT SUMMARY/ABSTRACT A major impediment to personalized medicine is the slow pace at which new genetic variants are designated as pathogenic or benign. Genome sequencing projects are rapidly uncovering new genetic variation, but a lack of functional annotation for newly discovered variants means that most are classified as Variants of Uncertain Significance (VUS), even in well-studied protein coding genes. Because of this problem, the NHGRI 2020 Strategic Vision emphasizes the need for new highly parallel technologies that assess the functional impact of genetic variants. One promising approach is Deep Mutational Scanning (DMS), in which large numbers of genetic variants are synthesized and assayed in parallel. The large scale of DMS has the potential to keep pace with efforts in variant discovery. This proposal addresses two problems that limit the reliable use of DMS. First, most published DMS are inappropriate for clinical use because they suffer from low biological reproducibility. Our analysis suggests that this problem is caused by the inability to identify and exclude outlier measurements caused by genetic anomalies that occur during the transfection and integration of variant libraries into cells. We will test whether a barcoding strategy designed specifically to detect these types of outliers improves the reproducibility of DMS. The barcoding strategy will be coupled with an improved landing pad system for genomic integration of DMS libraries. Another issue with DMS is the choice of cell type for functional assays. For most diseases, the relevant in vivo cell types are inaccessible. Investigators must compromise between difficult primary cell models and more tractable cell culture systems that less faithfully reflect in vivo biology. We will address this problem first focusing on DMS of transcription factors (TFs), an important class of disease genes. Because cell-type specific TFs work in concert with other TFs, we will test whether expressing groups of cell type-specific TFs in a tractable cell line allows us to perform a DMS that faithfully represents the in vivo cell type. We propose to test this premise using the Cone-Rod Homeobox (CRX) as a model TF. CRX is specific to photoreceptors in the retina, but several studies show that its activity can be recapitulated in HEK293 cells engineered to co-express groups of photoreceptor-specific TFs. To test the validity of this system for a DMS we will directly compare results from engineered HEK293 lines to those from live intact retinas. We hope to determine whether tractable cell lines engineered to express collections of cell-type specific TFs could be reasonable systems for DMS of TFs. Our overall goal is to improve the functionality and reliability of DMS by improving its methodologies and expanding the range of appropriate cell lines.

项目总结/摘要 个性化医疗的一个主要障碍是新的遗传变异的缓慢速度。 指定为致病性或良性。基因组测序项目正在迅速发现新的遗传变异， 但缺乏新发现的变异体的功能注释意味着大多数被归类为 不确定性显著性（VUS），即使在研究充分的蛋白质编码基因。由于这个问题，NHGRI 2020年战略愿景强调需要高度并行的新技术来评估功能影响 基因变异的证据一种很有前途的方法是深度突变扫描（DMS），其中大量的 平行地合成和测定遗传变体。目的地管理系统的大规模有可能跟上发展的步伐 致力于发现变异体 这一建议解决了限制目的地管理系统可靠使用的两个问题。首先，大多数已发布的DMS 因为它们的生物学再现性低而不适合临床使用。我们的分析表明， 这个问题是由于不能识别和排除由遗传异常引起的离群值测量而引起的 这发生在变体库转染和整合到细胞中的过程中。我们将测试条形码是否 专门设计用于检测这些类型的离群值的策略提高了DMS的再现性。的 条形码化策略将与改进的着陆平台系统结合，用于DMS文库的基因组整合。 DMS的另一个问题是功能测定的细胞类型的选择。对于大多数疾病， 体内细胞类型是不可接近的。研究人员必须在困难的原代细胞模型和 更易处理的细胞培养系统，其较不忠实地反映体内生物学。我们将首先解决这个问题 聚焦于转录因子（TF）的DMS，这是一类重要的疾病基因。因为细胞类型特异性 TF与其他TF协同工作，我们将测试在细胞中表达细胞类型特异性TF的组是否与其他TF协同工作。 易处理的细胞系使我们能够进行忠实地代表体内细胞类型的DMS。我们建议测试 这个前提使用锥杆Homeobox（CRX）作为TF模型。CRX特异性针对视网膜中的光感受器。 视网膜，但几项研究表明，它的活性可以重现在HEK 293细胞工程共表达 光感受器特异性转录因子。为了测试该系统对DMS的有效性，我们将直接比较 结果从工程化HEK 293系到来自活的完整视网膜的那些。我们希望能确定 工程化以表达细胞类型特异性TF集合的细胞系可能是DMS的合理系统， TF。我们的总体目标是通过改进管理系统的方法， 扩大了合适细胞系的范围。