Leveraging natural and engineered genetic barcodes from single cell RNA sequencing to investigate cellular evolution, clonal expansion, and associations between cellular genotypes and phenotypes

项目总结 无论是由于生理压力还是外部力量，细胞都在不断地改变自己的状态。克隆性 膨胀是一个明确定义的过程，它促成了这种改变，并且不加区别地发生在所有类型的 组织遍及全身，而不考虑该组织的恶性或疾病可能性。任何突变或 因此，一个人一生中持续的表观遗传变化有被克隆扩大的风险 并最终在细胞系15、16内传播。然而，为什么其中一些仍然存在问题 在其他细胞保持良性的情况下，扩张会导致癌症，以及单个细胞如何 从基因和转录上获得致病，并最终进化和体现不同 表型状态。这些表型包括表达细胞状态、突变过程的活性(例如， 内源性APOBEC DNA/RNA脱氨突变)，以及在治疗下持续存在的倾向。 了解细胞如何改变其状态有助于洞察如何控制细胞命运，这可能具有 对我们理解细胞的可塑性、发育、进化和疾病进展的影响。 单细胞基因组的计算分析提供了一个深入了解这些问题的机会 生物学，但目前的方法在从单一-变种叫声中提取自信变异叫声的能力方面存在差距- 细胞RNA测序数据。到目前为止，研究主要依靠费力、低效的方法，主要局限于细胞 线条或固有的噪声单细胞DNA数据，以试图理解细胞谱系之间的这种相互作用， 获得性突变和基因组特征(例如，创建人工诱导的遗传条形码或使用自然 DNA突变)17-20。这个项目的重点是开发一种更强大的基因组工具来构建这些 单细胞系统发育及其与细胞表型之间的关系 具有全长单链RNA序列的机械。这一项目的具体目标可以概括如下： 1.利用scRNA-seq和基于CRISPR的谱系追踪数据重建系统发育和鉴定 在单细胞水平上的特定基因组关联。 2.研究突变过程在克隆扩张和疾病进展中的作用 单细胞分辨率的组织。 为了实现这些项目目标以及我自己的职业目标，成为一名成功的独立人士 基因组科学家，我的培训计划包括机器学习、系统发育和机械学方面的培训 生物学，以及进一步的科学交流技能培训，如手稿写作和补助金 写作。我优秀的研究环境包括麻省理工学院和哈佛大学，我的家乡 盖德·盖兹博士的实验室位于。这是世界一流的基因组研究机构，拥有丰富的人力资源。 以及执行我提议的研究所需的所有其他必要资源。

PROJECT SUMMARY Cells are constantly altering their states, whether due to physiological stress or exogenous forces. Clonal expansion is a well-defined process that contributes to this alteration and indiscriminately occurs in all types of tissue throughout the body, irrespective of the malignant or disease potential of that tissue. Any mutations or epigenetic changes that one sustains over the course of a lifetime are thus at risk of being clonally expanded and ultimately propagated within cell lineages15,16. However, questions still remain as to why some of these expansions result in cancer while others remain benign and as to how the specific steps that individual cells take genetically and transcriptionally to become pathogenic and ultimately evolve and embody different phenotypic states. These phenotypes include expression cell state, activity of mutational processes (e.g., endogenous APOBEC DNA/RNA deamination mutagenesis), and propensity to persist under treatment. Understanding how cells change their states provides insight into how to control cell fate, which can have ramifications on our understanding of cell plasticity, development, evolution, and disease progression. Computational analysis of single-cell genomes offers an opportunity to provide insight into these questions in biology, but there is a gap in the current ability of existing methods to extract confident variant calls from single- cell RNA sequencing data. Research to date has relied on laborious, inefficient methods limited to mostly cell lines or inherently noisy single-cell DNA data to attempt to understand this interplay between cell lineages, acquired mutations and genomic features (i.e., creating artificially-induced genetic barcodes or using natural DNA mutations)17-20. This project focuses on the development of a more robust genomic tool for building these single cell phylogenies and associating them with cellular phenotypes by leveraging the cell’s transcriptional machinery with full length scRNA-seq. The specific aims of this project can be summarized as follows: 1. Utilize scRNA-seq and CRISPR-based lineage tracing data to reconstruct phylogenies and identify specific genomic associations at the single cell level. 2. Investigate the role mutational processes have on clonal expansion and disease progression across tissues at single-cell resolution. To achieve these project goals as well as my own career objectives to becoming a successful independent genomic scientist, my training plan includes training in machine learning, phylogenetics, and mechanistic biology, as well as further training in scientific communication skills such as manuscript writing and grant writing. My excellent research environment includes the Broad Institute of MIT and Harvard, where my home lab of Dr. Gad Getz is located. This is a world-class institution for genomics research rich in people resources and all other necessary resources needed to perform my proposed research.