Omics information maximization in single-cell sequencing with hybrid molecular and computational approaches

摘要 拟议研究计划的总体目标是通过以下途径提高我们对单细胞生物学的理解 信息最大化技术，通过应用分子工程和计算方法 测序。特别是，单细胞测序正在迅速成为研究人类的主要方法 生物学和疾病，因为它消除了大量测序细胞混合物的混杂因素。然而，它 有主要的缺陷：在图书馆准备过程中大量消耗材料，数据读出和信号噪声 辍学，以及跨数据集进行数据集成的路径不明确。 拟议研究方案的总体愿景是开发一种泛经济分析战略，使 任何单一细胞来源材料的永久重复使用。它围绕着一种混合分子工程和 一种计算框架，它松散地受到计算原理的启发。其实验核心是 拟议的研究计划围绕着一种名为APEX的新分子技术。 Based Primer Expansion‘)。APEX的主要创新是基因组材料的共价偶联(即 DNA或cDNA)连接到诸如琼脂糖磁珠之类的固相载体上，然后仅利用聚合酶- 基于非破坏性分子讯问的化验。 在这个项目中，我们将把APEX开发的重点放在单细胞转录组测序应用上， 基因组生物学的普遍适用性。作为一个模型系统，我们将利用外周血淋巴细胞 在基因组特征的多个水平上具有不同特征的复杂亚群。该项目将专注于 关于化验开发和优化、用于数据集成的生物信息学算法的开发、以及规模 最高可达大型队列，以展示该技术的可扩展性。

ABSTRACT The overall goal of the proposed research program is to improve our understanding of single cell biology through information maximization techniques, by applying molecular engineering and computational approaches in sequencing. Specifically, single cell sequencing is rapidly becoming the predominant method for studying human biology and disease because it removes the confounding factor of sequencing cell mixtures in bulk. However, it has major pitfalls: significant material consumption during library preparation, noisy data readouts and signal dropout, and unclear paths for data integration across datasets. The overall vision of the proposed research program is to develop a pan-omic analysis strategy that enables perpetual re-use of any single cell source material. It revolves around a hybrid molecular engineering and computational framework that is loosely inspired by principles found in computing. The experimental core of the proposed research program revolved around a new molecular technology referred to as APEX (‘Attachment- based Primer EXtension’). The major innovation of APEX is the covalent conjugation of genomic material (i.e. DNA or cDNA) to a solid phase support such as an agarose magnetic bead, followed by utilizing only polymerase- based assays for non-destructive molecular interrogation. In this project, we will focus APEX development on single cell transcriptome sequencing applications, with general applicability to genome biology. As a model system, we will utilize peripheral lymphocytes as they consist of complex subpopulations with distinct characteristics at multiple levels of omic features. The project will focus on assay development and optimization, development of bioinformatic algorithms for data integration, and scale up to large cohorts as a demonstration of the scalability of the technology.