Evaluation of Cellular Heterogeneity Using Patchclamp and RNA-Seq of Single Cells

描述（由申请人提供）：我们的总体目标是评估在许多人体组织类型的单细胞中测量的RNA水平中的技术和生物噪声，并开发分析工具来解决在单细胞水平上观察到的复杂性。了解技术和生物噪声的来源和相对大小已经变得至关重要，因为RNA- seq的最低检测限现在在总RNA的10皮克范围内，即单细胞中的RNA量。技术噪音可能来自几个不同的来源，我们将尝试分别评估。这些包括：1)样品获取和RNA检索，2)测序文库制备，3)测序方法，4)测序实验中的批量效应，5)数据分析的生物信息学方法，6)基因-基因变异性。评估来自不同来源的技术噪音的相对大小将有助于如何在未来的实验中减少噪音，从而减少对有意义的生物变异或噪音研究的干扰。生物噪声或细胞间差异源于细胞历史或命运的差异、细胞周期阶段、与邻近细胞的连接、表面相同细胞的真正功能差异（例如，嗅觉神经元之间的嗅觉受体不同）。我们建议研究三种不同的细胞系统，我们预计它们具有不同水平的细胞间变异（生物噪声）：首先，来自胎盘的合胞滋养母细胞，预计其细胞间变异相对较低；第二，来自鼻神经上皮的嗅觉神经元，每一个都有望表达不同的嗅觉受体，为RNA-Seq数据的差异提供积极的控制；第三，来自小脑的单个浦肯野神经元，可能有更大的细胞间变异。从单个细胞中提取细胞质的方法-膜片钳移液管提取-不需要完全

DESCRIPTION (provided by applicant): Our overall aim is to assess the technical and biological noise in measured RNA levels in single cells in a number of human tissue types, and to develop analytical tools to address the complexity observed at the single-cell level. Understanding the sources and relative sizes of technical and biological noise has become essential, as the lower detection limit of RNA-Seq is now in the range of 10 picograms of total RNA -- i.e. the amount of RNA in single cells. Technical noise can come from several different sources that we will attempt to evaluate separately. These include: 1) sample procurement and RNA retrieval, 2) sequencing library preparation, 3) sequencing methodology, 4) batch effects in sequencing experiments, 5) bioinformatics approaches for data analysis, 6) gene-gene variability. Assessing the relative magnitude of technical noise from different sources will infor how to reduce that noise in future experiments, and thereby reduce interference with studies of meaningful biological variations or noise. Biological noise, or inter-cell differences arise from differences in cellular history or fate, stages of cell cycle, connections to neighboring cells, an true functional differences of ostensibly identical cells (e.g., different olfactory receptors amon olfactory neurons). We propose to study three different cellular systems that we expect to have different levels of inter-cell variation (biological noise): first, syncytiotrophoblast cells from placenta, which are expected to have relatively low inter-cell variation; second, olfactory neurons from nasal neuroepithelium, each of which is expected to express a different olfactory receptor, providing a positive control for differences in the RNA-Seq data; and third, individual Purkinje neurons from the cerebellum, which may have larger inter-cell variation. The method to extract cytoplasm from individual cells -- patch clamp pipette extraction -- does not require fully disrupting the tissue or dispersing the cells. We have already used patch clamp to determine the transcriptomes of multiple individual neurons in the mouse brain, using the cytoplasm extracted from single cells on which we had already performed patch-clamp electrophysiology recordings, followed by RNA-Seq. For each of the cell types chosen - syncytiotrophoblasts, olfactory neurons, Purkinje neurons, cortical neurons we will generate single-cell transcriptome datasets to evaluate heterogeneity among ostensibly similar cells, using patch clamp to extract cell contents and RNA-Seq; investigate sources of technical noise and apply a systematic approach to reduce technical noise. We will test whether neuronal plasticity is reflected as a change in the transcriptome. All analytical tools and the transcriptome database developed here will be shared openly on our website and all project data will be deposited into dbGAP and the Short Read Archive (or its replacement) 6 months after data QC.