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许多人类组织类型中单细胞中测量的RNA水平的技术和生物噪声，并开发分析工具以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的检测下限现在在10皮克总RNA的范围内-即单细胞中RNA的量。技术噪音可能来自几个不同的来源，我们将尝试分别评估。其中包括：1）样品获取和RNA检索，2）测序文库制备，3）测序方法学，4）测序实验中的批次效应，5）用于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、细胞周期阶段、与相邻细胞的连接、表面上相同细胞的真正功能差异（例如，不同的嗅觉受体amon嗅觉神经元）。 我们建议研究三种不同的细胞系统，我们预计有不同水平的细胞间的变化（生物噪声）：第一，来自胎盘的合体滋养层细胞，预期其具有相对低的细胞间变异;第二，来自鼻神经上皮的嗅觉神经元，预期其各自表达不同的嗅觉受体，为RNA-Seq数据中的差异提供阳性对照;第三，来自小脑的单个浦肯野神经元，其可能具有较大的细胞间变异。从单个细胞中提取细胞质的方法--膜片钳吸管提取--不需要完全分离细胞质。 破坏组织或分散细胞。我们已经使用膜片钳来确定小鼠大脑中多个单个神经元的转录组，使用从我们已经进行膜片钳电生理记录的单细胞中提取的细胞质，然后进行RNA-Seq。 对于选择的每种细胞类型-合胞体滋养层细胞，嗅觉神经元，浦肯野神经元，皮质神经元，我们将生成单细胞转录组数据集，以评估表面相似细胞之间的异质性，使用膜片钳提取细胞内容物和RNA-Seq;研究技术噪音的来源并应用系统方法来减少技术噪音。我们将测试神经元可塑性是否反映为神经元可塑性的变化。 转录组所有分析工具和转录组数据库将在我们的网站上公开共享，所有项目数据将在数据QC后6个月存入dbGAP和Short Read Archive（或其替代品）。

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.