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

使用膜片钳和单细胞 RNA-Seq 评估细胞异质性

• 批准号: 8701402
• 负责人: ROBERT HSIU-PING CHOW
• 金额: $ 181.46万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-21 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8701402
• 关键词: Address; Aging; Algorithms; Archives; Bioinformatics; Biological; Brain; Cell Cycle Stage; Cell Extracts; Cell physiology; Cells; Cerebellum; Code; Cytoplasm; Data; Data Analyses; Data Set; Databases; Deposition; Detection; Disease; Electrodes; Electrophysiology (science); Evaluation; Floor; Future; Gene Expression Profile; Generations; Genes; Goals; Heterogeneity; Histocompatibility Testing; Individual; Investigation; Libraries; Life; Measures; Messenger RNA; Methodology; Methods; Mus; Neuronal Plasticity; Neurons; Noise; Nose; Olfactory Epithelial Cell; Operative Surgical Procedures; Patch-Clamp Techniques; Physiological; Placenta; Preparation; RNA; RNA amplification; Reading; Recording of previous events; Relative (related person); Reproducibility; Retrieval; Risk; Sampling; Source; Surface; Syncytiotrophoblast; System; Techniques; Termination of pregnancy; Testing; Tissues; Variant; analytical tool; base; cell type; human tissue; neuroepithelium; olfactory receptor; patch clamp; public health relevance; research study; sucking; tool; transcriptome sequencing; web site

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.

描述（由申请人提供）：我们的总体目标是评估多种人体组织类型中单细胞中测量的 RNA 水平的技术和生物噪音，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变得至关重要，因为 RNA-Seq 的检测下限目前在 10 皮克总 RNA（即单细胞中 RNA 的量）范围内。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来源。其中包括：1) 样品采购和 RNA 检索，2) 测序文库制备，3) 测序方法，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) 基因间变异。 评估不同来源的技术噪音的相对大小将为如何在未来的实验中减少噪音提供信息，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、与邻近细胞的连接、表面上相同细胞的真正功能差异（例如，嗅觉神经元中的不同嗅觉受体）的差异。 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，来自胎盘的合体滋养层细胞，预计其具有相对较低的细胞间变异；其次，来自鼻神经上皮的嗅觉神经元，每个嗅觉神经元预计表达不同的嗅觉受体，为RNA-Seq数据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——膜片钳移液器提取——不需要完全 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，使用从单个细胞中提取的细胞质，我们已经对其进行了膜片钳电生理学记录，然后进行 RNA 测序。 对于所选的每种细胞类型 - 合体滋养层、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；调查技术噪音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 转录组。这里开发的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质量控制后 6 个月存入 dbGAP 和短读存档（或其替代品）。