Versatile, exponentially scalable methods for single cell molecular profiling

用于单细胞分子分析的多功能、指数扩展方法

基本信息

批准号：
10447677
负责人：
Jay Ashok Shendure
金额：
$ 98.96万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-15 至 2024-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10447677
关键词：
A549 ATAC-seq Adoption Architecture Atlases Binding Biological Assay Biological Models Cell Nucleus Cells Cellular Assay Chemicals Chromatin Chromosomes Communities Computer software DNA Data Analyses Disease Emulsions Functional disorder Gene Expression Regulation Genes Genetic Genetic Screening Genetic Transcription Genome Genomics Goals Hi-C Human Biology Human body Individual Kinetics Label Measures Messenger RNA Methods Microfluidics Modeling Modernization Molecular Molecular Biology Molecular Conformation Molecular Profiling Normal Cell Nucleic Acids Organism Pathology Phenotype Physiologic pulse Proteins Protocols documentation RNA Regulatory Element Reporter Research Resolution Standardization Technology Transcription Initiation Work base chemical genetics combinatorial cost effective human disease human tissue indexing novel strategies transcription factor transcriptome sequencing

项目摘要

The field of single cell genomics is exploding. However, the vast majority of studies restrict themselves to quantifying mRNA transcription, typically in a few thousand cells. We have recently pioneered a new class of methods based on the concept of single cell combinatorial indexing (“sci”), wherein several rounds of splitting, molecular indexing, and pooling are used to uniquely label nucleic acids of cells or nuclei, without requiring the isolation or compartmentalization of each cell. The number of cells that can be uniquely labeled scales exponentially with the number of rounds of indexing, e.g. millions of cells can be profiled with as few as three rounds of indexing. Since 2015, we have developed sci- methods for quantifying chromatin accessibility (sci-ATAC-seq), transcription (sci-RNA-seq), chromatin architecture (sci-Hi-C), and genome sequence (sci-LIANTI), as well as a co-assay of chromatin accessibility and transcription (sci-CAR). Here, we propose to develop a much broader range of single cell methods, all based on the unifying concept of single cell combinatorial indexing. In our first aim, we will develop additional “single channel” sci- assays of various aspects of molecular state. In our second aim, we will develop additional “two channel” sci- assays, e.g. co-assays of RNA and DNA. In our third aim, we will adapt sci- assays to enable large-scale chemical and genetic screens in single cells. In our final aim, we will work to make the methods and associated software widely available to the research community. As a versatile, exponentially scalable platform, we anticipate that single cell combinatorial indexing will deepen and broaden the impact of single cell genomics for diverse goals, including for descriptive molecular atlases of organisms, for functional studies of genes and regulatory elements, and for modeling gene regulation.

单细胞基因组学领域正在呈爆炸式增长，然而，绝大多数研究仅限于这一领域。我们最近开创了一种新的方法，通常是在几千个细胞中定量 mRNA 转录。基于单细胞组合索引（“sci”）概念的方法，因此需要进行几轮分割，分子索引和池化用于独特地标记细胞或细胞核的核酸，而不需要每个细胞的分离或区室化可以被唯一标记的细胞数量。与索引轮数成指数关系，例如只需三轮即可分析数百万个细胞自 2015 年以来，我们开发了量化染色质可及性的科学方法。 (sci-ATAC-seq)、转录 (sci-RNA-seq)、染色质结构 (sci-Hi-C) 和基因组序列 (sci-LIANTI)，以及染色质可及性和转录的联合检测 (sci-CAR)。开发更广泛的单细胞方法，所有这些都基于单细胞的统一概念在我们的第一个目标中，我们将开发各种额外的“单通道”科学分析。在我们的第二个目标中，我们将开发额外的“双通道”科学测定，例如 RNA 和 DNA 的联合测定在我们的第三个目标中，我们将采用科学测定来实现大规模的化学和 DNA 测定。在我们的最终目标中，我们将致力于开发方法和相关软件。作为一个多功能、可指数扩展的平台，我们预计这一点将被广泛提供给研究界。单细胞组合索引将加深和扩大单细胞基因组学对不同目标的影响，包括生物体的描述性分子图谱、基因和调控的功能研究元素，以及用于基因调控建模。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

The landscape of alternative polyadenylation in single cells of the developing mouse embryo.

DOI：
10.1038/s41467-021-25388-8
发表时间：
2021-08-24
期刊：
Nature communications
影响因子：
16.6
作者：
Agarwal V;Lopez-Darwin S;Kelley DR;Shendure J
通讯作者：
Shendure J

High-Capacity Sample Multiplexing for Single Cell Chromatin Accessibility Profiling.

用于单细胞染色质可及性分析的高容量样品多重分析。

DOI：
10.1101/2023.03.05.531201
发表时间：
2023
期刊：
bioRxiv : the preprint server for biology
影响因子：
0
作者：
Booth,GregoryT;Daza,RizaM;Srivatsan,SanjayR;McFaline-Figueroa,JoséL;Gladden,RulaGreen;Furlan,ScottN;Shendure,Jay;Trapnell,Cole
通讯作者：
Trapnell,Cole

A human cell atlas of fetal gene expression.

DOI：
10.1126/science.aba7721
发表时间：
2020-11-13
期刊：
Science (New York, N.Y.)
影响因子：
0
作者：
Cao J;O'Day DR;Pliner HA;Kingsley PD;Deng M;Daza RM;Zager MA;Aldinger KA;Blecher-Gonen R;Zhang F;Spielmann M;Palis J;Doherty D;Steemers FJ;Glass IA;Trapnell C;Shendure J
通讯作者：
Shendure J