High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics
The importance of single-cell level data is increasingly appreciated, and significant advances in this direction have been made in recent years. Common to these technologies is the need to physically segregate individual cells into containers, such as wells or chambers of a micro-fluidics chip. High...
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| Format: | Online |
| Language: | English |
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Public Library of Science
2015
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4441486/ |
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pubmed-4441486 |
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pubmed-44414862015-05-28 High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics Rotem, Assaf Ram, Oren Shoresh, Noam Sperling, Ralph A. Schnall-Levin, Michael Zhang, Huidan Basu, Anindita Bernstein, Bradley E. Weitz, David A. Research Article The importance of single-cell level data is increasingly appreciated, and significant advances in this direction have been made in recent years. Common to these technologies is the need to physically segregate individual cells into containers, such as wells or chambers of a micro-fluidics chip. High-throughput Single-Cell Labeling (Hi-SCL) in drops is a novel method that uses drop-based libraries of oligonucleotide barcodes to index individual cells in a population. The use of drops as containers, and a microfluidics platform to manipulate them en-masse, yields a highly scalable methodological framework. Once tagged, labeled molecules from different cells may be mixed without losing the cell-of-origin information. Here we demonstrate an application of the method for generating RNA-sequencing data for multiple individual cells within a population. Barcoded oligonucleotides are used to prime cDNA synthesis within drops. Barcoded cDNAs are then combined and subjected to second generation sequencing. The data are deconvoluted based on the barcodes, yielding single-cell mRNA expression data. In a proof-of-concept set of experiments we show that this method yields data comparable to other existing methods, but with unique potential for assaying very large numbers of cells. Public Library of Science 2015-05-22 /pmc/articles/PMC4441486/ /pubmed/26000628 http://dx.doi.org/10.1371/journal.pone.0116328 Text en © 2015 Rotem et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Rotem, Assaf Ram, Oren Shoresh, Noam Sperling, Ralph A. Schnall-Levin, Michael Zhang, Huidan Basu, Anindita Bernstein, Bradley E. Weitz, David A. |
| spellingShingle |
Rotem, Assaf Ram, Oren Shoresh, Noam Sperling, Ralph A. Schnall-Levin, Michael Zhang, Huidan Basu, Anindita Bernstein, Bradley E. Weitz, David A. High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics |
| author_facet |
Rotem, Assaf Ram, Oren Shoresh, Noam Sperling, Ralph A. Schnall-Levin, Michael Zhang, Huidan Basu, Anindita Bernstein, Bradley E. Weitz, David A. |
| author_sort |
Rotem, Assaf |
| title |
High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics |
| title_short |
High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics |
| title_full |
High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics |
| title_fullStr |
High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics |
| title_full_unstemmed |
High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics |
| title_sort |
high-throughput single-cell labeling (hi-scl) for rna-seq using drop-based microfluidics |
| description |
The importance of single-cell level data is increasingly appreciated, and significant advances in this direction have been made in recent years. Common to these technologies is the need to physically segregate individual cells into containers, such as wells or chambers of a micro-fluidics chip. High-throughput Single-Cell Labeling (Hi-SCL) in drops is a novel method that uses drop-based libraries of oligonucleotide barcodes to index individual cells in a population. The use of drops as containers, and a microfluidics platform to manipulate them en-masse, yields a highly scalable methodological framework. Once tagged, labeled molecules from different cells may be mixed without losing the cell-of-origin information. Here we demonstrate an application of the method for generating RNA-sequencing data for multiple individual cells within a population. Barcoded oligonucleotides are used to prime cDNA synthesis within drops. Barcoded cDNAs are then combined and subjected to second generation sequencing. The data are deconvoluted based on the barcodes, yielding single-cell mRNA expression data. In a proof-of-concept set of experiments we show that this method yields data comparable to other existing methods, but with unique potential for assaying very large numbers of cells. |
| publisher |
Public Library of Science |
| publishDate |
2015 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4441486/ |
| _version_ |
1613227018972823552 |