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RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures
BACKGROUND: Rare cell subtypes can profoundly impact the course of human health and disease, yet their presence within a sample is often missed with bulk molecular analysis. Single-cell analysis tools such as FACS, FISH-FC and single-cell barcode-based sequencing can investigate cellular heterogenei...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4869385/ https://www.ncbi.nlm.nih.gov/pubmed/27189161 http://dx.doi.org/10.1186/s12864-016-2694-2 |
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author | Pellegrino, Maurizio Sciambi, Adam Yates, Jamie L. Mast, Joshua D. Silver, Charles Eastburn, Dennis J. |
author_facet | Pellegrino, Maurizio Sciambi, Adam Yates, Jamie L. Mast, Joshua D. Silver, Charles Eastburn, Dennis J. |
author_sort | Pellegrino, Maurizio |
collection | PubMed |
description | BACKGROUND: Rare cell subtypes can profoundly impact the course of human health and disease, yet their presence within a sample is often missed with bulk molecular analysis. Single-cell analysis tools such as FACS, FISH-FC and single-cell barcode-based sequencing can investigate cellular heterogeneity; however, they have significant limitations that impede their ability to identify and transcriptionally characterize many rare cell subpopulations. RESULTS: PCR-activated cell sorting (PACS) is a novel cytometry method that uses single-cell TaqMan PCR reactions performed in microfluidic droplets to identify and isolate cell subtypes with high-throughput. Here, we extend this method and demonstrate that PACS enables high-dimensional molecular profiling on TaqMan-targeted cells. Using a random priming RNA-Seq strategy, we obtained high-fidelity transcriptome measurements following PACS sorting of prostate cancer cells from a heterogeneous population. The sequencing data revealed prostate cancer gene expression profiles that were obscured in the unsorted populations. Single-cell expression analysis with PACS was subsequently used to confirm a number of the differentially expressed genes identified with RNA sequencing. CONCLUSIONS: PACS requires minimal sample processing, uses readily available TaqMan assays and can isolate cell subtypes with high sensitivity. We have now validated a method for performing next-generation sequencing on mRNA obtained from PACS isolated cells. This capability makes PACS well suited for transcriptional profiling of rare cells from complex populations to obtain maximal biological insight into cell states and behaviors. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2694-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4869385 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-48693852016-05-18 RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures Pellegrino, Maurizio Sciambi, Adam Yates, Jamie L. Mast, Joshua D. Silver, Charles Eastburn, Dennis J. BMC Genomics Methodology Article BACKGROUND: Rare cell subtypes can profoundly impact the course of human health and disease, yet their presence within a sample is often missed with bulk molecular analysis. Single-cell analysis tools such as FACS, FISH-FC and single-cell barcode-based sequencing can investigate cellular heterogeneity; however, they have significant limitations that impede their ability to identify and transcriptionally characterize many rare cell subpopulations. RESULTS: PCR-activated cell sorting (PACS) is a novel cytometry method that uses single-cell TaqMan PCR reactions performed in microfluidic droplets to identify and isolate cell subtypes with high-throughput. Here, we extend this method and demonstrate that PACS enables high-dimensional molecular profiling on TaqMan-targeted cells. Using a random priming RNA-Seq strategy, we obtained high-fidelity transcriptome measurements following PACS sorting of prostate cancer cells from a heterogeneous population. The sequencing data revealed prostate cancer gene expression profiles that were obscured in the unsorted populations. Single-cell expression analysis with PACS was subsequently used to confirm a number of the differentially expressed genes identified with RNA sequencing. CONCLUSIONS: PACS requires minimal sample processing, uses readily available TaqMan assays and can isolate cell subtypes with high sensitivity. We have now validated a method for performing next-generation sequencing on mRNA obtained from PACS isolated cells. This capability makes PACS well suited for transcriptional profiling of rare cells from complex populations to obtain maximal biological insight into cell states and behaviors. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2694-2) contains supplementary material, which is available to authorized users. BioMed Central 2016-05-17 /pmc/articles/PMC4869385/ /pubmed/27189161 http://dx.doi.org/10.1186/s12864-016-2694-2 Text en © Pellegrino et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article Pellegrino, Maurizio Sciambi, Adam Yates, Jamie L. Mast, Joshua D. Silver, Charles Eastburn, Dennis J. RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures |
title | RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures |
title_full | RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures |
title_fullStr | RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures |
title_full_unstemmed | RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures |
title_short | RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures |
title_sort | rna-seq following pcr-based sorting reveals rare cell transcriptional signatures |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4869385/ https://www.ncbi.nlm.nih.gov/pubmed/27189161 http://dx.doi.org/10.1186/s12864-016-2694-2 |
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