RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures

BMC Genomics

Methodology Article

Joshua D. Mast¹  Jamie L. Yates¹  Charles Silver¹  Maurizio Pellegrino¹  Adam Sciambi¹  Dennis J. Eastburn¹ 

[1]Mission Bio, Inc., 953 Indiana St., 94107, San Francisco, California, USA

关键词: Transcriptome;    Droplets;    Cell sorting;    Heterogeneity;    Single-cell;    Microfluidics;    Gene expression;    PCR;   

DOI  :  10.1186/s12864-016-2694-2

 received in 2015-11-11, accepted in 2016-05-04,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundRare 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.ResultsPCR-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.ConclusionsPACS 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.

【 授权许可】

CC BY   
© Pellegrino et al. 2016