Evidence map›Paper›PMID 27189161›Full record

ArticleBMC genomics2016

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

Maurizio Pellegrino, Adam Sciambi, Jamie L Yates, Joshua D Mast, Charles Silver, Dennis J Eastburn

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 29 citations in OpenAlex.

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  12. Platforms for Single-Cell Collection and Analysis.International journal of molecular sciences · 2018
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Maurizio PellegrinoMission Bio, Inc., 953 Indiana St., San Francisco, California, 94107, USA.
Adam SciambiMission Bio, Inc., 953 Indiana St., San Francisco, California, 94107, USA.
Jamie L YatesMission Bio, Inc., 953 Indiana St., San Francisco, California, 94107, USA.
Joshua D MastMission Bio, Inc., 953 Indiana St., San Francisco, California, 94107, USA.
Charles SilverMission Bio, Inc., 953 Indiana St., San Francisco, California, 94107, USA.
Dennis J EastburnMission Bio, Inc., 953 Indiana St., San Francisco, California, 94107, USA. eastburn@missionbio.com.
Mission Bio (United States) · US

Funding

High-throughput single-cell sorting and sequencing with PACSR44HG007814 · NHGRI · MISSION BIO, INC. · PI EASTBURN, DENNIS J · 2015 to 2016
$1.1M
Molecular characterization of circulating tumor cells with PCR-activated cell sortingR43CA199152 · NCI · MISSION BIO, INC. · PI EASTBURN, DENNIS J · 2015 to 2015
$200k
NCI NIH HHS R43 CA199152NHGRI NIH HHS R44 HG007814
6 · The paper itself

Abstract

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.

Indexed as

Gene Expression ProfilingHigh-Throughput Nucleotide SequencingPolymerase Chain ReactionTranscriptomeCell LineCluster AnalysisGene Expression RegulationHumansMultiplex Polymerase Chain ReactionReal-Time Polymerase Chain ReactionReproducibility of ResultsSensitivity and SpecificitySingle-Cell AnalysisWorkflowCell sortingDropletsGene expressionHeterogeneityMicrofluidicsPCRSingle-cellTranscriptome

Identifiers

PMID27189161
PMCPMC4869385
OpenAlexW2400786625

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.