Evidence map›Paper›PMID 33846365›Full record

ArticleScientific reports2021

A flexible microfluidic system for single-cell transcriptome profiling elucidates phased transcriptional regulators of cell cycle.

Karen Davey, Daniel Wong, Filip Konopacki, Eugene Kwa, Tony Ly, Heike Fiegler, Christopher R Sibley

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. High-throughput transcriptomics.Scientific reports · 2022
    Article
  3. Review
  4. Review
  5. Review
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

7 authors.

Karen Davey *Department of Medicine, Division of Brain Sciences, Imperial College London, Burlington Danes, London, UK.
Daniel Wong *Dolomite Bio, Unit 3, Anglian Business Park, Royston, UK.
Filip KonopackiDolomite Bio, Unit 3, Anglian Business Park, Royston, UK.
Eugene KwaDepartment of Medicine, Division of Brain Sciences, Imperial College London, Burlington Danes, London, UK.
Tony LyWellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh, UK.
Heike FieglerDolomite Bio, Unit 3, Anglian Business Park, Royston, UK.
Christopher R SibleyDepartment of Medicine, Division of Brain Sciences, Imperial College London, Burlington Danes, London, UK. chris.sibley@ed.ac.uk.ORCID 0000-0002-8286-4683

Funding

Wellcome TrustWellcome Trust 205990/Z/17/ZWellcome Trust 215454/Z/19/Z
6 · The paper itself

Abstract

Single cell transcriptome profiling has emerged as a breakthrough technology for the high-resolution understanding of complex cellular systems. Here we report a flexible, cost-effective and user-friendly droplet-based microfluidics system, called the Nadia Instrument, that can allow 3' mRNA capture of ~ 50,000 single cells or individual nuclei in a single run. The precise pressure-based system demonstrates highly reproducible droplet size, low doublet rates and high mRNA capture efficiencies that compare favorably in the field. Moreover, when combined with the Nadia Innovate, the system can be transformed into an adaptable setup that enables use of different buffers and barcoded bead configurations to facilitate diverse applications. Finally, by 3' mRNA profiling asynchronous human and mouse cells at different phases of the cell cycle, we demonstrate the system's ability to readily distinguish distinct cell populations and infer underlying transcriptional regulatory networks. Notably this provided supportive evidence for multiple transcription factors that had little or no known link to the cell cycle (e.g. DRAP1, ZKSCAN1 and CEBPZ). In summary, the Nadia platform represents a promising and flexible technology for future transcriptomic studies, and other related applications, at cell resolution.

Indexed as

Gene Expression ProfilingGene Expression RegulationMicrofluidicsSingle-Cell AnalysisTranscription, Genetic3T3 CellsAnimalsCell CycleGene Regulatory NetworksHEK293 CellsHumansMice

Identifiers

PMID33846365
PMCPMC8041752

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Registered trials

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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.