Evidence map›Paper›PMID 37719075›Full record

ArticleBio-protocol2023

Absolute Quantification of mRNA Isoforms in Adult Stem Cells Using Microfluidic Digital PCR.

Shubhangi Das Barman, Zofija Frimand, Antoine De Morree

Abstract read
In one paragraph

Article in Bio-protocol, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Shubhangi Das BarmanDepartment of Biomedicine, Aarhus University, Central Jutland, Denmark.
Zofija FrimandDepartment of Biomedicine, Aarhus University, Central Jutland, Denmark.
Antoine De MorreeDepartment of Biomedicine, Aarhus University, Central Jutland, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adult stem cells play key roles in homeostasis and tissue repair. These cells are regulated by a tight control of transcriptional programs. For example, muscle stem cells (MuSCs), located beneath the basal lamina, exist in the quiescent state but can transition to an activated, proliferative state upon injury. The control of MuSC state depends on the expression levels of myogenic transcription factors. Recent studies revealed the presence of different mRNA isoforms, with distinct biological regulation. Quantifying the exact expression levels of the mRNA isoforms encoding these myogenic transcription factors is therefore key to understanding how MuSCs switch between cell states. Previously, quantitative real-time polymerase chain reaction (qRT-PCR) has been used to quantify RNA expression levels. However, qRT-PCR depends on large amounts of RNA input and only measures relative abundance. Here, we present a protocol for the absolute quantification of mRNA isoforms using microfluidic digital PCR (mdPCR). Primary MuSCs isolated from individual skeletal muscles (gastrocnemius and masseter) are lysed, and their RNA is reverse-transcribed into cDNA and copied into double-stranded DNA. Following exonuclease I digestion to remove remaining single-stranded DNA, the samples are loaded onto a mdPCR chip with TaqMan probes targeting the mRNA isoforms of interest, whereupon target molecules are amplified in nanoliter chambers. We demonstrate that mdPCR can give exact molecule counts per cell for mRNA isoforms encoding the myogenic transcription factor Pax3. This protocol enables the absolute quantification of low abundant mRNA isoforms in a fast, precise, and reliable way.

Indexed as

Alternative polyadenylationDigital PCRMicrofluidicsmRNA isoformsMuscle stem cellsPax3Skeletal muscle

Identifiers

PMID37719075
PMCPMC10501916

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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.