Evidence map›Paper›PMID 39554011›Full record

ArticlebioRxiv : the preprint server for biology2024

Quantitative design of cell type-specific mRNA stability from microRNA expression data.

Lukas Oesinghaus, Sebastian Castillo-Hair, Nicole Ludwig, Andreas Keller, Georg Seelig

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Lukas OesinghausDepartment of Electrical & Computer Engineering, University of Washington, Seattle, WA, United States.ORCID 0000-0002-5464-1044
Sebastian Castillo-HairDepartment of Electrical & Computer Engineering, University of Washington, Seattle, WA, United States.ORCID 0000-0002-2384-3129
Nicole LudwigDepartment for Clinical Bioinformatics, Center for Bioinformatics, PharmaScienceHub, Saarland University, Germany.ORCID 0000-0003-4703-7567
Andreas KellerDepartment for Clinical Bioinformatics, Center for Bioinformatics, PharmaScienceHub, Saarland University, Germany.ORCID 0000-0002-5361-0895
Georg SeeligDepartment of Electrical & Computer Engineering, University of Washington, Seattle, WA, United States.ORCID 0000-0002-3163-8782

Funding

Engineering cell type-specific splicing regulationR01GM149631 · NIGMS · UNIVERSITY OF WASHINGTON · PI Georg Seelig · 2023 to 2026
$1.5M
Integrating the impacts of genetic variation with massively parallel mRNA and protein barcodingR56HG013312 · NHGRI · UNIVERSITY OF WASHINGTON · PI NIVALA, JEFFREY MATTHEW, SEELIG, GEORG · 2024 to 2024
$637k
NHGRI NIH HHS R56 HG013312NIGMS NIH HHS R01 GM149631
6 · The paper itself

Abstract

Limiting expression to target cell types is a longstanding goal in gene therapy, which could be met by sensing endogenous microRNA. However, an unclear association between microRNA expression and activity currently hampers such an approach. Here, we probe this relationship by measuring the stability of synthetic microRNA-responsive 3'UTRs across 10 cell lines in a library format. By systematically addressing biases in microRNA expression data and confounding factors such as microRNA crosstalk, we demonstrate that a straightforward model can quantitatively predict reporter stability purely from expression data. We use this model to design constructs with previously unattainable response patterns across our cell lines. The rules we derive for microRNA expression data selection and processing should apply to microRNA-responsive devices for any environment with available expression data.

Identifiers

PMID39554011
PMCPMC11565874

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.