Evidence map›Paper›PMID 36156153›Full record

ArticleNucleic acids research2022

A massively parallel reporter assay reveals focused and broadly encoded RNA localization signals in neurons.

Martin Mikl, Davide Eletto, Malak Nijim, Minkyoung Lee, Atefeh Lafzi, Farah Mhamedi, Orit David, Simona Baghai Sain, Kristina Handler, Andreas E Moor

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
3.0field-weighted citation impact, top 7% 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

31 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
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  3. Robust mammalian RNA localization elements are complex and multipartite.bioRxiv : the preprint server for biology · 2026
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  4. Review
  5. Cracking the (zip)code of dynein-dependent RNA localization.Nature structural & molecular biology · 2026
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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

10 authors at 2 institutions in 2 countries.

Martin MiklDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.ORCID 0000-0001-8913-7158
Davide ElettoDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Malak NijimDepartment of Human Biology, University of Haifa, Haifa, Israel.
Minkyoung LeeDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Atefeh LafziDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Farah MhamediDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Orit DavidDepartment of Human Biology, University of Haifa, Haifa, Israel.
Simona Baghai SainDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Kristina HandlerDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Andreas E MoorDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.ORCID 0000-0001-8715-8449
ETH Zurich · CHUniversity of Haifa · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Asymmetric subcellular mRNA localization allows spatial regulation of gene expression and functional compartmentalization. In neurons, localization of specific mRNAs to neurites is essential for cellular functioning. However, it is largely unknown how transcript sorting works in a sequence-specific manner. Here, we combined subcellular transcriptomics and massively parallel reporter assays and tested ∼50 000 sequences for their ability to localize to neurites. Mapping the localization potential of >300 genes revealed two ways neurite targeting can be achieved: focused localization motifs and broadly encoded localization potential. We characterized the interplay between RNA stability and localization and identified motifs able to bias localization towards neurite or soma as well as the trans-acting factors required for their action. Based on our data, we devised machine learning models that were able to predict the localization behavior of novel reporter sequences. Testing this predictor on native mRNA sequencing data showed good agreement between predicted and observed localization potential, suggesting that the rules uncovered by our MPRA also apply to the localization of native full-length transcripts.

Indexed as

NeuronsRNA StabilityNeuritesRNA, MessengerTrans-ActivatorsRNA, MessengerTrans-Activators

Identifiers

PMID36156153
PMCPMC9561380
OpenAlexW4297249505

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.