Evidence map›Paper›PMID 37283087›Full record

ArticleNucleic acids research2023

Efficient and sensitive profiling of RNA-protein interactions using TLC-CLIP.

Christina Ernst, Julien Duc, Didier Trono

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. 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 at 1 institution in 1 country.

Christina ErnstGlobal Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0002-3569-2209
Julien DucGlobal Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0001-8195-804X
Didier TronoGlobal Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0002-3383-0401
École Polytechnique Fédérale de Lausanne · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA-binding proteins are instrumental for post-transcriptional gene regulation, controlling all aspects throughout the lifecycle of RNA molecules. However, transcriptome-wide methods to profile RNA-protein interactions in vivo remain technically challenging and require large amounts of starting material. Herein, we present an improved library preparation strategy for crosslinking and immunoprecipitation (CLIP) that is based on tailing and ligation of cDNA molecules (TLC). TLC involves the generation of solid-phase cDNA, followed by ribotailing to significantly enhance the efficiency of subsequent adapter ligation. These modifications result in a streamlined, fully bead-based library preparation strategy, which eliminates time-consuming purification procedures and drastically reduces sample loss. As a result, TLC-CLIP displays unparalleled sensitivity, enabling the profiling of RNA-protein interactions from as few as 1000 cells. To demonstrate the effectiveness of TLC-CLIP, we profiled four endogenous RNA-binding proteins, showcasing its reproducibility and improved precision resulting from a higher occurrence of crosslinking-induced deletions. These deletions serve as an intrinsic quality metric and increase both specificity and nucleotide-resolution.

Indexed as

RNARNA-Binding ProteinsBinding SitesDNA, ComplementaryHigh-Throughput Nucleotide SequencingImmunoprecipitationReproducibility of ResultsDNA, ComplementaryRNARNA-Binding Proteins

Identifiers

PMID37283087
PMCPMC10359464
OpenAlexW4379599589

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.