Evidence map›Paper›PMID 37001915›Full record

ArticleRNA (New York, N.Y.)2023

Co-phase separation of Y14 and RNA in vitro and its implication for DNA repair.

Chia-Lin Yu, Tzu-Wei Chuang, Sabrina Yeo Samuel, Yuan-Chao Lou, Woan-Yuh Tarn

Open access · bronzeAbstract read
In one paragraph

Article in RNA (New York, N.Y.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

5 authors at 2 institutions in 1 country.

Chia-Lin YuInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.
Tzu-Wei ChuangInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.
Sabrina Yeo SamuelInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.
Yuan-Chao LouBiomedical Translation Research Center, Academia Sinica, Taipei 115, Taiwan.
Woan-Yuh TarnInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan wtarn@ibms.sinica.edu.tw.
Institute of Biomedical Sciences, Academia Sinica · TWNational Taiwan University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The multifunctional RNA recognition motif-containing protein Y14/RBM8A participates in mRNA metabolism and is essential for the efficient repair of DNA double-strand breaks (DSBs). Y14 contains highly charged, low-complexity sequences in both the amino- and carboxy-terminal domains. The feature of charge segregation suggests that Y14 may undergo liquid-liquid phase separation (LLPS). Recombinant Y14 formed phase-separated droplets, which were sensitive to pH and salt concentration. Domain mapping suggested that LLPS of Y14 involves multivalent electrostatic interactions and is partly determined by the net charge of its low-complexity regions. Phospho-mimicry of the carboxy-terminal arginine-serine dipeptides of Y14 suppressed phase separation. Moreover, RNA could phase separate into Y14 droplets and modulate Y14 LLPS in a concentration-dependent manner. Finally, the capacity of Y14 in LLPS and coacervation with RNA in vitro correlated with its activity in DSB repair. These results reveal a molecular rule for LLPS of Y14 in vitro and an implication for its co-condensation with RNA in genome stability.

Indexed as

ArginineRNADNA RepairProtein DomainsRNA-Binding ProteinsArginineRNARNA-Binding ProteinsDNA damage repairelectrostatic interactionliquid–liquid phase separationRNA processing factor

Identifiers

PMID37001915
PMCPMC10275266
OpenAlexW4362460273

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.