Evidence map›Paper›PMID 37246706›Full record

ArticleNucleic acids research2023

NOVA1 prevents overactivation of the unfolded protein response and facilitates chromatin access during human white adipogenesis.

Zhigang Yang, Ping Dong, Jiankun Cao, Na Lin, Shize Ma, Rui Cao, Lei Cai, Lei Wang, Changchang Cao, Yuanchao Xue and 8 more

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

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  5. Interaction of theCells · 2023
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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

18 authors at 2 institutions in 1 country.

Zhigang YangPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.ORCID 0000-0002-8195-7992
Ping DongPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Jiankun CaoPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Na LinPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Shize MaPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Rui CaoPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Lei CaiPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Lei WangKey Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
Changchang CaoKey Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
Yuanchao XueKey Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
Jing PanPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Xiu LiPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Kang WangPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Qiwei LiuPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Chen LiPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Fuxing GongPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.ORCID 0000-0001-8119-8474
Xin FuPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Ran XiaoPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNChinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The molecular mechanism underlying white adipogenesis in humans has not been fully elucidated beyond the transcriptional level. Here, we found that the RNA-binding protein NOVA1 is required for the adipogenic differentiation of human mesenchymal stem cells. By thoroughly exploring the interactions between NOVA1 and its binding RNA, we proved that NOVA1 deficiency resulted in the aberrant splicing of DNAJC10 with an in-frame premature stop codon, reduced DNAJC10 expression at the protein level and hyperactivation of the unfolded protein response (UPR). Moreover, NOVA1 knockdown abrogated the down-regulation of NCOR2 during adipogenesis and up-regulated the 47b+ splicing isoform, which led to decreased chromatin accessibility at the loci of lipid metabolism genes. Interestingly, these effects on human adipogenesis could not be recapitulated in mice. Further analysis of multispecies genomes and transcriptomes indicated that NOVA1-targeted RNA splicing is evolutionarily regulated. Our findings provide evidence for human-specific roles of NOVA1 in coordinating splicing and cell organelle functions during white adipogenesis.

Indexed as

ChromatinRNA-Binding ProteinsUnfolded Protein ResponseAdipogenesisAnimalsHumansMiceNeuro-Oncological Ventral AntigenRNA SplicingChromatinNeuro-Oncological Ventral AntigenNOVA1 protein, humanRNA-Binding Proteins

Identifiers

PMID37246706
PMCPMC10359595
OpenAlexW4378640530

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.