Evidence map›Paper›PMID 32256519›Full record

ReviewFrontiers in genetics2020

Epigenetic Reprogramming During Somatic Cell Nuclear Transfer: Recent Progress and Future Directions.

Xiangyu Wang, Jiadan Qu, Jie Li, Hongbin He, Zhonghua Liu, Yanjun Huan

Abstract readReview
In one paragraph

Review in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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  5. Article
  6. Article
  7. Cellular imbalance in proximal and distal lung of CFTRMolecular medicine (Cambridge, Mass.) · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Review
  14. Article
  15. Article
  16. Epigenetic Reprogramming and Somatic Cell Nuclear Transfer.Methods in molecular biology (Clifton, N.J.) · 2023
    Review
  17. Review
  18. Article
  19. Strategies to Improve the Efficiency of Somatic Cell Nuclear Transfer.International journal of molecular sciences · 2022
    Review
  20. 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

6 authors.

Xiangyu WangCollege of Veterinary Medicine, Qingdao Agricultural University, Qingdao, China.
Jiadan QuCollege of Veterinary Medicine, Qingdao Agricultural University, Qingdao, China.
Jie LiDepartment of Cadre Health Care, Qingdao Municipal Hospital, Qingdao, China.
Hongbin HeCollege of Life Sciences, Shandong Normal University, Jinan, China.
Zhonghua LiuCollege of Life Sciences, Northeast Agricultural University, Harbin, China.
Yanjun HuanCollege of Veterinary Medicine, Qingdao Agricultural University, Qingdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Somatic cell nuclear transfer (SCNT) has broad applications but is limited by low cloning efficiency. In this review, we mainly focus on SCNT-mediated epigenetic reprogramming in livestock and also describe mice data for reference. This review presents the factors contributing to low cloning efficiency, demonstrates that incomplete epigenetic reprogramming leads to the low developmental potential of cloned embryos, and further describes the regulation of epigenetic reprogramming by long non-coding RNAs, which is a new research perspective in the field of SCNT-mediated epigenetic reprogramming. In conclusion, this review provides new insights into the epigenetic regulatory mechanism during SCNT-mediated nuclear reprogramming, which could have great implications for improving cloning efficiency.

Indexed as

cloning efficiencyepigenetic modificationlong non-coding RNAnuclear reprogrammingsomatic cell nuclear transfer

Identifiers

PMID32256519
PMCPMC7093498

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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.