Evidence map›Paper›PMID 27438711›Full record

ArticlePloS one2016

DNA Methylation Variation Trends during the Embryonic Development of Chicken.

Shizhao Li, Yufei Zhu, Lihui Zhi, Xiaoying Han, Jing Shen, Yanli Liu, Junhu Yao, Xiaojun Yang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

22 citing papers in PubMed, 39 citations in OpenAlex.

  1. Review
  2. Review
  3. Effects ofFrontiers in veterinary science · 2024
    Article
  4. Review
  5. DNA methylation in poultry: a review.Journal of animal science and biotechnology · 2023
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Zygotic genome activation in the chicken: a comparative review.Cellular and molecular life sciences : CMLS · 2020
    Review
  16. Review
  17. Article
  18. Article
  19. Article
  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

8 authors at 2 institutions in 1 country.

Shizhao LiCollege of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China.
Yufei ZhuCollege of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China.
Lihui ZhiSchool of Mathematics and Computer Science, ShanXi Normal University, Linfen, Shanxi, People's Republic of China.
Xiaoying HanCollege of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China.
Jing ShenCollege of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China.
Yanli LiuCollege of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China.
Junhu YaoCollege of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China.
Xiaojun YangCollege of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China.
Northwest A&F University · CNShanxi Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The embryogenesis period is critical for epigenetic reprogramming and is thus of great significance in the research field of poultry epigenetics for elucidation of the trends in DNA methylation variations during the embryonic development of birds, particularly due to differences in embryogenesis between birds and mammals. Here, we first examined the variations in genomic DNA methylation during chicken embryogenesis through high-performance liquid chromatography using broilers as the model organism. We then identified the degree of DNA methylation of the promoters and gene bodies involved in two specific genes (IGF2 and TNF-α) using the bisulfite sequencing polymerase chain reaction method. In addition, we measured the expression levels of IGF2, TNF-α and DNA methyltransferase (DNMT) 1, 3a and 3b. Our results showed that the genomic DNA methylation levels in the liver, heart and muscle increased during embryonic development and that the methylation level of the liver was significantly higher in mid-anaphase. In both the muscle and liver, the promoter methylation levels of TNF-α first increased and then decreased, whereas the gene body methylation levels remained lower at embryonic ages E8, 11 and 14 before increasing notably at E17. The promoter methylation level of IGF2 decreased persistently, whereas the methylation levels in the gene body showed a continuous increase. No differences in the expression of TNF-α were found among E8, 11 and 14, whereas a significant increase was observed at E17. IGF2 showed increasing expression level during the examined embryonic stages. In addition, the mRNA and protein levels of DNMTs increased with increasing embryonic ages. These results suggest that chicken shows increasing genomic DNA methylation patterns during the embryonic period. Furthermore, the genomic DNA methylation levels in tissues are closely related to the genes expression levels, and gene expression may be simultaneously regulated by promoter hypomethylation and gene body hypermethylation.

Indexed as

AnimalsChick EmbryoChickensDNA (Cytosine-5-)-MethyltransferasesDNA MethylationEmbryonic DevelopmentGenomeInsulin-Like Growth Factor IIIntronsLiverMusclesPromoter Regions, GeneticReal-Time Polymerase Chain ReactionRNA, MessengerSequence Analysis, DNATumor Necrosis Factor-alphaDNA (Cytosine-5-)-MethyltransferasesInsulin-Like Growth Factor IIRNA, MessengerTumor Necrosis Factor-alpha

Identifiers

PMID27438711
PMCPMC4954715
OpenAlexW2491383955

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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.