Evidence map›Paper›PMID 39595311›Full record

ArticleAnimals : an open access journal from MDPI2024

Construction and Analysis of miRNA-mRNA Interaction Network in Ovarian Tissue of Wanxi White Geese Across Different Breeding Stages.

Ruidong Li, Yuhua Wang, Fei Xie, Xinwei Tong, Xiaojin Li, Man Ren, Qianqian Hu, Shenghe Li

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2024. 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
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. MiRNAs in Poultry Health and Production: Progress and Challenges.Animals : an open access journal from MDPI · 2025
    Review
  4. TheCurrent issues in molecular biology · 2025
    Article
  5. 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.

Ruidong LiCollege of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China.ORCID 0009-0007-1872-4399
Yuhua WangCollege of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China.
Fei XieCollege of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China.
Xinwei TongCollege of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China.
Xiaojin LiCollege of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China.
Man RenCollege of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China.
Qianqian HuCollege of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China.
Shenghe LiCollege of Animal Science, Anhui Science and Technology University, Chuzhou 239000, China.ORCID 0000-0001-8767-6991

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian development significantly influences the laying performance of geese. In this study, the transcriptome analysis was conducted on the ovarian tissues of Wanxi White Geese during the pre-laying (KL), laying (CL), and ceased-laying period (XL). Short Time-series Expression Miner (STEM) analysis and miRNA-mRNA regulatory network construction were performed to identify the key genes and miRNAs regulating laying traits. Comparative analysis of KL vs. CL, CL vs. XL, and XL vs. KL groups resulted in the identification of 337, 136, and 525 differentially expressed genes (DEGs), and 258, 1131, and 909 differentially expressed miRNAs (DEMs), respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis (

Indexed as

egg-laying periodsmiRNAmRNAovaryWanxi White Goose

Identifiers

PMID39595311
PMCPMC11591532

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.