Evidence map›Paper›PMID 34107874›Full record

ArticleBMC genomics2021

Transcriptome analysis of embryonic muscle development in Chengkou Mountain Chicken.

Lingtong Ren, Anfang Liu, Qigui Wang, Honggan Wang, Deqiang Dong, Lingbin Liu

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2021. 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
3.8field-weighted citation impact, top 5% 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

29 citing papers in PubMed, 43 citations in OpenAlex.

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  10. Building Haplotype-Resolved 3D Genome Maps of Chicken Skeletal Muscle.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
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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

6 authors at 2 institutions in 1 country.

Lingtong Ren *College of Animal Science and Technology, Southwest University, Beibei, 400715, Chongqing, P. R. China.
Anfang Liu *College of Animal Science and Technology, Southwest University, Beibei, 400715, Chongqing, P. R. China.
Qigui WangChongQing Academy of Animal Sciences, Rongchang, 402460, Chongqing, P. R. China.
Honggan WangCollege of Animal Science and Technology, Southwest University, Beibei, 400715, Chongqing, P. R. China.
Deqiang DongCollege of Animal Science and Technology, Southwest University, Beibei, 400715, Chongqing, P. R. China.
Lingbin LiuCollege of Animal Science and Technology, Southwest University, Beibei, 400715, Chongqing, P. R. China. liulb515@163.com.
Southwest University · CNChongqing Academy of Animal Science · CN

Funding

China Postdoctoral Science Foundation 2020M673157Chongqing Natural Science Foundation cstc2019jcyj-msxmX0513National Natural Science Foundation of China 32002155the Undergraduate Innovation and Entrepreneurship Training Program of Southwest University X202010635531
6 · The paper itself

Abstract

backgroundMuscle is the predominant portion of any meat product, and growth performance and product quality are the core of modern breeding. The embryonic period is highly critical for muscle development, the number, shape and structure of muscle fibers are determined at the embryonic stage. Herein, we performed transcriptome analysis to reveal the law of muscle development in the embryonic stage of Chengkou Mountain Chicken at embryonic days (E) 12, 16, 19, 21.

resultsDiameter and area of muscle fibers exhibited significant difference at different embryonic times(P < 0.01). A total of 16,330 mRNAs transcripts were detected, including 109 novel mRNAs transcripts. By comparing different embryonic muscle development time points, 2,262 in E12vsE16, 5,058 in E12vsE19, 6139 in E12vsE21, 1,282 in E16vsE19, 2,920 in E16vsE21, and 646 in E19vsE21differentially expressed mRNAs were identified. It is worth noting that 7,572 mRNAs were differentially expressed. The time-series expression profile of differentially expressed genes (DEGs) showed that the rising and falling expression trends were significantly enriched. The significant enrichment trends included 3,150 DEGs. GO enrichment analysis provided three significantly enriched categories of significantly enriched differential genes, including 65 cellular components, 88 molecular functions, and 453 biological processes. Through KEGG analysis, we explored the biological metabolic pathways involved in differentially expressed genes. A total of 177 KEGG pathways were enriched, including 19 significant pathways, such as extracellular matrix-receptor interactions. Similarly, numerous pathways related to muscle development were found, including the Wnt signaling pathway (P < 0.05), MAPK signalingpathway, TGF-beta signaling pathway, PI3K-Akt signaling pathway and mTOR signaling pathway. Among the differentially expressed genes, we selected those involved in developing 4-time points; notably, up-regulated genes included MYH1F, SLC25A12, and HADHB, whereas the down-regulated genes included STMN1, VASH2, and TUBAL3.

conclusionsOur study explored the embryonic muscle development of the Chengkou Mountain Chicken. A large number of DEGs related to muscle development have been identified ,and validation of key genes for embryonic development and preliminary explanation of their role in muscle development. Overall, this study broadened our current understanding of the phenotypic mechanism for myofiber formation and provides valuable information for improving chicken quality.

Indexed as

ChickensTranscriptomeAnimalsEmbryonic DevelopmentGene Expression ProfilingMuscle DevelopmentPhosphatidylinositol 3-KinasesPhosphatidylinositol 3-KinasesChengkou Mountain ChickenEmbryo muscle developmentTranscriptome analysis

Identifiers

PMID34107874
PMCPMC8191012
OpenAlexW3116722353

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.