Evidence map›Paper›PMID 36448436›Full record

ArticleJournal of veterinary science2022

Exploring differentially expressed genes related to metabolism by RNA-Seq in porcine embryonic fibroblast after insulin treatment.

Yingjuan Liang, Jinpeng Wang, Xinyu Li, Shuang Wu, Chaoqian Jiang, Yue Wang, Xuechun Li, Zhong-Hua Liu, Yanshuang Mu

Open access · goldAbstract read
In one paragraph

Article in Journal of veterinary science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 79% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

9 authors at 1 institution in 1 country.

Yingjuan Liang *Key Laboratory of Animal Cellular and Genetic Engineering of Heilongjiang Province, College of Life Science, Northeast Agricultural University, Harbin 150000, China.ORCID https://orcid.org/0000-0002-3083-8037
Jinpeng Wang *Key Laboratory of Animal Cellular and Genetic Engineering of Heilongjiang Province, College of Life Science, Northeast Agricultural University, Harbin 150000, China.ORCID https://orcid.org/0000-0002-7215-0193
Xinyu LiKey Laboratory of Animal Cellular and Genetic Engineering of Heilongjiang Province, College of Life Science, Northeast Agricultural University, Harbin 150000, China.ORCID https://orcid.org/0000-0001-8901-2953
Shuang WuKey Laboratory of Animal Cellular and Genetic Engineering of Heilongjiang Province, College of Life Science, Northeast Agricultural University, Harbin 150000, China.ORCID https://orcid.org/0000-0003-2992-3151
Chaoqian JiangKey Laboratory of Animal Cellular and Genetic Engineering of Heilongjiang Province, College of Life Science, Northeast Agricultural University, Harbin 150000, China.ORCID https://orcid.org/0000-0001-5387-8042
Yue WangKey Laboratory of Animal Cellular and Genetic Engineering of Heilongjiang Province, College of Life Science, Northeast Agricultural University, Harbin 150000, China.ORCID https://orcid.org/0000-0002-4744-216X
Xuechun LiKey Laboratory of Animal Cellular and Genetic Engineering of Heilongjiang Province, College of Life Science, Northeast Agricultural University, Harbin 150000, China.ORCID https://orcid.org/0000-0002-5849-9700
Zhong-Hua LiuKey Laboratory of Animal Cellular and Genetic Engineering of Heilongjiang Province, College of Life Science, Northeast Agricultural University, Harbin 150000, China. Liuzhonghua@neau.edu.cn.ORCID https://orcid.org/0000-0002-9199-6493
Yanshuang MuKey Laboratory of Animal Cellular and Genetic Engineering of Heilongjiang Province, College of Life Science, Northeast Agricultural University, Harbin 150000, China. muyanshuang@neau.edu.cn.ORCID https://orcid.org/0000-0001-8073-3869
Northeast Agricultural University · CN

Funding

Natural Science Foundation of Heilongjiang Province LH2020C016
6 · The paper itself

Abstract

backgroundInsulin regulates glucose homeostasis and has important effects on metabolism, cell growth, and differentiation. Depending on the cell type and physiological context, insulin signal has specific pathways and biological outcomes in different tissues and cells. For studying the signal pathway of insulin on glycolipid metabolism in porcine embryonic fibroblast (PEF), we used high-throughput sequencing to monitor gene expression patterns regulated by insulin.

objectivesThe goal of our research was to see how insulin affected glucose and lipid metabolism in PEFs.

methodsWe cultured the PEFs with the addition of insulin and sampled them at 0, 48, and 72 h for RNA-Seq analysis in triplicate for each time point.

resultsAt 48 and 72 h, 801 and 1,176 genes were differentially expressed, respectively. Of these, 272 up-regulated genes and 264 down-regulated genes were common to both time points. Gene Ontology analysis was used to annotate the functions of the differentially expressed genes (DEGs), the biological processes related to lipid metabolism and cell cycle were dominant. And the DEGs were significantly enriched in interleukin-17 signaling pathway, phosphatidylinositol-3-kinase-protein kinase B signaling pathway, pyruvate metabolism, and others pathways related to lipid metabolism by Kyoto Encyclopedia of Genes and Genomes enrichment analysis.

conclusionsThese results elucidate the transcriptomic response to insulin in PEF. The genes and pathways involved in the transcriptome mechanisms provide useful information for further research into the complicated molecular processes of insulin in PEF.

Indexed as

FibroblastsInsulinsAnimalsGlucoseLipid MetabolismRNA-SeqSwineGlucoseInsulinsfibroblastsInsulinlipid metabolismpigsRNA-Seq

Identifiers

PMID36448436
PMCPMC9715385
OpenAlexW4310568594

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.